Economic Survey 2018-19
Volume 1
Government of India Ministry of Finance Department of Economic Affairs Economic Division North Block New Delhi-110001 E-mail: [email protected] July, 2019
CONTENTS
Chapter Page Name of the Chapter No. No.
vii Acknowledgement ix Preface xi Abbreviations
1 Shifting Gears: Private Investment as the Key Driver of Growth, Jobs, Exports and Demand 2 Last Five Years: The Accomplishments 4 The Next Five Years: A Blueprint for Growth and Jobs 10 Going beyond the economics of "equilibrium" in the blueprint 12 Navigating a world of constant dis-equilibrium 17 Major Factors, Reforms and Risks
2 Policy for Homo Sapiens, Not Homo Economicus: Leveraging the Behavioural Economics of "Nudge" 29 The Influence Spectrum of Public Policy 32 Successful Applications of Behavioural Insights in India 40 Principles for Applying Behavioural Insights to Public Policy 41 An Aspirational Agenda for Path- Breaking Change 54 Implementing the Aspirational Agenda for Behavioural Change
3 Nourishing Dwarfs to Become Giants: Reorienting Policies for MSME Growth 57 Introduction 58 The Bane of Dwarfism and Its Impact on Jobs and Productivity 63 The Role of Policy in Fostering Dwarfism 74 Way Forward
4 Data "Of the People, By the People, For the People" 78 The Economics of Data and Social Welfare 81 Why Must Data be Treated as a Public Good 83 Building the System 90 Transforming India's Data Infrastructure 93 Applications 95 Way Forward
5 Ending Matsyanyaya: How to Ramp Up Capacity In The Lower Judiciary 98 Introduction 99 Pendency 100 Disposal 101 Case Clearance Rate 103 Can the Legal Logjam be Cleared? 105 How should the Additional Judges be Allocated? 111 Making Indian Courts more Productive
6 How does Policy Uncertainty affect Investment? 115 Introduction 117 Economic Policy Uncertainty in India 120 Decoupling of Economic Policy Uncertainty in India Since 2015 121 Green Shoots of Turn Around in Investment Activity 122 Relationship of Economic Policy Uncertainty with Investment in India 125 Conclusion and Policy Recommendations
7 India's Demography at 2040: Planning Public Good Provision for the 21st Century 128 Recent Demographic Trends 132 Projecting National and State Level Population 139 Policy Implications of Ageing 146 Conclusion
8 From Swachh Bharat to Sunder Bharat via Swasth Bharat: An Analysis of the Swachh Bharat Mission 148 Introduction 149 Swachh Bharat Mission-Gramin (SBM) 152 Comparison across states for ODF status (in per cent) 154 Solid and Liquid Waste Management 154 Analysis of SBM on Health Issues 157 Impact of SBM: Few Independent Studies 160 Way Forward
9 Enabling Inclusive Growth through Affordable, Reliable and Sustainable Energy 163 Introduction 164 Energy for Prosperity 166 Access to Energy-Energy Poverty 169 Energy Efficiency 172 Impact of Energy Efficiency Programmes 172 Energy Saving Potential of Various Sectors 174 Sustainability of Energy Generation 175 Potential of Renewable Energy 176 Electric Vehicles (EVs) In India 180 Way Forward 10 Effective Use of Technology for Welfare Schemes- Case of MGNREGS 183 Introduction 185 Use of Technology in implementation of MGNREGS 188 Impact of DBT on Effectiveness of MGNREGS 193 Use of Data on Consumption to Proxy Distress 195 Way Forward
11 Redesigning a Minimum Wage System in India for Inclusive Growth 199 Introduction 200 Minimum Wage System in India 200 National Level Minimum Wage 200 Complex Minimum Wage System in India 202 Different Minimum Wage Across States: Is It Justified? 202 Reflection of Gender Discrimination through Minimum Wage Provisions 204 Compliance with the Minimum Wage Act 206 Impact of Minimum Wages 209 Way Forward
Acknowledgements The Economic Survey is a result of teamwork and collaboration. The Survey has benefitted from the comments and insights of the Hon'ble Finance Minister Smt. Nirmala Sitharaman and Hon'ble Minister of State for Finance Shri. Anurag Singh Thakur. The Survey has also benefited from the comments and inputs of various officials, specifically, Subhash Chandra Garg, Ajay Bhushan Pandey, K. Rajaraman, Amarjeet Sinha and Arunish Chawla. Contributions to the Survey from the Economic Division include: Sanjeev Sanyal, Sushmita Dasgupta, Arun Kumar Jha, Arun Kumar, Rajiv Mishra, Rajasree Ray, A Srija, Surbhi Jain, A. Prathibha, S. Arputhaswamy, Nikhila Menon, Ashwini Lal, Abhishek Acharya, Rajani Ranjan, Sindhumannickal Thankappan, Prerna Joshi, Dharmendra Kumar, Aakanksha Arora, M. Rahul, Rabi Ranjan, Tulsipriya Rajkumari, Shamim Ara, J.D. Vaishampayan, Arya B.K., Abhishek Anand, Sonal Ramesh, Sanjana Kadyan, Amit Sheoran, Shreya Bajaj, Subhash Chand, Riyaz Ahmad Khan, Md. Aftab Alam, Pradyut Kumar Pyne, Narendra Jena, Sribatsa Kumar Parida, Mritunjay Kumar, Rajesh Sharma and Amit Kumar Kesarwani, Arpitha Bykere, Naveen Bali, Mahima, Ankur Gupta, Lipi Budhraja, Sonum Gayatri Malhotra and Lavisha Arora. The Survey benefited from the comments and inputs from officials, specifically Pranab Kumar Mukhopadhyay, DG, DGCI&S, Kolkata; Shri Ajay Srivastava, Economic Adviser, Department of Commerce; Ms. Shruti Shukla, Joint Director, DGCI&S, Kolkata; Dr. M. D. Patra, Executive Director, Reserve Bank of India (RBI); Shri Rajan Goyal, Adviser, Reserve Bank of India (RBI); Prof. K. S. James and Prof. Chander Shekhar, International Institute for Population Sciences; Prof. Suresh Sharma and Vandana Sharma, Institute of Economic Growth; Shri Rajiv Jain, Director, RBI; Shri Dhirendra Gajbhiye, Assistant Adviser, Reserve Bank of India (RBI); Mr. Surya Prakash B. S., Fellow and Programme Director (Daksh); Siddharth Mandrekar Rao, Research Associate (Daksh); Ms. Soumasree Tewari, Research Officer, RBI; Shri Sukhbir Singh, CAAA, Department of Economic Affairs, Ministry of Finance; Shri Abhay Bakre, Director General, Bureau of Energy Efficiency; Dr. Ashok Kumar, Director, Bureau of Energy Efficiency; Dr. Surya P Sethi and Shri Sameer Kumar- Joint Secretary, Ministry of Drinking Water and Sanitation. The Economic Survey team is thankful for inputs from National Judicial Data Grid, eCourts portal, and the International Labor Organisation, New Delhi. We are also grateful for comments and inputs from numerous academics and practitioners, including Tanuj Bhojwani, Sajjid Chinoy, Mohandas Pai, Harshini Shanker, Sharad Sharma, Prasanna Tantri and K. Vaidyanathan. Apart from the above, various ministries, departments and organisations of the Government of India made contributions in their respective sectors. Several ministries directly interacted with the CEA via presentations to provide their inputs. The Economic Survey is grateful for their valuable time, engagement and contributions. Able administrative support was given by K. Rajaraman, Rajkumar Tiwari, Jasbir Singh, Suresh Kumar, Anupam Shukla, Sadhna Sharma, Arun Gulati, Sushil Sharma, Manish Panwar, Muna Sah, Suresh Kumar, Jodh Singh, Ombir Singh, R R Meena, Subash Chand, Raj Kumar, Ram Niwas, Kesar Singh, Bal Kishan, Satish Kumar, Gajender Singh and other staff and members of the Economic Division and the Office of CEA. The cover page for the Survey was designed by India Brand Equity Foundation. Viba Press Pvt. Ltd. undertook the printing of the English and Hindi version of the Survey. Finally, the Economic Survey owes deep gratitude to the families of all those involved in its preparation for being ever so patient, understanding and encouraging and for extending their unflinching emotional and physical support and encouragement throughout the preparation. The families, indeed, are the unconditional pillars of support for the dedicated contributors to the Economic Survey.
Krishnamurthy V. Subramanian (Chief Economic Adviser) Ministry of Finance Government of India
(vii)
Preface At the outset, we would like to express our sincere gratitude to the leadership provided by previous Chief Economic Advisors, which has elevated the Economic Survey to a much anticipated event in India's economic calendar. The contribution they have made through their erudition, rigour and, most importantly, their ideas can only be expressed through Sir Isaac Newton's immortal quote: "If I have seen further than others, it is by standing upon the shoulders of giants." This Survey makes a humble effort to carry forward this glorious tradition.
This Survey is the first for the new Government, which came to power with an overwhelming mandate. With the aspirations that have been kindled among our predominantly young population, India stands at a historic moment when sustained high economic growth has become a national imperative. Aptly, the Honourable Prime Minister laid down the vision of India becoming a $5 trillion economy by 2025 (#Economy@5trillion) and has inspired every citizen to contribute his or her bit to this worthy cause. In his words, "If every one of the 130 crore Indians takes one step forward, the country too will go that many steps ahead." By laying out the strategic blueprint for fructifying this vision, the Survey extends its absolute commitment to a collective endeavour: 130 crore Indians creating an inclusive India by 2022 when we, as a nation, complete 75 years of Independence (#India@75).
Imbued by the power of the opportunity that beckons, the team for Economic Survey 2018-19 has been guided by "blue sky thinking." The Survey adopts an unfettered approach in thinking about the appropriate economic model for India. This endeavour is reflected in the sky blue cover of the Survey. To achieve the vision of #Economy@5trillion, India needs to shift its gears to accelerate and sustain a real GDP growth rate of 8%. The Survey departs from traditional thinking by viewing the economy as being either in a virtuous or a vicious cycle, and thus never in equilibrium. Rather than viewing the national priorities of fostering economic growth, demand, exports and job creation as separate problems, the Survey views these macroeconomic phenomena as complementary to each other. The cover design captures the idea of complementary inter-linkages between these macroeconomic variables using the pictorial description of several inter-linked gears.
Drawing upon the trajectories followed by East Asian economies that experienced long periods of high growth, the Survey postulates the centrality of investment as the "key driver" that catalyses the economy into a self- sustaining virtuous cycle when supported by a favourable demographic phase. After laying out the strategic blueprint for fulfilling the vision of #Economy@5trillion, the Survey describes some of the tactical devices required to navigate an uncertain world in constant dis-equilibrium. Inter alia, the Survey focuses on nourishing MSMEs to create jobs and become more productive so that they can become internationally competitive, enhancing legal reform, ensuring consistency of policy with the vision and the strategic blueprint, reducing the cost of capital, and rationalizing the risk-return trade-off for investments.
In its attempt at unfettered thinking, the Survey utilises the significant advances made in Behavioural Economics in the last few decades, which culminated in the 2017 Nobel Prize in Economic Sciences being awarded to Prof. Richard Thaler. The impact created by Government's flagship initiatives such as Swacch Bharat Mission, Jan Dhan Yojana and the Beti Bachao Beti Padhao provide testimony to the potential for behavioural change in India. Given our rich cultural and spiritual heritage, social norms play a very important role in shaping the behaviour of each one of us. Behavioural economics provides the necessary tools and principles to not only understand how norms affect behaviour but also to utilise these norms to effect behavioural change. The Survey, therefore, lays out an ambitious agenda for behavioural change by applying the principles of behavioural economics to several issues including gender equality, a healthy and beautiful India, savings, tax compliance and credit quality.
Heading into a century where data has become the new oil and analytics from data the new tool for decision making, the Survey foresees countless opportunities in creating data as a public good "of the people, for the people and by the people".
In preparing this Survey, time and talent have been devoted to make our analysis understandable to all readers while maintaining the necessary level of rigor. To illuminate the key insights and demystify the concept for readers across all disciplines, an Abstract and a Chapter at a Glance have been included for each Chapter of the Survey.
(ix) We chose to continue with the popular tradition of presenting the Survey in two volumes. Volume I, which attempts to capture our "blue sky thinking", provides evidence based economic analyses of recent economic developments to enable informed policymaking. Volume II reviews recent developments in the major sectors of the economy and is supported by relevant statistical tables and data. This would serve as the ready reckoner for the existing status and policies in a sector.
The Economic Survey attributes its existence and popularity to the collaborative effort of all Ministries and Departments of Government of India, the prodigious resource base of the Indian Economic Service officers, valuable inputs of researchers, consultants and think tanks both within and outside the government and the consistent support of all officials of the Economic Division, Department of Economic Affairs. The Survey has made a sincere effort to live up to the expectation of being an indispensable guide for following, understanding and thinking about the Indian economy. While our immensely enriching journey represents our ultimate reward, we hope readers share the sense of excitement with which we present the Survey.
Krishnamurthy V. Subramanian (Chief Economic Adviser) Ministry of Finance Government of India
(x) ABBREVIATIONS
AgDSM Agriculture Demand Side Management ICDS Integrated Child Development Services ANBC Adjusted Net Bank Credit ICT Information and Communications Technology API Application Programming Interface IDA Industrial Disputes Act APL Above Poverty Line IHHL Individual Household Latrine APL Aadhaar Linked Payments IIPS International Institute for Population Sciences ASI Annual Survey of Industries ILC International Labour Conference BAU Business as Usual ILO International Labour Organization BBBP Beti Bachao, Beti Padhao IMD India Meteorological Department BCE Before Christian Era ISRO Indian Space Research Organisation BEE Bureau of Energy Efficiency IVA Independent Verification Agency BEVs Battery Electric Vehicles JAM Jan Dhan, Aadhaar and Mobile BHIM Bharat Interface for Money KUSUM Kisan Urja Suraksha Evam Utthaan Mahabhiyan BPL Below Poverty Line LCR/R and P Lower Courts Records - Records and Proceedings BRICS Brazil, Russia, India, China, South Africa LED Light-Emitting Diode CAFE Corporate Average Fuel Efficiency LFPR Labour Force Participation Rate CAGR Compound Annual Growth Rates LPG Liquefied Petroleum Gas CBSE Central Board of Secondary Education MAA Mothers' Absolute Affection CCR Case Clearance Rate MGNREGA Mahatma Gandhi National Rural Employment CEPEJ Commission for the Efficiency of Justice Guarantee Act CO2 Carbon Dioxide MIS Management Information System CPI Consumer Price Index MoDWS Ministry of Drinking Water and Sanitation CSC Common Service Centre MoEF&CC Ministry of Environment, Forest and Climate CV Coefficient of Variation Change D&S courts District and Subordinate courts MoU Memorandum of Understanding DBT Direct Benefit Transfer MPCE Monthly Per Capita Expenditure DBTL Direct Benefit Transfer for LPG MSME Micro, Small & Medium Enterprises DC Designated Consumers MtCO2 Metric Tons of Carbon Dioxide Equivalent DDU GKY Deen Dayal Upadhyaya Grameen Kaushalya MTOE Million Tonne of Oil Equivalent Yojana NARSS National Annual Rural Sanitation Survey DISCOMs Distribution Companies NBFC AA Non Banking Financial Company Axxount DSM Demand Side Management Aggregators E- NAM National Agriculture Market NDC Nationally Determined Contribution ECBC Energy Conservation Building Code NEFMS National Electronic Fund Management System ECC Employment Conditions Commission NEMMP National Electric Mobility Mission Plan EESL Energy Efficiency Services Limited NEV New Energy Vehicle EODB Ease of Doing Business NFLMW National Floor Level Minimum Wage EPU Economic Policy Uncertainty NJDG National Judicial Data Grid ESCerts Energy Saving Certificates NRM Natural Resource Management EUS Employment & Unemployment Survey NSSO National Sample Survey Organisation EVs Electric Vehicles NVA Net Value Added FAME Faster Adoption and Manufacturing of Electric ODF Open Defecation Free vehicles OECD Organisation for Economic Cooperation and FCEVs Fuel Cell Electric Vehicle Development FII Foreign Institutional Investment OLS Ordinary Least Squares GHG Greenhouse Gas ORS Oral Rehydration Solutions GIS Geographic Information System OSH Occupational Safety and Health GST Goods and Services Tax PAN Permanent Account Number GVA Gross Value Added PAT Perform Achieve and Trade HDI Human Development Index PDS Public Distribution System HRD Human Resource Development PHEVs Plug-in Hybrid Electric Vehicles ICAR Indian Council of Agricultural Research PMAY-G Pradhan Mantri Awas Yojana- Gramin
(xi) PMJDY Pradhan Mantri Jan Dhan Yojana UAE United Arab Emirates PMO Prime Minister's Office UIDAI Unique Identification Authority of India PSL Priority Sector Lending UJALA Unnati Jyoti by Affordable LEDs RE Renewable Energy UK United Kingdom SBM Swachh Bharat Mission ULBs Urban Local Bodies SBM(G) Swachh Bharat Mission (Gramin) UNICEF United Nations International Children's Emergency SDGs Sustainable Development Goals Fund SLWM Solid and Liquid Waste Management UPI Unified Payments Interface SRB Sex Ratio at Birth USA United States of America SSI Small Scale Industries UTs Union Territories TFR Total Fertility Rate VDA Variable Dearness Allowance TOE Tonnes of Oil Equivalent WHO World Health Organization TWh Terawatt-hour ZEVs Zero Emission Vehicles
(xii) Shifting Gears: Private Investment as the Key Driver of Growth, Jobs, 01 CHAPTER Exports and Demand
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Although central grants THE NEXT FIVE YEARS: A to states saw compensatory cuts, the shift BLUEPRINT FOR GROWTH AND empowers states to manage their revenues JOBS and expenditures independently. 1.12 With the micro-economic and macro- 7KH ODXQFK RI WKH *67 *RRGV DQG economic foundations laid over the last 6HUYLFHV 7D[ LQ -XO\ DGGHG D QHZ ¿YH\HDUVWKH,QGLDQHFRQRP\LVUHDG\WR dimension to centre-state and inter-state shift gears so that economic growth, jobs ¿QDQFLDO UHODWLRQV 7KH *67 &RXQFLO and exports can be pushed up to the next experience provides key learning for OHYHO)RUWKLVSXUSRVHWKH6XUYH\SUHVHQWV implementing cooperative federalism in a blueprint. several other areas such as labour and land regulation. Niti Aayog has helped Emphasising Growth institutionalize cooperative federalism by 1.13 As articulated by the Prime Minister, setting up teams from both the states and 6KUL1DUHQGUD0RGL,QGLDDLPVWRJURZLQWR the central government to jointly evolve D86'WULOOLRQHFRQRP\E\ZKLFK strategies for addressing development will make India the third-largest economy FKDOOHQJHV6WDWHVKDYHDOVREHHQLQYROYHGLQ LQ WKH ZRUOG *LYHQ LQÀDWLRQ DV WKH a friendly competition to improve their Key 0RQHWDU\3ROLF\)UDPHZRUNVSHFL¿HGE\WKH Performance Indicators (KPIs). Government for the Reserve Bank of India, Corporate Exits WKLVUHTXLUHVUHDODQQXDOJURZWKUDWHLQ*'3 of 8 per cent.1 What are the ingredients of a 1.11 When the Insolvency and Bankruptcy model that can generate such growth? 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Shifting Gears: Private Investment as the Key Driver of Growth, Jobs, Exports and Demand 5 recent times, Chinese economic growth GHSDUWXUHVIURPWKHWUDGLWLRQDO$QJOR6D[RQ stands out for its explosive growth over view of the economy. a long period of four decades. Post war HFRQRPLF H[SDQVLRQ LQ :HVWHUQ (XURSH 1.18 First, the traditional view, which has led to high growth rates of its economies. FRPH XQGHU VLJQL¿FDQW FKDOOHQJH IROORZLQJ 'XULQJ -DSDQ V *'3 JURZWK UDWH the Global Financial Crisis, considers the frequently exceeded 10 per cent. Post World concept of equilibrium as a key tenet. In :DU,,+RQJ.RQJ6LQJDSRUH6RXWK.RUHD contrast, by imbibing some of the new and Taiwan successfully maintained a rapid learning from the economics literature growth rate of more than 7 per cent until following the Global Financial Crisis, we V view the economy as being in a constant state of disequilibrium as captured by a virtuous or A virtuous cycle of savings, investment, a vicious cycle. exports and growth with investment as the “central driver” 6HFRQG WKH WUDGLWLRQDO YLHZ RIWHQ attempts to solve job creation, demand, 1.15 The overwhelming evidence across the exports, and economic growth as separate JOREHHVSHFLDOO\IURP&KLQDDQG(DVW$VLD problems. In contrast, as we show below, in recent times, is that high growth rates have these macro-economic phenomena exhibit only been sustained by a growth model driven VLJQL¿FDQW FRPSOHPHQWDULWLHV 7KHUHIRUH by a virtuous cycle of savings, investment understanding the “key driver” and enhancing and exports catalysed and supported by a the same enables simultaneous growth in favourable demographic phase. As we explain each of the other macro phenomena. in detail below, investment, especially private investment, is the “key driver” that drives 1.20 When viewed in this manner, the demand, creates capacity, increases labour triggering macro-economic “key driver” productivity, introduces new technology, that catalyses the economy into a virtuous allows creative destruction, and generates F\FOHEHFRPHVFULWLFDO7KLV6XUYH\PDNHV jobs. the case for investment as the “key driver” that can create a self-sustaining virtuous 1.16 We depart from traditional thinking cycle in India. This investment can be both by outlining a growth model that views the government investments in infrastructure, economy as being in FRQVWDQWGLVHTXLOLEULXP as such investment crowds in private DYLUWXRXVF\FOHRUDYLFLRXVF\FOH. When the LQYHVWPHQW &KDNUDEDUWL 6XEUDPDQLDQ DQG economy is in a virtuous cycle, investment, 6HVKD DQG SULYDWH LQYHVWPHQW LQ productivity growth, job creation, demand itself. and exports feed into each other and enable animal spirits in the economy to thrive. In Evidence supporting the “virtuous contrast, when the economy is in a vicious cycle” view cycle, moderation in these variables dampen each other and thereby dampen the animal 1.21 Figure 2 shows how the share of GCF, spirits in the economy. VDYLQJV DQG H[SRUWV LQ *'3 HYROYHG IRU &KLQD DV D IXQFWLRQ RI WKH ORJ RI *'3 SHU 1.17 As we describe in the next section, our FDSLWDIURP WR&UXFLDOO\ZHQRWH view of the economy in either a virtuous or that all the three macro-variables increased a vicious cycle—with investment as the key as the country became richer. Thus, as the driver of this cycle—stems from two key economy started doing better, as measured by 6 Economic Survey 2018-19 Volume 1 Figure 2: Share of GCF, Savings and WKH ULVLQJ *'3 SHU FDSLWD &KLQD¶V VDYLQJV Exports in GDP vs. log GDP Per Capita in investment and exports increased further.3 constant 2010 US$: China (1980-2017)2 Figures 3 and 4 show the same relationships for saving and investment for four countries 50 LQ(DVW$VLD 7KDLODQG,QGRQHVLD0DOD\VLD 40 DQG 6RXWK .RUHD ZKLFK ZLWQHVVHG KLJK growth before the Asian Financial Crisis. The 30 WLPHSHULRGHPSOR\HGLQWKHVHFKDUWVLV 20 LHEHIRUHWKH$VLDQ)LQDQFLDO&ULVLV While Figure 3 shows the relationship of GCF, Savings and Exports(% Savings of GDP) GCF, 10 investment and savings, Figure 4 shows the 2.5 3.0 3.5 Log(GDP Per Capita) VDPHIRUH[SRUWVH[FHSWIRU6RXWK.RUHD7KH Exports GCF Savings inference that we made using China, thus, 6RXUFH :RUOG%DQN remains unchanged by examining Figure 3 1RWH *'3SHUFDSLWDLVLQFRQVWDQW86DQGWKH and 4. WLPHSHULRGXVHGLV 7KHORJDULWKPLFVFDOH taken for the x-axis is with base 10 to enable ease of 6DQGUL SURYLGHV D GLIIHUHQW reading. way of looking at the same phenomenon. Figure 3: Share of GCF and Savings in GDP vs. log GDP Per Capita in constant 2010 US$: High Growth East Asian Economies ex-China (1980-1995) 40 30 35 25 30 20 25 GCF, Savings(% of GDP) Savings(% GCF, of GDP) Savings(% GCF, 20 15 3.2 3.3 3.4 3.5 3.15 3.20 3.25 3.30 3.35 Log(GDP Per Capita): Thailand Log(GDP Per Capita): Indonesia GCF Savings GCF Savings 40 40 35 35 30 30 25 GCF, Savings(% of GDP) Savings(% GCF, of GDP) Savings(% GCF, 25 20 3.6 3.7 3.8 3.6 3.7 3.8 3.9 4.0 4.1 Log(GDP Per Capita): Malaysia Log(GDP Per Capita): Korea, Rep. GCF Savings GCF Savings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linear trend is still increasing. Shifting Gears: Private Investment as the Key Driver of Growth, Jobs, Exports and Demand 7 Figure 4: Share of Exports in GDP (%) vs. log GDP Per Capita in constant 2010 US$: High Growth East Asian Economies ex China (1980-1995) 30.0 40 35 27.5 30 25.0 Exports (% of GDP) 25 Exports (% of GDP) 22.5 20 3.2 3.3 3.4 3.5 3.15 3.20 3.25 3.30 3.35 Log(GDP Per Capita): Thailand Log(GDP Per Capita): Indonesia Exports Exports 90 33 80 30 70 27 Exports (% of GDP) 60 Exports (% of GDP) 50 24 3.6 3.7 3.8 3.6 3.7 3.8 3.9 4.0 4.1 Log(GDP Per Capita): Malaysia Log(GDP Per Capita): Korea, Rep. Exports Exports 6RXUFH :RUOG%DQN 1RWHV *'3SHUFDSLWDLVLQFRQVWDQW86DQGWKHWLPHSHULRGXVHGLV 7KHORJDULWKPLFVFDOH WDNHQIRUWKH[D[LVLVZLWKEDVHWRHQDEOHHDVHRIUHDGLQJ+LJK*URZWK(DVW$VLDQ(FRQRPLHV&RUUHVSRQGWR ,QGRQHVLD0DOD\VLD6RXWK.RUHDDQG7KDLODQG By averaging across 62 episodes of growth and investment with consumption decreasing VSXUWVIURP WRDPRQJQRQ2(&' VLJQL¿FDQWO\ DV D VKDUH RI *'3 )LJXUH FRXQWULHV 6DQGUL GHPRQVWUDWHV WKDW 6). China remains an investment-driven productivity growth across these episodes is economy even today with its investment and combined with a rapidly rising investment VDYLQJV UDWHV UHDFKLQJ DERXW RI *'3 rate and an even more steeply increasing even in 2017. savings rate. )RU &KLQD DQG RWKHU (DVW $VLDQ 1.23 China has relied primarily on savings (FRQRPLHV )LJXUH VKRZV WKH VWURQJ Figure 5: Changes in productivity, investment, savings and current account across 62 episodes of growth accelerations in non-OECD countries (1960-2011) 3 2 1 Current Account(% GDP) 0 t*-2 t* +2 +4 +6 6RXUFH 6DQGUL 8 Economic Survey 2018-19 Volume 1 Figure 6: Consumption, Gross Capital Figure 8: Gross Capital Formation to Formation and Savings to GDP for China GDP vs. Savings rate for China and High (1980-2017) Growth East Asian Economies ex-China (1980-2000) 60 40 40 50 38 35 36 40 30 GCF (% of GDP) GCF (% of GDP) GCF, Savings, Consumption Exp. (% GDP) Consumption Exp. Savings, GCF, 34 25 1980 1990 2000 2010 2020 Year Consumption Exp.(% of GDP) GCF share Savings rate 35.0 37.5 40.0 20 30 40 6RXUFH :RUOG%DQN Savings (% of GDP): China Savings (% of GDP): HGEs 6RXUFH :RUOG%DQN Figure 7: GDP Growth vs. Gross Capital 1RWHV 7KHOHIWSDQHOVKRZVWKHUHODWLRQVKLSIRU&KLQD Formation to GDP for China and High while the right panel shows the same for the four high JURZWK(DVW$VLDQHFRQRPLHVRI7KDLODQG,QGRQHVLD Growth East Asian Economies ex-China 0DOD\VLDDQG6RXWK.RUHD7LPHSHULRGWDNHQLV (1980-2000) 2000. VXJJHVWV WKDW VDYLQJV LQYHVWPHQW DQG *'3 12.5 growth have grown in a virtuous cycle in the 10 high growth economies, be it China or other (DVW$VLDQHFRQRPLHV 10.0 Importance of savings GDP Growth (%) GDP Growth 5 GDP Growth Rate (%) GDP Growth 7.5 $V )HOGVWHLQ DQG +RULRND demonstrated in what has since been labelled the “Feldstein-Horioka puzzle”, a high 5.0 32.5 35.0 37.5 40.0 42.5 20 25 30 35 40 investment effort must be backed by domestic GCF (% of GDP): China GCF (% of GDP): HGEs savings. Further research (Carroll and Weil, 6RXUFH :RUOG%DQN $WWDQDVLR 3LFFL DQG 6FRUFX 1RWHV 7KHOHIWSDQHOVKRZVWKHUHODWLRQVKLSIRU&KLQD Rodrik, 2000) has since shown that savings while the right panel shows the same for the four high and growth are not only positively correlated JURZWK(DVW$VLDQHFRQRPLHVRI7KDLODQG,QGRQHVLD 0DOD\VLDDQG6RXWK.RUHD7LPHSHULRGXVHGLV but their positive correlation is even stronger +*(VFRUUHVSRQGWRWKHIRXU+LJK*URZWK(DVW than that between growth and investment Asian economies of Thailand, Indonesia, Malaysia (Gourinchas and Jeanne, 2013). In fact, DQG6RXWK.RUHD 6DQGUL DUJXHV WKDW DV LQYHVWPHQW LV correlation between investment as measured risky, entrepreneurs are exposed to the risk of idiosyncratic business failure that leads to the E\ WKH *URVV &DSLWDO )RUPDWLRQ DQG *'3 growth while Figure 8 shows an equally loss of the invested capital. Therefore, savings stronger correlation between investment and have to increase more than investment to savings. allow for the accumulation of precautionary VDYLQJV 7KH HYLGHQFH IURP 6DQGUL 1.25 Thus, the evidence in this section for the 62 episodes of growth acceleration Shifting Gears: Private Investment as the Key Driver of Growth, Jobs, Exports and Demand 9 (Figure 5) and China (Figure 6) shows the Figure 9: Unemployment Rate vs. Gross same as well. Capital Formation (GCF) to GDP for Jobs (DVW$VLDDQG3DFL¿F 1.27 A general apprehension is that high 8 investment rate will substitute labour. This thinking has led to much debate about 6 labour-intensive versus capital-intensive modes of production. However, the Chinese 4 experience illustrates how a country with the highest investment rates also created the Rate (%) Unemployment 2 most jobs. What matters most is whether or not investment enhances productivity and 0 thereby international competitiveness. The 10 20 30 40 GCF(% of GDP) misconception arises from a view buried 6RXUFH :RUOG%DQN LQ WKH VLOR RI D VSHFL¿F DFWLYLW\ :KHQ examined in the full value chain, capital a force-multiplier when high income growth investment fosters job creation as capital IHHGV FRQVXPSWLRQ 6R ZKHUH ZRXOG WKH goods production, research and development, ¿QDOGHPDQGIRUWKHODUJHFDSDFLWLHVFUHDWHG and supply chains also generate jobs. by high investment come from? The answer International evidence also suggests that is exports. This is why an aggressive export capital and labour are complementary when strategy must be a part of any investment- high investment rate drives growth. For driven growth model. Figure 10 shows the instance, Lin (2011) shows that the coming of software and computers, while having Figure 10: GDP Growth vs. Growth in replaced some white collar tasks, have also Exports for High Growth East Asian generated new labour centric tasks related Economies (1980-2017) to software and application development, computer security, and specialised tasks for loan application analysts and medical 10 equipment technicians.4)LJXUH VKRZVKRZ unemployment rates decreases with greater JURVV FDSLWDO IRUPDWLRQ LQ (DVW $VLD DQG 5 3DFL¿FWKHUHE\SURYLGLQJDGGLWLRQDOHYLGHQFH (%) GDP Growth that labour and investment complement each other. Therefore, job creation can indeed be 0 fostered by encouraging investment. í 0102030 Exports Exports Growth (%): HGEs 6RXUFH :RUOG%DQN :LWKWKHVKDUHRIFRQVXPSWLRQLQ*'3 1RWH 7LPH SHULRG WDNHQ LV DQG +LJK constrained by the high level of savings, *URZWK (DVW $VLDQ (FRQRPLHV FRUUHVSRQG WR domestic consumption can be, at best, act as ,QGRQHVLD0DOD\VLD6RXWK.RUHDDQG7KDLODQG ______4 7KHVXFFHVVVWRU\RI7RZQDQG9LOODJH(QWHUSULVHV 79(V LQ&KLQDEHFRPLQJWKHHQJLQHVRILWVVSHFWDFXODUJURZWKVKRZV how labour-intensive manufacturing investment can simultaneously boost productivity, job creation and exports (Wei and %DODVXEUDPDQ\DP :KLOHLQ WKHUHZHUHDERXWPLOOLRQ79(VZLWKPLOOLRQHPSOR\HHVE\ WKHUH ZHUHPLOOLRQ79(VZLWKPLOOLRQZRUNHUVFRQWULEXWLQJQHDUO\RI&KLQD¶V*'3DQGRIWKHLQGXVWULDORXWSXW 3HURWWLHWDO %\ 79(H[SRUWVDFFRXQWHGIRURI&KLQD¶VWRWDOH[SRUWVDQGPXFKRIWKHVHZHUHODERXU intensive products involving simple production techniques (Fu and Balasubramanyam, 2005). 10 Economic Survey 2018-19 Volume 1 strong correlation between growth in exports LQKLVHIIRUWVWRLPSURYHWKHVRFLDORUGHUKH DQG *'3 JURZWK IRU WKH KLJK JURZWK (DVW ZLOOOHDUQWKDWLQWKLVDVLQDOORWKHU¿HOGV Asian economies. ZKHUH HVVHQWLDO FRPSOH[LW\ RI DQ RUJDQL]HG 7KH JOREDO PDUNHW LV H[WUHPHO\ NLQG SUHYDLOV KH FDQQRW DFTXLUH WKH IXOO FRPSHWLWLYH ZLWK WKH ¿UPV WKDW DUH DEOH WR NQRZOHGJH ZKLFK ZLOO PDNH PDVWHU\ RI WKH produce at the lowest costs having the ability HYHQWV SRVVLEOH +H ZLOO WKHUHIRUH KDYH WR WRJDLQPDUNHWVKDUHLQH[SRUWV6RDYHUDJH XVH ZKDW NQRZOHGJH KH FDQ DFKLHYH QRW WR SURGXFWLYLW\RI¿UPVLQWKHHFRQRP\EHFRPHV VKDSHWKHUHVXOWVDVWKHFUDIWVPDQVKDSHVKLV crucial to export competitiveness. As seen in KDQGLZRUNEXWUDWKHUWRFXOWLYDWHDJURZWK Figure 11, capital investment enhances total E\SURYLGLQJWKHDSSURSULDWHHQYLURQPHQWLQ factor productivity, which in turn enhances WKHPDQQHULQZKLFKWKHJDUGHQHUGRHVWKLV export performance. Therefore, investment IRUKLVSODQWV´ becomes crucial to enhancing export )ULHGHULFK9RQ+D\HN1REHOSUL]HVSHHFK performance. 1.30 While it is true that world trade is $VWKHDERYHTXRWHIURP+D\HN currently facing some disruptions, India’s illustrates, the blueprint starts from the share in global exports is so low that it should philosophy that economies are intricately focus on market share. One could even interwoven systems. Therefore, they can argue that the current disruptions provide an neither be meaningfully viewed in silos nor opportunity for India to insert itself into global can they be analysed without accounting supply chains. The High Level Advisory for dynamic effects over time. Moreover, *URXSFKDLUHGE\'U6XUMLW%KDOODVXEPLWWHG economies may rarely be in a state of LWV UHSRUW LQ -XQH RQ KRZ ,QGLD FDQ equilibrium. While writing about economic enhance its exports. Its recommendations need theories following the Global Financial to be studied and implemented where possible. &ULVLV5RGULN ODPHQWV GOING BEYOND THE ³:K\GRZHIRFXVVRPXFKRQWKHSHUIHFWO\ ECONOMICS OF EQUILIBRIUM ދ ތ UDWLRQDOLQGLYLGXDOHYHQWKRXJKUHDOSHRSOHGR IN THE BLUEPRINT QRWVHHPWREHKDYHTXLWHWKDWZD\"6KRXOGQ¶W ³,I PDQ LV QRW WR GR PRUH KDUP WKDQ JRRG ZH EH SD\LQJ D ZHH ELW PRUH DWWHQWLRQ WR Figure 11: Effect of GCFC Growth on Productivity and in turn on exports for OECD countries (1985-2017) 5.0 20 2.5 10 0.0 Exports (%) Growth Multi Factor Prodcutivity Growth (%) Prodcutivity Growth Multi Factor 0 í í 0 5 10 15 20 í 0.0 2.5 5.0 7.5 GFCF Growth (%) Multi Factor Productivity Growth(%) 6RXUFH 2(&''DWDEDVH Shifting Gears: Private Investment as the Key Driver of Growth, Jobs, Exports and Demand 11 GLVHTXLOLEULXP LQ DGGLWLRQ WR HTXLOLEULXP" $Q DSSURDFK WKDW LQWHJUDWHV EHKDYLRXUDO :K\ GR RXU PRGHOV H[FOXGH VRFLDO DQG HFRQRPLFV DQG FRPSOH[ V\VWHPV WKHRU\ DV LQVWLWXWLRQDOIHDWXUHVZLWKRXWZKLFKPDUNHWV ZHOODVHFRQRPLFKLVWRU\´ FRXOGQRWZRUN":K\GRZHHPSKDVL]HPDWK 1.33 As Box 1 illustrates, the meltdown VRPXFKDQGGLVUHJDUGWKLQJVWKDWFDQQRWEH of economic activity following the Global HDVLO\TXDQWL¿HG"´ Financial Crisis highlighted that economies 1.32 To highlight the inadequacies in may be in a vicious cycle, where moderation economic models following the Global in demand, jobs and investment feed )LQDQFLDO&ULVLVWKH2(&'FUHDWHGWKHJURXS into each other and thereby dampen the 1HZ $SSURDFKHV WR (FRQRPLF &KDOOHQJHV animal spirits in the economy. Therefore, 1$(& ,Q D EORJ SRVW RQ 1($& 5DPRV as highlighted by Romer (2015), Ramos KLJKOLJKWV (2017) and Rodrik (2018), economic thinkers now recognise the need for economics to ³7KH YHU\ QDPH RI WUDGLWLRQDO HFRQRPLF HPEUDFHWKHOHDUQLQJIURPRWKHU¿HOGV7KH\ PRGHOV JHQHUDO HTXLOLEULXP VKRZV WKDW acknowledge that the concept of treating WKH\DVVXPHWKDWWKHHFRQRP\LVEDVLFDOO\LQ an economy as always being in equilibrium EDODQFHXQWLODQRXWVLGHVKRFNXSVHWVLW7KH\ PD\³IRUFH¿W´WKH³VWDQGDUG´IUDPHZRUNWR DVVXPHWKDW\RXFDQXQGHUVWDQGWKHHFRQRP\ an ever-changing world. Instead, thinking E\ VWXG\LQJ D UHSUHVHQWDWLYH DJHQW ZKRVH about economies as being in the constant H[SHFWDWLRQV DQG GHFLVLRQV DUH UDWLRQDO disequilibrium of virtuous or vicious cycles 7KLVYLHZLVHVVHQWLDOO\OLQHDUDQGWKHSROLF\ provides a more apt framework for the DGYLFH LW JHQHUDWHV LV WDLORUHG WR D OLQHDU current times. Therefore, when the economy V\VWHP ZKHUH DQ DFWLRQ SURGXFHV D IDLUO\ is viewed, proper sequencing of policy levers SUHGLFWDEOH UHDFWLRQ« 5HDO OLIH LV QRW OLNH assumes importance, especially because of WKDW«:HQHHGDQHZDSSURDFKWRHFRQRPLFV the presence of complementarities between WKDWLVQ¶WMXVWDERXWTXDQWLWDWLYHHFRQRPLFV different elements of an economy. Box 1: The need for economic theory to be contextualised to India The Global Financial Crisis exposed the problems embedded in conventional macroeconomic WKHRULHV 6WDUWZLWK )LWWKH³standard´ ³3X]]OH´LIWKHdata ³standard´WKHRU\ theory to the real does not fit the world i.e., data ³standard´WKHRU\ &RQVLGHUWKHFODVVLFSDSHUE\/XFDV WRXQGHUVWDQGWKLVÀDZLQWKHWKHRU\EXLOGLQJSURFHVVLQ HFRQRPLFV7KHSDSHUDWWHPSWVWRH[SODLQZK\FDSLWDOGRHVQRWÀRZDVVWDQGDUGWKHRU\SUHGLFWVIURP capital-rich to capital-poor countries, because the latter would have higher returns. The theory starts 12 Economic Survey 2018-19 Volume 1 with some assumptions in “standard” theory such as individuals always making “rational” decisions, the preferences of a collection of individuals captured by the preference of a “representative agent”, the law of diminishing returns, etc. +DYLQJFRQVWUXFWHGWKH³VWDQGDUG´WKHRU\WKHSDSHU¿QGVWKDWWKHWKHRU\GRHVQRW¿WWKHUHDOZRUOG ZKHUHFDSLWDOÀRZVIURPWKHSRRUWRULFKFRXQWULHVUDWKHUWKDQYLFHYHUVD&DSLWDOÀRZVIURP&KLQD WRWKH8QLWHG6WDWHVSURYLGHVDVDOLHQWH[DPSOHWKRXJKWKHSKHQRPHQRQLVPRUHSHUYDVLYH$VWKH ³VWDQGDUG´WKHRU\GRHVQRW¿WWKHUHDOZRUOGWKHVWXG\ODEHOVWKHUHDOZRUOGSKHQRPHQRQ³DSX]]OH´ In contrast, in other disciplines, especially the natural sciences and engineering, the process of building WKHRULHVSURFHHGVLQWKHIROORZLQJGLUHFWLRQ 6WDUWZLWKthe real Construct the Change theory if world i.e., data theory to explain new data the data contradicts ,IZHDGRSWWKLVGLVFLSOLQHWKHSKHQRPHQRQVWXGLHGLQ/XFDV PD\QRWEHDSX]]OH&RQVLGHUD business that becomes extremely productive and is able to produce goods at very low prices, thereby FDSWXULQJODUJHPDUNHWVKDUHDQGJHQHUDWLQJKXJHSUR¿WV7KHSUR¿WVDUHXVXDOO\SORXJKHGEDFNLQWRWKH EXVLQHVVWRIXQGIXUWKHULQYHVWPHQW%XWVXSSRVHWKHSUR¿WVDUHVRODUJHWKDWHYHQDIWHUUHLQYHVWLQJWKH entire amount required for funding new projects, the business is still left with a surplus. What would the business do? Invest this excess surplus in “other assets.” For instance, the business may invest in RWKHU¿UPV7KLVLVZKDW&KLQDLVGRLQJ:K\LVLWDSX]]OHWKHQ" Another prominent example of “standard” theory is the use of the dynamic stochastic general HTXLOLEULXP '6*( PRGHOLQPDFURHFRQRPLFV'HVSLWHWKHODUJHOLWHUDWXUHLQWKLVDUHDZKLFKSRVLWHG '6*(PRGHOVRIHQRUPRXVYDULHWLHVWKHSUHFULVLVPRGHOVDVVXPHGWKH¿QDQFLDOVHFWRUDVDVLGHVKRZ 7KHUHIRUHDQ\SUREOHPVDULVLQJIURPSRWHQWLDOPLVDOORFDWLRQVZLWKLQWKH¿QDQFLDOVHFWRUZHUHDEVHQW IURPWKH'*6(PRGHOV7KLVLVHVSHFLDOO\UHOHYDQWLQWKH,QGLDQFRQWH[WJLYHQWKHUHFHQWH[SHULHQFHRI distress in the banking sector and the overhang that it created on the economy. :KLOHDJURZLQJOLWHUDWXUHKDVVLQFH¿[HGWKHSUREOHPLQ'*6(PRGHOVVXFKH[SRVWIDFWR¿[LQJPD\ not be adequate as some other critical element omitted from the current models will have to wait for QH[WFULVLVWRXQFRYHU7KLVH[SRVW¿[LQJVWHPVIURPWKHLQVLVWHQFHRQXVLQJWKH³VWDQGDUG´WKHRU\ WRXQGHUVWDQGUHDOZRUOGSKHQRPHRQD7KHDGDSWLQJRI'*6(PRGHOVWRWKH,QGLDQUHDOLW\LVFULWLFDO EHFDXVHWKH¿QDQFLDOVHFWRULQ,QGLDGLIIHUVVLJQL¿FDQWO\IURPWKRVHLQWKH$QJOR6D[RQFRXQWULHV 7KHFDVHRI/XFDV DQGWKHRYHUUHOLDQFHRQ'*6(PRGHOVDUHEXWWZRH[DPSOHVWKDWKLJKOLJKW WKHQHHGIRUHYROYLQJPDFURHFRQRPLFWKLQNLQJWKDW¿WVWKHLQVWLWXWLRQDOGLIIHUHQFHVLQDFRXQWU\OLNH ,QGLDYLVjYLVWKH$QJOR6D[RQHFRQRPLHV NAVIGATING A WORLD OF this uncertain world of dis-equilibrium CONSTANT DIS-EQUILIBRIUM UHTXLUHV WKUHH HOHPHQWV L D FOHDU YLVLRQ LL DJHQHUDOVWUDWHJ\WRDFKLHYHWKHYLVLRQ 1.34 An economy that is in a constant DQG LLL WKH ÀH[LELOLW\ DQG ZLOOLQJQHVV WR state of dis-equilibrium needs a new approach to navigate. The earlier attempt continously recalibrate tactics in response to WR FUHDWH ¿YH\HDU SODQV ODUJHO\ XVLQJ WKH unanticipated situations. In earlier sections, equilibrium framework, failed because we have described a broad strategy to achieve it was too prescriptive for an inherently WKH YLVLRQ RI D 86 WULOOLRQ HFRQRP\ unpredictable world. Therefore, navigating We now turn to some of the tactics. Figure Shifting Gears: Private Investment as the Key Driver of Growth, Jobs, Exports and Demand 13 Figure 12: Tools for navigating the economy in a constant state of disequilibrium CHANGE IN MODELLING BEHAVIOURAL INSIGHTS APPROACHES Incorporating insights from behavioural economics to Modelling the ‘virtuous’ or ‘viscous’ cycle (Ch. 1, Vol.1) change behaviour (Ch. 2, Vol.1) MEASUREMENT OF NEW MICRO DATA CONCEPTS Measuring job creation and productivity contributed by Employing data as a public good to enable welfare driven young firms vs old firms (Ch. 3, Vol.1) policy-making (Ch. 4, Vol.1) BOTH STOCKS & FLOWS DISTRIBUTIONS Using technology to administer welfare programmes Sustainable Development (Ch. 9, Vol. 1) effectively and thereby reduce inequality (Ch.10, Vol. 1) MULTI-DIMENSIONAL WELL-BEING 6RXUFH $GDSWHGIURP1($&2(&' 12 below shows the approach advocated for sustainable development of the Indian E\ 1($& 2(&' WR QDYLJDWH WKLV ZRUOG economy. Apart from the need to model the different elements of the economy simultaneously in Behavioural economics an integrated manner, this approach critically 1.35 As policymaking must keep real people requires assimilation of several other tools. as its focus, rather than the optimization- 6HYHUDOFKDSWHUVLQ9ROXPHRI7KH6XUYH\ focused robots that conventional economics lay out the policy details for navigating this assumes, the insights from behavioural world. This chapter lays out the framework economics need to be integrated into for integrated modelling of the various policymaking to foster productivity and economic phenomena. Chapter 2 in Volume HFRQRPLF JURZWK &KDSWHU RI WKH 6XUYH\ 1 delves deep into utilising the insights therefore, delves deep into this subject. By from behavioural economics for behaviour analysing the successful behavioural change change that can thereby foster productivity HIIHFWHGE\WKH6ZDFKK%KDUDW0LVVLRQDQG and economic growth. Chapter 3 in Volume the Beti Bachao, Beti Padhao campaigns, the 1 pursues the measurement of new concepts chapter incorporates their learning and lays by examining the impact of young versus old out frameworks for integrating behavioural ¿UPVLQIRVWHULQJMREFUHDWLRQDQGHQKDQFLQJ economics into policymaking in various productivity. Chapter 10 in Volume 1 studies FRQWH[WV KRZ WKH EHQH¿WV RI WHFKQRORJ\ FDQ EH DSSOLHG WR HQKDQFH WKH HI¿FDF\ RI ZHOIDUH (i) The Beti Bachao, Beti Padhao campaign programmes and thereby generate better has helped in improving child sex ratios, distributional outcomes in the Indian society. particularly in large states where the Chapter 4 in Volume 1 describes the use of child sex ratio was poor. Therefore, the data as a public good for enhancing welfare. campaign has had the maximum impact &KDSWHU IRFXVHV RQ WKH XVH RI HQHUJ\ in states that plausibly also needed the 14 Economic Survey 2018-19 Volume 1 greatest pivot in their social norms. improved the experience of a large Taking the learning from this campaign, majority of taxpayers. Behavioural the chapter attempts to further the cause insights can be leveraged to transform of Gender equality by coining the slogan the tax culture from one of tax evasion to RI%$'/$9 Beti Aapki 'han Lakshmi tax compliance. This would then provide Aur Vijay-lakshmi) to inter alia enhance the necessary revenues for investments contribution of women in the workforce in both the hard infrastructure of DQGWKHHFRQRP\ roads, ports, railways, etc. and the soft LL 7KH6ZDFKK%KDUDW0LVVLRQKDVKHOSHG LQIUDVWUXFWXUHRIVNLOOVDQGHGXFDWLRQ increase the percentage of villages Y 7KHLQWURGXFWLRQRIWKH*67UHSUHVHQWHG WKDWDUH2SHQ 'HIHFDWLRQ)UHH DQGKDV a salient instance where policymakers enhanced access and usage of toilets. exhibited the appetite to introduce bold This improvement in sanitation has reform by eschewing loss aversion, helped improve health outcomes as whereby a policy that creates some is seen in the number of malaria and short-term losses while creating diarrhoea cases and the number of ODUJH ORQJWHUP EHQH¿WV PD\ ODFN still births and children with low birth enough support (Milkman et al. 2012). weight. Incorporating the learning from Behavioural insights can build on the this successful behavioural change, positive outcome of enacting such a the chapter develops the framework to path-breaking policy change to reduce use behavioural insights for a healthy loss aversion and thereby improve policy India. The framework embeds the idea and legislative outcomes. RI WDNLQJ RII IURP WKH 6ZDFKK %KDUDW 0LVVLRQ LQWR 6ZDVWK $\XVKPDQ 1.36 Figure 13 below summarises the seven 6XQGDU %KDUDW 7KLV ZRXOG HQKDQFH principles of behavioural economics that can labour productivity and enhance savings, be applied to achieve the above outcomes. DQGWKHUHE\LQYHVWPHQW &KDSWHU RI WKH 6XUYH\ H[SOLFLWO\ OD\V RXW applications in each of these areas. (iii) The creation of the Insolvency and Bankruptcy (IBC) process has helped Data as a public good bring a large number of non-performing assets into the IBC process. Further, the ³&URVVWKHULYHUE\IHHOLQJWKHVWRQHV´ threat created of losing control under 'HQJ;LDRSLQJ IBC is helping change the credit culture in the country. Insights from behavioural 1.37 Having set out the broad strategy for economics can be utilised to enhance the DFKLHYLQJWKHJRDORID86WULOOLRQHFRQRP\ credit culture, especially with respect to continuous re-calibration of policies to frauds and wilful defaults, by drawing DFKLHYH WKLV JRDO LV QHFHVVDU\ 'DWDGULYHQ on the social and cultural norm of the HYLGHQFH HQDEOHV WKLV UHFDOLEUDWLRQ 'HQJ “doctrine of pious obligation.” This, ;LDRSLQJ¶VH[KRUWDWLRQWR³FURVVWKHULYHUE\ in turn, will foster credit growth and feeling the stones” is relevant in this context. investment. If the economy in constant disequilibrium UHSUHVHQWVWKHÀRZLQJULYHUWKHQGDWDGULYHQ LY 6HYHUDO FKDQJHV EURXJKW WKURXJK WKH policymaking represents the process of use of technology in tax administration feeling the stones for necessary re-calibration. have decreased manual intervention in tax administration, and have thereby &KDSWHU LQ9ROXPH RI WKH 6XUYH\ Shifting Gears: Private Investment as the Key Driver of Growth, Jobs, Exports and Demand 15 Figure 13: Principles of behavioural economics to foster behavioural change Principle 1: Leverage Principle 7: 'HIDXOW5XOHV Make Principle 2: Messages 0DNHLW(DV\ Mimic Mental to Choose Models Principle 3: (PSKDVL]H Principle 6: 6RFLDODQG Leverage Loss Cultural Aversion Norms Principle 5: Principle 4: Reinforce 'LVFORVH Repeatedly Outcomes lays out the framework for creating data “of create data as a public good within the legal the people, by the people, for the people.” framework of data privacy. The chapter surmises that society’s optimal Legal Systems and Contract consumption of data is higher than ever Enforcement before because of the exponential decline in the marginal cost of data combined with 7KH HFRQRPLF PRGHO GHVFULEHG LQ WKHPDQLIROGLQFUHDVHLQLWVPDUJLQDOEHQH¿WV the blueprint is explicitly about creating to society. While private sector does a good virtuous cycles in an evolving, complex MRERIKDUQHVVLQJGDWDZKHUHLWLVSUR¿WDEOH landscape. It is about investment, risk-taking government intervention is needed in and innovation in an environment that is social sectors of the country where private inherently uncertain and unpredictable due to investment in data remains inadequate. a range of factors from changing technology Governments already hold a rich repository and consumer preferences to geopolitics and of administrative, survey, institutional and HFRQRPLFF\FOHV7KLVLVDZRUOGRI³EXWWHUÀ\ transactions data about citizens. However, effects” and unintended consequences, where these data are scattered across numerous uncertainty is inevitable. As uncertainty government bodies. Utilising the information exacerbates the temptation to renege on embedded in these distinct datasets would contracts when the ex post outcome is inter alia enable government to enhance different from the one expected ex ante, the ease of living for citizens, enable truly ability to enforce contracts and the rule of law evidence-based policy, improve targeting become critical to navigating an uncertain in welfare schemes, uncover unmet needs, ZRUOG $FKDU\D DQG 6XEUDPDQLDQ integrate fragmented markets, bring greater $FKDU\D %DJKDL DQG 6XEUDPDQLDQ accountability in public services, generate &KDYDHWDO 6DSUD6XEUDPDQLDQ greater citizen participation in governance, DQG 6XEUDPDQLDQ 6XEUDPDQLDQ DQG etc. Given that sophisticated technologies 7XQJ 6XEUDPDQLDQ DQG 0HJJLQVRQ already exist to protect privacy and share 2018). While a well-functioning legal system FRQ¿GHQWLDO LQIRUPDWLRQ JRYHUQPHQWV FDQ is important to economies in all situations, it 16 Economic Survey 2018-19 Volume 1 is absolutely central to one that aims to drive the legal system may be the best investment economic growth through high investment Indian reformers can make. rates in an unpredictable world. Consistency in Economic Policymaking 1.40 The importance of the legal system 1.43 In the world of constant uncertainty, and contract enforcement are repeatedly economic policymaking can either alleviate emphasized by ancient Indian economic the uncertainty faced by investors or thinkers such as Kautilya and Kamandak. exacerbate it. The earlier attempt to create They saw the Rule of Law as key to averting ¿YH\HDUSODQVODUJHO\XVLQJWKHHTXLOLEULXP Matsya-nyaya or Law of the Fish (i.e., law framework, aimed to solve this problem. of the jungle). Nobel prize-winning Austrian However, as we discovered to our dismay, economist Friedrich von Hayek echoed the the best-laid plans can get unravelled in VDPH VHQWLPHQW LQ KLV IDPRXV ERRN 7KH an uncertain world that is in perpetual 5RDGWR6HUIGRP dis-equilibrium. Therefore, navigating ³1RWKLQJ GLVWLQJXLVKHG PRUH FOHDUO\ this uncertain world of dis-equilibrium FRQGLWLRQVLQDIUHHFRXQWU\IURPWKRVHLQD UHTXLUHV WKUHH HOHPHQWV L D FOHDU YLVLRQ FRXQWU\ XQGHU DUELWUDU\ JRYHUQPHQW WKDQ LL DJHQHUDOVWUDWHJ\WRDFKLHYHWKHYLVLRQ WKH REVHUYDQFH LQ WKH IRUPHU RI WKH JUHDW DQG LLL WKH ÀH[LELOLW\ DQG ZLOOLQJQHVV WR SULQFLSOHVNQRZQDVWKH5XOHRI/DZ´ continuously recalibrate tactics in response to unanticipated situations. Having taken the 1.41 Unfortunately, India’s legal system, 3ULPH 0LQLVWHU¶V YLVLRQ RI D 86 WULOOLRQ burdened by 3.5 crore pending cases, is HFRQRP\ WKLV (FRQRPLF 6XUYH\ OD\V RXW D arguably now the single biggest constraint to general blueprint as the strategy to achieve doing business in India and thereby fostering this vision. However, as discussed above, LQYHVWPHQW7KH:RUOG%DQN¶VODWHVW(DVHRI SROLFLHVPXVWUHVSRQGFRQWLQXDOO\WRWKHÀRZ 'RLQJ%XVLQHVV5HSRUWUDQNHG,QGLDDW of real-time data. IRUFRQWUDFWHQIRUFHPHQW([SHULHQFHVKRZV 1.44 The obvious problem from having WKDW HYHU\ RWKHU ¿HOG RI HFRQRPLF UHIRUP be it property rights, taxes and insolvency, VXFK WDFWLFDO ÀH[LELOLW\ LV WKDW LW FUHDWHV LWV own uncertainty. This is particularly the HYHQWXDOO\ÀRXQGHUVEHFDXVHLWJHWVHQWDQJOHG case when major reforms are being carried in the legal system. This is why the legal out. In this context, in Chapter 6 of Volume sector reforms must be a top priority. RIWKH6XUYH\ZHH[DPLQHKRZHFRQRPLF 1.42 The good news is that the problem policy uncertainty has evolved in India over is not insurmountable. A scenario analysis the last few years. More importantly, given of the effort needed to clear the backlog in our emphasis on investment as the key ¿YH\HDUVVXJJHVWVWKDWVLJQL¿FDQWHI¿FLHQF\ driver of the virtuous cycle, we examine the gains are also necessary. At sanctioned relationship of economic policy uncertainty strength, productivity will need to increase with investment. To capture economic policy by 24.5 per cent, 4.3 per cent and 18 per cent uncertainty, we use the Baker et al. (2016) IRU ORZHU FRXUWV +LJK &RXUW DQG 6XSUHPH index, which has been used widely across the Court respectively. The use of technology, ZRUOG:H¿QGWKDWZKLOHWKLVXQFHUWDLQW\ZDV increase in working days and administrative/ higher during episodes of greater uncertainty process reforms can enable these ambitious such as the taper tantrum in 2013, overall \HW DFKLHYDEOH HI¿FLHQF\ JDLQV *LYHQ WKH HFRQRPLFSROLF\XQFHUWDLQW\KDVVLJQL¿FDQWO\ potential economic and social multipliers of a decreased over the last decade (Figure 14). well-functioning legal system, strengthening A noteworthy feature of this Figure is that Shifting Gears: Private Investment as the Key Driver of Growth, Jobs, Exports and Demand 17 Figure 14: Economic policy uncertainty in Figure 15: Investment growth and India (2011-2019) economic policy uncertainty index 20.0 15.0 10.0 5.0 GFCF(%) gr 0.0 0.0 50.0 100.0 150.0 200.0 250.0 6RXUFH KWWS ZZZSROLF\XQFHUWDLQW\FRP -5.0 EPU index WKH LQWURGXFWLRQ RI *67 EDUHO\ LQFUHDVHG 6RXUFH KWWS ZZZSROLF\XQFHUWDLQW\FRP&62 the economic policy uncertainty despite the enormous change that it entailed. This UDWKHUWKDQIURPWDFWLFDOLQÀH[LELOLW\6HFRQG illustrates that path-breaking reforms that ³ZKDW JHWV PHDVXUHG JHWV DFWHG XSRQ´ 6R are consistent with a well-articulated vision economic policy uncertainty index must be do not create as much disruption as some tracked at the highest level on a quarterly people may fear. The continued decrease in basis. Finally, quality assurance of processes economic policy uncertainty in India post in policymaking must be implemented 2015 is as exceptional because it contrasts in government via international quality sharply with the increase in economic policy FHUWL¿FDWLRQV uncertainty in major countries during this MAJOR FACTORS, REFORMS SHULRGLQFOXGLQJWKH86 AND RISKS 6XUJHVLQHFRQRPLFSROLF\XQFHUWDLQW\ Role of demographics in the “virtuous increase the systematic risk, and thereby cycle” the cost of capital in the economy. As a result, higher economic policy uncertainty 1.47 As we shall discuss in Chapter 7 in lowers investment, especially because of 9ROXPH RI WKH 6XUYH\ ,QGLD KDV DOUHDG\ the irreversibility of investment. Consistent entered this demographic phase of a high ZLWK WKLV WKHVLV ZH ¿QG WKDW DQ LQFUHDVH share of working age population, and will in economic policy uncertainty dampens remain in this “demographic dividend” zone investment growth in India (Figure 15). The for over two decades. Figure 16, in fact, impulse-response function suggests that highlights that the working age population an increase in economic policy uncertainty \HDUV ZKLFK FRPSULVHG SHU DIIHFWV JURZWK LQ LQYHVWPHQW IRU DERXW ¿YH cent of the overall population in 2011, will quarters. increase to about 60 per cent in 2041. 1.46 This effect of economic policy 1.48 Change in demographics, especially in uncertainty, therefore, provides important the age structure of the population, has been policy implications for managing an VKRZQ WR KDYH KDG D VLJQL¿FDQW HIIHFW RQ economy in constant disequilibrium. First, economic growth throughout Asia between the predictability of policy stems from being DQG %ORRP DQG :LOOLDPVRQ consistent with the overall vision and strategy $ULVHLQWKHVKDUHRIWKHZRUNLQJDJH 18 Economic Survey 2018-19 Volume 1 Figure 16: Demographic composition in this accounting effect, but it also brought with India (2011-2041) LWEHKDYLRXUDOFKDQJHV6DYLQJVLQFUHDVHGDV 100 life expectancy increased (Lee, Mason and 8.6 12.4 0LOOHU %ORRP&DQQLQJ0DQV¿HOGDQG 75 Moore 2007), and consequently investment 50.5 55.8 58.8 increased. In fact, changes in growth of 50 labour force per capita, changes in the 25 savings rate, and changes in the investment 34.5 28.8 25.2 rate are three plausible mechanisms by which 0 demographics affects the economic growth 2011 2021 2031 2041 +LJJLQVDQG:LOOLDPVRQ %ORRPDQG \HDUV \HDUV \HDUV :LOOLDPVRQ 6RXUFH 6XUYH\&DOFXODWLRQV )LJXUH VKRZV KRZ VDYLQJV UDWH LQ population, brought about by a decline in the &KLQD DQG RWKHU KLJKJURZWK (DVW $VLDQ fertility rate, increases income per capita as HFRQRPLHVZDVGULYHQVLJQL¿FDQWO\E\FKDQJH output per worker remains unchanged but the in its demographics from a predominantly number of youth dependents declines. The young to an older population. While the top rise in the working-age share in Asia created panels show the change in the demographics, Figure 17: Impact of demographics on savings for China and other High-growth East Asian Economies 6KDUH 70 6KDUH 70 60 65 3RSXODWLRQ 55 1980 1990 2000 2010 3RSXODWLRQ Year 60 1980 1990 2000 2010 Ye a r Indonesia Korea, Rep. Malaysia Thailand 40 50 35 45 30 40 25 Savigs (% of GDP) Savigs 35 (% of GDP) Savigs 20 30 15 60 65 70 55 60 65 70 3RSXODWLRQ í Figure 18: Impact of composition of Figure 19: Impact of wages on savings in demographics on savings in Asia China (1963-2009) 2 1 6DYLQJ 0 -1 Investment -2 Age Distribution Age Distribution Coefficients -3 0-14 20 - 24 30 - 34 40 - 44 50 - 54 60 - 64 6RXUFH %RVZRUWKDQG&KRZGRURZ5HLFK 6RXUFH &XUWLV/XJDXHUDQG0DUN 20 Economic Survey 2018-19 Volume 1 enough. As demographics and wages are the UHFRJQLVHV D VWDUWOLQJ IDFW 'ZDUIV ZKLFK major factors that drive savings, policymakers ZH GH¿QH DV VPDOO ¿UPV WKDW QHYHU JURZ REWDLQDNH\GHJUHHRIIUHHGRP6SHFL¿FDOO\ beyond their small size, dominates the Indian WKH WZR SDUWV RI WKH ¿QDQFLDO V\VWHP WKH economy and holds back job creation and savers and the borrowers, can be disentangled. productivity. Firms employing less than 100 As investment depends crucially on a low ZRUNHUV DUH FDWHJRUL]HG DV VPDOO DQG ¿UPV cost of capital, reducing real interest rates employing 100 or more workers as relatively need not necessarily lower savings when the ODUJH7KRXJKD¿UPHPSOR\LQJZRUNHUV demographics are favourable. At the same LVGH¿QLWHO\QRWODUJHLQWKHJOREDOFRQWH[W time, the reduction in real interest rates can they are relatively large in the Indian context. foster investment and thereby set in motion Firms that are both small and older than ten the virtuous cycle of investment, growth, \HDUVDUHFDWHJRUL]HGDVGZDUIVDVWKHVH¿UPV exports and jobs. have continued to be stunted in their growth despite surviving for more than 10 years.5 Role of job creation and earnings 1.54 Figure 20 shows the share of dwarfs in &KDSWHU LQ9ROXPH RI WKH 6XUYH\ WKHQXPEHURI¿UPVWKHVKDUHLQHPSOR\PHQW )LJXUH 6KDUHRIGZDUIVYHUVXVRWKHU¿UPVLQQXPEHUHPSOR\PHQWDQGSURGXFWLYLW\ 55.8 46.1 60.0 50.0 50.0 40.0 40.0 26.2 30.0 30.0 21.2 20.0 10.2 20.0 7.3 6.2 6KDUHLQZRUNHUV 10.0 4.7 5.5 10.0 0.0 6KDUHLQWRWDOQXPEHURIILUPV 0.0 WR WR $ERYH WR WR $ERYH )LUP6L]H 1XPEHURI(PSOR\HHV )LUPVL]H 1XPEHURI(PSOR\HHV 6KDUHRI 60.0 51.3 50.0 37.2 40.0 30.0 20.0 6KDUHLQ19$ 5.6 10.0 1.3 2.7 2.0 0.0 WR WR $ERYH )LUP6L]H 1XPEHURI(PSOR\HHV 6KDUHRI )LJXUH *URZWKRIMREVDQGSURGXFWLYLW\ZLWKDJHIRU¿UPVLQ,QGLD0H[LFRDQG86 8 4 6 4 2 2 Average Productivity Average Employment Average Employment 0 0 <5 10--14 20-24 30-34 ! <5 10--14 20-24 30-34 ! Age Age India 86 Mexico India 86 Mexico 6RXUFH +VLHKDQG.OHQRZ 1RWH <D[LVVKRZVWKHDYHUDJHHPSOR\PHQWJURVVYDOXHDGGHGDWHDFKDJHFRKRUWDVDPXOWLSOHRIWKHDYHUDJH HPSOR\PHQWJURVVYDOXHDGGHGZKHQWKH¿UPZDVOHVVWKDQ¿YH\HDUVROG 22 Economic Survey 2018-19 Volume 1 states. The labour law changes are crucial WKHDFFHOHUDWRU¿YH\HDUVDJRLWZRXOGKDYH also because they can enhance investment DOPRVWFHUWDLQO\EHHQKLWE\DPDMRU¿QDQFLDO 6XEUDPDQLDQDQG7XQJ 6XEUDPDQLDQ crisis in a few years. Painful as it may have and Megginson, 2018). seemed, the banking sector clean up and the IBC framework are important foundations 7KHUROHRIWKH¿QDQFLDOVHFWRU WKDW ZLOO QRZ UHDS EHQH¿WV ZKHQ WKH 1.57 The investment-led growth model investment-driven growth model is put into LPSOLHV D UDSLG H[SDQVLRQ LQ WKH ¿QDQFLDO motion as the incentives get aligned towards V\VWHPE\DIDFWRURIPDJQLWXGH±ERWKEDQNV EHWWHUTXDOLW\OHQGLQJ 6DUNDU6XEUDPDQLDQ and capital markets. In turn, this runs up DQG7DQWUL the risk that such a rapid expansion could 1.58 Now that the foundations for expansion EHGLVUXSWHGE\DPDMRU¿QDQFLDOFULVLVWKDW derails the savings-investment dynamic. This KDYHEHHQODLGLWLVQRZWLPHWRVLJQL¿FDQWO\ is no idle concern as illustrated by the Asian lower the cost of capital. Figure 22 shows &ULVLV RI 6RPH 6RXWK(DVW $VLDQ how the real rate of interest has increased FRXQWULHVDSSHDUHGWREHUHFUHDWLQJWKH(DVW VLJQL¿FDQWO\LQ,QGLDRYHUWKH\HDUV,QIDFW Asian miracle in the nineties, but were unable a cross-country comparison shows that the to sustain the virtuous cycle because of large cost of capital remains quite high in India scale misallocation of capital. Our own (see Figure 23), which affects investment experience of rapid credit expansion from prospects in the country. 2006 to 2012 illustrates the same risk, where The risk-return trade-off in the the quality of credit sharply deteriorated economy when the quantity was expanded. In this context, recent efforts to clean up the banks $QRWKHU DVSHFW WKDW FRQVWUDLQV WKH and establish a bankruptcy process should savings-investment driven model for growth, be seen as valuable investment that must be jobs and exports pertains to the incentive completed. If India had attempted to press structure prevailing for risk-taking in the Figure 22: Real rates of interest (Jan 2012 – May 2019) 8 7 6 5 6%, 4 3 2 1 Real Base Rate - 0 -1 -2 Jan-12 Jan-13 Jan-18 Jan-14 -DQ Jan-15 Jan-16 Jan-17 6HS 6HS 6HS 6HS 6HS 6HS 6HS May-13 May-17 May-12 May-18 May-14 0D\ May-15 May-16 6RXUFH 6WDWH%DQNRI,QGLDDQG6XUYH\&DOFXODWLRQV Shifting Gears: Private Investment as the Key Driver of Growth, Jobs, Exports and Demand 23 Figure 23: Cross-country comparison of Cost of Capital across some sectors 5HDO(VWDWH *HQHUDO'LYHUVLILHG Retail (Grocery and Food) 14.0% 20.0% 12.0% 15.0% 10.0% 8.0% 10.0% 6.0% 4.0% 5.0% 2.0% 0.0% 0.0% India China 86 (XURSH Japan India China 86 (XURSH Japan Trucking (QJLQHHULQJ&RQVWUXFWLRQ 25.0% 12.0% 20.0% 10.0% 8.0% 15.0% 6.0% 10.0% 4.0% 5.0% 2.0% 0.0% 0.0% India China 86 (XURSH Japan India China 86 (XURSH Japan 6RXUFH 'DPRGDUDQ economy. The following aspects of the risk- to foster investment. return trade-off need attention. 1.61 Optimal tax policy plays a crucial role 1.60 As investment represents a forward- in this regard. Countries across the world looking activity, investors eventually make recognise the need to evolve tax system that their decisions to invest based on the risk- can foster innovation. Therefore, tax policy adjusted return they expect. In other words, and its implementation for start-ups must be if two projects offer the same return but rationalised to foster innovative investments one of them is riskier, then investors choose LQWKH,QGLDQHFRQRP\6HYHUDOVWXGLHVKDYH the less risky project to invest. Therefore, also suggested that capital gains tax can systematically lowering the risks faced by KDYHVLJQL¿FDQWHFRQRPLFFRQVHTXHQFHVIRU investors in India is critical for the success individual investors in terms of its lock-in of the investment-driven model for economic effects and associated deterring incentives growth. Risk pertains to the possibilities of to use capital gains into riskier investments upside, when a project performs well, and 0HDGH 'HVLJQ RI RSWLPDO WD[ GRZQVLGH ZKHQ WKH SURMHFW IDLOV 6R WKH SROLF\DOVRDLPVWRUDLVHUHYHQXHHI¿FLHQWO\ implementation of the IBC is crucial in this DQG IDLUO\ ZKLOH HQFRXUDJLQJ WKH ERQD¿GH regard as it puts into process a framework for WD[SD\HUV DQG SXQLVKLQJ WKH PDOD¿GH RQHV UHFRQ¿JXUDWLRQRIDVVHWVIROORZLQJEXVLQHVV However, achieving this optimality is not an failure. However, the after-tax return for easy task. Therefore, to foster investment, successful projects crucially affects the risk- getting this balance right is extremely critical return trade-off and thereby becomes critical in the Indian context. 24 Economic Survey 2018-19 Volume 1 1.62 Growth in the new economy cannot be 1.63 Ranked third in the world in the start- fostered without an ecosystem that rewards up ecosystem, a growing number of domestic innovation and entrepreneurship (Acharya Indian enterprises are developing solutions DQG 6XEUDPDQLDQ $FKDU\D %DJKDL aimed at managing and solving urban DQG6XEUDPDQLDQ &KDYDHWDO challenges. While a majority of these are tech- 6DSUD6XEUDPDQLDQDQG6XEUDPDQLDQ start-ups concerned with e-commerce and 6WDUWXSV DQG LQQRYDWLYH YHQWXUHV consumer products and services, 2018 was IDFH VLJQL¿FDQWO\ JUHDWHU XQFHUWDLQW\ WKDQ touted as the year of food start-ups. Figure 24 WUDGLWLRQDO ³EULFNDQGPRUWDU´ ¿UPV Figure 24: Trends in India’s start-ups (2018) &ƵŶĚƌĂŝƐŝŶŐ;sĂůƵĞ EŽ͘ŽĨsĞĂůƐ &ŝƌŵƐƚŚĂƚƌĂŝƐĞĚŵŽƐƚ ^ĞĐƚŽƌƐƚŚĂƚƌĂŝƐĞĚ ΨďŶͿ ;sŽůƵŵĞͿ ĐĂƉŝƚĂůŝŶϮϬϭϴ;ΨďŶͿ ŵŽƐƚĐĂƉŝƚĂůŝŶϮϬϭϴ ϴ ϳ͘ϱ ϲϬϬ ;ΨďŶͿ KzKZŽŽŵƐ ϳ Ϭ͘ϵ ZĞƚĂŝů Ϯ͘Ϭϵ ϱϬϬ ϰϳϳ ϰϯϵ LJũƵΖƐůĂƐƐĞƐ Ϭ͘ϱ &ŽŽĚ ϲ ϭ͘ϲϱ WĂLJƚŵDĂůů ϰϬϬ ϯϲϬ Ϭ͘ϰϱ &ŝŶdĞĐŚ ϭ͘ϰ ϱ ϰ͘ϯ ŽŵĂƚŽ Ϭ͘ϯϳ ŶƚĞƌƉƌŝƐĞ͙ ϭ͘ϮϮ ϰ ϯ͘ϱ ϯϬϬ ^ǁŝŐŐLJ Ϭ͘ϯϭ ƵƚŽ Ϭ͘ϲϳ ϯ ϮϬϬ WĂLJƚŵ Ϭ͘ϯ ,ĞĂůƚŚdĞĐŚ Ϭ͘ϱϵ Ϯ ŝŐĂƐŬĞƚ Ϭ͘ϯ ĚdĞĐŚ Ϭ͘ϱϳ ϭϬϬ ϭ hĚĂĂŶ Ϭ͘Ϯϴ ŶĞƌŐLJ Ϭ͘ϱϮ Ϭ Ϭ WŝŶĞůĂďƐ Ϭ͘Ϯ ƌƚŝĨŝĐŝĂů͙ Ϭ͘ϰϮ ϮϬϭϲ ϮϬϭϳ ϮϬϭϴ ϮϬϭϲ ϮϬϭϳ ϮϬϭϴ WŽůŝĐLJĂnjĂĂƌ Ϭ͘Ϯ DŽďŝůĞ Ϭ͘ϯϴ Unicorn Club Unicorn Aspirers Mergers and Acquisitions Total Post- Time taken Total Post- )XQGLQJ EQ money Target Acquired 9DOXH )XQGLQJ EQ money to become YDOXDWLRQ by bn) YDOXDWLRQ an bn) Flipkart Walmart 16 bn) unicorn(yrs) Rivigo 0.17 Embibe RIL 0.18 5+6 Billdesk 0.16 0.83 Saavn RIL 0.10 BookMyShow 0.23 0.78 Ridlr Ola Cabs 0.05 Flipkart 6.1 15.51 3 BigBasket 0.56 0.72 Minjar Nutanix 0.05 Mettl Mercer 0.40 OYO Rooms 1.35 4.18 5 Delhivery 0.26 0.60 Sharechat 0.12 0.50 TicketNew PayTm 0.40 Ola 2.8 4 2 UrbanClap 0.11 0.47 Liv.ai Flipkart 0.40 Byju's 0.74 3.02 4 CarDekho 0.28 0.45 Tapzo Amazon 0.40 Classes CarTrade 0.25 0.40 Walnut CapitalFloat 0.30 Snapdeal 1.8 2.47 3 CapitalFloat 0.11 0.35 Paytm Mall 0.653 2.01 Less than 1 Zomato 0.58 2 5 Swiggy 0.46 1.21 3 Quikr 0.37 0.88 7 PolicyBazaar 0.37 0.44 10 6RXUFH 6DUNDU Shifting Gears: Private Investment as the Key Driver of Growth, Jobs, Exports and Demand 25 but surely emerging. Figure 25 highlights this for private investment, especially in the fact as private investment into B2C start-ups new economy, is therefore critical to enable is much higher than that into B2B start-ups. the virtuous cycle of investment, demand, 1.64 Continuing the creation of an ecosystem exports, growth and jobs. Figure 25: Funding in B2C startups higher than in B2B startups 10 8 7 6 5 4 86ELOOLRQ 3 2 1 0 2014 2015 2016 2017 2018 B2B B2C 6RXUFH *R\DO CHAPTER AT A GLANCE ¾ 'XULQJWKHODVW¿YH\HDUV,QGLD¶VHFRQRP\KDVSHUIRUPHGZHOO%\RSHQLQJXSVHYHUDOSDWKZD\V IRUWULFNOHGRZQWKHJRYHUQPHQWKDVHQVXUHGWKDWWKHEHQH¿WVRIJURZWKDQGPDFURHFRQRPLF stability reach the bottom of the pyramid. ¾ 7RDFKLHYHWKHREMHFWLYHRIEHFRPLQJD86WULOOLRQHFRQRP\E\,QGLDQHHGVWRVXVWDLQ DUHDO*'3JURZWKUDWHRI,QWHUQDWLRQDOH[SHULHQFHHVSHFLDOO\IURPKLJKJURZWK(DVW$VLDQ economies, suggests that such growth can only be sustained by a “virtuous cycle” of savings, investment and exports catalysed and supported by a favourable demographic phase. Investment, especially private investment, is the “key driver” that drives demand, creates capacity, increases labour productivity, introduces new technology, allows creative destruction and generates jobs. ¾ ([SRUWVPXVWIRUPDQLQWHJUDOSDUWRIWKHJURZWKPRGHOEHFDXVHKLJKHUVDYLQJVSUHFOXGHGRPHVWLF FRQVXPSWLRQDVWKHGULYHURI¿QDOGHPDQG6LPLODUO\MREFUHDWLRQLVGULYHQE\WKLVYLUWXRXV cycle. While the claim is often made that investment displaces jobs, this remains true only when YLHZHGZLWKLQWKHVLORRIDVSHFL¿FDFWLYLW\:KHQH[DPLQHGDFURVVWKHHQWLUHYDOXHFKDLQFDSLWDO investment fosters job creation as production of capital goods, research & development and supply chains generate jobs. ¾ ,Q SRVWXODWLQJ WKH DERYH JURZWK PRGHO WKH 6XUYH\ GHSDUWV IURP WUDGLWLRQDO $QJOR6D[RQ thinking by viewing the economy as being either in a virtuous or a vicious cycle, and thus never in equilibrium. ¾ By presenting data as a public good, emphasizing legal reform, ensuring policy consistency, DQG HQFRXUDJLQJ EHKDYLRXU FKDQJH XVLQJ SULQFLSOHV RI EHKDYLRXUDO HFRQRPLFV WKH 6XUYH\ aims to enable a self-sustaining virtuous cycle. Key ingredients include a focus on policies that QRXULVK060(VWRFUHDWHPRUHMREVDQGEHFRPHPRUHSURGXFWLYHUHGXFHWKHFRVWRIFDSLWDODQG rationalise the risk-return trade-off for investments. 26 Economic Survey 2018-19 Volume 1 REFERENCES Chakrabarti, Rajesh, Krishnamurthy V. 6XEUDPDQLDQ DQG 6HVKD 0HND Acharya, Viral V. and Krishnamurthy V. ³/RFDOL]DWLRQ RI )', ÀRZV (YLGHQFH RQ 6XEUDPDQLDQ ³%DQNUXSWF\ &RGHV Infrastructure as a critical determinant and Innovation,” 7KH 5HYLHZ RI )LQDQFLDO RI )',´ -RXUQDO RI /DZ )LQDQFH DQG 6WXGLHV $FFRXQWLQJ 2(1), 205-246. Acharya, Viral, Ramin, Baghai and &KDYD6$OH[DQGHU2HWWO$MD\6XEUDPDQLDQ .ULVKQDPXUWK\ 9 6XEUDPDQLDQ DQG .ULVKQDPXUWK\ 9 6XEUDPDQLDQ “Labor Laws and Innovation,” -RXUQDO RI ³%DQNLQJ 'HUHJXODWLRQ DQG ,QQRYDWLRQ´ /DZDQG(FRQRPLFV -RXUQDO RI )LQDQFLDO (FRQRPLFV Acharya, Viral, Ramin, Baghai and .ULVKQDPXUWK\ 9 6XEUDPDQLDQ &XUWLV &KDGZLFN & 6WHYHQ /XJDXHU DQG ³:URQJIXO'LVFKDUJH/DZVDQG,QQRYDWLRQ´ 1HOVRQ&0DUN³'HPRJUDSKLF3DWWHUQV 7KH5HYLHZRI)LQDQFLDO6WXGLHV 27(1). DQG+RXVHKROG6DYLQJLQ&KLQD´$PHULFDQ Attanasio, Orazio P., Lucio Picci, and (FRQRPLF -RXUQDO 0DFURHFRQRPLFV $QWRQHOOR(6FRUFX³6DYLQJ*URZWK DQG,QYHVWPHQW $0DFURHFRQRPLF$QDO\VLV &XUWLV &KDGZLFN & 6WHYHQ /XJDXHU DQG Using a Panel of Countries,” 7KH5HYLHZRI 1HOVRQ&0DUN³'HPRJUDSKLFVDQG (FRQRPLFVDQG6WDWLVWLFV aggregate household saving in Japan, China, and India.” -RXUQDO RI 0DFURHFRQRPLFV %DNHU6FRWW51LFKRODV%ORRPDQG6WHYHQ & -'DYLV³0HDVXULQJ(FRQRPLF3ROLF\ Uncertainty.” 7KH 4XDUWHUO\ -RXUQDO RI 'DPRGDUDQ$VZDWK ³'DWD &XUUHQW´ (FRQRPLFV ± 'DPRGDUDQ 2QOLQH EORJ -DQXDU\ KWWS pages.stern.nyu.edu/~adamodar/New_ %ORRP 'DYLG ( DQG -HIIUH\ * Home_Page/datacurrent.html. :LOOLDPVRQ ³'HPRJUDSKLF7UDQVLWLRQV DQG(FRQRPLF0LUDFOHVLQ(PHUJLQJ$VLD´ (XURSHDQ &RPPLVVLRQ (IIHFWLYHQHVV RI WD[ 7KH :RUOG %DQN (FRQRPLF 5HYLHZ LQFHQWLYHV IRU YHQWXUH FDSLWDO DQG EXVLQHVV ± DQJHOVWRIRVWHUWKHLQYHVWPHQWRI60(VDQG VWDUWXSV %UXVVHOV (XURSHDQ &RPPLVVLRQ %ORRP 'DYLG ( 'DYLG &DQQLQJ 5LFKDUG KWWSV HFHXURSDHXWD[DWLRQBFXVWRPV . 0DQV¿HOG DQG 0LFKDHO 0RRUH VLWHVWD[DWLRQ¿OHV¿QDOBUHSRUWBBWD[XGB ³'HPRJUDSKLF FKDQJH VRFLDO VHFXULW\ venture-capital_business-angels.pdf. systems, and savings.” -RXUQDORI0RQHWDU\ (FRQRPLFV Feldstein, Martin, and Charles Horioka. ³'RPHVWLF VDYLQJ DQG LQWHUQDWLRQDO Bosworth, Barry, and Gabriel Chodorow- FDSLWDO ÀRZV´ (FRQRPLF -RXUQDO 5HLFK ³6DYLQJ DQG 'HPRJUDSKLF &KDQJH 7KH *OREDO 'LPHQVLRQ´ 6651 KWWSV VVUQFRPDEVWUDFW )X ;LDRODQ DQG 9 1 %DODVXEUDPDQ\DP ³([SRUWV IRUHLJQ GLUHFW LQYHVWPHQW &DUUROO&KULVWRSKHU'DQG'DYLG1:HLO DQGHPSOR\PHQW 7KHFDVHRI&KLQD´:RUOG ³6DYLQJDQGJURZWK DUHLQWHUSUHWDWLRQ´ (FRQRP\ &DUQHJLH5RFKHVWHU &RQIHUHQFH 6HULHV RQ 3XEOLF3ROLF\ Gourinchas, Pierre-Olivier, and Olivier Shifting Gears: Private Investment as the Key Driver of Growth, Jobs, Exports and Demand 27 -HDQQH³&DSLWDO)ORZVWR'HYHORSLQJ Cities, and New Work.” 5HYLHZRI(FRQRPLFV &RXQWULHV 7KH $OORFDWLRQ 3X]]OH´ 7KH DQG6WDWLVWLFV ± 5HYLHZ RI (FRQRPLF 6WXGLHV 1515. /XFDV 5REHUW ( -U ³:K\ GRHVQ¶W FDSLWDO ÀRZ IURP ULFK WR SRRU FRXQWULHV"´ *R\DO 0DOLQL ³+RZ WKH FHQWUH RI $PHULFDQ(FRQRPLF5HYLHZ ± gravity of India’s startup ecosystem is 0HDGH -DQHW $ ³7KH ,PSDFW RI shifting towards B2B startups.” (FRQRPLF 'LIIHUHQW&DSLWDO*DLQV7D[5HJLPHVRQWKH 7LPHV 0DUFK KWWSV HFRQRPLFWLPHV /RFN,Q (IIHFW DQG 1HZ 5LVN\ ,QYHVWPHQW indiatimes.com/small-biz/startups/features/ 'HFLVLRQV´ 7KH $FFRXQWLQJ 5HYLHZ how-the-centre-of-gravity-of-indias-startup- 406-431. ecosystem-is-shifting-towards-b2b-startups/ DUWLFOHVKRZFPV"IURP PGU Milkman, Katherine L., Mary Carol Mazza, /LVD / 6KX &KLD-XQJ 7VD\ DQG 0D[ +DVNHO -RQDWKDQ ( 6RQLD & 3HUHLUD H. Bazerman. 2012. “Policy Bundling DQG 0DWWKHZ - 6ODXJKWHU ³'RHV WR 2YHUFRPH /RVV $YHUVLRQ $ 0HWKRG inward foreign direct investment boost the for Improving Legislative Outcomes.” SURGXFWLYLW\RIGRPHVWLF¿UPV"´7KH5HYLHZ 2UJDQL]DWLRQDO %HKDYLRU DQG +XPDQ RIHFRQRPLFVDQGVWDWLVWLFV 'HFLVLRQ3URFHVVHV +D\HN )ULHGULFK $XJXVW YRQ ³7KH 3HURWWL (QULFR & /DL[LDQJ 6XQ DQG Pretence of Knowledge.” Prize Lecture, /LDQJ =RX ³6WDWH2ZQHG YHUVXV 7KH 6YHULJHV 5LNVEDQN 3UL]H LQ (FRQRPLF 7RZQVKLSDQG9LOODJH(QWHUSULVHVLQ&KLQD´ 6FLHQFHVLQ0HPRU\RI$OIUHG1REHOKWWSV &RPSDULWLYH(FRQRPLF6WXGLHV www.nobelprize.org/prizes/economic- VFLHQFHV KD\HNOHFWXUH Ramos, Gabriela. 2017. “We need an HPSRZHULQJ QDUUDWLYH´ 2(&' ,QVLJKWV Higgins Matthew, and Jeffrey .G. Williamson. EORJ -XQH KWWS RHFGLQVLJKWV ³$JH VWUXFWXUH G\QDPLFV LQ$VLD DQG org/2017/06/23/we-need-an-empowering- dependence on foreign capital.” 3RSXODWLRQ narrative/. DQG'HYHORSPHQW5HYLHZ 5RGULN 'DQL ³6DYLQJV 7UDQVLWLRQV´ Hsieh, Chang-Tai, and Peter J. Klenow. :RUOG %DQN (FRQRPLF 5HYLHZ 2014. “The Life Cycle of Plants in India 507. and Mexico.” 7KH 4XDUWHUO\ -RXUQDO RI 5RGULN 'DQL ³6HFRQG WKRXJKWV RQ (FRQRPLFV ± economics rules.” -RXUQDO RI (FRQRPLF -LQ .H\X ³,QGXVWULDO 6WUXFWXUH DQG 0HWKRGRORJ\ Capital Flows.” $PHULFDQ(FRQRPLF5HYLHZ Romer, Paul. 2015. “Mathiness in the theory ± of economic growth.” $PHULFDQ (FRQRPLF Lee, Ronald, Andrew Mason, and Tim 5HYLHZ 0LOOHU ³/LIH &\FOH 6DYLQJ DQG WKH 6DQGUL'DPLDQR³*URZWKDQGFDSLWDO 'HPRJUDSKLF 7UDQVLWLRQ 7KH &DVH RI ÀRZVZLWKULVN\HQWUHSUHQHXUVKLS´$PHULFDQ Taiwan.” 3RSXODWLRQ DQG 'HYHORSPHQW (FRQRPLF -RXUQDO 0DFURHFRQRPLFV 5HYLHZ 102-123. Lin, Jeffrey. 2011. “Technological Adaptation, 6DSUD + $MD\ 6XEUDPDQLDQ DQG 28 Economic Survey 2018-19 Volume 1 .ULVKQDPXUWK\ 9 6XEUDPDQLDQ of markets or failure of regulation? ³&RUSRUDWH *RYHUQDQFH DQG ,QQRYDWLRQ 0DFURHFRQRPLFV DQG )LQDQFH LQ (PHUJLQJ 7KHRU\DQG(YLGHQFH´-RXUQDORI)LQDQFLDO 0DUNHW(FRQRPLHV DQG4XDQWLWDWLYH$QDO\VLV ± 6XEUDPDQLDQ.ULVKQDPXUWK\9DQG:LOOLDP 6DUNDU 5DQMX ³:LWK UHFRUG FDSLWDO 0HJJLQVRQ ³(PSOR\PHQW 3URWHFWLRQ raising, 2018 was year of transformation for Laws and Privatization,” -RXUQDORI/DZDQG start-ups.” %XVLQHVV 6WDQGDUG 'HFHPEHU (FRQRPLFV KWWSV ZZZEXVLQHVVVWDQGDUGFRP article/companies/with-record-capital- 6XEUDPDQLDQ.ULVKQDPXUWK\9DQG)UHGHULFN raising-2018-was-year-of-transformation- Tung, 2016. “Law and Project Finance,” 25(1), IRUVWDUWXSV BKWPO -RXUQDO RI )LQDQFLDO ,QWHUPHGLDWLRQ 154-177. 6DUNDU $ .ULVKQDPXUWK\ 9 6XEUDPDQLDQ DQG 3UDVDQQD 7DQWUL ³(IIHFWV RI :HL rdksZ¿izfr"B% Jqr;ksfofHkUukuSdks Íf"k;ZL; era izek.ke~A We cannot rely totally on rational thinking to gain information, as it is not without its bias. Decisions made by real people often deviate from the impractical robots theorized in classical economics. Drawing on the psychology of human behaviour, behavioural economics provides insights to ‘nudge’ people towards desirable behaviour. This chapter illustrates how the Swachh Bharat Mission (SBM) and the Beti Bachao Beti Padhao (BBBP) have successfully employed behavioural insights. Using such learning, the chapter lays out an ambitious agenda for social change: (i) from BBBP to BADLAV (Beti Aapki Dhan Lakshmi Aur Vijay Lakshmi); (ii) from Swachh Bharat to Sundar Bharat; (iii) from “Give it up” for the LPG subsidy to “Think about the Subsidy”; and (iv) from tax evasion to tax compliance. First, a key principle of behavioural economics is that while people’s EHKDYLRXULVLQÀXHQFHGVLJQL¿FDQWO\E\VRFLDOQRUPVXQGHUVWDQGLQJWKHGULYHUVRI these social norms can enable change. In India, where social and religious norms SOD\VXFKDGRPLQDQWUROHLQLQÀXHQFLQJEHKDYLRXUEHKDYLRXUDOHFRQRPLFVFDQ WKHUHIRUHSURYLGHDYDOXDEOHLQVWUXPHQWIRUFKDQJH6REHQH¿FLDOVRFLDOQRUPV FDQEHIXUWKHUHGE\GUDZLQJDWWHQWLRQWRSRVLWLYHLQÀXHQFHUVHVSHFLDOO\IULHQGV neighbours that represent role models with which people can identify. Second, as people are given to tremendous inertia when making a choice, they prefer sticking to the default option. By the nearly costless act of changing the default to overcome this inertia, desired behaviour can be encouraged without affecting SHRSOH¶VFKRLFHV7KLUGDVSHRSOH¿QGLWGLI¿FXOWWRVXVWDLQJRRGKDELWVUHSHDWHG reinforcements and reminders of successful past actions can help sustain changed behaviour. THE INFLUENCE SPECTRUM children, respecting the human rights of OF PUBLIC POLICY fellow citizens or saving for retirement. 6RPH SROLFLHV VXEWO\ LQÀXHQFH E\ IRVWHULQJ 2.1 Public policy affects all aspects of our the right incentives while others mandate OLYHV3XEOLFSROLF\LQÀXHQFHVSHRSOHWRDFWLQ desired behaviour or ban undesirable ones. a socially desirable way, be it driving safely, 2.2 Public policies can, therefore, be conserving natural resources, educating graded on a spectrum capturing how strongly 30 Economic Survey 2018-19 Volume 1 WKH\ LQÀXence (or coerce) behaviour (see incentivize good behaviour or dis-incentivize Figure 1). On one extreme is laissez faire, bad behaviour, such as subsidies for i.e. doing nothing and leaving individuals/ renewable energy and taxes on tobacco. ¿UPVWRFKDUWWKHLURZQFRXUVHLaissez faire works well when markets achieve socially 2.3 Recently, behavioural economists have desirable outcomes on their own. Where GLVFRYHUHG WKH HI¿FDF\ RI D QHZ FODVV RI markets fail, laissez faire fails. For instance, “nudge” policies that lie between laissez faire and incentives. Such policies leverage insights LQGLYLGXDOV¿UPV LQ D IUHH PDUNHW ZRXOG not restrain pollution. Public policy – in the IURPKXPDQSV\FKRORJ\WRLQÀXHQFHWKHFKRLFH form of regulation – mandates people to act architecture of people. Nudge policies gently in a socially desirable manner. Sandwiched steer people towards desirable behaviour even between these extremes are policies that while preserving their liberty to choose. )LJXUH )URP0LQLPDO,QÀXHQFHWR&RHUFLRQ Laissez faire Nudge Incentivize Mandate 2.4 Adam Smith, in his book the ‘Theory 2.5 As individuals suffer from tremendous of Moral Sentiment’, noted that a wide range inertia when they have to make a choice, they of human choices are driven and limited by tend to stick to the default option (Thaler our mental resources i.e., cognitive ability, and Sunstein 2008; Samson 2014). The attention and motivation. Behavioural nearly costless act of changing the default economics relies on this essential insight on an enrolment form harvests this inertia from human psychology that real people for people’s own good. At the same time, do not always behave like robots, rational this form of paternalism preserves people’s and unbiased individuals that form the right to choose as the choice architecture basis of classical economic theory called makes it easy for an individual to opt out “homo economicus” (Thaler, 2000). To a of the scheme. For example, studies have homo economicus, the choice architecture shown that enrolment rates in a healthcare or is irrelevant, as she will make the optimal retirement savings plan improve dramatically choice irrespective of the way the choices if the plan is designed as an opt-in by default are presented to her. However, real people embedded with the option to opt-out, as respond to the choice architecture. For opposed to voluntary enrolment by opting in. example, a large fraction of individuals 2.6 Understanding these principles of opt for the default choice, irrespective of behavioural economics, therefore, can bridge their intrinsic preferences. This is because the gap between people’s preferences and individuals suffer from a cognitive bias the choices they make, and thereby enable called “anchoring bias”, viz., once a default informed policymaking. Many governments, option is presented to them, they anchor including the U.S., the U.K. and Australia, on to it (Tversky and Kahneman, 1974). have set up dedicated units to use behavioural Anchoring bias, along with several others insights for effective policymaking. that we describe in this chapter, drives a Innovative interventions across the world wedge between people’s intrinsic preferences that utilize the principles of behavioural and the choices they eventually make. economics are tabulated in Table 1. Policy for Homo Sapiens, Not Homo Economicus 31 Table 1: Innovative Global Behaviour Change Interventions Sector Problem Intervention Observations Pension Policy People tend to go with Instead of employees Automatic enrolment (USA) defaults. When the default checking a box to enrol in increased savings by up to in a saving plan is non- savings plans, employees 40 per cent (Beshears et. al, enrolment, most people check a box to not enrol; 2005) do not enrol even when i.e. the default option is to they want to. be enrolled. Tax Compliance People need reminders and People were sent People who owed most tax (UK) positive reinforcement to variations of text were also most responsive sustain socially desirable messages on how their to messages asking them to behaviour. taxes make a difference to pay. Compliance increased public services. without increase in tax surveillance costs (UK &DELQHW2I¿FH%HKDYLRXUDO Insights Team, 2012). Agriculture Inertia makes people To tackle farmers’ Fertilizer use increased by (Africa) procrastinate important, procrastination in buying SHU FHQW 'XÀR HW DO time-sensitive decisions fertilizer (possibly because 2011). Early home delivery even when they are aware of the hassle of traveling increased fertilizer use by of the consequences of to town), home delivery 70 per cent. The effect was delay. of fertilizer early in the as much as a 50 per cent season was attempted. price subsidy would have accomplished. Savings People save much less People were offered Nearly 30 per cent of those (Philippines) than they want to because specially designed savings who were offered the of lack of adequate self- accounts that locked up account adopted it. Saving control in spending. IXQGVXQWLODVHOIVSHFL¿HG balance increased by 81 per target was met. cent in a year (Ashraf et al., 2006). Savings (Bolivia, People save much less People were sent periodic Reminders increased the Peru, Philippines) than they want to because and timely reminders amount saved by six per of inertia and lack of about their self- cent (Karlan et al., 2010). positive reinforcement. determined saving goals. Education Many parents Parents were informed Information dissemination (Madagascar) underestimate the returns about the average income increased children’s test to spending another year gains from spending scores by 0.37 standard at school. They think one more year in school deviations, particularly schooling is worthless for children from for those parents who had unless the child is able backgrounds like their underestimated the return to to go all the way through own. education (Nguyen, 2008). high school. Many allow their children to drop out with even fewer years of schooling than they can afford. 32 Economic Survey 2018-19 Volume 1 2.7 Behavioural economics is, however, nudges. In fact, many incentive and mandate- not a panacea to policymaking; its potential based policies may be clubbed with a nudge needs to be understood and put in perspective. HIIHFWWRLQFUHDVHWKHLUHI¿FDF\ Nudge policies cannot and should not supplant every incentive-based and mandate-based SUCCESSFUL APPLICATIONS policy. For example, a policy that merely OF BEHAVIOURAL INSIGHTS IN nudges people to refrain from assaulting INDIA others will fail as such situations warrant 2.8 In India, policies to alter behaviour strict decree or, at least, a stronger push than a KDYH VSDQQHG WKH LQÀXHQFH VSHFWUXP DV LV mere nudge. However, the majority of public shown in Figure 2. policy issues are amenable to incorporating )LJXUH 3ROLFLHVVSDQQLQJWKHLQÀXHQFHVSHFWUXPLQ,QGLD Level of influence Policy Laissez faire Nudge Incentivize Mandate Give It Up Aadhaar Jan DhanYojana Beti Bachao, Beti Padhao Swachh Bharat Mission Taxes on tobacco Compulsory voting in panchayat elections in some states Ban on alcohol in some states 2.9 Many Indian schemes that employ Swachh Bharat Mission (SBM) insights from behavioural economics have nd met with success. The Swachh Bharat 2.10 SBM was launched on 2 October, Mission (SBM) and the Beti Bachao, Beti 2014 to achieve universal sanitation coverage. Padhao (BBBP) scheme are cases in point. ,W LV QRW WKH ¿UVW SURJUDPPH WR DGGUHVV Behavioural economists have long touted sanitation concerns. However, there were no the power of the “social norm” as most dramatic shifts in the access rates until SBM people want to behave or be seen to behave DVLVVKRZQLQ)LJXUH6%0LVWKH¿UVWRQH in congruity with these norms (Dolan et to emphasize behaviour change as much as, if al., 2010). People are more likely to stop not more than, construction of toilets. Within defecating in the open if their neighbours stop ¿YH\HDUVRIWKHODXQFKRI6%0KRXVHKROG or are more likely to value their girl children access to toilets has increased to nearly 100 if that is touted as the social norm. per cent in all states. Policy for Homo Sapiens, Not Homo Economicus 33 Figure 3: National Sanitation Coverage before and after SBM Source: Ministry of Drinking Water and Sanitation (MoDWS) Note: Data for 1981-2011 is as per Census. 2.11 SBM has achieved success in not status of 90.7 per cent of villages that were only providing toilets but also in ensuring SUHYLRXVO\GHFODUHGDQGYHUL¿HGDV2')E\ that these toilets are used. An independent various districts/states. This is also evident YHUL¿FDWLRQ RI 6%0 WKURXJK WKH 1DWLRQDO in the maps/charts below depicting the state- Annual Rural Sanitation Survey (NARSS) wise increase in coverage of individual 2018-19 has found that 93.1 per cent of household latrines (IHHL) from 2015-16 to rural households had access to toilets, 96.5 2018-19 (Figure 4) and the percentage of per cent of the households in rural India villages in each state that have been declared who have access to a toilet use it. This re- DQGYHUL¿HG2') )LJXUH FRQ¿UPHGWKH2SHQ'HIHFDWLRQ)UHH 2') Figure 4: Coverage of Individual Household Latrine (IHHL) 2015-16 2018-19 Source: MoDWS 34 Economic Survey 2018-19 Volume 1 )LJXUH 9HUL¿HG2')9LOODJHV 2015-16 2018-19 Source: MoDWS 7KH DERYH ¿JXUHV KLJKOLJKW increased with behavioural nudges that push the tremendous success of SBM. As is female literacy rates up and discourage highlighted in Figure 2, the principles of early marriages of girls. In this respect, the behavioural economics were applied in BBBP scheme, which we describe next as SBM. Figures 6 to 8 examine the role of these a scheme aimed at empowering the girl principles in the success of SBM. Measures of child, complements SBM strongly as factors female literacy and early marriages of girls, related to gender empowerment are seen to which associate strongly with rigid social EHVLJQL¿FDQWO\FRUUHODWHGZLWKWRLOHWDFFHVV norms, correlate powerfully with access and and usage. This interplay can be effectively usage of toilets across states. This shows XVHG WR LPSURYH WKH HI¿FDF\ RI ERWK WKH that toilet access and usage can be suitably schemes. Figure 6: Correlation between Access to Toilets with Female Literacy and Female Age at Marriage Source: MoDWS, Census 2011, NFHS 2015-16 Policy for Homo Sapiens, Not Homo Economicus 35 Figure 7: Correlation between Use of Toilets (given access) with Female Literacy and Female Age at Marriage Source:MoDWS, Census 2011, NFHS 2015-16 Figure 8: Correlation between IHHL Coverage with Female Literacy and Female Age at Marriage Source: MoDWS, Census 2011, NFHS 2015-16 36 Economic Survey 2018-19 Volume 1 Box 1: Use of Behavioural insights in the SBM SBM, as a nation-wide cleanliness drive, was launched on 2nd October, 2014, the birthday of India’s most revered ‘role model’ Mahatma Gandhi. The day was chosen to leverage the values propagated by him and thereby create a mass movement on the lines of ‘satyagraha’ for a cleaner India. The symbol used for SBM invokes Gandhiji’s ideas. Behavioural economics emphasises the role of context LQ LQÀXHQFLQJ FKRLFHV DQG GHFLVLRQV ZKLFK KDV EHHQ effectively adopted by the SBM campaign. 7RLQLWLDWHEHKDYLRXUDOFKDQJHLQXVDJHRIWRLOHWVPRUHWKDQ¿YHODNKswachhagrahis, foot soldiers of the SBM, were recruited; the similarity with satyagrahis is intentional to reinforce the message. As each village has at least one swachhagrahi, who is a local, these swachhagrahis were able to leverage their social ties within their villages to effect change. People are more likely to listen to and emulate someone they know, which is why local ambassadors of change are more effective in getting through to people than mass media campaigns. Further, SBM relies on community-based approaches to sanitation. Behaviour change techniques such as Participatory Rural Appraisal and Community-led Total Sanitation induce people to come together, appraise their community’s open defecation situation and plan the next course of action. This makes sanitation a community-level concern rather than an obscure campaign of a distant JRYHUQPHQW1RQFRQIRUPHUVWKHUHIRUH¿QGWKHLUDFWPRUHYLVLEOHWRWKHLUFRPPXQLW\7KHIHDU RIFRPPXQLW\VFRUQRUDGHVLUHWR¿WLQRUERWKKDYHOHGPDQ\WRUHQRXQFHRSHQGHIHFDWLRQ SBM used yet another behavioural insight – that people internalize messages better when these messages make them feel a certain way. Arcane concerns about hygiene and disease appeal to few; it is natural that those who have defecated in the open all their lives without consequence would fail to absorb the message that open defecation can have deleterious effects. On the other hand, appealing to people’s emotions, for example by attaching a sense of disgust to open defecation, has a better chance of moving people to change. Many swachhagrahis delivered the message that open defecation is tantamount to eating one’s RZQH[FUHWDDVÀLHVVLWRQH[FUHWDOHIWLQRSHQVSDFHVDQGWKHQVLWRQIRRG7KHDFWRISURYRNLQJ disgust or shaming people for open defecation has been controversial; some have considered it disrespectful. That may well be the case, but it does not take away from the fact that campaigns that elicit emotional reactions are more effective than those that deliver plain, recondite messages. Beti Bachao, Beti Padhao (BBBP) in quick succession to arrest this trend. 2.13 As is well known, India’s child sex ratio 2.14 BBBP Scheme was launched on 22nd had been consistently falling for decades. January, 2015 to address the issue of decline Between the 2001 and 2011 censuses, 21 out in Child Sex Ratio and related issues of of 29 states registered a decline in child sex empowerment of girls and women. The 1 ratio. India’s sex ratio at birth (SRB) was FDPSDLJQZDVÀDJJHGIURP3DQLSDW+DU\DQD RQDVWHDG\GHFOLQHXQWLOWKH¿UVWGHFDGHRI which had the worst child sex ratio at 834 WKH WZHQW\¿UVW FHQWXU\ ZKHQ D QXPEHU RI among Indian states as compared with the initiatives, including BBBP, were launched national average of 919 (as per Census, 2011). ______1 Sex Ratio at Birth = (Total Number of Live Female Births/Total Number of Live Male Births)*1000 Policy for Homo Sapiens, Not Homo Economicus 37 The choice of Panipat in the battle against the to launch to reinforce the stress on gender socially ingrained bias against the girl child empowerment and establish the social norm was also symbolic through the association of ‘girls are valuable’. with the famous battles fought at Panipat in 1526, 1556 and 1761. As we highlight ,WLVRIFRXUVHGLI¿FXOWWRDWWULEXWHWKH improving child sex ratio to a single scheme, later, one of the principles of behavioural especially because awareness programmes economics is to adapt the message to match do not create results overnight. However, the “mental models” of people. The symbolism timing of the launch of these schemes and the captured by the choice of Panipat in Haryana inter-state variation in existing social norms KHOSHGVLJQL¿FDQWO\LQPDWFKLQJWKHPHVVDJH may be used to assess the impact of BBBP. to the relevant mental model. Consider the large states of Uttar Pradesh, 2.15 The scheme was initially launched in Madhya Pradesh, Rajasthan, Chhattisgarh, 100 districts in 2014-15, and was expanded Andhra Pradesh and Jharkhand, all of which to 61 additional districts in 2015-16. The had registered declining child sex ratios initiative was expanded to all districts of the between the 2001 and 2011 censuses. Around Country on March 8, 2018 from Jhunjunu, the launch of the BBBP in 2015-16, they Rajasthan. The date and location was had among the poorest sex ratios at birth, again selected carefully to ensure that the as evident in Figure 9. But by 2018-19, all symbolism behind the message matched these states showed a reversal of the trend, the relevant mental model. Rajasthan was registering an increase in SRB between 2015- chosen as the State improved by 34 points 16 and 2018-19 (Figure 10). BBBP has had an from 888 girls per 1000 boys in 2011 to 922 impact particularly on large states with very per 1000 boys in 2017-18 to indicate that poor child sex ratios – states that plausibly good performance receives a reward. Also, also needed the greatest pivot in their social International Women’s Day was chosen norms. Figure 9: Sex Ratio at Birth 2015-16 2018-19 Source: Derived from Health Management Information System (HMIS), Ministry of Health and Family Welfare 1RWH 65%¿JXUHVDUHFDOFXODWHGXVLQJDYHUDJHRI%%%3GLVWULFWV 38 Economic Survey 2018-19 Volume 1 Figure 10: States with an improvement in Sex Ratio at Birth from 2015-16 to 2018-19 Source: Derived from Health Management Information System(HMIS), Ministry of Health and Family Welfare 2.17 The impact of BBBP in the 161 districts 2015-16 to 2018-19. On an average, the sex where it was initially implemented is shown ratio for 161 districts has improved from 909 in Figure 11. The SRB has improved in 107 in 2015-16 to 919 in 2018-19. districts within a period of 4 years viz., from Figure 11: Change in Sex Ratio at Birth from 2015-16 to 2018-19 in 161 BBBP Districts Source: Derived from Health Management Information System (HMIS), Ministry of Health and Family Welfare Policy for Homo Sapiens, Not Homo Economicus 39 Box 2: Effective Use of “Social norm” in BBBP The success of the BBBP Scheme demonstrates a powerful use of WKHLQVLJKWRQµVRFLDOQRUP¶LQLWV 6HO¿HZLWK'DXJKWHU LQLWLDWLYH This scheme was launched to address a highly imbalanced child sex ratio in India. People’s attitude towards the girl child needed to change – people needed to stop viewing girls as burdens and start FHOHEUDWLQJWKHPLQVWHDG7KHVHO¿HFDPSDLJQVKRZFDVHGH[DPSOHV of parents around the country who were doing exactly that. The celebration of the girl child quickly became the norm. Most people ZDQWHGWRFRQIRUPDQGPRUHDQGPRUHSDUHQWVSRVWHGVHO¿HVZLWK their girls. Started by one proud father in a village in Haryana, the FDPSDLJQZHQWYLUDODQG6HO¿H:LWK'DXJKWHUEHFDPHDZRUOGZLGH hit. 7ZRHOHPHQWVHQDEOHGWKHFDPSDLJQ¶VVXFFHVV ¿UVWWHOOLQJSHRSOHZKDWWKHQRUPLVDQGVHFRQG showcasing the thousands of other people who were acting in line with that norm. The strategy addresses a cognitive bias called ‘failure bias’ (Baumeister and Bratslavsky, 2001). The failure bias is the tendency to focus on failures rather than successes, mostly because failures have greater visibility. Because failures get the spotlight, people tend to think that failing is the norm, or at least that failing is more prevalent than it really is. Therefore, in the context of BBBP, focus must be on people who treat their girls fairly; this corrects the failure bias and makes the social norm of fair treatment of girls unequivocally clear. BBBP’s work is far from over, RI FRXUVH DV SRVWLQJ D VHO¿H LV not tantamount to subverting entrenched orthodox mind-sets overnight, but its leverage of social norms is certainly a step in the right direction. The Power of Clear Messaging FXOWXUDOO\ LGHQWL¿DEOH QDPHV JLYHV D FOHDU message of the objectives of the programme 2.18 Apart from the SBM and BBBP – one of the principles of behavioural programmes that have successfully economics is that the messaging needs to be employed the power of messaging, several clear and simple and aligned to a mental other programmes have utilised this power. model. This is evident from the names used The success of any programme depends for various recent schemes, some of which upon the level of involvement of all the are tabulated in table 2 below. relevant stakeholders. Use of socially and 40 Economic Survey 2018-19 Volume 1 Table 2: Use of clear messaging for Schemes Name of the Scheme Literal Meaning of the Objective of the Scheme Name Cultural/Societal aspect used Namami Gange Namami Gange means ‘I pray To arrest the pollution of Ganga to Ganga’ as the river Ganga River and revive the river. is revered in our culture. POSHAN Abhiyan Poshan means holistic Multi-ministerial convergence nutrition mission to ensure a malnutrition free India by 2022. Ujjwala Means ‘bright, clear’ To safeguard the health of women by providing them with clean cooking fuel – LPG. PM Mudra Yojana Mudra means “currency, Provides loans upto 10 lakh to the coins” non-corporate, non-farm small/ micro enterprises. Jan DhanYojana Jan Dhan implies “money of Financial inclusion program the people” WR H[SDQG DFFHVV WR ¿QDQFLDO services. Ayushman Bharat Ayushman means “Being Universal and affordable access to Blessed with long life” good quality health care services. PRINCIPLES FOR APPLYING economics, there is still ample scope for BEHAVIOURAL INSIGHTS TO leveraging these insights to enhance the PUBLIC POLICY HI¿FDF\RISURJUDPPHVLQ,QGLD7RRXWOLQH such applications, Figure 12 describes 2.19 While several Indian programmes the seven key principles of behavioural have applied the principles of behavioural economics that public policy must employ. Figure 12: Principles of Behavioural Economics Principle 1: Leverage Principle 7: Default Rules Make Principle 2: Messages Make it Easy Mimic Mental to Choose Models Principle 3: Principle 6: Emphasize Leverage Loss Social Norms Aversion Principle 5: Principle 4: Reinforce Disclose Repeatedly Outcomes Policy for Homo Sapiens, Not Homo Economicus 41 2.20 The cognitive biases, the principle that and the relevant applications are summarized can be applied to alleviate the cognitive bias, below in Table 3. Table 3: Using Behavioural Principles to Overcome Cognitive Biases Cognitive Behavioural General application across all programs bias principle Anchoring Principle 1: x Choose the right default; default choice should maximise welfare. bias Leverage x Make the default ‘opt-in’ for welfare programs like insurance, retirement default rules savings, organ donation, etc. x Make the default ‘opt-out’ for purchasing add-on services, enrolling for a subsidy, etc. Principle 2: x Keep options few in number and easy to comprehend. Make it easy x Reduce logistical and administrative impediments to choosing. to choose x Offer micro-incentives. Failure bias Principle 3: x (PSKDVL]HWKHQXPEHURISHRSOHZKRYRWHVDYHUHJXODUO\¿OHWD[HVRQ Emphasize time, etc. – the enhancers of good behaviour. social norm x :KHUHYHUSRVVLEOHFODULI\WKHLQVLJQL¿FDQWUROHRIGHWUDFWRUVQHJDWLYH LQÀXHQFHUVWRDYRLG³IDLOXUHELDV´ x )RFXVRQLQÀXHQFHUVWKDWSHRSOHFDQUHODWHWRIRUH[DPSOHWKRVHLQWKH same geography or age group. Principle x 'LVFORVHWKHUHDOL]HGEHQH¿WVRIJRRGEHKDYLRXU 4: Disclose outcomes Sunk cost Principle 5: x Remind people of past good behaviour, for example, that they saved bias Reinforce regularly for the last three months, to invoke the sunk cost fallacy; repeatedly people tend to continue their past behaviour, especially when reminded about the same. x Elicit a pre-commitment for desired behaviour, and if possible, enable immediate action as per the commitment. Loss Principle 6: x Design incentives to reward good behaviour ex ante with threat to aversion bias Leverage revoke reward later if behaviour fails to match expectations. loss aversion Flawed Principle x 7UDLQSHRSOHWRVKLIWWRQHZUXOHVRIWKXPEIRUH[DPSOH³ÀXLGVRXW±VR mental 7: Make ÀXLGVLQ´WRLQFUHDVHÀXLGLQWDNHGXULQJGLDUUKRHD models and messages FRQ¿UPDWLRQ match x Make the rules of thumb catchy, easy to remember and intuitive. bias mental models AN ASPIRATIONAL AGENDA section draws on the principles outlined FOR PATH-BREAKING CHANGE above to create an aspirational agenda for path-breaking change. The section combines 2.21 The successful application of (i) suggestions for transforming some of behavioural insights, both in India and the existing programmes into revolutionary elsewhere, illustrates how their power can be ones aimed at removing social ills; and tapped in several other programs to enhance (ii) ways to radically improve existing policy impact. To this purpose, the current programmes. 42 Economic Survey 2018-19 Volume 1 Box 3: Citizen@75-Using Behavioral Economics to Avoid the Seven Social Sins The destiny of a nation is shaped by its citizens. India @75 is envisaged as a ‘New India’ where every individual realizes his or her full potential and looks for opportunities to contribute rather than claim entitlements. A new spirit of independence needs to be imbibed from all extrinsic and intrinsic fetters to shape the future of India. Mahatma Gandhi’s Seven Social Sins, published in Young India on October 22, 1925, provide deep insights into the role of social and political conditions shaping human behavior. Each of these is a statement of principle that can be interpreted and utilized for nudging people towards desirable behaviour. Sin 1: Politics without principle Sin 7: Worship Sin 2: Wealth without without work sacrifice Sin 3: Pleasure Sin 6: Science without without conscience humanity Sin 5: Sin 4: Commerce Knowledge without without morality character Social Sins of Related Applications Gandhiji Principles of Behavioral Economics Politics without Leverage loss Growing perceptions of criminalization of politics, misuse principle aversion RISXEOLFRI¿FHDQGODFNRIHIIHFWLYHJRYHUQDQFHKDVOHGWR increased apathy towards participation in political processes. Studies from behavioral economics and public administration show that policy makers and legislators exhibit loss-aversion in decision-making and seemingly harsh policy decisions do not garner enough support. Behavioral insights to address the loss aversion of policymakers can improve policy and legislative outcomes and uphold ‘Politics with principle’. This would also enhance broader participation in politics and contribute to a vibrant democracy. Policy for Homo Sapiens, Not Homo Economicus 43 Wealth without Disclose “Work is worship” – Indian ethos has always worshipped the work outcomes fruits of one’s own efforts. Work also leads to dignity and self- reliance. The perception of getting things for ‘free’ as an entitlement has to be reoriented towards discharging our obligations towards society by rendering productive work and contributing to national growth. The Principles of behavioral economics, viz. disclose the UHDOL]HGEHQH¿WVRIJRRGEHKDYLRUDQGWKHDGYHUVHRXWFRPHV of bad behaviour, on the one hand, and emphasizing social norms, on the other hand, offer insights towards enhancing productivity and tax compliance. Pleasure without Leverage :KHQOHVVGHVHUYLQJSHRSOHFODLPEHQH¿WVRIDGHYHORSPHQW conscience default rules programme, it is an act of pleasure without conscience or a VHQVH RI UHVSRQVLELOLW\ 6XFK FODLPLQJ RI EHQH¿WV QHJOHFWV welfare concerns of their relatively unfortunate fellow FRXQWHUSDUWV7ROHDUQWRJLYHDQGWDNHWROLYHVHOÀHVVO\WREH sensitive, to be considerate, is our challenge. The behavioural principle of leveraging default rules like making the default ‘opt-out’ for availing subsidy, etc. can EH HPSOR\HG WR QXGJH SHRSOH WRZDUGV FRQ¿GHQW GLVSOD\V and conduct of altruism. The “Give it up” campaign can use this principle more effectively to broaden its adoption to surrendering all types of subsidies. Knowledge Match With globalizing societies witnessing an information explosion without character messages to today, a lack of moral element underlying this information mental models bears the risk of desensitizing societies to ethics of harmony and brotherhood. Gender based violence, internet trolling, and rise of drug abuse amongst teenagers show how people, while mindlessly becoming more aware about the world around them, are ironically becoming less self-aware of their actions and outcomes of the same. People can be nudged with messages matching their mental models to make them realize that such biases exist and that soft skills like self-control, altruism, patience, and trust are as important as cognitive skills. Commerce Emphasizing Ethics are moral principles that govern a person’s actions and without morality social norms UHÀHFWEHOLHIVDERXWULJKWDQGZURQJMXVWDQGXQMXVWLQWHUPV of human behaviour. These morals are shaped by social and cultural norms and religious practices. 44 Economic Survey 2018-19 Volume 1 Emphasizing social norms is a powerful way of shaping choices and navigating human actions towards desired behaviour. Highlighting information regarding people who exhibit JRRGEHKDYLRXUDQGFODULI\LQJLQVLJQL¿FDQWUROHRIQHJDWLYH LQÀXHQFHUVFDQKHOSHQKDQFHFRQIRUPLW\DQGGHWHUXQHWKLFDO social behaviours. The National Corporate Social Responsibility Awards of Ministry of Corporate Affairs is an initiative in this direction. These awards emphasize ethical behaviour and acknowledge companies that have positively impacted both business and society. Science without Making it easy Science and Technology has a huge potential to simplify and humanity to choose EHQH¿WKXPDQOLYHV Chapter 10 in this volume dwells on an application of technology to improve the effectiveness of welfare programmes. Chapter 4 shows how data can be created as a public good within the legal framework of data privacy using technology. Using the behavioral principle of “Making it easy to choose”, technology can make things simple to understand, cut WKURXJKOD\HUVRISURFHVVHVDQGWDUJHWWKHEHQH¿WWRWKHDFWXDO EHQH¿FLDU\ Worship without Reinforce Practicing religion without developing an embedded sense of VDFUL¿FH repeatedly VDFUL¿FH HPSDWK\ DQG KXPLOLW\ WR VHUYH WKH QHHGV RI RWKHU people is self-defeating. Across all religions, positive mythological insights about gender and caste equality as well as universal brotherhood have been available and deeply understood in Indian society since the ages. So, repeatedly reinforcing examples of people following these positive sentiments as truly spiritual people can help establish the correct social norm that “serving man is serving God.” This may also be seen in the MARD (Men Against Rape and 'LVFULPLQDWLRQ FDPSDLJQXQGHUO\LQJZKLFKLVWKHVDFUL¿FHRI the male ego in a patriarchal society for the larger good of gender equality. The Good Samaritan guidelines of the Central Government and the policy adopted by several State governments, where people who help road accident victims receive a monetary LQFHQWLYHDQGDQDSSUHFLDWLRQFHUWL¿FDWHOHYHUDJHEHKDYLRUDO LQVLJKWVWRUHLQIRUFHWKHFRUUHFWVRFLDOQRUPRIVHOÀHVVVHUYLFH of mankind. Policy for Homo Sapiens, Not Homo Economicus 45 Transforming Gender Equations: Therefore, this campaign can be labelled From BBBP to BADLAV (Beti Aapki BADLAV (Beti Aapki Dhan Lakshmi Aur Dhan Lakshmi Aur Vijay Lakshmi) Vijay Lakshmi) to represent the 'change' towards gender equality. By drawing on the ğȡè[ ǕǗÏÛÛȯ ğȯ ȯȡ )) imagery of the forms of Goddess Lakshmi 2.22 While the BBBP campaign has helped, that symbolises wealth (Dhan Lakshmi) gender inequality needs a revolutionary and victory (Vijay Lakshmi), the message FDPSDLJQ WKDW XWLOLVHV WKH EHQH¿WV RI of treating women as the forms of Lakshmi behavioural economics. Our scriptures needs to be emphasized. Box 3 outlines worship women as the embodiment of Shakti ideas for utilising the power of role models and exhort, as captured in the shloka above, from Indian mythology to create the social that societies where women are respected norm that “women are equal to men.” prosper. Given the importance of messaging Table 4 details the explicit use of the seven as highlighted before, the campaign must behavioural principles outlined above to draw on cultural and social norms because empower BADLAV and thereby create the they affect behaviour so crucially in India. new norm. Box 4: Drawing on Mythological role models to reinforce the message of BADLAV (Beti Aapki Dhan Lakshmi Aur Vijay Lakshmi) Indian women have enjoyed a position of respect and reverence in ancient Indian society. Ardhanareshwar – a half male-half female representation of Lord Shiva – captures the equality EHWZHHQ PHQ DQG ZRPHQ 7KH 5LJYHGD LGHQWL¿HG PDQ\ ZRPHQ VDJHV DV WUHDVXUHV RI NQRZOHGJH and foresight: the prophetess Gargi, who questioned the origin of all existence in her Vedic hymns and the great Maitreyi, who rejected half her husband’s wealth in favour of spiritual knowledge. The long philosophical conversations between sage Agasthya and his highly educated wife Lopamudra DUHOHJHQGDU\0HQLQDQFLHQW,QGLDQVRFLHW\ZHUHLGHQWL¿HGZLWKWKHLUPRWKHUVYashoda-Nandan, Kaushalya-Nandan, Gandhari-Putra, as well as their wives/consorts, Janaki-Raman, Radha-Krishna. Since such positive mythological insights about gender equality are readily available and deeply understood in Indian society, these can be used as part of a revolutionary BADLAV programme for the following: a) to explicity state the new norm of gender equality, b) to focus attention on all those who adopt the new norm, and c) to continuously reinforce the norm over time. The last step is crucial because people’s memories are short-lived. They need to be reminded of what is socially acceptable behaviour and repeatedly shown examples of their conforming neighbours, until the norm becomes entrenched in society. Seeing is believing, i.e. only when people can see counter- stereotypical role models of gender equality often, will their beliefs start to change. A marketing campaign by the U.S. government leveraged this idea perfectly when they sought to recruit women for “men’s jobs” in factories. They supported their marketing effort by caricaturing a cultural icon –Rosie the Riveter – a female taking a “man’s job” without losing her femininity. 46 Economic Survey 2018-19 Volume 1 Telling people what the others are doing is most effective when people can relate to the ‘others’. People are more likely to alter their behaviours if the ‘others’ belong to their community. Information campaigns promoting gender equality should emphasize, for each group of people, what the others from their own geography or ethnic identity are doing in this direction. This would help the “What is” to become the “What should be” because of people’s innate desire to follow the herd, compete with them and/or gain social approval. Table 4: Using Behavioural Principles for BADLAV Principle Applying the principle to BADLAV 1. Make it easy xSimplify procedures to make it easier for women to, inter alia, report incidences to choose of harassment and discrimination, to open bank accounts, to get government documents such as passports, visas etc. 2. Emphasize xProminent women, including many female and male Hollywood and Bollywood social norms VWDUV SOD\HG DQ LPSRUWDQW UROH LQ UDLVLQJ WKH SUR¿OH RI WKH UHFHQW ³0H WRR´ movement, thereby contributing to changing the norm and illustrating that change in social norm is possible. xInstead of highlighting the number of top companies that have few women on their boards, it is more effective to highlight how many do. Similarly, showing how prevalent and pervasive gender based violence is, runs the risk of normalising it; instead emphasising on how many people are not perpetrators or reinforcing injunctive norms against it can be more helpful in shaping correct norms towards gender equality. xResearch shows that girls and women who observed female village chiefs exhibit behaviour that highlights them as equal to men. Villagers who had exposure to at least two female chiefs rated male and female leaders equally. Therefore, women village leaders must be advertised as role models as people can relate to proximate “others”. Mass media must be utilised for regular efforts to change the social norm via BADLAV. 3. Disclose xPublishing gender rankings or audits in public domain, whether for numbers of outcomes women in legislatures, in political parties, in bureaucracy or on company boards, can prompt organisations to take action to avoid bad publicity or looking worse than their competitors. Mandating organisations to report the “Gender pay gap” can reinforce this trend. 4. Reinforce xHaving multiple visually descriptive posters in every corridor of workplaces and repeatedly public places regarding what constitutes sexual harassment at workplace can reinforce the norm of it not being acceptable. Similarly, regular TV advertisements that reinforce the positive norm of gender equality can help to reinforce repeatedly. 5. Leverage loss x(YLGHQFHIURP¿HOGVWXGLHVDQGH[SHULPHQWVVKRZVWKDWDPRQJPHQDQGZRPHQ aversion of equal abilities, men often choose to compete twice as often as women. Reward VWUXFWXUHV FDQ EH PRGL¿HG WR DPHOLRUDWH WKH KLJKHU DYHUVLRQ RI ZRPHQ WR competition. For instance, application fees for women applicants in jobs can be waived. Removing demographic information from job applications can also help. Policy for Homo Sapiens, Not Homo Economicus 47 6. Make x:RPHQFRQVLVWHQWO\WHQGWRSODFHPRUHYDOXHRQÀH[LELOLW\DWZRUNSODFH&RPSDQLHV messages match WKDWRIIHUÀH[LELOLW\DVWKHGHIDXOWQRUPKDYHPDQ\PRUHZRPHQDSSOLFDQWVDQG mental models employees. xWomen are less likely to apply for jobs perceived as “male-labelled.” Skill training and apprenticeship programmes can be redesigned with appropriately gendered wording to attract female applicants in male dominated professions. xStereotypes regarding innate ability linked to gender and/or race can impact VWDQGDUGL]HG WHVW SHUIRUPDQFH*HQGHU VWHUHRW\SH WKUHDWV ¿OOLQJ GHPRJUDSKLF LQIRUPDWLRQEHIRUHWHVWV FDQLQÀXHQFHWHVWVFRUHVRIJLUOVDQGER\VGLIIHUHQWLDOO\ These insights are crucial for building gender and race sensitive curriculum and evaluation procedures in schools. From Swachh and Ayushman Bharat to how this rate has improved after the adoption Sundar Bharath of sanitation practices. When people realize 2.23 A strong way to reinforce behaviour is the tangible outcomes of their actions, they are by getting people to pre-commit to a certain more likely to sustain their behaviour. This is FRXUVHRIDFWLRQ6WXGLHV¿QGWKDWLISHRSOH of tremendous importance for SBM because it pre-commit to doing something, they are relies on a sustained change in behaviour, not much more likely to do it. For instance, a a one-time change. To drive the point home, simple act of asking people if they will vote, swachhagrahis may also help individual enrol in a smoking cessation programme or KRXVHKROGVUHÀHFWRQWKHLQFLGHQFHRILOOQHVV save money, increases the likelihood that in their own families in, say, the last six months people will act in accordance with their goals. or since the time they quit open defecation. SBM swachhagrahis may use this strategy to ,ISHRSOH¿QGWKDWWKHLUKHDOWKRXWFRPHVDUH make people pre-commit to sanitation goals. better after adopting the new practice, they are Further, the swachhagrahis may also assist likely to persist in that practice. people in assessing themselves periodically, 2.25 Taking our learning from the power of VD\ RQFH D PRQWK $Q DVVLVWHG UHÀHFWLRQ behavioural economics in the Swachh Bharat session in the community or on a one-on-one scheme, the way forward is to develop an basis with the local swachhagrahi can prompt all-encompassing behavioural economics people to think about whether they acted as architecture for the entire health sector as planned and how many times they detracted. KHDOWK VLJQL¿HV LQQHU EHDXW\ *LYHQ WKH 7KHVHUHÀHFWLRQVHVVLRQVVKRXOGFXOPLQDWHLQ unique characteristics of the health sector a commitment about how people plan to act i.e. information asymmetry between the in the near-term future – whether they will doctor and the patient, hyperbolic tendencies refrain from open defecation next month or of health consumers, and high variability of not. health care expenditures, people often make 2.24 Further, people often respond to decisions in health care that are not in their disclosure of outcomes; they are more likely best interest. This ranges from failing to enrol to sustain their new behaviour if told about in health insurance to which they are entitled, WDQJLEOH EHQH¿WV WKDW WKH\ FDQ LQWHUQDOL]H to engaging in harmful behaviour like smoking not aggregate statistics that they may not care and drug abuse. A potentially richer set of about. For example, a swachhagrahi may behavioural tools than provided by traditional disseminate information about the incidence economic theory is necessary to understand of sanitation-related illness in her village and DQGLQÀXHQFHKHDOWKFDUHEHKDYLRXU 48 Economic Survey 2018-19 Volume 1 Table 5: Using Behavioural Principles for Sundar Bharat Principle Applying the principle 1. Leverage x*LYLQJ LQGLYLGXDOV GHIDXOW ÀX VKRW DSSRLQWPHQW WLPH FDQ LQFUHDVH LQÀXHQ]D default rules vaccination rates. x3URYLGLQJVPDUWLQVXUDQFHSODQGHIDXOWVFDQVLJQL¿FDQWO\VLPSOLI\KHDOWKLQVXUDQFH choice. 2. Make it easy xAsking consumers the factors that are most important to them while choosing a to choose health plan and restricting the plan to these factors can make choice easier and thereby enhance take-up of health insurance. xMinor behavioural alterations in school and college canteen menus (giving interesting names to healthy options, putting them near the cash counter, making the process of buying unhealthy options more time taking) can increase uptake of nutritious food. 3. Emphasize xAdolescents often overestimate how much alcohol or drugs their peers take social norms making heavier consumption to be perceived as a socially desirable behaviour. Campaigns focusing on number of people who don’t drink or take drugs may be more effective. xYouth may be more responsive to a drug prevention program after the death of a celebrity from drug overdose. xGiving out messages in information campaigns such as “90 per cent of doctors DJUHH WKDW YDFFLQHV DUH VDIH´ FDQ VLJQL¿FDQWO\ UHGXFH SXEOLF FRQFHUQ DERXW childhood vaccine, establish the social norm that vaccinations are safe and enhance vaccination. xPresenting information on how many people in the neighbourhood have chosen WRWDNHXSWKHKHDOWKLQVXUDQFHSODQDQGWKHEHQH¿WVLWKDVRIIHUHGWRIDPLOLHVZLWK similar disease in that area can increase enrolment rates. 4. Disclose x'LVFORVLQJWRSHRSOHDERXWWKHUHDOL]HGEHQH¿WVRIKDQGZDVKLQJDQGRUIDPLO\ outcomes planning practices experienced by other people in their community, can enable them to take up these health practices. 5. Reinforce xSending messages to patients that asked the patient to write down the day and time repeatedly they planned to get their next vaccination can boost uptake of vaccines. xDoctors asking patients coming to hospitals for a signed pledge or a verbal commitment, preferably in the presence of someone the signee respects, called “accountability partner” to take up Yoga and walks can encourage such healthy lifestyle practices. A monthly appreciation (joint coupon rewards) for following WKHSOHGJHDIWHUEHLQJFHUWL¿HGE\WKH³DFFRXQWDELOLW\SDUWQHU´FDQVXVWDLQVXFK behaviour. xMany people suffering from critical diseases do not take their medicines regularly. Use of simple text messages & pill bottles that light up if not opened at the right WLPHFDQLQFUHDVHGUXJDGKHUHQFH'HOLYHULQJDQDSSUHFLDWLRQFHUWL¿FDWHDWWKHHQG of the month for following their prescription schedule can sustain adherence. 6. Leverage x3HRSOHRIWHQ¿QGLWGLI¿FXOWWRDFKLHYHJRDOVOLNHZHLJKWORVVRUFHDVLQJWRVPRNH loss aversion People voluntarily made to post bonds (deposit contracts) or lottery tickets on a website that will be returned to them if they achieve their goals, but are forfeited RWKHUZLVHFDQKHOSWKHPDFKLHYHWKHVHGLI¿FXOWJRDOV Policy for Homo Sapiens, Not Homo Economicus 49 7. Make x&RQWURORIGLDUUKRHDVXIIHUVIURPDÀDZHGPHQWDOPRGHO WKHSHUFHSWLRQWKDWWKH messages VROXWLRQLVWRGHFUHDVHWKHFKLOG¶VÀXLGLQWDNHDQGWRNHHSWKHFKLOGµGU\¶LPSO\LQJ match mental less use of Oral Rehydration Solution. Information campaigns on adoption of ORS models FDQRYHUWXUQWKLVÀDZHGPHQWDOPRGHO xMessage boards in public hospitals and medical advertisements on media must emphasize gains from smoke cessation and breastfeeding to foster preventive action. Similarly, messages for sexually transmitted diseases and breast cancer must focus on the loss to deter and encourage early diagnosis respectively. xThe Mother’s Absolute Affection (MAA) Programme campaign leverages role RILQÀXHQFHUV WKHUHODWLRQVKLSEHWZHHQPRWKHULQODZDQGWKHGDXJKWHULQODZ and the idea of commitment devices (“Vaada” i.e., promise) to reinforce the idea of breastfeeding the child within one hour of birth. Cultural tailoring of health messages in this area can nudge them to adopt breastfeeding. Think about the Subsidy it up. While this represents a good beginning, 2.26 “Give It Up” encouraged Above- the potential to expand this number remains poverty line (APL) households to voluntarily large. It can be further observed that north surrender their LPG subsidies – for every eastern states like Arunachal Pradesh, household that “gave it up,” a BPL household Nagaland, Manipur and Mizoram have would receive a gas connection. The lack higher rate of subsidy surrender as compared of economic incentives in this programme to larger states availing much more subsidy. means the campaign relies entirely on the Like BBBP and SBM, “Give It Up” also better judgment of people to voluntarily give relies on a change in behaviour. In fact, Give up their subsidies. It Up’s task is less arduous than BBBP and 2.27 As Figure 13 shows, while the “Give It SBM – while the latter programmes require 8S´FDPSDLJQKHUDOGHGDVLJQL¿FDQWFKDQJHLQ continuous effort to dislodge mind-sets the form of voluntary giving up of subsidies, that have prevailed for decades, “Give It the overall response to the campaign could be Up” requires only a one-time action that is improved from the one crore who have given LQFRQVHTXHQWLDOWRPRVWDIÀXHQWKRXVHKROGV Figure 13: State-wise percentage of APL Consumers who surrendered LPG Subsidy Source: Data from Ministry of Petroleum & Natural Gas 50 Economic Survey 2018-19 Volume 1 2.28 Behavioural economics tells us that others act. Information campaigns do not, even if people are truly interested in giving however, adequately emphasize what the up their subsidies; their actions may differ (metaphorical) neighbours are doing. The from their intent as they need to be moved Give It Up website has a “scroll of honour” to to action with a gentle nudge. A good choice felicitate participants, but this feature relies architecture can aid in closing this gap on people to go looking for the social norm, between intention and action. For campaigns instead of actively advertising the social like Give It Up, the default choice matters norm. A click on the “scroll of honour” makes immensely. People have a strong tendency the user choose between three gas companies, to go with the status quo. Many governments as the lists are maintained on these companies’ have leveraged this insight to change the ZHEVLWHV7R¿QGDQDPHRQWKHVHORQJOLVWV GHIDXOWRSWLRQDQGWKHUHE\LQFUHDVHHI¿FDF\ one needs to enter one’s consumer number. of their programmes. “Give It Up” needs to Since no one is likely to know anyone else’s employ this insight. Given their inertia, of FRQVXPHU QXPEHU SHRSOH FDQQRW ¿QG WKHLU the nineteen crore people who did not give friends, relatives or neighbours. up their subsidy, many may have intended to give up their subsidy but have simply not 2.31 People act positively when they see been nudged to action. others act positively, and particularly when they can relate to such individuals. In fact, 2.29 Give It Up, however, incorporates people can relate to others through even other behavioural insights. It is easy and seemingly innocuous traits such as a shared nearly effortless to give up one’s subsidy – an geographical locality. The “scroll of honour” intuitive online interface ensures the process does not leverage this crucial insight, as people takes only a few minutes. This is essential VLPSO\FDQQRW¿QGRWKHUVWKH\PD\NQRZRU because every additional minute that it takes can relate to. Maintaining a centralized list to give up the subsidy increases the chances of names (independent of the gas company) that one will drop out in the middle of the and displaying the photographs of other process. participants in the same locality may increase WKHHI¿FDF\RIWKH³VFUROORIKRQRXU´7DEOH 2.30 The campaign also attempts to describes the applications of the behavioural leverage the power of social norms, but with principles to implement the “Think about the limited success. People act when they see Subsidy.” Table 6: Using Behavioural Principles for “Think about the Subsidy” Principle Applying the principle 1. Leverage For campaigns like Give It Up, the default choice matters immensely. People have a strong default rules WHQGHQF\WRJRZLWKWKHVWDWXVTXR7KHGHIDXOWRSWLRQFDQEHPRGL¿HGVRWKDWKRXVHKROGVDERYH a certain income threshold have to opt in to continue their subsidies with the default option being ³RSWRXW´RIWKHVXEVLG\,WLVFULWLFDOWRHQVXUHWKDWSHRSOH¿QGLWH[WUHPHO\HDV\±WKURXJKRQO\D text message, a phone-call or a few clicks – to opt in to continue their subsidy. 2. Make it easy For people who donate impulsively, reducing the friction between the moment when their intention to choose to give up the subsidy appears and when they feel they can take action can make them more likely WRJLYHXSWKHVXEVLG\3UHSRSXODWLQJ¿HOGVRIVXEVLG\JLYLQJXSIRUPVFDQPDNHLWPRUHOLNHO\ that people will submit applications. Mobile phones and apps can also make impulsive giving up easier. Policy for Homo Sapiens, Not Homo Economicus 51 3. Emphasize Making people feel good about giving up subsidies can help establish the correct social norm. To social norms discourage the middle-class and the comparatively rich people from enrolling for subsidies like kerosene, cooking gas etc., the government could, in its advertisements of the particular schemes, state that the scheme is intended to help the poor who make X per cent of the population and who earn less than R Y per month. Advertisements could suggest that by not enrolling, the rich are becoming contributors to eradication of extreme poverty from the country. Social networks could support live “Give it Up” events where participation is acknowledged with YLVXDOFKDQJHVWRSHRSOH¶VRQOLQHSUR¿OHV Creating quick outlets such as a simple phone app or physical kiosks for exercising our general intentions of donating small amounts can build the overall social norm of being charitable. Increasing visibility of donors can encourage giving up of subsidies, especially for people who think and donate based on their alignment with the causes they choose to support. Highlighting the noble act of giving in general using respected leaders in the world, and not just giving up a subsidy could increase the visibility of a more deliberate approach to giving. 4. Disclose Displaying the names and photographs of people who give up subsidy on the website and while outcomes ¿OOLQJWKHIRUPFDQEROVWHUWKHDFWRIJLYLQJLWXS 5. Reinforce Immediately and vividly showing givers the effect of them giving up the subsidy can make giving repeatedly IHHOUHDOO\JRRG*LYHUVFRXOGYLHZSHUVRQDOSKRWRVRIWKHSHRSOHEHQH¿WWLQJIURPWKHVXEVLG\RU DYLGHRZLWKDEHQH¿FLDU\VD\LQJWKDQN\RX 'XULQJWD[¿OLQJWLPHSHRSOHFRXOG¿OODQH[WUD¿HOGLQWKHIRUPDERXWZKHWKHUWKH\ZRXOGOLNH to give up their subsidy (a form of tax payment) for the cause of the nation. Givers could sign up for personalized reminders to bring attention to their giving up objectives throughout the year. 6. Leverage Loss aversion can be used to explain why majority of LPG users have not given up their subsidy. loss aversion This reinforces the policy of setting the subsidy schemes default to opt-out with a fairly easy process to opt in. Asking individuals to pledge a certain amount of subsidy when they feel most inspired, possibly when watching a social movie in the theatre, with the payment coming later can encourage giving. They can be prompted to set a giving goal in advance to track their progress. 7. Match Behavioural techniques can help achieve desirable outcomes from subsidy programmes and in messages to turn reduce the effective costs of subsidy. mental models Sometimes individuals do not take up vaccinations because they either forget the location of the clinic or the time of appointment. Fiscal subsidies to make people take up vaccinations can be made more cost effective if such set of individuals are reminded more frequently about the time and locationor encouraged to make a concrete plan about when and where they will get their vaccination. Jan Dhan Yojana accounts but to enable access to credit, 2.32 While the Jan Dhan Yojana opened insurance, pension schemes and other a large number of bank accounts in a short facilities offered by the formal banking span of time, its success relies on people sector. Going forward, the programme offers using these accounts regularly. The tremendous scope to employ behavioural programme’s mandate is not only to open insights. Table 7: Using Behavioural Principles to enhance impact of Jan DhanYojana Principle Applying the principle 1. Leverage xMake auto enrolment into a savings plan the default while offering people the default rules option to opt out. 52 Economic Survey 2018-19 Volume 1 2. Make it xRegulator must ensure that products for the poor do not confound with too many easy to choose options. The Government’s Jeevan Jyoti Bima Yojana is an example of a straight forward product that implements this option. 3. Emphasize xInformation campaigns should highlight the number of people who use their bank social norms accounts in the local village. Every person can be sent an SMS at the end of the month about his/her transactions, those of others in his village, and his relative standing in the village on this metric. This simple strategy can further the social norm for use of Jan Dhan account. 4. Disclose xHolders of dormant accounts may be periodically reminded of the number of people outcomes in their neighbourhood who actively use their accounts. To regular users, even a simple SMS such as “You made three withdrawals this month – congratulations” in the vernacular language, followed by a happy emoticon, may remind people of the norm and sustain their usage of bank accounts. 5. Reinforce xReminding people about the savings that they have done can in the past can help repeatedly reinforce good behaviour. By simply asking people whether they plan to save next month, the intention to save can be reinforced. Committing people to how much they plan to save can also help reinforce the intention to save. 6. Leverage xA propitious time to get people to save more is when salary increases. At such loss aversion times, people are less likely to consider increased savings as a loss than at other times of year. This feature can be combined with default rules to automatically increase enrolment into the savings while offering people the option to opt out of such automatic increases. 7. Make xMoney set aside for, say, education will unlikely be used for another purpose, messages whereas ‘general’ money not earmarked for any purpose is spent much faster. match mental People may be asked to choose their own names such as “home savings plan” or models “education savings plan.” All outgoing communications from banks should stress the chosen name to reinforce savings. Improving Tax Compliance honourable.” A start has been made through 2.33 The great philosopher, Plato, the budget speech of February 2019, which convincingly argued centuries ago: “What publicly and explicitly thanked tax payers, is honoured in a country is cultivated there.” SHUKDSVIRUWKH¿UVWWLPHWKHUHE\VHHNLQJWR Consider military service in India, which honour honest tax payers. employs one of the largest group of armed 2.34 Across countries, research has personnel in the world (over 14 lakhs). highlighted that tax evasion is driven While the economic incentives offered to VLJQL¿FDQWO\E\tax morale, viz., the intrinsic army personnel are attractive, a large section motivation of taxpayers in a country to pay joins the armed forces because serving in taxes. Tax morale itself is driven primarily by the armed forces is considered honourable. two perceptive factors: (i) vertical fairness, Similarly, in order to enhance tax compliance, i.e. what I pay in taxes is commensurate to behavioural insights need to be employed to WKH EHQH¿WV , UHFHLYH DV VHUYLFHV IURP WKH modify the social norm from “evading taxes Government; and (ii) horizontal fairness, is acceptable” to “paying taxes honestly is i.e., differences in the taxes paid by various Policy for Homo Sapiens, Not Homo Economicus 53 sections of society. For instance, citizens Such information can propagate the perceive vertical fairness to be low if they social norm that “paying taxes honestly is ¿QGWKHLUWD[SD\PHQWVEHLQJVTXDQGHUHGLQ honourable.” wasteful public expenditure or by corruption. 2.36 As people often indulge in conspicuous Similarly, perceptions of horizontal fairness consumption to convey their social status, suffer when the employee class is forced to top 10 highest tax payers within a district contribute disproportionately to income taxes can be highlighted and accorded due while the class of self-employed gets away recognition. This may take the form of paying minimal taxes. Both perceptions expedited boarding privileges at airports, contribute to high tax evasion in a country. fast-lane privileges on roads and toll booths, 2.35 To correct vertical unfairness that special “diplomatic” type lanes at immigration can lead to tax evasion, the Government counters, etc. Further, the highest taxpayers should utilise the behavioural insight that over a decade could be recognised by naming people identify with their neighbourhood. important buildings, monuments, roads, Signboards showing “tax money at work” trains, initiatives, schools and universities, in constructions projects in a panchayat/ hospitals and airports in their name. The district explicitly convey to citizens that their idea is to create exclusive membership of tax money is used in valuable public goods, “clubs” that exude not only social status thereby lowering perceptions of vertical but also honour. Such steps can also help unfairness. Similarly, highlighting the tax propagate the social norm that “paying taxes paid by other taxpayers, especially self- honestly is honourable.” Table 8 describes employed individuals, in the panchayat/ the applications of the behavioural principles district through SMS, billboards etc., can to enhance tax compliance. correct perceptions of horizontal unfairness. Table 8: Using Behavioural Principles to enhance tax compliance Principle Applying the principle 1. Leverage Automatic deduction of tax and directing all or portion of refunds into savings accounts can be default rules used to encourage savings, including retirement savings. Sending messages to individuals suggesting that not declaring taxes is a deliberate and intentional choice on their part can help them overcome status quo bias and improve compliance. 2. Make it Filing of tax forms even for zero payment of tax. easy to choose 5HPRYLQJEDUULHUVWR¿OLQJWD[HVSURFUDVWLQDWLRQKDVVOHRI¿OOLQJIRUPVRUIDLOLQJWRXQGHUVWDQG the terms- can improve compliance. Automated tax collection can make individuals pay less attention to tax collected (Salience effects). 3. Emphasize Providing information about peer behaviour can make taxpayers adjust their reported income. social norms Messages in the form of moral appeals to taxpayers regarding payment of taxes may have limited effects. Tax amnesties might reduce tax compliance if taxpayers perceive amnesties as unfair. Amnesties can decrease the government’s credibility and the taxpayers’ intrinsic motivation to comply by setting the incorrect social norm. 54 Economic Survey 2018-19 Volume 1 4. Disclose Public shaming of individuals who don’t pay taxes can reduce non-compliance if they are outcomes reintegrated immediately. However, persistent public shaming can be detrimental for compliance because of stigmatisation effects. If cheaters feel that the probability of their detection has increased, voluntary disclosure programs for tax payments can increase tax evasion incidence as these programs may offer the possibility to avoid strict punishments. 5. Reinforce Repeatedly sending fairness driven and normative messages added to standard reminder letters repeatedly that referred to the facts that (a) most people in your local community pay their taxes on time and (b) the person concerned was in the very small minority who had not yet done so can help reduce late tax payments. 6. Leverage 7D[ZLWKKROGLQJIROORZHGE\UHIXQGVDWWKHWLPHRIWD[¿OLQJPD\LQFUHDVHWD[FRPSOLDQFH loss aversion and total taxes paid. Taxpayers are more concerned about tax deduction claims when they owe DGGLWLRQDOWD[ ORVV DWWKHWLPHRI¿OLQJWKDQZKHQWKH\H[SHFWDUHIXQG JDLQ Framing tax cuts: tax cuts presented as a bonus (gain) are more likely to be spent than tax cuts presented as a rebate (loss). 7. Match Reminding tax payers that public goods can only be provided in return for tax compliance messages to (reciprocity appeal) can boost tax morale. mental models Box 5:Tax evasion, wilful default, and the Doctrine of Pious Obligation In Hinduism, non-payment of debts is a sin and also a crime. The scriptures ordain that if a person’s debts are not paid and he dies in a state of indebtedness, his soul may have to face evil consequences. Therefore, it is the duty of his children to save him from such evil consequences. This duty or obligation of a child to repay the debts of the deceased parent is rested upon a special doctrine, known as “The Doctrine of Pious Obligation”. Under Islam, Prophet Muhammad advocated – “Allaahummainnia’oodhibika min al-ma’thamwa’l- maghram (O Allaah, I seek refuge with You from sin and heavy debt).” A person cannot enter Paradise XQWLOKLVGHEWZDVSDLGRII$OORIKLVZHDOWKFRXOGEHXVHGWRSD\WKHGHEWDQGLILWLVLQVXI¿FLHQWWKHQ one or more heirs of the deceased could voluntarily pay for him. The Bible says, “Let no debt remain outstanding except the continuing debt to love one another - Romans 13:8” and “The wicked borrows and does not repay, but the righteous shows mercy and gives -Psalm 37:21.” Thus, the repayment of debt in one’s own life is prescribed as necessary by scriptures across religions. Given the importance of religion in the Indian culture,the principles of behavioural economics need to be combined with this “spiritual/religious norm” to reduce tax evasion and wilful default in the country. IMPLEMENTING THE the Subsidy”, and from tax evasion to tax ASPIRATIONAL AGENDA FOR compliance. The possibilities, however, BEHAVIOURAL CHANGE to employ the principles of behavioural economics to policymaking, especially 2.37 The previous section outlines an in India where social norms so crucially ambitious agenda for behavioural change, LQÀXHQFH EHKDYLRXU DUH HQRUPRXV7R DYDLO from BBBP to BADLAV, from Swachh WKHVH EHQH¿WV WKH IROORZLQJ PHDVXUHV DUH Bharat to Swasth Bharat, from “Give It suggested for implementation. Up” for the LPG subsidy to “Think about Policy for Homo Sapiens, Not Homo Economicus 55 2.38 First, the proposal to set up a behavioural FDQ VLJQL¿FDQWO\ HQKDQFH WKH HI¿FDF\ RI economics unit in the Niti Aayog must be the program. A simple application of this immediately activated. Care, however, must approach is in the Government communication be taken in setting up the unit as applying the that goes to citizens. For example, recent principles of behavioural economics seems experience of the Department of Revenue innocuously and misleadingly simple; after showed that perceptions of “tax terrorism” all, everyone can claim to be an expert in often had more to do with the language understanding human behaviour. However, employed in the communication than any as research in behavioural economics Government action in reality. Therefore, itself clearly highlights, there is a world of by the mere act of altering the language, it difference between anecdotes and averages. may be possible to change the relationship While insights gathered from careful research between the Department and the taxpayer rely on averages, everyday experience is from adversarial to collaborative. often driven by anecdotes. As anecdotes are more likely to represent outliers than 2.40 Third, as several programs are averages, behavioural policymaking driven administered by state governments, the by anecdotal evidence can create more behavioural economics team can work with damage than good. Therefore, the temptation various state governments not only to inform to appoint those who are not experts in this WKHPDERXWWKHSRWHQWLDOEHQH¿WVEXWDOVRKHOS area must be avoided. WKHPWRLPSURYHWKHHI¿FDF\RIWKHSURJUDPV 2.39 Second, every program must go through 2.41 While social norms impact behaviour a “behavioural economics” audit before its VLJQL¿FDQWO\ LQ ,QGLD WKH SRZHU WR HPSOR\ implementation. This audit may adhere to the behavioural change to alter these norms has principles of behavioural economics outlined not been adequately tapped. Implementing above to conduct its audit. Such an audit the agenda in this chapter would be a valuable DQG WKH PRGL¿FDWLRQV XQGHUWDNHQ WKHUHLQ step in this direction. CHAPTER AT A GLANCE ¾ Decisions made by real people often deviate from the impractical robots theorized in classical economics ¾ Drawing on the psychology of human behaviour, behavioural economics provides insights to ‘nudge’ people towards desirable behaviour. ¾ 7KH NH\ SULQFLSOHV RI EHKDYLRXUDO HFRQRPLFV DUH µHPSKDVLVLQJ WKH EHQH¿FLDO VRFLDO norm’, ‘changing the default option’ and ‘repeated reinforcements’. ¾ Swachh Bharat Mission (SBM) and the Beti Bachao Beti Padhao (BBBP) have successfully employed behavioural insights. ¾ Insights from behavioural economics can be strategically utilised to create an aspirational agenda for social change: (i) from BBBP to BADLAV (Beti Aapki Dhan Lakshmi Aur Vijay Lakshmi); (ii) from Swachh Bharat to Sundar Bharat; (iii) from “Give It Up” for the LPG subsidy to “Think about the Subsidy”; and (iv) from tax evasion to tax compliance. 56 Economic Survey 2018-19 Volume 1 REFERENCES Statistics 95(1): 64-73. Allcott, H., and S. Mullainathan. 2010. 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"Using Washington, DC: World Bank. http://www. 1RQ3HFXQLDU\ 6WUDWHJLHV WR ,QÀXHQFH worldbank.org/content/dam/Worldbank/ Behaviour: Evidence from Large Scale Field Publications/WDR/WDR%202015/WDR- Experiment." The Review of Economics and 2015-Full-Report.pdf. Nourishing Dwarfs to become Giants: 03 Reorienting policies for MSME Growth1 CHAPTER ¬ iw.kZen% iw.kZfene~&iw.kkZr~ iw.kZeqnp~&;rsA From the complete, the complete is born. From a seed, a mature tree is born. 060(VWKDWJURZQRWRQO\FUHDWHJUHDWHUSUR¿WVIRUWKHLUSURPRWHUVEXWDOVR FRQWULEXWHWRMREFUHDWLRQDQGSURGXFWLYLW\LQWKHHFRQRP\2XUSROLFLHVPXVW WKHUHIRUHIRFXVRQHQDEOLQJ060(VWRJURZE\XQVKDFNOLQJWKHP-REFUHDWLRQ LQ,QGLDKRZHYHUVXIIHUVIURPSROLFLHVWKDWIRVWHUGZDUIVLHVPDOO¿UPVWKDW QHYHUJURZLQVWHDGRILQIDQW¿UPVWKDWKDYHWKHSRWHQWLDOWRJURZDQGEHFRPH JLDQWVUDSLGO\:KLOHGZDUIVLH¿UPVZLWKOHVVWKDQZRUNHUVGHVSLWHEHLQJ PRUHWKDQWHQ\HDUVROGDFFRXQWIRUPRUHWKDQKDOIRIDOORUJDQL]HG¿UPVLQ PDQXIDFWXULQJE\QXPEHUWKHLUFRQWULEXWLRQWRHPSOR\PHQWLVRQO\SHUFHQW DQGWRSURGXFWLYLW\LVDPHUHSHUFHQW,QFRQWUDVWODUJH¿UPV PRUHWKDQ HPSOR\HHV DFFRXQWIRUWKUHHTXDUWHUVRIVXFKHPSOR\PHQWDQGFORVHWR SHU FHQWRISURGXFWLYLW\GHVSLWHDFFRXQWLQJIRUDERXWSHUFHQWE\QXPEHU7KH SHUFHSWLRQRIVPDOO¿UPVEHLQJVLJQL¿FDQWMREFUHDWRUVSHUYDGHVEHFDXVHMRE GHVWUXFWLRQE\VPDOO¿UPVLVLJQRUHGLQWKLVFDOFXOXV VPDOO¿UPV¿QGLWGLI¿FXOW WRVXVWDLQWKHMREVWKH\FUHDWH,QFRQWUDVWODUJH¿UPVFUHDWHSHUPDQHQWMREVLQ ODUJHUQXPEHUV$OVR\RXQJ¿UPVFUHDWHPRUHMREVDWDQLQFUHDVLQJUDWHWKDQ ROGHU¿UPV6L]HEDVHGLQFHQWLYHVWKDWDUHSURYLGHGLUUHVSHFWLYHRI¿UPDJHDQG LQÀH[LEOHODERXUUHJXODWLRQZKLFKFRQWDLQVL]HEDVHGOLPLWDWLRQVFRQWULEXWHWR WKLVSUHGLFDPHQW7RXQVKDFNOH060(VDQGWKHUHE\HQDEOHWKHPWRJURZDOOVL]H EDVHGLQFHQWLYHVPXVWKDYHDVXQVHWFODXVHRIOHVVWKDQWHQ\HDUVZLWKQHFHVVDU\ JUDQGIDWKHULQJ 'HUHJXODWLQJ ODERXU ODZ UHVWULFWLRQV FDQ FUHDWH VLJQL¿FDQWO\ PRUHMREVDVVHHQE\WKHUHFHQWFKDQJHVLQ5DMDVWKDQZKHQFRPSDUHGWRWKHUHVW RIWKHVWDWHV INTRODUCTION IRUPRI¿QDQFLDODQGVRFLDOLQFOXVLRQWRQRW only the individual but also his/her entire 3.1 Job creation in large numbers remains family. Chapter 7 in this volume of the Survey DQXUJHQWLPSHUDWLYHWRSURYLGH¿QDQFLDODQG predicts that the working-age population will social inclusion for our young population. grow by roughly 97 lakh per year during the After all, a well-paying job provides the best coming decade and 42 lakh per year in the ______1 'LVFODLPHU ,QWKLVFKDSWHUWKHWHUP³GZDUIV´IRU¿UPVWKDWUHPDLQVPDOOGHVSLWHEHLQJROGLVFRQWUDVWHGWR³LQIDQWV´IRU ¿UPVWKDWDUHVPDOOEHFDXVHWKH\DUH\RXQJThis usage is purely for ¿UPV and has no correlation with such usage for individuals and is therefore not intended to harm any sensibilities, whatsoever. 58 Economic Survey 2018-19 Volume I 2030s. If we assume that the labour force context. Firms that are both small and older participation rate (LFPR) would remain at than ten years are categorized as dwarfs as about 60 per cent in the next two decades, WKHVH ¿UPV KDYH FRQWLQXHG WR EH VWXQWHG LQ about 55-60 lakh jobs will have to be created their growth despite surviving for more than annually over the next decade. In this context, 10 years.2 this chapter examines how policies followed 3.3 Figures 1(a) to (c) show the share of RYHUWKHODVWVHYHQGHFDGHVVWLÀHWKHJURZWK GZDUIVLQWKHQXPEHURI¿UPVWKHVKDUHLQ of Micro, Small & Medium Enterprises employment and their share in Net Value (MSMEs) in the economy. MSMEs that Added (NVA). This analysis has been JURZQRWRQO\FUHDWHJUHDWHUSUR¿WVIRUWKHLU conducted using ¿UPOHYHO data from the promoters but also contribute to job creation Annual Survey of Industries (ASI) for the and productivity in the economy. Our policies year 2016-17, which is the latest available. must, therefore, focus on enabling MSMEs :KLOHGZDUIVDFFRXQWIRUKDOIRIDOOWKH¿UPV to grow by unshackling them. The chapter in organized manufacturing by number, their then lays out the policy map for re-orienting share in employment is only 14.1 per cent. the policy stance to foster the growth of In fact, their share in NVA is a miniscule MSMEs and thereby greater job creation and 7.6 per cent despite them dominating half productivity in the economy. the economic landscape. In contrast, young, THE BANE OF DWARFISM AND ODUJH ¿UPV ¿UPV WKDW KDYH PRUH WKDQ ITS IMPACT ON JOBS AND employees and are not more than 10 years PRODUCTIVITY ROG DFFRXQW IRU RQO\ SHU FHQW RI ¿UPV by number but contribute 21.2 per cent of Domination of ‘Dwarfs’ in number the employment and 37.2 per cent of the 3.2 A startling fact is how the bane of dwarfs, 19$/DUJHEXWROG¿UPV ¿UPVWKDWKDYH ZKLFKDUHGH¿QHGDVVPDOO¿UPVWKDWQHYHU more than 100 employees and are more grow beyond their small size, dominates the than 10 years old) account for only 10.2 Indian economy and holds back job creation SHU FHQW RI ¿UPV E\ QXPEHU EXW FRQWULEXWH and productivity. For the purposes of the half of the employment as well as the NVA. DQDO\VLVLQWKLVVHFWLRQ¿UPVHPSOR\LQJOHVV 7KXV ¿UPV WKDW DUH DEOH WR JURZ RYHU than 100 workers are categorized as small time to become large are the biggest DQG¿UPVHPSOR\LQJRUPRUHZRUNHUVDV contributors to employment and productivity UHODWLYHO\ODUJH7KRXJKD¿UPHPSOR\LQJ in the economy. In contrast, dwarfs that ZRUNHUVLVGH¿QLWHO\QRWODUJHLQWKHJOREDO remain small despite becoming older remain FRQWH[WDVZHVKRZEHORZ¿UPVHPSOR\LQJ the lowest contributors to employment and 100 workers are relatively large in the Indian productivity in the economy. ______2 'LVFODLPHU ,QWKLVFKDSWHUWKHWHUP³GZDUIV´IRU¿UPVWKDWUHPDLQVPDOOGHVSLWHEHLQJROGLVFRQWUDVWHGWR³LQIDQWV´IRU¿UPV WKDWDUHVPDOOEHFDXVHWKH\DUH\RXQJ7KLVXVDJHLVSXUHO\IRU¿UPVDQGKDVQRFRUUHODWLRQZLWKVXFKXVDJHIRULQGLYLGXDOV and is therefore not intended to harm any sensibilities, whatsoever. Nourishing Dwarfs to become Giants: Reorienting policies for MSME Growth 59 Figure 1(a). Share of dwarfs versus others Figure 1 (b). Share of dwarfs versus LQQXPEHURI¿UPV DVRI others in employment (as of 2016-17) 55.8 46.1 60.0 50.0 50.0 40.0 40.0 26.2 30.0 30.0 21.2 20.0 10.2 20.0 7.3 7.9 6.2 Share in workers 4.9 10.0 4.7 5.5 10.0 3.9 0.0 Share in total number of firms number Share in total 0.0 0 to 49 50 to 99 Above 99 0 to 49 50 to 99 Above 99 Firm Size (Number of Employees) Firm size (Number of Employees) Share of Young firms Share of Old firms Share of young firms Share of old firms Source: ASI Firm level data Source: ASI Firm level data Figure 1(c). Share of dwarfs versus others in Net Value Added (as of 2016-17) 60.0 51.3 50.0 37.2 40.0 30.0 20.0 Share in NVA 5.6 10.0 1.3 2.7 2.0 0.0 0 to 49 50 to 99 Above 99 Firm Size( Number of Employees) Share of Young firms Share of Old firms Source: ASI Firm level data 3.4 When examined purely according to GH¿QLWHO\GRPLQDWHWKHHFRQRPLFODQGVFDSH size, we note that the proportion of small LQ ,QGLD &UXFLDOO\ KRZHYHU VPDOO ¿UPV ¿UPV LQ RUJDQL]HG PDQXIDFWXULQJ LV DURXQG accounted for only 23 per cent of the total SHUFHQW,QFRQWUDVWODUJH¿UPVDFFRXQW employment in organized manufacturing in IRURQO\DURXQGSHUFHQWRIDOOWKH¿UPVLQ ZKLOHWKHODUJH¿UPVDFFRXQWHGIRU organized manufacturing. These proportions over 77 per cent of the total employment. have not changed much over time as seen These proportions remain similar to those in LQ )LJXUH D 7KXVVPDOO¿UPV 2010-11 (Figure 2(b)). Even more tellingly, 60 Economic Survey 2018-19 Volume I the share ofVPDOO¿UPVLQ1HW9DOXH$GGHG dominate the most numerically but create the (NVA) from organized manufacturing was least jobs and remain the most unproductive. only 11.5 per cent whereas the share of large 7KXVWKHFRQWULEXWLRQRIVPDOO¿UPVWRRXWSXW ¿UPVLQ19$ZDVSHUFHQWLQ and employment in the manufacturing sector these proportions are not different in 2010-11 LVLQVLJQL¿FDQWWKRXJKWKH\DFFRXQWIRUFORVH either (Figure 2(c)). Even among the small WRSHUFHQWRIDOO¿UPV ¿UPV ¿UPV ZLWK OHVV WKDQ HPSOR\HHV Figure 2(a). Distribution of number of Figure 2(b). Distribution of employment IDFWRULHVE\¿UPVL]H DFURVV¿UPVE\¿UPVL]H 77.1 80 72 80 71.9 72.3 70 70 60 60 50 50 40 40 30 16.8 30 16 12.1 12.0 15.7 20 12.8 11.2 10.1 20 Share in workers 10 10 0 Share in total number of firms number Share in total 0 0 to 49 50 to 99 Above 99 0 to 49 50 to 99 Above 99 Firm Size (Number of Employees) Firm Size(Number of Employees) 2010-11 2016-17 2010-11 2016-17 Source: ASI Firm level data Source: ASI Firm level data )LJXUH F 'LVWULEXWLRQRI19$6KDUHE\¿UPVL]H 100 84 88.5 80 60 40 Share in NVA 20 8.6 6.9 7.4 4.6 0 0 to 49 50 to 99 Above 99 Firm Size (Number of Employees) 2010-11 2016-17 Source: ASI Firm level data 7KH DERYH ¿QGLQJV dispel the levels of net job creation (Li and Rama, 2015). FRPPRQQRWLRQWKDWVPDOO¿UPVJHQHUDWHWKH This common perception also stems from PRVWHPSOR\PHQW6PDOO¿UPVPD\JHQHUDWH the fact that the effect of size confounds the a higher number of new jobs. However, they HIIHFWRIDJH6SHFL¿FDOO\PRVW\RXQJ¿UPV destroy as many jobs as well. Thus, higher DUH VPDOO WKRXJK PRVW VPDOO ¿UPV DUH QRW OHYHOVRIMREFUHDWLRQLQVPDOO¿UPVFRH[LVW young, at least in the Indian context). Absent with job destruction, thereby leading to lower careful distinction between the effect of age Nourishing Dwarfs to become Giants: Reorienting policies for MSME Growth 61 YHUVXVWKDWRIVL]HWKHQRWLRQWKDWVPDOO¿UPV than 10 years of age account for about 30 per create jobs has prevailed because it is the cent of employment and about half the NVA. \RXQJ ¿UPV ZKR DOVR KDSSHQ WR EH VPDOO In fact, we crucially note that the share in create the most jobs. To establish this fact, employment as well the share in NVA trend WKHSURSRUWLRQRI¿UPVVKDUHRIHPSOR\PHQW GRZQZDUGV ZLWK DQ LQFUHDVH LQ ¿UP DJH and share of NVA by age has been examined. 7KLVLVGHVSLWHWKHIDFWWKDW\RXQJ¿UPVDUH RQ DYHUDJH VPDOOHU WKDQ ROGHU ¿UPV 7KXV (IIHFWRI6L]HFRPSDUHGWR(IIHFWRIDJH \RXQJ ¿UPV DFFRXQW IRU D GLVSURSRUWLRQDWH share of employment and productivity $V FRPSDUHG WR WKH VPDOO ¿UPV LW LV WKH\RXQJ¿UPVWKDWFRQWULEXWHVLJQL¿FDQWO\ (Figure 3). to employment and value added. Firms less )LJXUH D 3URSRUWLRQRI¿UPVE\¿UP )LJXUH E (PSOR\PHQWVKDUHE\¿UP age age 25.0 20.0 18.7 20.8 15.8 20.0 17.0 15.6 15.0 13.0 15.0 14.0 11.4 10.7 10.4 10.0 7.6 10.0 6.6 6.7 5.3 5.0 3.7 4.1 5.0 3.1 3.4 2.2 1.4 1.7 1.7 1.9 1.6 1.0 0.8 Share in workers 0.0 0.0 Share in total number of firms number Share in total -5.0 -5.0 Firm Age Firm Age Source: ASI Firm level data Source: ASI Firm level data )LJXUH F 19$VKDUHE\¿UPDJH 30.0 24.0 25.0 19.3 20.0 16.4 15.0 9.3 10.0 7.0 5.4 4.5 Share in NVA 5.0 3.6 3.0 2.2 1.3 1.9 2.2 0.0 -5.0 Firm Age Source: ASI Firm level data 62 Economic Survey 2018-19 Volume I Cross-Sectional Comparison the employment when the enterprise is newly set up. In contrast, the average employment 3.7 What is the impact of the above size OHYHOIRU\HDUROG¿UPVLQ,QGLDZDVRQO\ GLVWULEXWLRQRI¿UPVRQMREVDQGSURGXFWLYLW\" 40 per cent greater than the employment when Figure 4 compares growth of employment the enterprise is newly set up. Thus, once DQG SURGXFWLYLW\ ZLWK ¿UP DJH LQ WKUHH they survive for forty years, the average 40- countries: U.S., Mexico and India (Hseih \HDUROG¿UPLQWKH86JHQHUDWHV¿YHWLPHV and Klenow, 2014). The comparison is (=7/1.4) as much more employment than done using both organized and unorganized WKH DYHUDJH \HDU ROG ,QGLDQ ¿UP (YHQ PDQXIDFWXULQJ ¿UPV )RU ,QGLD WKH GDWD Mexico does far better on this dimension include both from the ASI and the surveys than India. The average employment level of unorganized manufacturing organized by IRU \HDU ROG ¿UPV LQ 0H[LFR LV GRXEOH the National Sample Survey Organization that of the employment when the enterprise (NSSO). The left and the right panels use the is newly set up. Thus, once they survive for VL]HDQGSURGXFWLYLW\DVRIDJH¿YHRU\RXQJHU IRUW\\HDUVWKHDYHUDJH\HDUROG¿UPLQ as the base for comparison. The average Mexico generates 40 per cent more (=2/1.4) employment level for 40-year old enterprises employment than the average 40-year old in the U.S. was more than seven times that of ,QGLDQ¿UP )LJXUH D &KDQJHLQHPSOR\PHQWZLWK¿UP )LJXUH E &KDQJHLQSURGXFWLYLW\ZLWK¿UP age age 8 4 6 4 2 2 Average Productivity Average Employment Average Employment 0 0 <5 5--9 10--14 15-19 20-24 25-29 30-34 >=35 <5 5--9 10--14 15-19 20-24 25-29 30-34 35-39 >=40 Age Age India US Mexico India US Mexico Source: Hseih and Klenow (2014) 3.8 A similar tale unfolds with productivity up. Thus, once they survive for forty years, as well when we compare these three countries WKH DYHUDJH \HDU ROG ¿UP LQ WKH 86 LV IRUWKHHIIHFWRIDJLQJRI¿UPVRQSURGXFWLYLW\ 2.5 times (=4/1.6) more productive than the The average productivity level for 40-year DYHUDJH\HDUROG,QGLDQ¿UP0H[LFRGRHV old enterprises in the U.S. was more than four far better than India on this dimension as times that of the productivity of an enterprise well. The average productivity level for 40- that is newly set up. In contrast, the average \HDUROG¿UPVLQ0H[LFRLVWLPHVWKDWRI SURGXFWLYLW\ OHYHO IRU \HDU ROG ¿UPV LQ the productivity of an enterprise that is newly India was only 60 per cent greater than the set up. productivity of an enterprise that is newly set Nourishing Dwarfs to become Giants: Reorienting policies for MSME Growth 63 3.9 Thus, the comparison with other The lack of productivity and growth inhibits countries highlights that both employment the ability of the dwarfs to create jobs. creation and productivity do not grow DGHTXDWHO\DV¿UPVDJHLQ,QGLD Impact of Labour Regulation 3.12 India has a plethora of labour laws, THE ROLE OF POLICY IN regulations and rules, both at the centre and FOSTERING DWARFISM the state levels that govern the employer- 3.10 In this section, we highlight that our employee relationship. Each of these policies – across the board – protect and OHJLVODWLRQV H[HPSWV VPDOOHU ¿UPV IURP complying with these legislations. Table 1 foster GZDUIV rather than LQIDQWV. The key shows the size thresholds applicable to each GLVWLQFWLRQKHUHLVWKDWZKLOHLQIDQW¿UPVDUH small and young, dwarfs are small but old. piece of labour regulation. For instance, the Industrial Disputes Act (IDA), 1947 (Chapter 7KXVZKLOHLQIDQW¿UPVFDQJURZWREHFRPH VB) mandates companies to get permission ODUJH¿UPVWKDWDUHQRWRQO\PRUHSURGXFWLYH from the Government before retrenchment DQGJHQHUDWHVLJQL¿FDQWHPSOR\PHQWGZDUIV remain small and contribute neither to of employees. This restriction is, however, productivity nor to jobs. DSSOLFDEOHRQO\WR¿UPVZLWKPRUHWKDQ HPSOR\HHV 7KXV ¿UPV ZLWK OHVV WKDQ 3.11 As we show below, these policies create employees are exempt from the need to get D ³SHUYHUVH´ LQFHQWLYH IRU ¿UPV WR UHPDLQ permission from the Government before VPDOO,IWKH¿UPVJURZEH\RQGWKHWKUHVKROGV retrenching their employees. Given the that these policies employ, then they will be transaction costs inherent in complying with XQDEOHWRREWDLQWKHVDLGEHQH¿WV7KHUHIRUH such regulations, naturally a large majority of UDWKHU WKDQ JURZ WKH ¿UP EH\RQG WKH VDLG ¿UPVZRXOGSUHIHUWREHEHORZWKHWKUHVKROGRI WKUHVKROGHQWUHSUHQHXUV¿QGLWRSWLPDOWRVWDUW 100 employees. Thus, such labour legislation DQHZ¿UPWRFRQWLQXHDYDLOLQJWKHVHEHQH¿WV FUHDWHV SHUYHUVH LQFHQWLYHV IRU ¿UPV WR As economies of scale stem primarily from remain small. In this sense, labour legislation ¿UPVL]HWKHVH¿UPVDUHXQDEOHWRHQMR\VXFK FRPSOHPHQWVRWKHUEHQH¿WVSURYLGHGWRVPDOO EHQH¿WV DQG WKHUHIRUH UHPDLQ XQSURGXFWLYH ¿UPVLQSURviding such perverse incentives. 7DEOH6L]HEDVHG/LPLWDWLRQVSRVHGE\.H\/DERXU/HJLVODWLRQV S.No. Labour Acts Applicability to Establishments 1 Industrial Disputes Act,1947, Chapter V relating to Employing 100 or more workers strikes, lockouts, retrenchment, layoff 2 Trade Union Act, 2001-Registration of trade Membership of 10 per cent or 100 unions workmen whichever is less 3 Industrial Employment (Standing Orders) Act, 100 or more workmen 1946 4 Factories Act,1948 10 or more workers with power and 20 or more workers without power 5 Contract Labour (Regulation & Abolition) Act, 20 or more workers engaged as contract 1970 labour 6 The Minimum Wages Act, 1948 Employment in the schedule having more than 1000 workers in the State 7 Employees’ State Insurance Act,1948 - ESI 10 or more workers and employees Scheme monthly wage does not exceed `21000 8 Employees’ Provident Fund & Miscellaneous 20 or more workers Provisions Act, 1952 Source: Compiled from Ministry of Labour and Employment 64 Economic Survey 2018-19 Volume I Comparing productivity indicators in Answers were then scored as “1” if they ³LQÀH[LEOH´YHUVXV³ÀH[LEOH´VWDWHV reduced transaction costs, “0” if they did not, and (for two questions) “2” for a further 3.13 To examine the impact of labour reduction, with a maximum score of 50. UHJXODWLRQV VWDWHV DUH FODVVL¿HG DV ÀH[LEOH This index has been updated by covering DQG LQÀH[LEOH EDVHG RQ WKH UHVWULFWLYHQHVV the labour reforms initiated by the States till of their labour regulations. For this purpose, 2013-14. we build on the state-level survey that was conducted by OECD in 2007.3 This 3.14 No major labour reforms were initiated survey covered eight major labour related by the states from 2007 to 2014. In 2014, legislations and indicators: IDA, 1947, 5DMDVWKDQZDVWKH¿UVW6WDWHWKDWLQWURGXFHG Factories Act, 1948, State Shops and labour reforms in the major Acts. Thereafter Commercial Establishments Acts (State Act), many States followed on the path of Rajasthan. Contract Labour (Regulation & Abolition) 7KH\HDULVWKHUHIRUH¿[HGDVWKHFXWRII Act, 1970, the role of inspectors, the year to classify and rank States as )OH[LEOH and PDLQWHQDQFHRIUHJLVWHUVWKH¿OLQJRIUHWXUQV ,QÀH[LEOH. )OH[LEOH states include those states and union representation. 21 States were that score 20 or more out of a maximum score surveyed and the responses were compiled of 50, i.e., states that have reduced transaction E\WKH2(&'LQWRDQLQGH[WKDWUHÀHFWVWKH costs by at least 40 per cent. Other states are extent to which procedural changes have denoted as ,QÀH[LEOH. Figure 5 shows that reduced transaction costs by limiting the Assam, Jharkhand, Kerala, Bihar, Goa, scope of regulations, providing greater &KKDWWLVJDUKDQG:HVW%HQJDODUHFODVVL¿HG clarity in the application of regulations, DVLQÀH[LEOHVWDWHVZKLOHWKHRWKHUVWDWHV or simplifying compliance procedures. DUHFODVVL¿HGDVÀH[LEOH )LJXUH&ODVVL¿FDWLRQRI6WDWHVDV)OH[LEOH ,QÀH[LEOHEDVHGRQODERXUUHVWULFWLRQV Overall Score 30 27 24 Index High: Flexible States 21 18 15 Index Low: Inflexible States 12 UP HP TN Raj Del MP Guj Pub WB MH Goa K'tka Bihar Kerala Assam H'yana Odisha J'khand AP/ TL AP/ Ch'garh U'khand Source: OECD Economic Survey, 2007 updated with Survey calculations. 3.15 A comparison between the indicators Flexible States makes it amply clear that for labour, capital and productivity of ÀH[LELOLW\ LQ ODERXU ODZV FUHDWHV D PRUH PDQXIDFWXULQJ ¿UPV LQ WKH ,QÀH[LEOH DQG conducive environment for growth of industry ______3 OECD Economic Surveys: India. Volume 2007, Issue no. 14. Nourishing Dwarfs to become Giants: Reorienting policies for MSME Growth 65 and employment generation. The comparison )OH[LEOH VWDWHV WKDQ LQ WKH ,QÀH[LEOH VWDWHV RIYDULRXVLQGLFDWRUVEHWZHHQ,QÀH[LEOHDQG Moreover, the linear trend lines in each case Flexible States using ASI data is displayed in indicate that the number of workers, capital Figure 6. and NVA are increasing at a faster pace in )OH[LEOH States than in the ,QÀH[LEOH states. 3.16 The )OH[LEOH 6WDWHV contribute disproportionately more on average, to labour, 3.17 Moreover, due to rigidity in the labour capital and productivity when compared to laws, employers in ,QÀH[LEOH States prefer WKH,QÀH[LEOH6WDWHV7KHDJJUHJDWHQXPEHU substituting labour with capital. This can be RIZRUNHUVFDSLWDODQG19$DUHVLJQL¿FDQWO\ seen from (a) negative rate of growth in total higher on average in the )OH[LEOH6WDWHV than number of workers in the state and average in the ,QÀH[LEOH6WDWHV. The average number number of workers per factory, and (b) of workers per factory, capital per factory SRVLWLYHUDWHRIJURZWKLQWRWDO¿[HGFDSLWDOLQ and wages per factory are also higher in the WKHVWDWHDQGDYHUDJH¿[HGFDSLWDOSHUIDFWRU\ )LJXUH&RPSDULVRQEHWZHHQ,QÀH[LEOHYV)OH[LEOH6WDWHV (a) Total Number of Workers in the State* (b) 7RWDO)L[HG&DSLWDOLQWKH6WDWH 8 Inflexible Flexible Inflexible Flexible 200 7 160 6 5 '000 crore) 120 4 80 3 40 2 1 Total fixed capital ( Total No. of workers (lakh) 0 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 (c) Total NVA in the State* (d) Average Number of Workers per Factory 75 Inflexible Flexible 70 Inflexible Flexible 60 65 60 45 '000 crore) 55 30 50 15 45 Total NVA ( 0 40 Average No. of workers per factory 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 66 Economic Survey 2018-19 Volume I (e) Average Wages per Factory I $YHUDJH)L[HG&DSLWDOSHU)DFWRU\ 105 Inflexible Flexible Inflexible Flexible 24 95 crore) lakh) 22 85 20 75 18 16 65 14 55 Av. wage per factory ( 12 45 10 Av fixed capital per factory ( 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 Source: ASI data (2011-17). * shows mean values per state per year 3.18 Thus, the evidence comparing the or Gujarat, are 25.4 per cent more productive )OH[LEOH VWDWHV WR WKH ,QÀH[LEOH VWDWHV ZLWK than their counterparts in states like West respect to the rigidity of their labour laws Bengal or Chhattisgarh that continue to FOHDUO\ VKRZV WKDW WKH LQÀH[LEOH VWDWHV DUH have labour rigidities (Dougherty, Frisancho suffering in all dimensions. They are unable and Krishna, 2014). In this context, the to create enough employment, cannot attract case study of Rajasthan is examined, which adequate capital into their states and their implemented labour reforms in 2014-15. The wages are lower as their productivity is factory level data from ASI from 2011 to lower. Furthermore, these parameters are 2017 is analyzed to see the effect of the said either deteriorating or growing at a slower labour law amendments. SDFHLQWKH,QÀH[LEOHVWDWHVZKHQFRPSDUHG to the Flexible states. 3.20 As described in Table 2, the major reforms undertaken by the State of Rajasthan Impact of the labour law change in included the amendments in IDA, 1947, Rajasthan Factories Act, 1948, The Contract Labour (Regulation & Abolition) Act, 1970 and the 3.19 Studies have found that on average, Apprentices Act, 1961. The summary of the plants in labour-intensive industries and major amendments made in these legislations in states that have transited towards more WRPDNHWKHODERXUPDUNHWPRUHÀH[LEOHDUH ÀH[LEOHODERXUPDUNHWVVXFKDV8WWDU3UDGHVK stated in Table 2. Table 2. Summary of labour reforms in Rajasthan Labour Acts Amendments introduced in Rajasthan as part of Labour Reforms Industrial Disputes Act, x To form any union, requirement of membership as a proportion of 1947 total workmen increased from 15 per cent to 30 per cent. x No government nod required for companies employing up to 300 workers for retrenching, laying off or shutting down units. Earlier limit was 100 workers. x A worker should raise an objection within three years. There was no timeline set in the earlier version with regard to discharge or termination. Nourishing Dwarfs to become Giants: Reorienting policies for MSME Growth 67 Factories Act, 1948 x Threshold limit increased from 10 or more workers with power to 20 or more workers with power. x 20 or more workers without power to 40 or more workers without power. x Complaints against the employer about violation of this Act would not receive cognizance by a court without prior written permission from the State government. The Contract Labour x Applicable to establishments that employ 50 or more workers on (Regulation and contract against the earlier 20 or more workers. Abolition) Act, 1970 Apprentices Act, 1961 x Fix the number of apprentice-training related seats in industry and establishments. x The stipend for apprentices will be no less than the minimum wage. x To encourage skilling, government to bear part of costs of apprentice training. Source: Ministry of Labour & Employment and Survey compilation 3.21 The effect of the amendments in labour of India. However, following the law change, laws in Rajasthan on various outcomes are WKH QXPEHU RI ¿UPV ZLWK HPSOR\HHV evaluated in Figures 7 and 8 using data from RU PRUH KDYH LQFUHDVHG DW D VLJQL¿FDQWO\ ASI. Figure 7 shows the time-series of the higher rate in Rajasthan than in the Rest of average number of factories having more than ,QGLD 7KLV ¿JXUH LOOXVWUDWHV LQ HVVHQFH WKH 100 employees for Rajasthan and the Rest of difference-in-difference that is estimated: the India1. The measure for the Rest of India4 before-after difference for Rajasthan vis-à- is averaged over all the states. As the law changes occurred in 2014-15, we examine vis the same estimate for the Rest of India. this variable from two years before to two As the law change that Rajasthan effected years after the law change. In 2014-15, the did not occur for the Rest of India, Figure 7 DYHUDJHQXPEHURI¿UPVZLWKHPSOR\HHV clearly shows that the law change increased or more are similar for Rajasthan and the Rest WKHQXPEHURIODUJHU¿UPV Figure 7. Average number of factories employing at least 100 workers in Rajasthan and Rest of India Rajasthan Rest of India 1,130 1,680 1,080 1,630 1,580 1,030 1,530 980 1,480 930 1,430 880 1,380 830 1,330 2013 2014 2015 2016 2017 Source: Survey Computations using ASI, 2013-2017. ______Note: Averages are computed for Rajasthan and for the Rest of India (RoI) separately. 4 Rest of India includes 20 biggest states of India namely, Assam, Bihar, Chhattisgarh, Delhi, Goa, Gujarat, Haryana, Himachal Pradesh, Jharkhand, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Odisha, Punjab, Andhra Pradesh &Telangana, Tamil Nadu, Uttarakhand, Uttar Pradesh, and West Bengal. These states cumulatively constitute over 95 per cent to Net Value Added. 68 Economic Survey 2018-19 Volume I 3.22 Figure 8 shows explicitly the change 5DMDVWKDQ KDV LQFUHDVHG VLJQL¿FDQWO\ YLVj in Compound Annual Growth Rates (CAGR) vis the Rest of India. Table 3 shows the results two years before and two years after the of estimating this difference-in-difference in law change. We compare the number of a panel data setup including tighter controls operating factories employing more than for various confounding factors. The results 100 employees in the state, average number remain unchanged from those seen in of workers per factory in a state, total output Figure 8. Thus, overall the evidence clearly in the state and total output per factory in demonstrates that each of these outcomes the state. It can be clearly seen that, for all was positively impacted by the labour law variables, CAGR post labour reforms in change in Rajasthan. Figure 8. Impact of Deregulation of Labour market in Rajasthan DVUHÀHFWHGLQ&$*5RIWKHYDULDEOHV a) Number of factories with >100 employees (b) Total output Before Reform After Reform Before Reform After Reform 9.33% 12% 5.52% 4.56% 5.71% 4.80% 3.65% 3.13% Rajasthan Rest of India Rajasthan Rest of India (c) Number of workers per factory (d) Total output per factory Before Reform After Reform Before Reform After Reform 11.18% 11.24% 4.17% 2.14% 2.60% 6.71% Rajasthan Rest of India 1.43% -8.89% Rajasthan Rest of India Source: Survey Computations using ASI, 2011-2017. Note: Averages are computed for Rajasthan and for the Rest of India separately. Nourishing Dwarfs to become Giants: Reorienting policies for MSME Growth 69 Table 3. Difference-in-Difference estimates of Labour Law Amendments in Rajasthan Variables Log (No of Log Log (No of Log Log (Total Log Log Factories (No. of Workers (Total Output per (Total (Wages with >100 Workers) per Output) Factory) Wages) per employees) Factory) Factory) Difference- in-difference 0.04*** 0.02** 0.05*** 0.04*** 0.05*** 0.04*** 0.05*** estimate (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) Observations 146 146 146 146 146 146 146 R-squared 0.9924 0.9957 0.9605 0.9933 0.9735 0.9921 0.9655 State FE Yes Yes Yes Yes Yes Yes Yes Year FE Yes Yes Yes Yes Yes Yes Yes Source: Computations based on ASI data. Robust standard errors in parentheses 1RWH DQG GHQRWHVWDWLVWLFDOO\VLJQL¿FDQWDW DQG SHUFHQWOHYHORIVLJQL¿FDQFH. Impact of Small Scale Reservation UHDFKDQLQYHVWPHQWXSSHUOLPLWTXDQWL¿HGLQ terms of investment in plant & machinery. 7KHSROLFLHVWDUJHWHGDWWKHVPDOO¿UPV As Table 4 shows, all these policies promote referred to as the MSMEs include priority VPDOO¿UPVLUUHVSHFWLYHRIWKHLUDJH sector lending, incentives/exemptions till they Table 4. Incentives Available to Small Scale Firms (irrespective of their age) Scheme Objective Priority Sector Lending 'LUHFWDQGLQGLUHFW¿QDQFHDWVXEVLGL]HGLQWHUHVWUDWHVVKDOOLQFOXGH all loans given to micro and small enterprises, irrespective of their age. Credit Guarantee Fund Scheme This scheme makes available collateral-free credit to the micro and small enterprises, irrespective of their age. Purchase Preference Policy A group of items (Group IV) are reserved for exclusive purchase from small scale units, irrespective of their age. Group V items are to be purchased from MSMEs, irrespective of their age, up to 75 per cent of the requirement. Price Preference Policy For selected items that are produced by both small scale and large VFDOHXQLWVSULFHSUHIHUHQFHLVSURYLGHGWRVPDOO¿UPVLUUHVSHFWLYH of their age. This price preference amounts to a 15 per cent premium over the lowest quotation of the large-scale units. %HQH¿WVLQWHQGHULQJ 060(V LUUHVSHFWLYH RI WKHLU DJH FDQ DYDLO EHQH¿WV VXFK DV availability of tender sets free of cost, exemption from payment of earnest money deposit, exemption from payment of security deposit. Raw Material Assistance This scheme aims to help MSMEs, irrespective of their age, with Scheme of National Small ¿QDQFLQJ WKH SXUFKDVH RI UDZ PDWHULDO ERWK LQGLJHQRXV DQG Industries Corporation (NSIC) imported). 70 Economic Survey 2018-19 Volume I Marketing Assistance Scheme Provides assistance to MSMEs, irrespective of their age, for the following activities: organization of exhibitions abroad, co- sponsoring of exhibitions organized by other organizations, organizing buyer-seller meets, intensive campaigns and marketing promotion activities. GST Composition scheme 6FKHPHDOORZV060(¿UPVLUUHVSHFWLYHRIWKHLUDJHWRSD\*67 DWDÀDWUDWH7KHWXUQRYHUOLPLWIRUEXVLQHVVHVDYDLOLQJRIWKH*67 composition scheme is set at `1.5 crore. Exemption under Central Small scale units below a turnover of `4 crore, irrespective of their Excise law DJHPDQXIDFWXULQJJRRGVSHFL¿HGLQ66,DUHHOLJLEOHIRUH[HPSWLRQ 3.24 The Small Scale Industries (SSI) SRVLWLYH YDOXH LQGLFDWHV WKDW D ¿UP LQ WKH reservation policy was introduced in 1967 (size, age) cohort is likely to manufacture the to promote employment growth and income de-reserved product while a negative value re-distribution. Given the predominance of LQGLFDWHVWKDWD¿UPLQWKH VL]HDJH FRKRUW dwarfs in the Indian economy and the low is likely to manufacture the reserved product. productivity and employment generation, as 7KH ¿JXUH FOHDUO\ VKRZV WKDW GZDUIV LH shown above, it is crucial to examine the role ¿UPVWKDWDUHVPDOODQGROGDUHVLJQL¿FDQWO\ of the SSI reservation policy. more likely to manufacture reserved SURGXFWV WKDQ DQ\ RWKHU FDWHJRU\ RI ¿UP 3.25 Figure 9 below plots the share of $OVRODUJHU¿UPV DERYHHPSOR\HHV DQG establishments manufacturing de-reserved \RXQJHU ¿UPV DUH VLJQL¿FDQWO\ PRUH OLNHO\ products minus the share of establishments to manufacture de-reserved products than manufacturing reserved products within VPDOOHU¿UPV a (size, age) cohort in the year 2007. A )LJXUH 8VHRI6PDOO6FDOH5HVHUYDWLRQE\)LUPVRI'LIIHUHQW6L]HDQG$JH ŝĨĨĞƌĞŶĐĞ ĞƚǁĞĞŶ ZĞƐĞƌǀĞĚĂŶĚ ĞͲZĞƐĞǀĞĚ ϯ͘Ϭй Ϯ͘Ϭй ϭ͘Ϭй Ϭ͘Ϭй ϭϭͲϭϮ Ͳϭ͘Ϭй ͲϮ͘Ϭй ϱͲϲ ŐĞ Ϭ ^ŝnjĞ Source: Martin, Nataraj & Harrison, 2014. Notes: The chart plots the share of establishments manufacturing de-reserved products minus the share of establishments manufacturing reserved products within a (size, age) cohort as of 2007. A SRVLWLYHYDOXHLQGLFDWHVWKDWD¿UPLQWKH VL]HDJH FRKRUWLVOLNHO\WRPDQXIDFWXUHWKHGHUHVHUYHG SURGXFWZKLOHDQHJDWLYHYDOXHLQGLFDWHVWKDWD¿UPLQWKH VL]HDJH FRKRUWLVOLNHO\WRPDQXIDFWXUH the reserved product. Nourishing Dwarfs to become Giants: Reorienting policies for MSME Growth 71 3.26 From 1997 to 2007, several product across various product categories. It is clear FDWHJRULHV UHVHUYHG IRU VPDOOVFDOH ¿UPV IURP WKH ¿JXUH WKDW SODQW DQG PDFKLQHU\ were eliminated in a phased manner. Martin, LQFUHDVHG WKH PRVW DPRQJ LQFXPEHQW ¿UPV Nataraj & Harrison (2014) analyse the just below the threshold in the 9-10 million impact of this phased de-reservation on job category. In contrast, plant and machinery creation and destruction among incumbents GHFUHDVHGDPRQJLQFXPEHQW¿UPVEHORZWKH and entrants by their size and age. Figure 10 thresholds in the 0.1-0.5 million and 0.5-1.5 examines whether the size based reservation million categories. Thus, this analysis at the ZDV OLPLWLQJ LQ WKH ¿UVW SODFH RU QRW $V 060(VZHUHGH¿QHGEDVHGRQWKHVL]HRIWKHLU threshold clearly suggests that small-scale SODQWDQGPDFKLQHU\WKLV¿JXUHH[DPLQHVWKH UHVHUYDWLRQOLPLWHGWKHLQFXPEHQW¿UPVWKDW change in the plant, property and equipment intended to grow before de-reservation but DPRQJWKHLQFXPEHQW¿UPV WKHYHUWLFDOOLQH FRXOGQRWGRVRZLWKRXWORVLQJRXWWKHEHQH¿WV LQ WKH ¿JXUH VKRZV WKH WKUHVKROG DYHUDJHG provided by the reservation. Figure 10. The Impact of Small Scale Reservation at the Threshold Source: Martin, Nataraj & Harrison, 2014. 3.27 Figure 11 shows the impact of the each age cohort, job destruction was the phased elimination of small scale reservations PD[LPXP DPRQJ WKH VPDOOHVW ¿UPV on employment (from Martin, Nataraj & HPSOR\HHV DQG OHDVW DPRQJ WKH ¿UPV ZLWK +DUULVRQ 7KLV ¿JXUH FOHDUO\ VKRZV 50-99 employees. In contrast, within each age WKDW ZKLOH VPDOO ¿UPV ORVW MREV IROORZLQJ cohort, job creation was the maximum among GHUHVHUYDWLRQ ODUJH ¿UPV FUHDWHG MREV ,Q WKHODUJHVW¿UPV HPSOR\HHV DQGOHDVW fact, across all age categories, the effect of DPRQJWKH¿UPVZLWK HPSOR\HHV7KLV de-reservation on net job creation (negative ¿JXUHDOVRVKRZVWKDWDFURVVWKHYDULRXVVL]H in the case of job destruction and positive categories, the effect of de-reservation on net in the case of job creation) monotonically MREFUHDWLRQGHFUHDVHGZLWK¿UPDJH LQFUHDVHGZLWK¿UPVL]H6SHFL¿FDOO\ZLWKLQ 72 Economic Survey 2018-19 Volume I Figure 11. Impact of Removal of Small Scale Reservations on (PSOR\PHQWE\6L]HDQG$JH ĨĨĞĐƚŽĨĞͲ ZĞƐĞƌǀĂƚŝŽŶŽŶ ϭ ŵƉůŽLJŵĞŶƚ Ϭ͘ϱ Ϭ ͲϬ͘ϱ Ͳϭ Ͳϭ͘ϱϭͲϮ ϱͲϲ ϱϬϬн ϮϱϬͲϰϵϵ ŐĞ ϵͲϭϬ ϭϬϬͲϮϰϵ ϱϬͲϵϵ ϮϬͲϰϵ ϭϯͲϭϱ ϭϬͲϭϵ ϱͲϵ ϬͲϰ EĞŐĂƚŝǀĞ WŽƐŝƚŝǀĞ ^ŝnjĞ Source: Martin, Nataraj & Harrison, 2014. 3.28 Figures 12 and 13 display the category respectively (from Martin, Nataraj impact of the phased elimination of small & Harrison, 2014). Figure 12 shows the scale reservations on employment for both impact by size categories while Figure 13 incumbents and entrants by their size and age shows the impact by age categories. )LJXUH8VHRI6PDOO6FDOH5HVHUYDWLRQE\)LUPVRI'LIIHUHQW6L]HV Source: Martin, Nataraj & Harrison, 2014. 1RWHV 7KHFKDUWSORWVWKHSRLQWHVWLPDWHDQGWKH FRQ¿GHQFHLQWHUYDOIRUWKHHIIHFWRIWKH de-reservation of products on employment. The chart shows the effect for both new entrants and incumbents by different size categories. 3.29 Figure 12 provides several key FUHDWHGPRUHHPSOR\PHQWWKDQVPDOO¿UPV takeaways. First, on average, after the Across both new entrants and incumbents, HOLPLQDWLRQ RI UHVHUYDWLRQV ODUJH ¿UPV ± WKHVPDOO¿UPVGHVWUR\HGMREVZKLOHWKHODUJH be it new entrants or incumbents – have ¿UPVFUHDWHGMREV6HFRQGQHWMREFUHDWLRQ Nourishing Dwarfs to become Giants: Reorienting policies for MSME Growth 73 (negative in the case of job destruction and created the maximum employment as seen positive in the case of job creation) increased in the effect of entrants with more than 500 ZLWK ¿UP VL]H IRU ERWK QHZ HQWUDQWV DQG employees. Finally, the growth in employment LQFXPEHQWV6SHFL¿FDOO\MREGHVWUXFWLRQZDV was both by the entrants that started producing the maximum among the smallest incumbent the de-reserved products, especially the ¿UPV HPSOR\HHV DQG OHDVW DPRQJ WKH large incumbents that were constrained LQFXPEHQW ¿UPV ZLWK HPSOR\HHV5 by the ceilings on production owing to the In contrast, job creation was the maximum 66, UHVHUYDWLRQ SROLF\ $PRQJ ¿UPV ZLWK DPRQJ WKH ODUJHVW HQWUDQW ¿UPV at least 50 employees, job creation by HPSOR\HHV DQGOHDVWDPRQJWKHHQWUDQW¿UPV entrants was greater than job creation by with 50-99 employees. Third, large entrants incumbents. Figure 13. Use of Small Scale Reservation by Firms of Different Ages Source: Martin, Nataraj & Harrison, 2014. 1RWHV 7KH FKDUW SORWV WKH SRLQW HVWLPDWH DQG WKH FRQ¿GHQFH LQWHUYDO IRU WKH HIIHFW RI WKH de-reservation of products on employment. The chart shows the effect for both new entrants and incumbents by different age categories. 3.30 Figure 13 provides the following RU ROGHU ORVW MREV KRZHYHU WKH HIIHFW ZDV takeaways. First, when the effects of de- LQVLJQL¿FDQWIRUWKH\RXQJHULQFXPEHQWV,Q UHVHUYDWLRQRQLQFXPEHQW¿UPVDUHH[DPLQHG FRQWUDVW\RXQJHUHQWUDQWV ¿UPVWKDWDUH by their age, i.e., when one averages across \HDUVRU\RXQJHU FUHDWHGMREV KRZHYHUWKH DOOVL]HFDWHJRULHVDPRQJ¿UPVRIDSDUWLFXODU HIIHFWZDVLQVLJQL¿FDQWIRUWKHROGHUHQWUDQWV age, a very different picture emerges from 2YHUDOO ZKHQ EHQH¿WV UHVHUYHG IRU WKDW REVHUYHG LQ )LJXUH 6SHFL¿FDOO\ VPDOO ¿UPV DUH HOLPLQDWHG \RXQJHU DQG DFURVV DOO DJH FDWHJRULHV LQFXPEHQW ¿UPV larger entrants create the most jobs while either lost jobs or did not create jobs. The older and smaller incumbents destroy the ROGHVW LQFXPEHQWV ¿UPV WKDW DUH \HDUV ______5 $VWKHFRHI¿FLHQWLVWKHORJRIODERXUWKHHFRQRPLFPDJQLWXGHKDVWREHFDOFXODWHGDVH[S FRHI¿FLHQW ±)RULQVWDQFHIRU the 1-4 category, the economic magnitude is calculated as exp(-1.1)-1 = -67%. 74 Economic Survey 2018-19 Volume I maximum jobs. Together with the fact that )RXUWKWKHLQHI¿FLHQWDOORFDWLRQRIUHVRXUFHV ROGHUDQGVPDOOHU¿UPVXWLOL]HWKHUHVHUYDWLRQ results in price of manufactured products in policies the most, this evidence highlights restricted economy being too high, which IXUWKHUWKDWEHQH¿WVSURYLGHGWRVPDOOVFDOH then renders these products uncompetitive in ¿UPVLUUHVSHFWLYHRIWKHLUDJHFUHDWHSHUYHUVH a global economy. LQFHQWLYHV IRU ¿UPV WR UHPDLQ GZDUIV DQG 3.34 Overall, the evidence clearly shows that thereby limit their contribution to jobs. LQIDQWVQRWGZDUIVFRQWULEXWHVLJQL¿FDQWO\WR ,Q FRQWUDVW LQIDQW ¿UPV HVSHFLDOO\ QHZ job creation and productivity in the economy. HQWUDQWVFUHDWHWKHPRVWMREV7KHVH¿QGLQJV are consistent with the evidence provided $V\RXQJ¿UPVDUHXVXDOO\VPDOOWKRXJKDOO by Li and Rama (2015), who show that in VPDOO¿UPVDUHQRW\RXQJWKHUHLVDVWURQJ FRUUHODWLRQ EHWZHHQ ¿UP VL]H DQG ¿UP DJH GHYHORSLQJFRXQWULHV\RXQJ¿UPVH[SHULHQFH rapid gains in productivity and employment (DUOLHU GDWD RQ ¿UP DJH ZDV QRW VR HDVLO\ available. So, the effect on employment of making them one of the most important sources of economic growth. ¿UPDJHFRXOGQRWEHGLVWLQJXLVKHGIURPWKH HIIHFWRI¿UPVL]H%XWZLWKDYDLODELOLW\RI 6DQWDQD DQG 3LMRDQ0DV ¿QG VXFKGDWDWKDWGLVWLQJXLVKHV¿UPVL]HDQGDJH that the distortions brought forth by size the evidence for both U.S. and India clearly dependent policies like SSI reservation VKRZV WKDW \RXQJ ¿UPV QRW VPDOOHU ¿UPV have resulted in substantial misallocation produce more jobs (Haltiwanger, Jarmin of resources and productivity losses to the and Miranda, 2012 for the U.S. and Martin, Indian economy. They provide empirical Nataraj & Harrison, 2014 and Li and Rama, evidence that the lifting of the SSI reservation 2013 for India). policy would increase output per worker by 3.2 per cent, capital per worker by 7.1 per WAY FORWARD cent and aggregate Total Factor Productivity 3.35 MSMEs that grow not only create (TFP) by 0.8 per cent in India. When focused JUHDWHU SUR¿WV IRU WKHLU SURPRWHUV EXW DOVR only within the manufacturing sector, lifting contribute to job creation and productivity in of the SSI reservation policy would increase the economy. Our policies must, therefore, output per worker would increase by 9.8 per focus on enabling MSMEs to grow by cent, capital per worker by 12.5 per cent and unshackling them. TFP by 3.6 per cent. 3.36 The evidence provided above highlights 3.33 The misallocation of resources due WKDW GZDUIV LH VPDOO ¿UPV WKDW KDYH to SSI reservation policy originates from continued to remain small despite aging, four sources (Santana and Pijoan-Mas, have low productivity and low value added in 2010). First, SSI policies substantially lower manufacturing. In contrast, infants, i.e., small the average capital to labour ratio when ¿UPVWKDWDUHVPDOOZKHQWKH\DUH\RXQJEXW FRPSDUHG WR WKH HI¿FLHQW OHYHO 6HFRQG FDQJURZWREHFRPHODUJH¿UPVDVWKH\DJH because of the lower capital accumulation, have high productivity and higher value added the overall demand for labour and the market in manufacturing. Therefore, while dwarfs wage rate are much lower due to SSI policies consume vital resources that could possibly WKDQ WKH HI¿FLHQW OHYHO 7KLUG 66, SROLFLHV EHJLYHQWRLQIDQW¿UPVWKH\FRQWULEXWHOHVV UHVXOWLQLQHI¿FLHQWDOORFDWLRQRIPDQDJHULDO to creation of jobs and economic growth as talent, which in turn affects productivity. FRPSDUHG WR LQIDQW ¿UPV 7KLV QHFHVVLWDWHV Nourishing Dwarfs to become Giants: Reorienting policies for MSME Growth 75 re-calibration of policy towards supporting Under MSME’s PSL targets, it is necessary LQIDQW¿UPVDVGHWDLOHGEHORZ to prioritize ‘start ups’ and ‘infants’ in high employment elastic sectors. This would 3.37 ,QFHQWLYL]LQJ µLQIDQW¶ ¿UPV UDWKHU HQKDQFHGLUHFWFUHGLWÀRZWRVHFWRUVWKDWFDQ With the appropriate WKDQ µVPDOO¶ ¿UPV create the most jobs in the economy. The table grandfathering of existing incentives, they below shows the high employment elastic need to be shifted away from dwarfs to sub-sectors and their employment elasticity. infants. When such incentives are provided to ¿UPVLUUHVSHFWLYHRIWKHLUDJHWKHLQFHQWLYHV Table 5. Employment Elasticity of Various FUHDWH³SHUYHUVH´LQFHQWLYHVIRU¿UPVWRVWD\ Subsectors in Manufacturing small. Such perverse incentives would not be Employment there if age is the criterion. Misuse of the age Subsector Elasticity based criterion can be easily avoided using Rubber and Plastic Products 0.85 Aadhaar. For instance, if a promoter starts a Electrical and Optical QHZ ¿UP XWLOL]HV WKH EHQH¿WV IRU WHQ \HDUV Equipment 0.48 when the age-based policy is available and Transport Equipment 0.27 WKHQ FORVHV WKH ¿UP WR VWDUW D QHZ RQH WR Electricity, Gas and Water DYDLOWKHDJHEDVHGEHQH¿WVWKURXJKWKLVQHZ Supply 0.22 ¿UP WKHQ WKH$DGKDDU RI WKH SURPRWHU FDQ alert authorities about this misuse. Therefore, Machinery 0.15 JLYHQWKHEHQH¿WVRI$DGKDDUWKHDJHEDVHG Basic Metals and Fabricated policies can be implemented to ensure Metal Products 0.10 removal of the perverse incentives. Once Chemicals and Chemical VPDOO ¿UPV NQRZ WKDW WKH\ ZRXOG UHFHLYH Products 0.07 QR EHQH¿W IURP FRQWLQXLQJ WR UHPDLQ VPDOO Textiles, Textile Products, despite aging, their natural incentives to Leather and Footwear 0.02 grow would get activated. This will generate Other Non-Metallic Mineral economic growth and employment. Products 0.02 Wood and Products of wood 0.01 3.38 Re-orienting Priority Sector Lending Source: Derived from KLEMS data from 2005-06 to (PSL): As per extant policy, certain targets 2015-16 have been prescribed for banks for lending to the Micro, Small and Medium (MSME) 3.39 Sunset Clause for Incentives: With sector that exacerbates perverse incentives to appropriate grandfathering, every incentive ¿UPVWRUHPDLQVPDOO$VSHU36/JXLGHOLQHV for fostering growth should have a ‘sunset’ 7.5 per cent of Adjusted Net Bank Credit FODXVHVD\IRUDSHULRGRI¿YHWRVHYHQ\HDUV (ANBC) or Credit Equivalent Amount of DIWHUZKLFKWKH¿UPVKRXOGEHDEOHWRVXVWDLQ Off-Balance Sheet Exposure, whichever is itself. The policy focus would thereby remain higher is applicable to Micro enterprises.6 RQLQIDQW¿UPV ______6 As on 28th'HFHPEHUIRUFODVVL¿FDWLRQXQGHUSULRULW\VHFWRUQROLPLWVDUHSUHVFULEHGIRUEDQNORDQVVDQFWLRQHGWR 0LFUR6PDOODQG0HGLXP(QWHUSULVHVHQJDJHGLQWKHPDQXIDFWXUHRUSURGXFWLRQRIJRRGVXQGHUDQ\LQGXVWU\VSHFL¿HGLQ WKH¿UVWVFKHGXOHWRWKH,QGXVWULHV 'HYHORSPHQWDQG5HJXODWLRQ $FW DQGDVQRWL¿HGE\WKH*RYHUQPHQWIURPWLPH WRWLPH7KHPDQXIDFWXULQJHQWHUSULVHVDUHGH¿QHGLQWHUPVRILQYHVWPHQWLQSODQWDQGPDFKLQHU\XQGHU060('$FW %DQNORDQVWR0LFUR6PDOODQG0HGLXP(QWHUSULVHVHQJDJHGLQSURYLGLQJRUUHQGHULQJRIVHUYLFHVDQGGH¿QHGLQWHUPVRI LQYHVWPHQWLQHTXLSPHQWXQGHU060('$FWLUUHVSHFWLYHRIORDQOLPLWVDUHHOLJLEOHIRUFODVVL¿FDWLRQXQGHUSULRULW\ sector, w.e.f. March 1, 2018. 76 Economic Survey 2018-19 Volume I 3.40 Focus on High Employment Elastic high Spillover Effects such as Tourism: Sectors: The manufacture of rubber and Developing key tourist centres will have plastic products, electronic and optical ripple effects on job creation in areas such products, transport equipment, machinery, as tour and safari guides, hotels, catering basic metals and fabricated metal products, and housekeeping staff, shops at tourist spots chemicals and chemical products, textiles etc. It is possible to identify 10 tourism spots and leather & leather products, are the sub- in each of the larger 20 states and 5 spots sectors with highest employment elasticities. in the 9 smaller states and build road and air connectivity in these tourist attractions, To step up the impact of economy growth on which would boost economic activity along employment, the focus has to be on such high the entire route and would also reduce the employment elastic sectors. migration of the rural labour force who form 3.41 Focus on Service Sectors with a major proportion of the total labour force. CHAPTER AT A GLANCE 060(VWKDWJURZQRWRQO\FUHDWHJUHDWHUSUR¿WVIRUWKHLUSURPRWHUVEXWDOVRFRQWULEXWHWR ¾ job creation and productivity in the economy. Our policies must, therefore, focus on enabling MSMEs to grow by unshackling them. -REFUHDWLRQLQ,QGLDKRZHYHUVXIIHUVIURPSROLFLHVWKDWIRVWHUGZDUIVLHVPDOO¿UPVWKDW ¾ QHYHUJURZLQVWHDGRILQIDQW¿UPVWKDWKDYHWKHSRWHQWLDOWRJURZDQGEHFRPHJLDQWVUDSLGO\ :KLOHGZDUIVLH¿UPVZLWKOHVVWKDQZRUNHUVGHVSLWHEHLQJPRUHWKDQWHQ\HDUVROG DFFRXQWIRUPRUHWKDQKDOIRIDOORUJDQL]HG¿UPVLQPDQXIDFWXULQJE\QXPEHUWKHLUFRQWULEXWLRQ ¾ to employment is only 14 per cent and to productivity is a mere 8 per cent. In contrast, large ¿UPV PRUHWKDQHPSOR\HHV DFFRXQWIRUWKUHHTXDUWHUVRIVXFKHPSOR\PHQWDQGFORVHWR 90 per cent of productivity despite accounting for about 15 per cent by number. 7KHSHUFHSWLRQRIVPDOO¿UPVEHLQJVLJQL¿FDQWMREFUHDWRUVSHUYDGHVEHFDXVHMREGHVWUXFWLRQ E\VPDOO¿UPVLVLJQRUHGLQWKLVFDOFXOXV VPDOO¿UPVGHVWUR\MREVDVPXFKDVWKH\FUHDWH,Q ¾ FRQWUDVWODUJH¿UPVFUHDWHSHUPDQHQWMREVLQODUJHUQXPEHUV$OVR\RXQJ¿UPVFUHDWHPRUH MREVDWDQLQFUHDVLQJUDWHWKDQROGHU¿UPV 6L]HEDVHGLQFHQWLYHVWKDWDUHSURYLGHGLUUHVSHFWLYHRI¿UPDJHDQGLQÀH[LEOHODERXUUHJXODWLRQ ¾ which contain size-based limitations, contribute to this predicament. To unshackle MSMEs and thereby enable them to grow, all size-based incentives must have a ¾ sunset clause of less than ten years with necessary grand-fathering. 'HUHJXODWLQJODERXUODZUHVWULFWLRQVFDQFUHDWHVLJQL¿FDQWO\PRUHMREVDVVHHQE\WKHUHFHQW ¾ changes in Rajasthan when compared to the rest of the States. 'LUHFWFUHGLWÀRZWR\RXQJ¿UPVLQKLJKHPSOR\PHQWHODVWLFVHFWRUVWRDFFHOHUDWHHPSOR\PHQW ¾ generation by re-calibrating Priority Sector Lending (PSL) guidelines. Focus must be on service sectors such as tourism, which has high spillover effects on other ¾ sectors such as hotel & catering, transport, real estate, entertainment etc. Identifying and promoting tourist spots for development will help create jobs. Nourishing Dwarfs to become Giants: Reorienting policies for MSME Growth 77 REFERENCES Manuel Garcia-Santana, Josep Pijoan-Mas. n.d. "Small Scale Reservation Laws and the Chang-Tai Hsieh, Peter J. Klenow. 2014. "The Misallocation of Talent." Working Paper Life Cycle of Plants in India and Mexico." wb2010_1010,&(0),. 7KH4XDWHUO\-RXUQDORI(FRQRPLFV. Sean Dougherty, Veronica Frisancho,k John C. Haltiwanger, Ron S. Jarmin, Javier Krishna. 2014. "The costs of employment 0LUDQGD :KR &UHDWHV -REV" 6PDOO protection." ,GHDVIRU,QGLD, April 30. vs. Large vs. Young." 1%(5Working Paper No. 16300. Yue Li, Martin Rama. 2015. "Firm Dynamics, Productivity Growth, and Job Creation in Leslie A. Martin, Shanthi Nataraj, Ann Developing Countries: The Role of Micro- Harrison. 2014. "In with the Big, Out with the and Small Enterprises." 7KH :RUOG %DQN Small: Removing Small-Scale Reservations 5HVHDUFK2EVHUYHU9ROXPH,VVXH. in India." 1%(5 Working Paper No. 19942. Data “Of the People, By the People, 04 For the People” CHAPTER “Cross the river by feeling the stones.” - Deng Xiaoping Navigating in an uncertain, wobbly world requires constant monitoring of the path followed by the economy using real-time indicators. Thus, data can serve as the stones that enable one to cross the river. Concurrent with the data explosion of recent years, the marginal cost of data has declined exponentially ZKLOHLWVPDUJLQDOEHQH¿WWRVRFLHW\KDVLQFUHDVHGPDQLIROG7KHUHIRUHVRFLHW\¶V optimal consumption of data is higher than ever. While private sector does a JRRGMRERIKDUQHVVLQJGDWDZKHUHLWLVSUR¿WDEOHJRYHUQPHQWLQWHUYHQWLRQLV needed in social sectors of the country where private investment in data remains inadequate. Governments already hold a rich repository of administrative, survey, institutional and transactions data about citizens, but these data are scattered across numerous government bodies. Utilising the information embedded in these distinct datasets would inter alia enable government to enhance ease of living for citizens, enable truly evidence-based policy, improve targeting in welfare schemes, uncover unmet needs, integrate fragmented markets, bring greater accountability in public services, generate greater citizen participation in governance, etc. Given that sophisticated technologies already exist to protect SULYDF\ DQG VKDUH FRQ¿GHQWLDO LQIRUPDWLRQ JRYHUQPHQWV FDQ FUHDWH GDWD DV a public good within the legal framework of data privacy. In the spirit of the Constitution of India, data should be “of the people, by the people, for the people.” THE ECONOMICS OF DATA AND is being generated at an unprecedented scale. SOCIAL WELFARE The global data infrastructure has largely proved reliable, fast and secure enough to 4.1 In recent years, the world has witnessed handle this deluge of data (Mckinsey, 2011). an information explosion – exponential increases in the amount of published data. As 4.2 Concurrent with this data explosion, people increasingly use digital services to talk the marginal cost of data has declined to each other, look up information, purchase H[SRQHQWLDOO\ DQG WKH PDUJLQDO EHQH¿W WR society of using this data is higher than ever. goods and services, pay bills, transact in ¿QDQFLDO PDUNHWV ¿OH WD[HV DYDLO ZHOIDUH 4.3 As people shift their day-to-day services and engage with local leaders, data activities online, they leave digital footprints Data “Of the People, By the People, For the People” 79 Figure 1: Falling Marginal Cost of Data Increasing skills Falling prices of and resources to data storage process data rapidly Nearly costless Increasing ways to efficiency of disseminate data gathering Falling data marginal cost of data of these activities. Put differently, people colossal quantities of data in a reasonable produce data about themselves and store this time. Fortunately, human and technical data on public and private servers, every day, capital to process data has evolved in parallel of their own accord. Data that would have to the data inundation. Data science has involved a laborious survey to gather a few HYROYHG DV D GLVWLQFW ZHOOIXQGHG ¿HOG RI decades ago is today accumulating online at a study that is constantly innovating ways to near-zero cost, although it is scattered across SXWGDWDWRHI¿FLHQWXVH&RXUVHVLQDQDO\WLFV sources. have become ubiquitous. An increasing 4.4 Not everyone participates in the digital number of people are equipped with skills to economy, of course. A majority of the poor handle large datasets. Data is still relatively still have no digital footprint. Among those expensive to process because it tends to who do, the range of activities undertaken be noisy, heterogeneous and inconsistent online is quite limited. However, the cost of across sources, but technology is incessantly gathering data is still much lower than it was developing solutions to these problems. a few decades ago. Even if a door-to-door 4.6 Once processed, the cost of survey is the only way to gather a certain disseminating insights is negligible – it kind of data, we possess cheap technologies is nearly costless to transfer information to log data online in real time, circumventing through the internet. However, dissemination an otherwise laborious paper-based survey of data entails another cost – that of ensuring followed by a tedious data entry process. data privacy and security. Before data is 4.5 Alongside the decreasing cost of disseminated, it needs to be stripped of gathering data, storage costs have decreased SHUVRQDO LGHQWL¿HUV DQG DJJUHJDWHG :KLOH precipitously. The cost per gigabyte of this is a direct cost, an indirect cost also exists storage has fallen from U61,050 in 1981 to – the cost of misuse of data. Accidental data less than U3.48 today. However, the surfeit of leaks may bring forth legal consequences and data and a limitless capacity to store it is of VXEVWDQWLDO ¿QDQFLDO LPSOLFDWLRQV +RZHYHU no use unless one can make sense of these technology has largely kept pace to mitigate 80 Economic Survey 2018-19 Volume 1 these risks. to. The government can thereby deliver a better experience to the citizen by bringing 4.7 Together, the advancements in disparate datasets scattered across various gathering, storing, processing and ministries together. dissemination have lowered the marginal cost of data to unprecedented levels. Figure 1 4.9 If the information embedded in summarises this phenomenon. Concurrently, these datasets is utilised together, data WKH PDUJLQDO EHQH¿W RI GDWD LV KLJKHU WKDQ offers potential to reduce targeting error in HYHU $ GLVWULFW HGXFDWLRQ RI¿FHU FDQ PDNH welfare schemes. For example, consider better decisions if he knows, for each school D K\SRWKHWLFDO LQGLYLGXDO ZKR LV DIÀXHQW in his district, attendance rates of students enough to own a car but is able to avail BPL and teachers, average test scores and status ZHOIDUHVFKHPHVWKRXJKXQZDUUDQWHG:KHQ of school toilets. Similarly, parents can datasets are unconnected, the vehicle registry make better decisions about which school does not speak to, say, the public distribution to send their children to if they know the system registry. Consequently, the public average absenteeism rate of teachers in their distribution system continues to subsidise village and can compare the rate to that in this individual erroneously. However, if the the neighbouring village. A multitude of two datasets are integrated, such inclusion scenarios exist in which harnessing the error can be minimised, saving valuable marginal unit of data can lead to sharp Government resources. In the same way, increases in public welfare. H[FOXVLRQHUURUVFDQEHUHFWL¿HG 4.8 Consider data that the Government 4.10 In fact, the declining cost of data has maintains about its citizens. Currently, much VSDZQHG QHZ EHQH¿WV WKDW GLG QRW H[LVW D of the data is dispersed across different few years ago. Consider, for example, an app registries maintained by different ministries. that informs farmers of the prices of produce This is why every time a citizen has to access across the country. There was a time when, a new service, they are asked to collect all the documents to prove their identity and prove even if the app existed, it would have been their claim on the process. For example, to useless – knowing that prices are higher in JHW VXEVLGLHV RU EHQH¿WV GXH WR D IDUPHU the next district would not have mattered to a such as free electricity, an incomplete list of farmer as he would have had no way to access GRFXPHQWVLQFOXGHWKH2ZQHUVKLS&HUWL¿FDWH those prices without substantial costs in LVVXHG E\ 9LOODJH $GPLQLVWUDWLYH 2I¿FHU transport, storage and distribution (including Chitta Adangal (extract from land registry), the cost of a dozen middlemen). Today, with a Patta (Record of Rights) or Sale Deed, No platforms such as e-NAM (the electronic 2EMHFWLRQ&HUWL¿FDWHIURPDQ\*RYHUQPHQW National Agriculture Market, we possess Project nearby and other documents to prove the technology to allow farmers to make the that one is a farmer on that land. The effort sale online, locking in the higher price with involved in this application mostly doesn’t delivery to follow seamlessly. In this way, involve any new audits or inspections from data has the potential to integrate markets any government department. The citizen faces nationally, reduce the need for middlemen, the inconvenience of having to retrieve data reduce prices for end consumers and increase WUDSSHGLQSDSHU¿OHVZLWKLQWKHJRYHUQPHQW prices for farmers. Figure 2 summarises these V\VWHP WR XQORFN D EHQH¿W VKH LV HQWLWOHG FRVWVDQGEHQH¿WV Data “Of the People, By the People, For the People” 81 )LJXUH ,QFUHDVLQJ0DUJLQDO%HQH¿WVDQG'HFUHDVLQJ0DUJLQDO&RVWRI'DWD Marginal benefits Marginal costs Evidence-based policy Gathering data Accountability in public Storing data Decreasing marginal cost services Processing data Better targeting of welfare Disseminating data programmes Nationally integrated markets Increasing marginal benefit Increasing marginal Product innovation WHY MUST DATA BE TREATED PDUNHW,IWKHPDUJLQDOEHQH¿WWRDIDUPHURI AS A PUBLIC GOOD? acquiring price information is higher than the marginal cost of that information, he would 4.11 The decline in marginal cost of data pay for that information. Consequently, the FOXEEHGZLWKDQLQFUHDVHLQPDUJLQDOEHQH¿W private sector would cater to his need by means that the optimal quantum of data that gathering and selling him the information society should consume is much higher than he wants. This would eventually lead to before. If so, economic theory predicts that a nationally integrated agriculture market the economy should have, by now, seen a with one price. However, India does not yet surge in efforts to harness and use data. This have such a nationally integrated agriculture has indeed happened, but only partially. market, which should have happened if the PDUJLQDO EHQH¿W RI GDWD WRGD\ LV LQGHHG 4.12 Private sector investment in data- KLJKHUWKDQWKHFRVW:K\KDVWKHFRUSRUDWH related endeavours is higher than ever sector’s data wave not found a parallel in the before. A 2017 Forbes survey found that 53 agriculture sector? per cent of companies actively use big data to make decisions (Dresner, 2017). The 4.14 The economics of data we considered trend holds across industries as disparate as so far is as it pertains to society, not to an KHDOWKFDUHDQG¿QDQFLDOVHUYLFHVDQGDFURVV LQGLYLGXDO DJHQW EH LW D IDUPHU RU D ¿UP geographies and company sizes. In fact, in the The economics facing a private company last two decades, the world has witnessed the that contemplates providing data to farmers emergence of companies, such as Facebook, is different from that facing a social Amazon, Instagram, etc., who earn revenue SODQQHU7RWKHSULYDWH¿UPWKHSURVSHFWRI exclusively from people’s data. a nationally integrated agriculture market, and the resulting social welfare, is a positive 4.13 But, there are several areas where H[WHUQDOLW\,WLVQRWDEHQH¿WWKDWDFFUXHVWR data is not as ubiquitously harnessed and WKH¿UPDVWKH¿UPFDQQRWLQSUDFWLFHFKDUJH used. Consider, for example, the agriculture the numerous agents in the economy who 82 Economic Survey 2018-19 Volume 1 would experience welfare gains. Therefore, incentive structure faced by the private sector, WKHSULYDWH¿UP¶VPDUJLQDOEHQH¿WLVQRWDV depending on the nature and sensitivity of KLJK DV VRFLHW\¶V PDUJLQDO EHQH¿W %HFDXVH data. Indeed, in the agriculture sector, the WKH ¿UP GRHV QRW LQWHUQDOL]H WKH EHQH¿W RI Government has done exactly this by creating social welfare, the optimal amount of data the e-NAM, as it is unlikely that the private WKDW WKH ¿UP ZRXOG JDWKHU DQG GLVVHPLQDWH sector would come up with a solution like falls short of the social optimum. this on its own. 4.15 Second, data comes in many forms (QVXULQJ GDWD SULYDF\ ZKLOH FUHDWLQJ ZLWK HDFK IRUP RIIHULQJ D GLIIHUHQW EHQH¿W GDWDDVDSXEOLFJRRG Data linked to an individual can range from 4.18 In the endeavour to create data as a extremely intimate – such as their biometric public good, it is very important to consider details, to the extremely public – such as their the privacy implications and inherent name. It includes data that is generated by fairness of data being used. Needless to say, human actions, and data that is derived through the processes required for ensuring privacy analysis, typically involving an algorithm. of intimate data is very different from that For example, whether an individual has paid required for anonymized or public data. The his taxes is a generated data point. But, using key difference in dealing with these different the tax records and other data points, a credit types of data is the knowledge and consent bureau may assign the individual a credit of the data principal. Even if not explicitly score, which is a derived data point. Data that mentioned every time data is talked about in LVQRWOLQNHGWRDVSHFL¿FLQGLYLGXDOEXWLVVWLOO this chapter, it is assumed that the processing available at an individual level of granularity, of data will be in compliance with accepted is called Anonymized data. Anonymized privacy norms and the upcoming privacy law, data is critical in some areas such as medical currently tabled in Parliament. research. Data neither linked to an individual, nor at an individual level of granularity is (FRQRPLHV RI VFDOH DQG VFRSH LQ WKH known as public data, such as the census. GDWDJHQHUDWLRQSURFHVV :KLOH WKH SULYDWH VHFWRU KDV GRQH DQ 4.19 Apart from the obvious necessity impressive job of harnessing some kinds of that data must be accurate, the need for data – the kind that can be converted into a Government-driven data revolution is D SULYDWH SUR¿W ± JRYHUQPHQW LQWHUYHQWLRQ motivated by three key characteristics that is required in other areas where private GDWDPXVWSRVVHVVIRUWKHV\QHUJLVWLFEHQH¿WV investment in data remains inadequate. WR DFFUXH 6SHFL¿FDOO\ WKH GDWD JHQHUDWLRQ The social sectors of the economy, such SURFHVV H[KLELWV VLJQL¿FDQW HFRQRPLHV RI as education and healthcare, have lagged scale and scope. the commercial sectors in exploiting data. Because the private sector cannot internalize 4.20 First, when it comes to data, the whole WKHVRFLDOEHQH¿WVRIGDWDLQWKHVHVHFWRUVWKH is larger than the sum of its parts, i.e., it is market for data in these sectors has so far not more useful when it is married with other developed. data. Consider, for example, the merging of disparate datasets maintained by different 4.17 To ensure that the socially optimum government agencies, such as transactions amount of data is harvested and used, the data extracted from the Jan Dhan accounts government needs to step in, either by of the Department of Financial Services, providing the data itself or correcting the Ministry of Finance, married to demand Data “Of the People, By the People, For the People” 83 for MGNREGA work from the Ministry of make the necessary investments required Rural Development. As MGNREGA can for generating data that possesses all three be a real-time indicator of rural distress (as characteristics, viz., marries disparate discussed in Chapter 10 in this volume), the datasets, covers a critical mass of individuals/ credit scoring done using the transactions ¿UPV DQG VSDQV D ODUJH WLPHVHULHV (YHQ data of Jan Dhan accounts can be used to if private sector were to put such rich data provide credit in districts/panchayats that together, this would result in a monopoly are experiencing distress. Such combining of that would reduce citizen welfare, on the one disparate datasets can be extremely useful in hand, and violate the principle of data by obtaining the necessary richness required to citizens, and, therefore, for citizens. design and implement welfare policies. 4.24 Most importantly, data carries some 4.21 Second, data needs to cover a critical of the characteristics of public goods. It PDVVRILQGLYLGXDOV¿UPVVRWKDWFRPSDULVRQV is non-rivalrous, i.e., consumption by one and correlations can be assessed among individual does not reduce the quantum LQGLYLGXDOV¿UPV WR JHQHUDWH XVHIXO SROLF\ available for others. In principle, data can insights. Thus, to gather price data on trades be made excludable, i.e., it is possible to across various product markets and across exclude people from accessing data, as many the country, a very large number of producers GDWDEDVH ¿UPV GR E\ HUHFWLQJ SD\ ZDOOV and buyers need to log their transactions on However, there are some kinds of data – a platform in real time. To induce numerous particularly data gathered by governments on issues of social interest – that should be agents to report transaction information democratised in the interest of social welfare. UHJXODUO\ LV D WDVN WKDW UHTXLUHV VLJQL¿FDQW Such data should be made public goods. As initial investment, which may prove the private sector would fail to provide an prohibitive for the private sector. optimal amount of any non-rivalrous, non- 4.22 Finally, data must have a long enough excludable good, government intervention is time-series so that dynamic effects can be required. studied and employed for policymaking. 4.25 Data are generated by the people, of the For instance, to undertake before-after people and should be used for the people. As evaluations to assess the effectiveness of a public good, data can be democratised and policies, data that spans a long-enough time put to the best possible use. Box 1 describes series is critical. the Open Government Data initiative taken 4.23 Data that contains all these three by the Government, which is an illustration features is much more valuable than three RIWKHVSLULWRIGDWDDVDSXEOLFJRRG:KLOH different and disparate datasets that possess this is an excellent start, the enormous each of these criteria separately. Thus, the EHQH¿WVWKDWFDQEHUHDSHGIURPWUHDWLQJGDWD GDWD JHQHUDWLRQ SURFHVV H[KLELWV VLJQL¿FDQW as a public good imply that Government must economies of scope. Also, the scale of redouble its efforts in this direction. effort required to create such data that BUILDING THE SYSTEM exhibits all three features implies that the GDWD JHQHUDWLRQ SURFHVV H[KLELWV VLJQL¿FDQW 4.26 The data system envisioned here economies of scale as well because the involves predominantly data that people XSIURQW ¿[HGFRVWVLQYROYHGLQJHQHUDWLQJ share with Government bodies with fully VXFKGDWDDUHVLJQL¿FDQW3ULYDWHVHFWRUPD\ informed consent or is data that is legally not have the risk appetite or the capital to sanctioned to be collected by the state for 84 Economic Survey 2018-19 Volume 1 %R[ 2SHQ*RYHUQPHQW'DWDDQGFLWL]HQHQJDJHPHQW The Union government’s Open Government Data platform allows citizens to access a range of government data in machine-readable form in one place. The portal allows union ministries and departments to publish datasets, documents, services, tools and applications collected by them for public XVH([FOXGLQJGDWDVHWVZKLFKFRQWDLQFRQ¿GHQWLDOLQIRUPDWLRQDOORWKHUGDWDVHWVDUHPDGHDYDLODEOH to the public, ranging from data on welfare schemes to surveys to macroeconomic indicators. The platform also includes citizen engagement tools like feedback forms, data visualisations, Application Programming Interface (APIs) etc. 2SHQGDWDQRWRQO\KHOSVJRYHUQPHQWRI¿FLDOVPDNHEHWWHUGHFLVLRQVEXWDOVRJHWVSHRSOHLQYROYHG in solving problems. Throwing open government data to the public multiplies the number of people analysing and deriving insights from data. Consequently, the usability of data itself increases. To engage people meaningfully in solving problems, the Ministry of Human Resource Development recently initiated the Smart India Hackathon – an open innovation model to discover new, disruptive technologies that could solve India’s most pressing problems. Smart India Hackathons are product development competitions in which participants get a problem statement and relevant data, using which they develop a prototype software or hardware. These competitions crowd-source solutions to LPSURYHJRYHUQDQFHDQGLQFUHDVHWKHHI¿FDF\RIZHOIDUHVFKHPHV1RQHRIWKLVZRXOGEHSRVVLEOHRI course, without reliable data. an explicit purpose such as tax collection, or DQG%R[IRUGHWDLOV :KLOHWKHODWWHUWZR delivering welfare. The Government of India GDWDEDVHV DUH LQ D ÀHGJOLQJ VWDWH WKH ¿UVW collects four distinct sets of data about people two are comprehensive and robustly – administrative, survey, institutional and maintained. transactions data (see Figure 3 for summary )LJXUH 'DWDFROOHFWHGE\WKH*RYHUQPHQWRI,QGLD Administrative data Survey data Birth and death records, pensions, Census data, National Sample tax records, marriage records, etc. Survey data, etc. Data about citizens maintained by governments Transactions data Institutional data e-National Agriculture Market data, Public school data on pupils, public United Payments Interface data etc. hospital data on patients, etc. Data “Of the People, By the People, For the People” 85 %R[ 5LFKGDWDRQFLWL]HQVWKDW*RYHUQPHQWFDQKDUQHVVIRUWKHZHOIDUHRILWVFLWL]HQV Governments hold administrative data for mainly non-statistical purposes. Administrative datasets include birth and death records, crime reports, land and property registrations, vehicle registrations, movement of people across national borders, tax records etc. Governments also gather data to evaluate ZHOIDUHVFKHPHV IRUH[DPSOHWKH0LQLVWU\RI'ULQNLQJ:DWHUDQG6DQLWDWLRQJDWKHUVGDWDRQWRLOHW XVDJHWRDVVHVVWKHHI¿FDF\RIWKH6ZDFKK%KDUDW0LVVLRQ Survey data, on the other hand, is data gathered predominantly for statistical purposes through V\VWHPDWLFSHULRGLFVXUYH\V)RUH[DPSOHWKH1DWLRQDO6DPSOH6XUYH\2I¿FHFRQGXFWVODUJHVFDOH sample surveys across India on indicators of employment, education, nutrition, literacy etc. Because these data are gathered for statistical analyses, the identity of participants is irrelevant and unreported, although these identities may be securely stored at the back-end without violating any legal guidelines on privacy. Institutional data refers to data held by public institutions about people. For example, a government- run district hospital maintains medical records of all its patients. A government-run school maintains personal information about all its pupils. State-run universities maintain records of students’ educational attainment and degrees awarded to them. Most such data are held locally, predominantly in paper- based form. This data can be digitized to enable aggregation at the regional or national level. Transactions data are data on an individual’s transactions such as those executed on the United Payment Interface (UPI) or BHIM Aadhaar Pay. This is a nascent category of data but is likely to grow as more people transition to cashless payment services. 4.27 Data collection in India is highly information gathered in the decennial decentralised. For each indicator of social Census survey. Because these datasets are welfare, responsibility to gather data lies unconnected (see below), each ministry only with the corresponding union ministry and has a small piece of the jigsaw puzzle that its state counterparts. Consequently, data LV WKH LQGLYLGXDO¿UP +RZHYHU LI WKHVH gathered by one ministry is maintained different pieces could be put together, we separately from that gathered by another. ZRXOG ¿QG WKDW WKH ZKROH LV JUHDWHU WKDQ Data on an individual’s vehicle registrations, the sum of parts. As learning from global for example, is maintained by one ministry, best practices, boxes 3 and 4 highlight the whereas the same individual’s property case studies of Transport for London’s data ownership records lie with another ministry. initiative and the data initiatives of the These datasets are further distinct from the U.S. Government. Box 5 illustrates similar individual’s educational attainment records learning from closer home: the Samagra maintained by the state-run university he/ Vedika initiative by the Government of she attended and from other demographic Telangana. %R[ %HQH¿WVRIRSHQLQJXS7UDQVSRUWIRU/RQGRQ¶VGDWD 7UDQVSRUWIRU/RQGRQ 7I/ UHOHDVHVDVLJQL¿FDQWDPRXQWRIGDWD±VXFKDVWLPHWDEOHVVHUYLFHVWDWXV and disruption information – in an open format for anyone to use, free of charge. Open travel data can support travel apps and real-time alerts to save time, reduce uncertainty and lower information costs, supporting growth in the tech economy and increasing the use of public transport. At last count, more WKDQDSSVZHUHEHLQJSRZHUHGVSHFL¿FDOO\XVLQJWKH7I/RSHQGDWDIHHGVXVHGE\SHUFHQWRI Londoners. 86 Economic Survey 2018-19 Volume 1 TfL has demonstrated that releasing data to the public can save users time to the economic value of between £15m and £58m per year. An analysis by Deloitte found that the provision of transport information through travel apps and real-time alerts is saving £70m-£95m per year in time, reduced uncertainty and lower information costs. Further, release of open data by TfL has supported the growth of London’s tech economy to the value of £14m annually in gross value added (GVA) and over 700 jobs. It has also unlocked new revenue and savings opportunities and new ways of working at TfL, including a £20m increase in bus usage as customers are more aware of service opportunities. This data has been used by a range of apps, from early stage start-ups to global leading technology platforms, saving time and reducing stress. There are currently 13,700 registered users of TfL’s open data. The London Infrastructure Mapping Application is a new platform that allows utilities, boroughs, the Mayor of London and TfL to share information relevant to infrastructure investment and planning. By bringing together a range of data, the application facilitates improved collaboration between actors, MRLQHGXS DSSURDFKHV WR FRQVWUXFWLRQ DQG GHVLJQ DQG EHWWHU LGHQWL¿FDWLRQ RI IXWXUH GHPDQG DQG capacity constraints. Information is visualised spatially through a bespoke mapping application that has been developed in consultation with users. Early evidence has found that the tool supports better alignment of investment – unlocking housing growth and reducing disruption throughout London – by allowing projects such as road works to be timed better, and saving costs through joined-up approaches to construction (e.g. joint ducting of utility cables and pipes). TfL is currently developing a new tool that will analyse data feeds from Tube trains to provide maintenance staff with live information about the condition of a train. Using the tool, staff can analyse the data and identify where faults exist or might be developing and remedy them before they cause VHUYLFHLVVXHV7KHWRROKDVVWURQJSRWHQWLDOWRPDNHPDLQWHQDQFHSODQQLQJPRUHHI¿FLHQWDQGSUHYHQW costly faults leading to service delays from occurring. The in-house capability will also help TfL VDYHPRQH\E\UHGXFLQJWKLUGSDUW\VSHQG±FXUUHQWO\DURXQG PRYHU¿YH\HDUVRQDQH[WHUQDO maintenance support contract. Source: National Infrastructure Commission Report on Data as a Public Good available at https://www.nic.org. uk/wp-content/uploads/Data-for-the-Public-Good-NIC-Report.pdf Box 4: Data Initiatives taken by U.S. Government On January 29, 2009, U.S. President Barack H. Obama issued a memorandum on open and transparent government and asked his administration to establish "a system of transparency, public participation, and collaboration". The open-government initiative mandates federal government and public agencies to publish their data online for public use in machine-readable format. In a bid to democratise its data, U.S. government made more than 138,000 data sets available to the public. In February 2015, the 86JRYHUQPHQWDSSRLQWHG'-3DWLODVLWV¿UVWHYHU&KLHI'DWD6FLHQWLVWLQWKH2I¿FHRI6FLHQFHDQG 7HFKQRORJ\3ROLF\WRXQOHDVKWKHSRZHURIGDWDIRUWKHEHQH¿WRIWKH$PHULFDQSXEOLF Data.gov, the preeminent platform of U.S. Government shares data and meta-data from various public agencies and has ‘value added’ features like: L $ELOLW\WR¿OWHUE\ORFDWLRQGDWDVHWW\SHWDJIRUPDWFRPPXQLW\HWF (ii) A tool to integrate data-sets and create visualizations; (iii) Engagement with public to provide feedback and participation in various forums, blogs and communities to improve the quality of data-sets; Data “Of the People, By the People, For the People” 87 (iv) Resources that provide links to all federal agency API’s; (v) Developer hub with software development kits, open-source resources and repositories of code; (vi) Enabling of data-driven decisions through education apps (search for college, search for public school districts), energy and environment apps (alternate fuel locator) and food and nutrition apps (fooducate, goodguide); (vi) A platform of cities.data.gov to publish datasets from different cities across U.S.; (vii) disaster.data.gov web portal for collaborative efforts in disaster management, healthcare, policing, and climate change; (viii) Precision Medicine Initiative (PMI), a leading open data project that aims to create individualized treatments, expand genetically based clinical cancer trials and establish a national "Cancer Knowledge Network" to help with treatment decisions. United States Department of Agriculture (USDA) releases regular forecasts for prices of various agricultural commodities that are used worldwide. The projections identify major forces and uncertainties affecting future agricultural markets; prospects for long-term global economic growth, agricultural production, consumption, and trade; and U.S. exports of major farm commodities and future price movements. The projections can also be used to analyse impacts of alternative policy scenarios. This easy availability of data projections, in effect, drives agricultural markets across the U.S. %R[ )HGHUDOLVPLQOHDUQLQJDPRQJJRYHUQPHQWV 7HODQJDQD*RYHUQPHQW¶V 6DPDJUD9HGLNDLQLWLDWLYH 7KH7HODQJDQD*RYHUQPHQW¶V6DPDJUD9HGLNDLQLWLDWLYHJLYHVDÀDYRXURIWKHSRWHQWLDOEHQH¿WVRI LQWHJUDWLQJ GDWD VHWV 7KH LQLWLDWLYH OLQNV DURXQG WZHQW\¿YH H[LVWLQJ JRYHUQPHQW GDWDVHWV XVLQJ D FRPPRQLGHQWL¿HU±WKHQDPHDQGDGGUHVVRIDQLQGLYLGXDO6HYHQFDWHJRULHVRILQIRUPDWLRQDERXWHDFK individual were linked in this aggregation exercise – crimes, assets, utilities, subsidies, education, taxes and identity information. Each individual was then further linked to relatives such as spouse, siblings, parents and other known associates. The initiative also puts in place all the necessary safeguards to preclude any tampering of data or violation of privacy. The right to add or edit data in the database YDULHVE\PLQLVWU\RUGHSDUWPHQW$JLYHQGHSDUWPHQWFDQRQO\ZULWHGDWDIRUVHOHFW¿HOGV±WKHPRWRU vehicles department cannot, for instance, manipulate data relating to education, even though it can view the data. 4.28 Of late, there have been some “one-way”. Banks can now use the tokenized discussions around the “linking” of datasets – Aadhaar Number (i.e., a proxy 64-digit primarily through the seeding of an Aadhaar number that is based on, but not equal to number across databases such as PAN the individual’s 12-digit Aadhaar Number) database, bank accounts, mobile numbers, to combine duplicate records and weed out HWF$SRLQWRIFODUL¿FDWLRQLVLQRUGHUKHUH benaami accounts. But, this does not mean :KHQ RQH DGGV DQ $DGKDDU QXPEHU WR DQ that the UIDAI or government can now read existing database such as a database of bank the bank account information or other data accounts, it is only one more column that is related to the individual. added to the table. The linking is so to speak 88 Economic Survey 2018-19 Volume 1 )LJXUH ,OOXVWUDWLRQ 'DWDDERXWDK\SRWKHWLFDOFLWL]HQ;LVGLVSHUVHG DFURVVPXOWLSOHXQFRQQHFWHGGDWDVHWV Data about whom? Citizen X What type of data exist? Administrative Data Survey Data Transactions Data Institutional Data Birth and Land Employ- Agri Education Tax Nutrition Medical What sub-types of data exist? Death titles ment transac- records records Records records records status Status tions Ministry Ministry Ministry Ministry Ministry Ministry of Ministry Ministry Who holds this data? of Home of Rural of of of Agriculture of Health of HRD Affairs Dev. Finance Labour Statistics Note: Names of some ministries abbreviated. Data types and sub-types are illustrative examples only and not exhaustive. Figure 5: An enterprise architecture for Governance 4.29 Figure 4 illustrates the current system. the government is responsible for making Data about a hypothetical citizen X is spread available the data they hold as a data across ministries. In fact, the illustration is provider. These departments must take care DQ RYHUVLPSOL¿FDWLRQ )RU H[DPSOH GDWD to appropriately treat private data and public about X’s medical records would lie with the data with the standards they require. This Government-run district hospital where she data is then made available through a Data was most recently treated. In all likelihood, Access Fiduciary to the Data Requestors. these medical records are in paper-based Data Requestors may be public or private form and do not get aggregated for analysis institutions but can only access the data if at the state level, let alone the central level. they have appropriate user consent. The Nevertheless, the illustration depicts the Data Access Fiduciary themselves have union ministries ultimately responsible for no visibility on the data due to end-to-end each kind of data. encryption. Such a model puts user consent LQWKHFHQWUHRIWKHJRYHUQPHQW¶VLQLWLDWLYHWR 4.30 Figure 5 illustrates the Data Access make Data a Public Good. Fiduciary Architecture. Each department of Data “Of the People, By the People, For the People” 89 4.31 A citizen is, of course, not the only ministry should be able to view the complete possible unit of analysis. One may want database, a given ministry can manipulate to analyse schools, villages or hospitals. RQO\ WKRVH GDWD ¿HOGV IRU ZKLFK LW LV Different databases of villages, for example, responsible. Second, updating of data should PD\EHXWLOLVHGWRJHWKHULIDXQLTXHLGHQWL¿HU happen in real time and in such a way that for every village exists. Unfortunately, in one ministry’s engagement with the database many cases, ministries and departments have does not affect other ministries’ access. their own codes for a given geographical area; Third and most importantly, the database for example each village is characterised by a should be secure with absolutely no room for pin code assigned by the Department of Post, tampering. a village code assigned by the Department 4.34 The prospect of empowering the of Rural Development and a health block government with such comprehensive, assigned by the Ministry of Health and Family exhaustive information about every citizen :HOIDUH 7KH ODFN RI D FRPPRQ LGHQWL¿HU PD\ VRXQG DODUPLQJ DW ¿UVW +RZHYHU WKLV PDNHVLWGLI¿FXOWWRFRQVROLGDWHLQIRUPDWLRQ is far from the truth. First, large quantities of 4.32 An initiative to address this issue is the data already exist in government records, and Local Government Directory, an application the objective is only to use this data in a more developed by the Ministry of Panchayati HI¿FLHQWZD\7KHSURSRVDOHQYLVLRQHGKHUH Raj. A comprehensive directory of all local does not gather any new information; rather, administrative units, the platform maps each it seeks to make available all data within land region entity to a local Government the government for citizens, government, body (like villages with their respective private and public institutions to utilize the gram panchayats) and assigns location codes data subject to user consent and appropriate compliant with Census 2011. The Local privacy and fairness related constraints. Government Directory is a great example 4.35 Second, people can always opt out of of Data as a Public Good. The Ministry of divulging data to the government, where Panchayati Raj has made important headway possible. For example, one can choose not to LQ VROYLQJ D GLI¿FXOW SUREOHP FRPPRQ WR participate in a survey or use government-run every government and private institution payments services. There are exceptions, of trying to serve rural India – the lack of formal course. People cannot buy and drive vehicles addresses – by assigning a code to every place. Instead of simply sitting on that data, ZLWKRXWDOLFHQVHDQGUHJLVWUDWLRQFHUWL¿FDWH but not requiring these data would threaten the Ministry has also published it for all to the enforcement of property rights, road use. If all government databases requiring safety and national security, which cannot location codes are aligned with the codes in be compromised. But for the remaining this directory, then all databases will share categories of data – institutional, survey and D FRPPRQ ORFDWLRQ ¿HOG WKDW FDQ KHOS LQ transactions – people have the choice. merging data, and reduce accuracy errors in the distribution of welfare. 4.36 Third, even if there is no viable private market choice of certain public services, the 8WLOL]LQJ WHFKQRORJLFDO DGYDQFHV WR choice to share the individually linked data eliminate all privacy concerns from such services will always be with the 7KHLQWHJUDWHGV\VWHP¶VHI¿FDF\UHOLHV citizen under the Data Access Fiduciary on three critical features. First, while any Architecture. Further, immutable access logs 90 Economic Survey 2018-19 Volume 1 for all data would be available so that citizens *DWKHULQJGDWD 'LUHFWO\GLJLWDOUDWKHU know who has seen their data and why. WKDQSDSHUWRGLJLWDO 4.37 The principle is that most data are 4.39 Unless data is in a digital, machine generated by the people, of the people and readable format, its utility is limited. Paper should be used for the people. Enabling the records of data cannot be accessed by all sharing of information across datasets would stakeholders. Even if paper records of improve the delivery of social welfare, schemes are scanned and stored in a digital empower people to make better decisions, repository, they do not lend themselves to and democratize an important public good. easy analysis. For data to serve its purpose, it 75$16)250,1*,1',$¶6'$7$ needs to be transmuted into a digital, machine INFRASTRUCTURE readable form that can be downloaded and DQDO\VHG:KLOHPRVWVWDWHDQGQDWLRQDOOHYHO 4.38 Undoubtedly, the system outlined data is already in this form, digital records above requires a robust data infrastructure. are not yet ubiquitous at the more granular :KLOH FRPELQLQJ GDWDVHWV ZLOO LWVHOI UHDS administrative levels. For example, a citizen UHZDUGV WKH EHQH¿W LV OLPLWHG LI GDWD LV RI cannot view his village’s sanitation status on an uncertain quality, not amenable to easy a digital database. At best, he can look up his processing etc. Harnessing data consists of district. For many schemes, data is available four steps – gathering, storing, processing only at the state level. and disseminating data, each of which offers room for improvement in India (see 4.40 The recently launched Digitize India Figure 6). initiative is an ingenious solution to the )LJXUH 7UDQVIRUPLQJGDWDJDWKHULQJVWRUDJHSURFHVVLQJDQGGLVVHPLQDWLRQ •Digitize existing paper-based data Gathering data •Initiate digital data collection at source •Initiate real-time storage for select data Storing data •Reduce time lag between collection and data entry •Build capacities of govt. bodies to analyse data Processing data •Involve private sector in analysis and insight generation •Create scheme dashboards Disseminating data •Open district-level dashboard to the public •Open data from third party studies to the public Data “Of the People, By the People, For the People” 91 tedious task of converting paper-based data citizen dashboard called St. Pete Stat, where into digital form. The initiative crowd- citizens can view dynamically updated sources the data entry effort by presenting information about the performance of city volunteering citizens with snippets of scanned departments, status of development projects. documents, which they type into a data entry The dashboard includes various interactive portal. Correct entries earn cash rewards for tools such as an interactive map of all police the contributor (see Box 6 for details). calls in the city. :KLOHWKHVFKHPHJRHVDORQJZD\WR 4.43 Not all types of data are amenable to digitize existing paper records, a parallel real-time storage, of course. Further, the initiative is needed to convert the very incremental cost of a real-time database process of data collection into a digital PD\QRWDOZD\VMXVWLI\LWVPDUJLQDOEHQH¿W RQHDVRSSRVHGWRFROOHFWLQJRQSDSHU¿UVW However, there are a few sectors where, if not and converting to a digital format later. real-time, at least a high frequency of logging Undoubtedly, the exercise of supplying every data on the server can yield substantial hospital, gram panchayat, school or block EHQH¿WV RI¿FH ZLWK DQ HOHFWURQLF GDWDHQWU\ GHYLFH 4.44 Education is one such example. Even is quite ambitious, but achievable. Digital a seemingly short period of six months is a data collection at the source ensures that long time in the life of a child – it amounts data is logged exactly as observed, obviates to half an academic year. Say a school does the redundancy of data entry, and eliminates not have a functional toilet for girls, leading data entry errors. A truly digital ecosystem is girls to remain absent from school. The achievable only when all layers of information SUREOHP QHHGV WR EH UHFWL¿HG DV VRRQ DV that constitute the ecosystem are digitized. possible; otherwise these girls would lose out on valuable schooldays. The block or district 6WRULQJGDWD HGXFDWLRQRI¿FHUVKRXOGUHFHLYHDGDLO\RUDW 3XEOLF VHUYLFH GHOLYHU\ FDQ EHQH¿W least weekly, report of the status of toilets so from real-time storage of data. The city of WKDWLQFDVHDSUREOHPLVQRWUHFWL¿HGZLWKLQD St. Petersburg, Florida, recently created a week or two, they can take the required action. %R[ +RZ'LJLWL]H,QGLDZRUNV Government departments upload scanned copies of paper records on the Digitize India platform. These scanned documents are shredded into snippets with meaningful data. These snippets are randomly served to digital contributors. Digital contributors are citizens who volunteer their time on the portal. Upon receiving snippets, the contributor reads the information and types it into a data entry portal. All FRQYHUWHGGDWDDUHYHUL¿HGDJDLQVWWKHFRUUHVSRQGLQJVQLSSHW&RUUHFWHQWULHVHDUQWKHLUFRQWULEXWRUV reward points, which can either be redeemed for cash or donated to the Digital India initiative. Once all snippets corresponding to a particular document are converted into digital data, the platform reassembles the document in digital form and supplies it back to the government department. Any Indian citizen with an Aadhaar number can participate as a digital contributor. Citizens are incentivised WKURXJKUHZDUGSRLQWVDQGUHFRJQLWLRQDVµGLJLWDOFRQWULEXWRUV¶DQGPD\HYHQHDUQFHUWL¿FDWHVDVµ'DWD Entry Operators’. Ingeniously, the program also features a mobile app so that even citizens without a laptop or desktop computer can participate. 92 Economic Survey 2018-19 Volume 1 If the problem takes months to come to the 4.48 The government may also consider QRWLFHRIWKHEORFNRUGLVWULFWRI¿FHUWKHJLUO opening certain kinds of data to private children in the school will have lost months’ players with all the necessary security worth of learning! Digital dashboards updated safeguards. Data shared with the public on the in real time or at least weekly would avert Open Government Data portal is completely such harsh consequences. Similarly, consider anonymised and aggregated over a large agriculture, where farmers need data about number of individuals. Such data precludes weather conditions, expected rainfall, input careful statistical analyses, where individual- and output prices in real time to make daily level observations are required. However, decisions. Facilitating real-time access to DIWHU REIXVFDWLQJ DOO SHUVRQDOO\ LGHQWL¿DEOH such data is essential to improve agricultural information, if this data is shared with the productivity and farmer incomes. private sector, government can harness the skills and enthusiasm of data analytics :LWK WKH ZLGHVSUHDG DGRSWLRQ RI ,&7 professionals to gain the maximum possible approaches in public service delivery, real insights from the data. time data collection and storage is no longer an ambitious and distant dream but very 'LVVHPLQDWLQJGDWD much realisable, at least in select sectors and 4.49 The Open Government Data portal is contexts. an effective tool to disseminate data to the 3URFHVVLQJGDWD public. But, as most citizens do not have the time or skills to employ analytical tools 4.46 A deluge of data will be created when to dissect databases, easy visualisation tools data is collected digitally, stored in real-time, are critical. The portal has enabled several DQG XWLOLVHG ZLWK H[LVWLQJ GDWD :KLOH WKLV visualisation tools already, and these may be deluge has tremendous potential to transform augmented with the following. governance, unleashing this potential UHTXLUHVVNLOO$GLVWULFWJRYHUQPHQWRI¿FLDO 4.50 First, the Government may initiate for example, should have the analytical skills scheme dashboards for every major to make use of the data in that district. In the Government scheme with granular data, absence of such skill, investing in the data all the way to the village level. Dashboards infrastructure is of limited use. should be ready recipients of data from the concerned government body and ready 4.47 Governments at all administrative displayers of the same data in real-time to levels should invest in building their internal the public. The Swachh Bharat Mission is an capacities to exploit data in real time, perform exemplar dashboard that may be replicated analyses and translate data into meaningful for other schemes to allow citizens to track LQIRUPDWLRQ :KLOH HYHU\ JRYHUQPHQW WKH SK\VLFDO DQG ¿QDQFLDO SHUIRUPDQFH RI department may have a dedicated analytics or welfare schemes. Currently, these dashboards data insights division, Ministry of Statistics exist only for a small number of schemes. and Program Implementation and Ministry For example, ICDS Anganwadi Services of Electronics & Information Technology can scheme, the largest scheme for women and act as nodal departments to steer such efforts child development in India, does not have a at the national level. publicly available dashboard. Data “Of the People, By the People, For the People” 93 4.51 In existing dashboards, the metrics (broken links), others display outdated data. showcased may be augmented, especially :KLOH WKH LQYHVWPHQW WR LQLWLDWH VXFK D to show progress at the more granular levels GDVKERDUGLVFRPPHQGDEOHWKHEHQH¿WVZLOO of administration. For example, the Swachh be greater if the state governments continually Bharat dashboard can include information maintain these dashboards to disseminate on the number of swachhta doots (sanitation information. helpers) deployed at the district level or 4.53 Finally, many central ministries and the number of information, education and state departments commission data collection communication (IEC) campaigns in that initiatives to conduct needs assessments or district. In all likelihood, the data on these impact evaluations of schemes. Although metrics is available with the government but most of these studies are made public, the is not open to the public, perhaps because the underlying data are not. As these studies are data is not in digital form. carried out in partnership with government 4.52 Second, many state governments have bodies, they should be made available to the instituted district-level dashboards based on public so that independent analyses may be Management Information Systems (MIS) for FDUULHG RXW WR YDOLGDWH WKH ¿QGLQJV RI WKHVH various programmes. These states include studies. $QGKUD 3UDGHVK :HVW %HQJDO 0DGK\D APPLICATIONS Pradesh and Chhattisgarh. Except for the $QGKUD 3UDGHVK DQG :HVW %HQJDO RQHV 4.54 Once the infrastructure is in place, the these dashboards are not easily accessible applications are innumerable. A robust data to citizens. They require a password, which backbone can empower every stakeholder is only available to the local administration. in society, from the Central Government to Some dashboards are not operational anymore a local government body, from citizens to %R[ 15(*$VRIWDQGHJRYHUQDQFHLQ0*15(*$ NREGAsoft is a comprehensive e-governance system for the MGNREGA scheme. Accessible by a UDQJHRIVWDNHKROGHUVLWFDSWXUHVWKHFRPSOHWHÀRZRIDOO0*15(*$ZRUNDWHYHU\OHYHO±IURPWKH centre all the way to the panchayat. In the spirit of citizens’ right to information, the system makes available documents like muster rolls, registration application register, job card/employment register/ muster roll issue register and muster roll receipt register, which are otherwise inaccessible to the public. The system has no language barriers to usage; it is accessible in a number of local languages. In fact, even the illiterate can use the interface as it leverages sounds and icons in a touch-screen kiosk model. ,WLVGHVLJQHGWREHXVHGE\DUDQJHRIVWDNHKROGHUVIURPZRUNHUVZKRDUHEHQH¿FLDULHVRIWKHVFKHPH WRJUDPSDQFKD\DWVWRGLVWULFWSURJUDPPHFRRUGLQDWRUVWREDQNVDQGSRVWRI¿FHV(YHQFLWL]HQVZKR DUHQRWEHQH¿FLDULHVRIWKHVFKHPHPD\YLHZLQIRUPDWLRQRQWKHSRUWDO The software consists of several modules, which together comprehensively span all activities and all stakeholders. For example, while the worker management module forms the backbone of all worker- related services, a fund management module tracks the movement of funds from the central ministry all the way to the workers’ pockets, a grievance redressal module helps stakeholders including the illiterate WRORGJHFRPSODLQWVDQGWUDFNUHVSRQVHVDQGDEDQNSRVWRI¿FHPRGXOHDOORZV¿QDQFLDOLQVWLWXWLRQVWR get wage information and enter details of money credited in accounts. Other modules assist with cost estimation, social audit, knowledge network etc. 94 Economic Survey 2018-19 Volume 1 the private sector. A few (inexhaustive and test scores across districts (with all personal LOOXVWUDWLYH SRWHQWLDO EHQH¿WV DUH GHVFULEHG information completely obfuscated). below. Using test scores of students, demographic characteristics of each district and publicly Governments themselves as DYDLODEOH GDWD RQ WKH HI¿FDF\ RI SXEOLF EHQH¿FLDULHV HGXFDWLRQ VFKHPHV D SULYDWH ¿UP PD\ EH 4.55 Being able to retrieve authentic data able to uncover unmet needs in education and and documents instantly, governments cater to these needs by developing innovative can improve targeting in welfare schemes WXWRULQJSURGXFWVWDLORUHGWRWKHVSHFL¿FQHHGV and subsidies by reducing both inclusion RI VSHFL¿F GLVWULFWV 7KHVH SURGXFWV ZRXOG and exclusion errors. Datasets that utilise QRWRQO\FUHDWHSUR¿WVIRUWKHSULYDWHVHFWRU information across various datasets can but also monetize data and generate revenues also improve public service delivery. For for the government, in addition to improving H[DPSOH FURVVYHUL¿FDWLRQ RI WKH LQFRPH education levels and social welfare. tax return with the GST return can highlight 4.58 Alternatively, datasets may be sold possible tax evasion. to analytics agencies that process the data, 3ULYDWHVHFWRU¿UPVDVEHQH¿FLDULHV generate insights, and sell the insights further to the corporate sector, which may in turn use 4.56 The private sector may be granted these insights to predict demand, discover access to select databases for commercial untapped markets or innovate new products. use. Consistent with the notion of data as a Either way, there is tremendous scope for public good, there is no reason to preclude WKH SULYDWH VHFWRU WR EHQH¿W IURP WKH GDWD FRPPHUFLDO XVH RI WKLV GDWD IRU SUR¿W and they should be allowed to do so, at a Undoubtedly, the data revolution envisioned charge. Fortunately, stringent technological here is going to cost funds. Although the mechanisms exist to safeguard data privacy VRFLDO EHQH¿WV ZRXOG IDU H[FHHG WKH FRVW DQG FRQ¿GHQWLDOLW\ HYHQ ZKLOH DOORZLQJ WKH to the government, at least a part of the SULYDWHVHFWRUWREHQH¿WIURPWKHGDWD generated data should be monetised to ease WKHSUHVVXUHRQJRYHUQPHQW¿QDQFHV*LYHQ &LWL]HQVDVEHQH¿FLDULHV that the private sector has the potential to 4.59 Citizens are the largest group of reap massive dividends from this data, it is EHQH¿FLDULHVRIWKHSURSRVHGGDWDUHYROXWLRQ only fair to charge them for its use. Consider the case of Digital Locker. It is 4.57 Consider, for example, allowing the in many ways similar to the plan we have private sector access to data about students’ outlined above. But it is restricted to certain Box 8: The National Scholarship Portal The Government of India has already made headway in integrating data on scholarships. The National Scholarship Portal was initiated to harmonize all scholarship schemes implemented by various ministries at the central and state levels. The portal serves as an umbrella platform for all scholarship related services ranging from student application, application receipt, processing and sanction to disbursal of IXQGV,QDGGLWLRQWRFUHDWLQJDWUDQVSDUHQWGDWDEDVHRIDOOEHQH¿FLDULHVRIDOOJRYHUQPHQWVFKRODUVKLS schemes at various levels, the portal reduces hassles in discovering scholarships and facilitates direct EHQH¿WWUDQVIHU '%7 Data “Of the People, By the People, For the People” 95 documents that the state issues. Citizens no One may hold a bank account with State Bank longer need to run from pillar to post to get of India, but take a loan from HDFC. Their “original” documents from the state such mutual fund investments may be through as their driving licence, Aadhaar card, PAN Axis Bank, but their insurance is through card, CBSE results, etc. These documents are LIC. They also have a credit card from critical in the life of every resident of India. Standard Chartered and use Motilal Oswal to These documents are most needed by those invest in some stocks directly. In such a case, who depend on the state for welfare. They are the data needed by the individual to piece also often the hardest to secure for the same WRJHWKHUWKHLURZQ¿QDQFLDOOLIHLVGLVWULEXWHG vulnerable group. across many data providers. The NBFC-AA allows users to pull that data together, for any 4.60 DigiLocker makes all their documents purpose the citizen requires. This may be for DYDLODEOHLQDYHUL¿HGIRUPDWLQRQHSODFH SHUVRQDO ¿QDQFH PDQDJHPHQW RU PD\EH WR on the cloud. Citizens only need an internet apply digitally for a new housing loan. The connected device, smartphone or computer to NBFC-AA neither reads data nor creates an access the locker. It helps digitize downstream invasive 360-degree dataset. It simply enables processes such as college admissions. For citizens to demand their data from these anyone who has had to retrieve a lost or institutions in a machine-readable format, so missing document from the government that it can be used by them meaningfully. or have to get photocopies “attested”, the DigiLocker experience is immensely more WAY FORWARD time-saving and user-friendly. They do not have to live in the fear of their precious Through Aadhaar, India has been at the documents being lost to the elements or other forefront of the data and technology revolution misfortune. that is unfolding. As data for social welfare may not be generated by the private sector in 4.61 In a similar vein, the Reserve Bank optimal quantity, government needs to view of India has announced the Non-Banking data as a public good and make the necessary Financial Company-Account Aggregator LQYHVWPHQWV7KHEHQH¿WVRIFUHDWLQJGDWDDVD 1%)&$$ (YHQLQWKH¿QDQFHLQGXVWU\DQ public good can be generated within the legal LQGLYLGXDOOHDGVDFRPSOH[¿QDQFLDOOLIHZLWK framework of data privacy. Going forward, their data spread across multiple providers. the data and information highway must be %R[ ,GHDRID1DWLRQDO+HDOWK5HJLVWU\ For Swachh Bharat to transform into Swasth Bharat and eventually Sundar Bharat, citizens’ health is paramount. Prevention is far more important in this endeavour than cure. A national health register, that maintains health records of citizens with all the necessary privacy safeguards can go a long way in enabling health analytics for predictive and prescriptive purposes. Such a national health register ZRXOGEHLGHQWL¿HGXVLQJDFLWL]HQ¶V$DGKDU$VDGRFWRUFDQDFFHVVWKHPHGLFDOKLVWRU\RIDSDWLHQW from this national health register, this facility would be especially useful in emergency/trauma cases and can potentially save several lives. The various components of this register can include databases for (i) hospitals and public health centres, (ii) surveillance of syndromes, (iii) immunization information systems, (iv) electronic laboratory reporting, and (v) sub-registries for key diseases requiring intervention such as diabetes, hypertension, cancer, AIDS, etc. Anonymized data from the register can be sold to private parties for analytics, which would then enhance prevention by offering predictive and prescriptive knowledge. 96 Economic Survey 2018-19 Volume 1 viewed as equally important infrastructure its people. In the spirit of the Constitution as the physical highways. Such a stance can of India, data “of the people, by the people, KHOS,QGLDOHDSIURJWRXWLOLVHWKHEHQH¿WVRI for the people” must therefore become the technological advances for the welfare of mantra for the government. CHAPTER AT A GLANCE ¾ Given technological advances in gathering and storage of data, society’s optimal consumption of data is higher than ever. ¾ $VSULYDWHVHFWRUPD\QRWLQYHVWLQKDUQHVVLQJGDWDZKHUHLWLVSUR¿WDEOHJRYHUQPHQWPXVW intervene is creating data as a public good, especially of the poor and in social sectors of the country. ¾ Governments already hold a rich repository of administrative, survey, institutional and transactions data about citizens, but these data are scattered across numerous government bodies. Merging WKHVHGLVWLQFWGDWDVHWVZRXOGJHQHUDWHPXOWLSOHEHQH¿WVZLWKWKHDSSOLFDWLRQVEHLQJOLPLWOHVV ¾ *LYHQWKDWVRSKLVWLFDWHGWHFKQRORJLHVDOUHDG\H[LVWWRSURWHFWDQGVKDUHFRQ¿GHQWLDOLQIRUPDWLRQ data can be created as a public good within the legal framework of data privacy. In thinking about data as a public good, care must also be taken to not impose the elite’s preference of privacy on the poor, who care for a better quality of living the most. ¾ As data of societal interest is generated by the people, it should be “of the people, by the people, for the people.” REFERENCES 2011. Big Data: The next frontier for innovation, competition, and productivity. Brook, E., Rosman, D., Holman, C. 2008. Mckinsey Global Institute. “Public good through data linkage: measuring UHVHDUFKRXWSXWVIURPWKH:HVWHUQ$XVWUDOLDQ https://www.mckinsey.com/~/media/ data linkage system.” Australian and New McKinsey/Business%20Functions/ Zealand journal of public health 32(1): 19- McKinsey%20Digital/Our%20Insights/ 23. Big%20data%20The%20next%20 Dresner Advisory Services, LLC. 2017. Big frontier%20for%20innovation/MGI_big_ Data Analytics Market Study. https://www. data_exec_summary.ashx microstrategy.com/getmedia/cd052225- Lane, J., Stodden, V., Bender, S. and H. be60-49fd-ab1c-4984ebc3cde9/Dresner- Nissenbaum. 2014. Privacy, Big Data, and the Report-Big_Data_Analytic_Market_Study- Public Good: Frameworks for Engagement. :LVGRPRI&URZGV6HULHVSGI New York: Cambridge University Press. http:// Hilbert, Martin. 2016. “Big Data for assets.cambridge.org/97811070/67356/ Development: A Review of Promises and frontmatter/9781107067356_frontmatter.pdf Challenges.” Development Policy Review Ministry of Electronics & Information 34:135-174. Technology. 2019. “Open Government Data James M., Chui M., Brown B., Bughin J., Portal: An Overview.” Accessed June 20. Dobbs R., Roxburgh C., and Angela Hung https://www.meityJRYLQZULWHUHDGGDWD¿OHV Byers. OGD_Overview%20v_2.pdf. Data “Of the People, By the People, For the People” 97 Nilekani, Nandan. 2018. “Data to the People. Rodwin MA, and JD. Abramson. 2012. India's Inclusive Internet.” Foreign Affairs “Clinical trial data as a public good.” JAMA 97(5). 308: 871-2. 5LWFKLH ) DQG 5LFKDUG :HOSWRQ Taylor, L. 2016. “The ethics of big data as ³6KDULQJ ULVNV VKDULQJ EHQH¿WV 'DWD DV D DSXEOLFJRRG :KLFKSXEOLF":KRVHJRRG"´ public good.” Presentation at Joint UNECE/ Philosophical Transactions of the Royal Eurostat work session on statistical data Society 374: 1–13. FRQ¿GHQWLDOLW\ 7DUUDJRQD 6SDLQ 2FWREHU 26-28. http://eprints.uwe.ac.uk/22460/1/21_ 5LWFKLH:HOSWRQSGI Ending Matsyanyaya: How To Ramp 05 Up Capacity In The Lower Judiciary CHAPTER “The Rule of Law and maintenance of order is the science of governance” - Kautilya’s Arthashastra, 4th century B.C. “No branch of knowledge and policy is of any avail if the Rule of Law is neglected” - Kamandak’s Nitisara, 4th century A.D. Arguably the single biggest constraint to ease of doing business in India is now the ability to enforce contracts and resolve disputes. This is not surprising given the 3.5 crore cases pending in the judicial system. Much of the problem is concentrated in the district and subordinate courts. Contrary to conventional belief, however, the problem is not insurmountable. A case clearance rate of 100 per cent (i.e. zero accumulation) can be achieved with the addition of merely 2,279 judges in the lower courts and 93 in High Courts even without ef¿ciency gains. This is already within sanctioned strength and only needs ¿lling vacancies. Scenario analysis of ef¿ciency gains needed to clear the backlog in ¿ve years suggest that the required productivity gains are ambitions, but achievable. Given the potential economic and social multipliers of a well-functioning legal system, this may well be the best investment India can make. INTRODUCTION closely linked to the ability to enforce contracts and resolve disputes. 5.1 The relationship between economic governance and the Rule of Law (Dandaniti) 5.2 Last year’s Economic Survey (2017- has been emphasized by Indian thinkers 18) presented evidence of the backlog of since ancient times. It is seen as the key cases that weighs down the Indian judiciary, to prosperity, and a bulwark against economic tribunals and the tax department, Matsyanyaya (i.e. law of the ¿sh/jungle). thereby constraining economic growth. It also It should be no surprise, therefore, that the highlighted how the government’s efforts to Preamble to the Constitution of India de¿nes improve the present regime, by introducing that the ¿rst role of the State is ‘to secure for the Insolvency and Bankruptcy Code and the all its citizens: Justice, social, economic, and adoption of the Goods and Services Tax, have political’. In other words, it is well accepted had a profound impact on improving Ease of that economic success and prosperity are Doing Business (EODB) in India1. 1 India was one of the biggest ‘improvers’ in the World Bank’s Ease of Doing Business Report (EODB), 2019 with its rank jumping to 77 from 142 in the last four years. Ending Matsyanyaya: How To Ramp Up Capacity In The Lower Judiciary 99 5.3 This progress notwithstanding, India 5.5 Given that District and Subordinate continues to lag on the indicator for enforcing courts (D&S courts) account for 87.54 per contracts, climbing only one rank from 164 cent of pending cases, this chapter will focus to 163 in the latest report of EODB, 2018. In on this segment and evaluate its performance spite of a number of actions to expedite and on parameters such as disposal time, pendency improve the contract enforcement regime, time, case types and case clearance rate. The economic activity is being affected by the Chapter further analyses the requirement of long shadow of delays and pendency across additional judges and ef¿ciency gains across the legal landscape2. Contract enforcement the various levels of courts to achieve 100 per remains the single biggest constraint to cent clearance rate as well as to eliminate the improve our EODB ranking. This is ironical stock of pendency in the next ¿ve years. for a country that has long idealized contract 5.6 The following sections provide an enforcement. As Tulsi Ramayana puts it, overview of the performance of D&S “praan jayi par vachan na jayi” i.e., “one’s courts, using metrics that quantify different promise is worth more than one’s life”. aspects of the litigant’s experience. These 5.4 The Indian judicial system has over include average age of cases, (both pending 3.53 crore pending cases3 (see Figure 1). At and disposed), the number of days between ¿rst glance, this number looks very large and hearings, and the average amount of time insurmountable, but this Chapter will argue spent on the life cycle of cases. it is a potentially solvable problem. Indeed, given the potential bene¿ts, this may be the PENDENCY best investment that the Indian economy can 5.7 The pendency of a case on a given make. date is the time since the date of ¿ling. The distribution of ages of pending cases as on Figure 1: Distribution of Pending Cases May 31, 2019 is shown in Figure 2. It reveals among different levels of Courts in India that the distribution of pendency of both civil Figure 2: Distribution of Pending Cases (age-wise) in D&S courts 0-1 years 1-3 years 3-5 years 5-10 years > 10 years 100 90 80 70 60 50 40 Percentage of pending cases 30 20 All cases Civil cases Criminal cases Source: Supreme Court of India and NJDG, 2019. Source: NJDG, As on May 31, 2019. 2 See Economic Survey 2018 Chapter 9, Volume I. 3 Source: Data for High Courts and Subordinate Courts is from the National Judicial Data Grid (NJDG) as on May 31, 2019 and data for the Supreme Court of India is from its website, as on May 1, 2019. 100 Economic Survey 2018-19 Volume 1 Figure 3: State-wise Average Pendency in D&S courts 6 All cases Civil cases Criminal cases 5 4 3 2 1 Average age of pending cases (years) 0 Delhi Bihar Kerala Assam Punjab Odisha Gujarat All India All Rajasthan Karnataka Tamil Nadu Tamil Maharashtra Chhattisgarh West Bengal Uttar Pradesh Uttar Andhra Pradesh Madhya Pradesh Source: NJDG, As on May 31, 2019. and criminal cases is more or less the same. Figure 4: Distribution of Disposed Cases in More than 64 per cent of all cases are pending D&S courts - 2018 for more than one year. Figure 3 shows the 0-3 years 3-5 years 5-10 years >10 years inter-state variation in average pendency of 100 cases in D&S courts. It reveals that Odisha, 90 Bihar, West Bengal, Uttar Pradesh and Gujarat have higher average pendency for 80 both civil and criminal cases as compared 70 to the national averages whereas Punjab and 60 Delhi have the least average pendency of Percentage of disposed cases 50 cases. It may not be a coincidence that the All cases Civil cases Criminal cases worst performing states are usually (albeit Source: NJDG, 2019. not always) also the poorest. DISPOSAL reveals that 74.7 per cent of the civil cases and 86.5 per cent of the criminal cases are 5.8 Disposal time is measured as the time disposed within three years. Further, the span between the date of ¿ling and the date distribution of state-wise disposal rate is when the decision is passed. The age-wise presented in Figure 5. It shows that Bihar, distribution of the disposal time for D&S Odisha and West Bengal have higher average courts in 2018 is presented in Figure 4. It disposal time than the national average for Ending Matsyanyaya: How To Ramp Up Capacity In The Lower Judiciary 101 Figure 5: State-wise Average Disposal Time in D&S courts (2018) All cases Civil cases Criminal cases 5 4 3 2 (years) 1 0 Average age of disposed cases Bihar Delhi Kerala Assam Punjab Odisha Gujarat All India Rajasthan Karnataka Tamil Nadu Tamil Maharashtra Chhattisgarh West Bengal Uttar Pradesh Andhra Pradesh Madhya Pradesh Madhya Source: NJDG, 2019. both civil and criminal cases. Further, Punjab 5.9 International comparison of disposal and Delhi have the lowest average disposal rate is presented in Figure 6. The data reveals time. These trends are consistent with the that the average disposal time for civil and distribution of average pendency age across criminal cases in Indian D&S courts in 2018 states. Again, the states in eastern India was 4.4 fold and 6 fold higher respectively perform poorly although Gujarat too has when compared with the average of Council higher disposal time. of Europe members (2016). This indicates that there is huge scope for improvement in Figure 6: Average Disposal Time - India and the disposal time for Indian D&S courts. The Council of Europe following section provides a detailed analysis 3 India COE member states of the effectiveness and ef¿ciency of courts using the framework of Case Clearance 2.5 Rate. 2 CASE CLEARANCE RATE 1.5 (years) 5.10 The Case Clearance Rate (CCR) is the 1 ratio of the number of cases disposed of in a 0.5 given year to the number of cases instituted Average age of disposed cases 0 in that year, expressed as a percentage. It Civil cases Criminal cases may be noted that the cases disposed of need not have been ¿led in the same year, Source: NJDG, 2019 Council of Europe, European Commission for the Ef¿ciency of Justice (CEPEJ, as some proportion of them will typically be 2016). backlog from previous years – clearance rate 102 Economic Survey 2018-19 Volume 1 Figure 7: Institutions, Disposals, and Case Clearance Rate in D&S courts Institution of Cases Disposal of Cases Case Clearance Rate (RHS) 150 91 Case clearance rate 125 89 100 87 75 85 (p 50 er cent Number of cases (lakhs) 25 83 ) 0 81 2015 2016 2017 2018 Source: NJDG, 2019. is mainly used to understand the ef¿ciency Figure 8: International Comparison of Case of the system in proportion to the inÀow of Clearance Rate cases. India (2018) COE member states (2016) 5.11 Figure 7 shows the relationship USA District Courts (2018) UK (2017) between the institution, disposal of cases, 105 and CCR at all India level. While the number 95 of cases instituted each year in D&S courts 85 has gone up, so has the number of disposals. 75 However, the gap between institution and Per cent 65 disposals allows cases to accumulate and 55 results in an increase in pendency. This is 45 because the CCR remains structurally below Civil Cases Criminal Cases 100 per cent. An encouraging sign was that Source: NJDG, CEPEJ, US Courts, UK Parliament the CCR had increased from 86.1 per cent research brie¿ng, 2019. in 2015 to 90.5 per cent in 2017, but then declined to 88.7 per cent in 2018. per cent in 2016 for both civil and criminal cases. With a CCR below 100 per cent and a 5.12 The international comparison of CCR heavy backlog of pre-existing cases, Indian is presented in Figure 8. It shows that the courts suffer from increasing delays. USA’s CCR for civil and criminal cases in India district courts have better CCR of 98 per cent was 94.76 per cent and 87.41 per cent and 92 per cent for civil cases and criminal respectively in 2018 while the COE member cases respectively. While criminal courts in has already achieved the CCR above 100 Ending Matsyanyaya: How To Ramp Up Capacity In The Lower Judiciary 103 the UK’s England and Wales court system the concept of an input–output matrix of cases perform relatively well, with a clearance rate at different court levels. It is recognized that of roughly 100 per cent, their civil courts fare the disposal rate can be increased. However, poorly in comparison to India, the USA, and productivity is assumed to be constant for the the COE average, with a clearance rate of just purpose of this analysis. 62 per cent. 5.14 Using a simple input-output model, the CAN THE LEGAL LOGJAM BE survey estimates the number of additional CLEARED? lower court judges that would be needed to stop further accretion of pendency and 5.13 There are two key issues at hand that clear the backlog. The D&S courts received need to be dealt with in order to make the 1.5 crore additional cases in 2018 and had judiciary more ef¿cient. Firstly, to achieve a a backlog of 2.87 crore (as on January 1, 100 per cent clearance rate must be achieved 2018). The number of cases disposed of so that there is zero accumulation to the in 2018 was 1.33 crore. Thus, the closing existing pendency. Secondly, the backlog of balance in end-2018 was 3.04 crore. There cases already present in the system must be are currently 17,891 judges compared to the removed. The following analysis is done to sanctioned strength of 22,750. On average, a solve the above mentioned issues by using judge disposes 746 cases. Chart 1 shows the Chart 1: Additional Judges required in D&S courts (At Current Ef¿ciency) Pendency (As on Dec’17) Institution of cases (Jan-Dec’18) 2.87 crore 1.5 crore Total Workload (Dec’18) 4.37 crore Total Disposal cases (Jan-Dec’18) Pendency (As on Dec’18) 1.33 crore 3.04 crore Court characteristics (Dec’18) Judge Strength: • Sanctioned: 22,750 • Working: 17,891 (79%) Annual Disposal Rate (per judge): 746 Clearance Rate: 89% Additional judges required to Additional judges required to clear achieve 100% clearance in a year all backlog in 5 years *.1-.1,8<).,;!'= " #,424. 9 : ~ 8,152 : (117+0)/5325+04+6. &#% $ Source: Court News-Supreme Court, NJDG, 2019 and Survey calculations. 104 Economic Survey 2018-19 Volume 1 calculation for the requirement of additional This is already within the present sanctioned judges in D&S courts. In order to reach 100 strength for High Courts. To clear all backlogs per cent CCR in 2018, the D&S courts needed in the next ¿ve years, the High Courts need a 2,279 additional judges. This is within the further 361 additional judges. sanctioned strength! However, in order to 5.16 As of October 2018, Supreme Court clear all the backlog in the next ¿ve years, judges were working at 90 per cent of further 8,152 judges are needed. This is no their sanctioned strength. With a high case more than a rough calculation, but it shows clearance rate of 98 per cent, each judge that ef¿ciency gains are also required. disposes 1,415 cases per year on average. 5.15 Applying the same framework to The backlog of cases as on October 2018 higher courts, we found that the numbers are was 56,320. In order to reach 100 per cent even smaller (note that the data sets here are CCR, the Supreme Court would have needed from July-June). As of June 2017, High Court only one extra judge in 2018. To clear all judges were working at 62 per cent of their backlog in the next ¿ve years, an additional sanctioned strength. With a case clearance eight judges are required. In May 2019, rate of 88 per cent, each judge achieved an three additional judges were appointed to average disposal rate of 2,348 cases per year. the Supreme Court raising their number to The backlog of cases as on June, 2018 was the full sanctioned strength of 31. To clear 44.40 lakh. In order to reach 100 per cent backlog, the Supreme Court needs to increase CCR, they needed just 93 additional judges. its sanctioned strength by six. Chart 2: Additional Judges required in High Courts (At Current Ef¿ciency) Pendency (As on June’17) Institution of cases (July’17- June’18) 40.22 lakh 17.93 lakh Total Workload (June’18) 58.15 lakh Total Disposal (July’17- June’18) Pendency (As on June’18) 15.75 lakh 44.40 lakh Court characteristics (June’18) Judge Strength: • Sanctioned: 1,079 • Working: 671 (62%) Annual Disposal Rate (per judge): 2,348 Clearance Rate: 88% Additional judges required to achieve Additional judges required to clear 100% clearance in a year all backlog in 5 years : )-2,-2+9=(82-< %> ### 1*0. ; ; ~ 361 &228*1'/6436*15*7- !"#% $ Source: Supreme Court Annual Report, 2018 and Survey calculations. Ending Matsyanyaya: How To Ramp Up Capacity In The Lower Judiciary 105 Chart 3: Additional Judges required in the Supreme Court (At Current Ef¿ciency) Pendency (As on Dec’17) Institution of cases (Jan- Oct’18) 55,558 33,743 Total Workload (Oct’18) 89,331 Total Disposal (Jan- Oct’18) Pendency (As on Oct’18) 33,011 56,320 Court characteristics (Oct’18) Judges Strength: • Sanctioned: 31 • Working: 28 (90%) 10 Month Disposal Rate (per judge): 1,179 Clearance Rate: 98% Additional judges required to Additional judges required to achieve 100% clearance in a clear all backlog in 5 years "##$# " " %(#') & & ~ 8 " " !# ! $ $ " " !# (Criteria met in May 2019) Source: Supreme Court Annual Report, 2018 and Survey calculations. Note: For calculation of additional judges to clear all backlog in ¿ve years, disposal rate is adjusted for full year. 5.17 The main point of this analysis is that Case Types a major hurdle to economic growth and 5.19 The types of civil and criminal social well-being can be stabilized through cases, based on their subject matter and a relatively small investment in the legal the legislation under which they have been system. The numbers above are illustrative, ¿led, can result in signi¿cant variation along but it shows that the much debated judicial with the metrics used in this chapter. The logjam is solvable. complexity and gravity of a case type can determine the stages and process that it must HOW SHOULD THEADDITIONAL go through. A snapshot of the distribution of JUDGES BE ALLOCATED? common pending case type for both civil and 5.18 In order to optimally allocate these criminal cases at the national level in D&S additional D&S judges, the following section courts is presented in Table 1 below: has analysed common case types in both 5.20 Table 1 reveals that as on May 31, civil and criminal pendency. This will help 2019, the civil cases contribute a mere 28.38 understand which case types require per cent of total pendency while criminal additional judges. cases contribute about 71.62 per cent in D&S 106 Economic Survey 2018-19 Volume 1 Table 1: Common Cases Types Weight in Total Pendency (As on May 31, 2019) Common Case Types in Per cent A. Civil cases Civil Suit 14.00 Motor Vehicle 2.84 Civil Original Suits Marriage Petition 1.22 Land Reference 0.49 Other Civil 2.06 Total Civil Original Suits 20.60 Civil Application 1.96 Civil Execution 4.21 Civil Appeal 1.61 Total Civil Suits 28.38 B. Criminal cases Warrant/ Summons 56.63 Criminal Original Suits Sessions Cases 5.60 Other Criminal 2.03 Total Criminal Original Suits 64.26 Pre-Trail 1.57 Criminal Applications Bail Application 1.57 Others Application 2.66 Total Criminal Applications 5.80 Criminal Appeal 1.56 Total Criminal Suits 71.62 Source: NJDG, 2019. courts. Further, civil suit, civil execution, to understand which of these cases have a warrant/ summons and criminal application tendency to have backlogs. This is presented are common case types stuck in the backlog. in Table 2 below: These contribute 14 per cent, 4.21 per cent, 5.21 Table 2 reveals that average CCR for 55.63 per cent and 2.8 per cent share in total all civil and criminal cases in D&S courts for backlog, respectively. We calculate case type 2018 was 94.76 per cent and 87.41 per cent clearance rate in D&S courts for 2018, so as Ending Matsyanyaya: How To Ramp Up Capacity In The Lower Judiciary 107 Table 2: Case Type Institution, Disposal and CCR for D&S courts in 2018 Common Case Types Institution Disposal CCR (%) A. Civil cases (Overall) 32,96,242 31,23,642 94.76 Civil Original Suits 21,77,722 21,09,102 96.85 Civil Suit 11,66,259 10,81,236 92.71 Motor Vehicle 3,71,686 3,99,873 107.58 Marriage Petition 3,06,932 2,66,649 86.88 Land Reference 30,409 58,586 192.66 Civil Application 4,02,449 3,76,400 93.53 Civil Execution 5,11,118 4,46,677 87.39 Civil Appeal 1,74,283 1,71,790 98.57 B. Criminal cases (Overall) 1,16,23,439 1,01,60,317 87.41 Criminal Original Suit 86,10,411 73,44,581 85.30 Warrant/ Summons 76,28,227 64,52,314 84.58 Sessions Cases 5,29,694 4,79,828 90.59 Criminal Applications 27,20,351 25,44,683 93.54 Pre Trail 3,76,786 3,45,299 96.71 Bail Application 11,50,573 11,12,717 93.68 Criminal Appeal 2,63,407 2,46,756 93.68 Source: NJDG, 2019. respectively. This means that not only the we will take up in a future Economic Survey). backlog of criminal cases is about 2.5 fold Lastly, it may be noted that ‘Motor Vehicle’ higher than civil cases, criminal case type also and ‘Land Reference’ case types have done has lower CCR (even lower than the national quite well, maintaining a CCR of 107.58 and CCR of 88.7 per cent). This means that the 192.66 per cent respectively in 2018. These situation for criminal cases is distinctly areas need to maintain the current pace. worsening. The problem is especially acute for criminal original suits such as summons, 5.22 Some economists may take the view warrants etc. These contribute 64 per cent of that the relatively poor performance of the total pendency as of May 31, 2019 with the criminal justice system is of no direct a clearance rate of 85.3 per cent. This implies consequence to the economy. However, that the additional judges need to specialize a behavioural approach would make no in these case types so as to speed up the distinction since human beings are seen disposal of such cases. Note that this is a case to respond to the overall context. A culture not merely for additional judges and legal of Rule of Law must pervade as all of the reforms, but also for police reforms (a matter governance and cannot be improved in silos. 108 Economic Survey 2018-19 Volume 1 Figure 9: Average Number of Days Spent at a given Stage - Civil Cases Stages in chronological order Stages which may occur at any point in a case 400 300 200 100 Average number of days 0 Others Orders Hearing For Trial Evidence Arguments Amendments Consideration LCR/ R and R and LCR/ P Resolution Framing Issues of Notice/ Summons Notice/ Objection/ Reply Objection/ Written Statement/ Written Alternative Dispute Admission and and Denial Admission Final Order/ Judgement Order/ Final Source: eCourts and Daksh, 2019. Life-cycle Analysis of its life in that stage. 5.23 The progress of a case through various 5.25 The data from eCourts shows that stages reveals to a large extent where judicial most of the time is spent in the ދLCR/R delays occur and can aid policy formulation and P’ (Lower Courts Records – Records to reduce delays and backlog. Analysis of and Proceedings) stage. Here, cases cannot life-cycle can be used to precisely identify proceed as the court must ¿rst receive the causes of delay, whether they are procedural case’s records from the lower court. Civil inef¿ciencies or shortages of human and cases spend an average of 398 days in this physical resources. The average per cent of stage and 369 days in the ދHearing’ stage. case life-cycle spent in a civil case is presented This inef¿ciency consumes a signi¿cant below. For the purpose of this section, we proportion of a case’s life, and is a major have used data from eCourts services portal factor contributing to delays and backlog. The covering District and Sessions Courts across ދNotice/Summons’ and ދEvidence’ stages are 15 States, extracted between September 18, also time consuming at 322 and 325 days on 2018 and January 29, 2019. average, respectively. 5.24 Figure 9 shows the stages in 5.26 Figure 10 reveals that, as with civil chronological order, from left to right. cases, awaiting lower court records causes However, not all occur at speci¿c points delays for criminal cases, being the stage in of a stage, as some can occur at any point, which they spend the largest amount of time such as orders. In addition, not all cases go of 243 days, on average. The ދEvidence’ stage through all stages, but those that go through a and ދFraming of Charges’ stages consume particular stage may spend a signi¿cant part 235 and 231, respectively, while all other Ending Matsyanyaya: How To Ramp Up Capacity In The Lower Judiciary 109 Figure 10: Average Number of Days Spent at a given Stage - Criminal Cases Stages in chronological order Stages which may occur at any point in a case 250 200 150 100 50 Average number of days 0 Others Orders Hearing For Bail Evidence Arguments Amendments LCR/R and P and LCR/R Consideration Objection/ Reply Objection/ Framing of Charges of Framing Admission and and Denial Admission Final Order/ Judgement Order/ Final Appearance of Accused Appearance Notice/ Warrants/ Summons Warrants/ Notice/ Source: eCourts and Daksh, 2019. stages of criminal cases take much less time. State-wise CCR The process for both civil and criminal cases 5.28 Figure 12 shows that Gujarat and can be signi¿cantly sped up by targeting the Chhattisgarh have clearance rates of above delay in these speci¿c stages. 100 per cent in 2018. These states have 5.27 Further, Figure 11 shows that state-wise achieved a level of ef¿ciency where they average number of the days between hearings are not only able to cope with fresh ¿lings for civil and criminal cases. Its shows that but can also address backlog from previous West Bengal, particularly for civil matters, years. Madhya Pradesh, Assam and Tamil spends much more time between hearings Nadu have impressively high clearance than any other state – approximately 301.4 rates of close to 100 per cent. Again, eastern days, as compared to the average (across Indian states perform poorly. Bihar, Odisha, 15 states) of 78.1 days for civil cases. The and West Bengal have low clearance rates average for all cases is also the highest in of 55.58 per cent, 62.18 per cent, and 78.63 West Bengal - 167.7 days between hearings, per cent respectively. Hence, we suggest that compared to the 15-state average of 55.1 these states should be given priority in the days. appointment of additional judges. 110 Economic Survey 2018-19 Volume 1 Figure 11: State-wise Average Number of Days between Hearings - Civil and Criminal Cases 320 All cases Civil cases Criminal cases 240 160 80 Average number of days 0 Bihar Delhi Punjab Odisha Gujarat Haryana Karnataka Telangana Puducherry Tamil Nadu Tamil Maharashtra Chhattisgarh West Bengal All 15 States Uttar Pradesh Uttar Andhra Pradesh Andhra Source: eCourts and Daksh, 2019. 5.29 There is a great amount of variation in huge gaps between the demand for courts and the extent to which the subordinate judiciary the current capacity of the subordinate courts in each state is capable of dealing with the in many states – possibly a key factor in the inÀow of new cases. There are, therefore development inequalities between states. Figure 12: State-wise Institution - Disposal Gap and CCR in D&S courts - 2018 Institution-Disposal Gap (Percentage of filings) Case Clearance Rate (RHS) 110 40 Case Clearance Rate (per cent) 90 30 70 20 50 10 0 30 Filings accumulated ( per cent) -10 10 Bihar Delhi Kerala Assam Punjab Odisha Gujarat All India Rajasthan Karnataka Tamil Nadu Tamil Maharashtra Chhattisgarh West Bengal Uttar Pradesh Andhra Pradesh Madhya Pradesh Madhya Source: NJDG, 2019. Ending Matsyanyaya: How To Ramp Up Capacity In The Lower Judiciary 111 5.30 Figure 13 reveals that there is some 5.31 It may be further noted that although correlation between vacancy and pendency. Gujarat and Madhya Pradesh have high This is especially true for Uttar Pradesh and pendency, they have also achieved CCR Bihar. In these states, the focus should be on of 108.59 per cent and 99.94 per cent ¿lling vacancies. However, note that West respectively. NJDG data suggests that this Bengal and Maharashtra have few vacancies is due to relatively recent improvements. but high pendency. This means that the Perhaps the ef¿ciency gains of these states national allocation of judges also has to be should be studied and replicated. revisited. Figure 13: State-wise Pendency of Cases, Vacancy of Judges CCR in D&S courts 1,250 Vacancy Pendency (RHS) CCR (RHS) 120 Pendency (lakhs) 1,000 100 CCR (per cent) 80 750 60 500 40 250 Vacancy of Judges 20 0 0 Delhi Bihar Kerala Assam Punjab Odisha Gujarat Rajasthan Karnataka Tamil Nadu Tamil Maharashtra Chhattisgarh West Bengal Uttar Pradesh Uttar Andhra Pradesh Madhya Pradesh Source: NJDG and Lok Sabha Unstarred Question No. 675, 2019. Note: Pendancy as on June 2, 2019. MAKING INDIAN COURTS cent. With full sanctioned strength, High MORE PRODUCTIVE Courts would need only 4.3 per cent increase in ef¿ciency to clear the backlog although, 5.32 The analysis thus far has provided a given high vacancy rates, the required rate at gauge of how many judges would be needed current working strength is 68 per cent. The in order to increase the clearance rate at the equivalent numbers for the Supreme Court existing ef¿ciency rate and the nature of are 18 per cent and 31 per cent respectively. the delays. However, there is a large scope for improving the ef¿ciency of the process. 5.33 Over the years, many suggestions have As shown in Table 3, the backlog in lower been put forward by researchers and of¿cial courts can be cleared in ¿ve years at full committees for enhancing productivity in sanctioned strength with an ef¿ciency gain the judiciary. Some of the suggestions are of 24.5 per cent. At current working strength, discussed below: it would take an ef¿ciency gain of 58 per 112 Economic Survey 2018-19 Volume 1 Table 3: Scenario Analysis of Required Ef¿ciency Gains Particulars D&S courts High Supreme Courts Court Institution of cases in 2018 1,50,40,971 17,93,546 33,743 Disposal of cases in 2018 1,33,41,478 15,75,435 33,011 Backlog of cases 3,03,95,534 42,39,966 56,320 Sanctioned Strength of Judges 22,750 1,079 31 Working Strength of Judges 17,891 671 28 Current Disposal Rate per Judge 746 2,348 1,415* Case Clearance Rate 89% 88% 98% Scenario I: Constant Productivity Total judges required to reach 100% CCR 20,170 764 29 Additional Judges required to reach 100% CCR 2,279 93 1 (above existing working strength) Additional Judges required to clear backlog in ¿ve 10,431 454 9 years Additional Judges required to clear backlog in ¿ve 5,572 46 6 years (above existing sanctioned strength) Scenario II: Required Productivity Gains Required Productivity Gains to clear backlog in ¿ve 24.5% 4.3% 18% years at full sanctioned strength Required Productivity Gains to clear backlog in ¿ve 58% 68% 31%# years at current working strength Average number of working days 244 232 190 Source: Supreme Court Annual Report 2018, Various Court Calenders 2019, NJDG 2019 and Survey calculations. Note: Data for backlog of cases, sanctioned and working strength of judges for D&S courts, HCs and SC is as on December 2018, June 2018 and October 2018 respectively. *Adjusted for full year using January-October 2018 data. # As of May 2019, SC is working at its full sanctioned strength. a) Increase number of working days: It close for 49 days for summer vacations, has often been pointed out that Indian 14 days for winter break, and a further courts close down for signi¿cant periods 18 days for Holi, Diwali and Dussehra. due to vacations. The length of these After accounting for weekends and vacations varies a great deal from court- public holidays, it leaves 190 working to-court, but appears to have a palpable days for the Supreme Court. In contrast, impact on the number of working days. the average is 232 working days for High For instance, the Supreme Court’s of¿cial Courts and 244 days for Subordinate calendar for 2019 suggests that it would courts. There is a great deal of variation Ending Matsyanyaya: How To Ramp Up Capacity In The Lower Judiciary 113 between states, and many courts make up is not conducive to systemic reforms and for vacations by working on Saturdays. gradual accumulation of institutional For comparison, central government knowledge on administrative matters. of¿ces will be open for 244 working days In this context, it has been proposed to in 2019 (note that the above calculations create a specialized service called Indian exclude personal leaves). Courts and Tribunal Services (ICTS) that focuses on the administrative aspects of The main ¿nding is that increasing the the legal system. The major roles to be number of working days may improve played by ICTS would be (i) provide productivity of the Supreme Court and administrative support functions needed in some High Courts, but is unlikely by the judiciary (ii) identify process to signi¿cantly impact lower courts. inef¿ciencies and advise the judiciary on Subordinate courts, which account for the legal reforms (iii) implement the process bulk of pendency, seem to work almost re-engineering. as many days as government of¿ces. The ICTS is not a unique model. Similar, b) Establishment of Indian Courts and court management services exist in other Tribunal Services: Most judicial reforms countries: Her Majesty’s Court and tend to focus only on the quality and Tribunals Services (UK), Administrative quantity of judges, but a major problem Of¿ce of US Courts (US), Court lies with the quality of the administration Administration Service (Canada). of the courts system, particularly backend functions and processes. This is critical c) Deployment of Technology: Technology to reducing the process delays identi¿ed can signi¿cantly improve the ef¿ciency earlier in this Chapter. As a recent report of courts. One major effort in this by the National Institute of Public direction is the eCourts Mission Mode Finance and Policy put it, “For effective Project that is being rolled out in phases functioning, courts require competent by the Ministry of Law and Justice. This administration to ensure that processes has allowed the creation of the National are followed, documents are submitted Judicial Data Grid (NJDG). The system is and stored, facilities are maintained and already able to capture most cases, their human resources are managed. Court status and progress. Most of the analysis administration must support the judges in this chapter has been made possible by in performing their core judicial function real time data made publicly available ef¿ciently.”4 on the NJDG and eCourts portals. The digitalization of cases is now allowing In the current system, the main stake-holders to keep track of individual responsibility for administration in cases and their evolving status. It is not Indian courts is assigned to the chief possible yet to statistically measure the judicial of¿cer. In addition to signi¿cant ef¿ciency gains from this effort, but it is demands on his/her time, this approach certainly a big step forward. 4 Pratik Dutta et al., “How to Modernize the Working of Courts and Tribunals in India”, NIPFP Working Paper, 258, March 2019. 114 Economic Survey 2018-19 Volume 1 5.34 There are signi¿cant productivity gains that the required ef¿ciency gains for clearing to be derived from better administration, the backlog are ambitious but achievable if increase in working days, and technology combined with speeding up appointments. deployment (including likely future Given the social and economic importance of applications of Arti¿cial Intelligence). It is this issue, it should be given top priority by dif¿cult to predict the exact improvement, policy-makers. but the purpose of this analysis is to show CHAPTER AT A GLANCE ¾ Delays in contract enforcement and disposal resolution are arguably now the single biggest hurdle to the ease of doing business in India and higher GDP growth. ¾ Around 87.5 per cent of pending cases are in the District and Subordinate courts. Therefore, this segment must be the focus of reform. ¾ The study found that 100 per cent clearance rate can be achieved by merely ¿lling out the vacancies in the lower courts and in the High Courts (even without the productivity gains) ¾ Simulations of ef¿ciency gains and additional judges needed to clear the backlog in ¿ve years suggest that the numbers are large but achievable. ¾ The states of Uttar Pradesh, Bihar, Odisha and West Bengal need special attention. REFERENCES European Union. CEPEJ. European Judicial Systems Ef¿ciency and Quality of Justice. Court News. Publication. Supreme Court of Series 26. Brussels: Council of Europe, 2018. India. 2018. Accessed June 29, 2019. https:// www.sci.gov.in/pdf/CourtNews/COURT_ India. Ministry of Law. Department of Justice. Lok Sabha Unstarred Question No. NEWS_OCTOBER-DECEMBER_2017. 675. New Delhi, 2019. 1-40. pdf. ____. Department of Justice. Ministry of Dutta, Pratik, et.al., "How to Modernise Law. National Judicial Data Grid. Accessed the Working of Courts and Tribunals in June 29, 2019. https://njdg.ecourts.gov.in/ India." NIPFP Working Paper Series No. njdgnew/index.php. 258, March 25, 2019. Accessed June 29, Supreme Court. Indian Judiciary: Annual 2019. https://www.nipfp.org.in/media/ Report 2017–2018. New Delhi, DELHI, medialibrary/2019/03/WP_2019_258.pdf. 2018. How does Policy Uncertainty affect 06 Investment? CHAPTER (FRQRPLF3ROLF\8QFHUWDLQW\LQ,QGLDKDVUHGXFHGVLJQL¿FDQWO\RYHUWKHODVWGHFDGH&RLQFLGLQJ ZLWK WKH \HDUV RI SROLF\ SDUDO\VLV HFRQRPLF SROLF\ XQFHUWDLQW\ ZDV WKH KLJKHVW LQ 6LQFH WKHQ HFRQRPLF SROLF\ XQFHUWDLQW\ KDV GHFOLQHG VHFXODUO\ 7KH FRQWLQXHG GHFUHDVH LQ economic policy uncertainty in India post 2015 is exceptional because it contrasts sharply with the increase in economic policy uncertainty in major countries during this period, including the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¿YH TXDUWHUV 8QOLNH JHQHULF HFRQRPLF XQFHUWDLQW\ ZKLFK FDQQRW EH FRQWUROOHG SROLF\PDNHUV FDQ UHGXFH HFRQRPLFSROLF\XQFHUWDLQW\WRIRVWHUDVDOXWDU\LQYHVWPHQWFOLPDWHLQWKHFRXQWU\7KHIROORZLQJ SROLF\ FKDQJHV DUH UHFRPPHQGHG )LUVW SROLF\PDNHUV¶PXVW PDNH WKHLU DFWLRQV SUHGLFWDEOH SURYLGH IRUZDUG JXLGDQFH RQ WKH VWDQFH RI SROLF\ DQG UHGXFH DPELJXLW\DUELWUDULQHVV LQ SROLF\LPSOHPHQWDWLRQ6HFRQG³ZKDWJHWVPHDVXUHGJHWVDFWHGXSRQ´6RHFRQRPLFSROLF\ XQFHUWDLQW\ LQGH[ PXVW EH WUDFNHG DW WKH KLJKHVW OHYHO RQ D TXDUWHUO\ EDVLV )LQDOO\ TXDOLW\ DVVXUDQFHRISURFHVVHVLQSROLF\PDNLQJPXVWEHLPSOHPHQWHGLQ*RYHUQPHQWYLDLQWHUQDWLRQDO TXDOLW\FHUWL¿FDWLRQV INTRODUCTION policy action, provides forward guidance on policy action, maintains broad consistency 6.1 What is the effect of uncertainty/ in actual policy with the forward guidance, ambiguity in policy making on the investment reduces ambiguity and arbitrariness in policy climate in the economy? Consider, for implementation creates economic policy instance, a poorly drafted law that is riddled certainty. Investors may enjoy the certainty ZLWKDPELJXLWLHVDPHQGPHQWVFODUL¿FDWLRQV SURYLGHGE\VXFKDQHQYLURQPHQWDQGÀRFN and exemptions that inevitably lead to to invest in this environment. FRQÀLFWLQJLQWHUSUHWDWLRQVDQGVSDZQHQGOHVV litigation. Needless to say, such uncertainty 6.2 To examine this critical question and can spook investors and spoil the investment frame appropriate policy responses, it is climate in the economy. Such uncertainty in critical to understand the differences between economic policy can be avoided. In contrast, risk and uncertainty. Both fundamentally a nation state that ensures predictability of affect economic activity. However, while risk 116 Economic Survey 2018-19 Volume 1 FDQ EH TXDQWL¿HG XQFHUWDLQW\ LV LQKHUHQWO\ ދ¿QDQFH PLQLVWHU¶ ދODZPDNHUV ދSODQQLQJ hard to measure1. As policy making relies FRPPLVVLRQ¶ ދHFRQRPLF DGYLVRU¶ ދ3ULPH on judgment – within the framework set by 0LQLVWHU¶V 2I¿FH¶ ދ30 2I¿FH¶ ދ3ULPH constitutional rules and other legal constraints 0LQLVWHU (FRQRPLF $GYLVRU\ &RXQFLO¶ – it often involves discretion. Such discretion 2QO\WKRVHDUWLFOHVWKDWKDYHZRUGVIURPall can generate uncertainty, which can impact three categories are counted for measuring economic activity. Among different sources economic policy uncertainty. Articles are of economic uncertainty, economic policy taken from various newspapers, including, uncertaintyPDWWHUVVLJQL¿FDQWO\EHFDXVHWKLV Economic Times, Times of India, Hindustan uncertainty refers to one that policymakers Times, The Hindu, Financial Express, Indian FDQFRQWURODQGWKHUHE\LQÀXHQFHHFRQRPLF Express and the Statesman using access activity. For instance, while the monsoon world news. impacts economic activity, policymakers have absolutely no control over it. However, 6.4 As shown later in this chapter, EPU economic policy uncertainty captures index picks up the period of economic policy uncertainty that policymakers can control. uncertainty, such as the taper tantrum of 2013, and correlates very well with other 6.3 As uncertainty itself inherently cannot YXOQHUDELOLW\LQGLFHVOLNHLQÀDWLRQYRODWLOLW\ EHTXDQWL¿HGHFRQRPLFSROLF\XQFHUWDLQW\LV stock market volatility, business sentiment GLI¿FXOW WR TXDQWLI\ +RZHYHU DGYDQFHV LQ index, and other macroeconomic vulnerability data analytics, in general, and text analytics, indices. in particular, have made it possible to quantify uncertainty, in general, and economic 6.5 We then examine the impact of policy uncertainty, in particular. A globally economic policy uncertainty on investment as recognized attempt at quantifying economic it forms the core of the process of economic policy uncertainty is the one by Baker growth. Two key features of the decision to et al. (2016), who develop an Economic invest highlight the key role of uncertainty. Policy Uncertainty (EPU) index for various First, investment represents a forward- countries including India. To measure looking activity. Second, it is irreversible economic policy uncertainty, the index is 3LQG\FN DQG 6DOLPDQR &DEDOOHUR created by quantifying newspaper coverage DQG3LQG\FN &KHQDQG)XQNH of policy-related economic uncertainty. The Bloom, Floetotto and Jaimovich, 2009). LQGH[UHÀHFWVIUHTXHQF\RIDUWLFOHVLQOHDGLQJ As investment is forward-looking, future newspapers that contain the following triple: expectations play a critical role in the decision ދHFRQRPLF¶ RU ދHFRQRP\¶ ދXQFHUWDLQ¶ RU WRLQYHVW6SHFL¿FDOO\DQLQYHVWRULQYHVWVLQ ދXQFHUWDLQW\¶ DQGRQHRUPRUHRISROLF\UHODWHG a project if the upfront costs are less than the ZRUGV ދ¿VFDO SROLF\¶ ދPRQHWDU\ SROLF\¶ present value of the expected rewards from ދ302¶ދSDUOLDPHQW¶2WKHUWHUPVIRUދSROLF\¶ WKH LQYHVWPHQW $V XQFHUWDLQW\ LQÀXHQFHV LQFOXGH ދUHJXODWLRQ¶ ދGH¿FLW¶ ދOHJLVODWLRQ¶ these expectations, irrespective of its source, ދUHIRUP¶ ދFHQWUDO EDQN¶ ދ5%,¶ ދ5HVHUYH it affects the decision to invest. Conceptually, %DQN¶ ދ¿QDQFH PLQLVWU\¶ ދSROLF\PDNHUV the Capital Asset Pricing model postulates 7KH:HEVWHU¶VGLFWLRQDU\GH¿QHVULVNDVWKH³SRVVLELOLW\RIORVVRULQMXU\ SHULO´DQGXQFHUWDLQW\DV³LQGH¿QLWHLQGHWHUPLQDWH´ DQG³QRWNQRZQEH\RQGDGRXEW´.QLJKW ZKRGLGVHPLQDOZRUNLQGLVWLQJXLVKLQJULVNIURPXQFHUWDLQW\GLVWLQJXLVKHV ULVNDQGXQFHUWDLQW\DVIROORZV ³ULVNLVSUHVHQWZKHQIXWXUHHYHQWVRFFXUZLWKPHDVXUDEOHSUREDELOLW\ZKLOHXQFHUWDLQW\LV SUHVHQWZKHQWKHOLNHOLKRRGRIIXWXUHHYHQWVLVLQGH¿QLWHRULQFDOFXODEOH´ How does Policy Uncertainty affect Investment? 117 that the required return on investment ECONOMIC POLICY correlates positively with the systematic UNCERTAINTY IN INDIA risk underlying the investment. An increase 6.6 Economic Policy Uncertainty when in uncertainty in the economy increases this measured using EPU index was the highest in systematic risk and thereby increases the rate 2011-12 coinciding with the years of policy of return required to justify the investment. paralysis. Economic policy uncertainty has As a result, projects that generate a return UHGXFHGVLJQL¿FDQWO\RYHUWKHODVWGHFDGHLQ lower than this required return become India. Figure 1 shows that economic policy unviable when uncertainty increases in uncertainty has secularly declined from July WKH HFRQRP\ $OVR DV ¿[HG LQYHVWPHQW LV 2012 onwards, though with intermittent irreversible, uncertainty exacerbates risk- episodes of elevated uncertainty in aversion, increases the premium demanded between. As is expected, episodes of greater uncertainty, such as the taper tantrum in for assuming risk, and eventually dampens 2013, exhibit elevated levels of the economic investment. Consistent with this thesis, the policy uncertainty index. Following the analysis indicated that an increase in economic DQQRXQFHPHQW E\ WKH )HGHUDO 5HVHUYH policy uncertainty dampens investment of tapering of their policy of monetary JURZWKLQ,QGLDIRUDERXW¿YHTXDUWHUV2QH easing, investors in emerging markets faced standard deviation increase in uncertainty uncertainty about the policies that would leads to about one percentage point decline be adopted in these countries to control the in investment growth rate. Thus, economic impact of this Fed policy change. Thus, the policy uncertainty materially impacts the EPU index captures this economic policy investment climate in the country. uncertainty as expected. Figure 1: Economic Policy Uncertainty in India 300 Growth slowdown 250 200 Taper tantrum 150 EPU index 100 50 0 Jul-13 Jul-18 Jan-16 Jun-11 Jun-16 Oct-14 Sep-12 Feb-13 Sep-17 Feb-18 Apr-12 Apr-17 Dec-13 Dec-18 Mar-15 Nov-11 Aug-15 Nov-16 May-14 May-19 Source: http://www.policyuncertainty.com/ 118 Economic Survey 2018-19 Volume 1 6.7 The index of economic policy Economic Survey 2014-15. This measure is uncertainty for India shows peaks in few DVXPRIWZLQGH¿FLWVLH¿VFDOGH¿FLWDQG PRQWKVRIDQGUHÀHFWLQJWKHSROLF\ FXUUHQWDFFRXQWGH¿FLWDQGLQÀDWLRQ)LJXUH paralysis during that period, which witnessed 2 shows a strong correlation of 0.8 of this WKH SUREOHPV RI WKH KLJK WZLQ GH¿FLWV vulnerability measure with EPU index. Both DQG KLJK LQÀDWLRQ WKHUHE\ H[DFHUEDWLQJ the indices show almost same movements macroeconomic vulnerability. The index is over time. This also points towards aptness also high in the second half of 2013 when the of economic policy uncertainty index to be HFRQRP\IDFHGWKHHSLVRGHRI³WDSHUWDQWUXP´ used as a yardstick for measuring impact of OHDGLQJWRYRODWLOHFDSLWDOÀRZVGHSUHFLDWLRQ of rupee vis-à-vis US dollar (Figure 2). The uncertainty with investment. peak during GST is not as sharp, maybe 6.9 Apart from this, EPU index is very due to the fact that the discussions around strongly correlated to volatility in exchange GST policy were happening much before UDWH VWRFN PDUNHW LQÀDWLRQ DQG YDULRXV it was actually implemented in July 2017. other macroeconomic variables. There is a This shows that the index is picking up time correlation of around 0.7 between volatility periods characterized by increasing economic in exchange rate and EPU index. The EPU policy uncertainty. index closely tracks both the deterioration of 6.8 The EPU index correlates very strongly the future expectation index and India VIX to macroeconomic stability. To examine index which monitors the volatility in stock this correlation, we use the vulnerability PDUNHW ,W LV VWURQJO\ FRUUHODWHG WR LQÀDWLRQ measure created and employed in the rate and repo rate as well (Figures 3 to 8). Figure 2: Correlation of EPU index with macroeconomic vulnerability EPU index (left scale) Vulnerability measure (right scale) 200 30 180 25 160 140 Correlation 20 120 Coefficient: 0.79 100 15 80 EPU index 10 60 40 Vulnerability measure 5 20 0 0 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 2017-18 2018-19 6RXUFH 5%,&62DQG&HQWUDO*RYHUQPHQW%XGJHW'RFXPHQWV 1RWH 9XOQHUDELOLW\LQGH[LVPHDVXUHGDVVXPRI)LVFDO'H¿FLWWR*'3&$'WR*'3DQG,QÀDWLRQUDWH How does Policy Uncertainty affect Investment? 119 Figure 3: Exchange rate volatility and Figure 4: Future expection index and EPU index EPU index 250 250 200 200 150 150 EPU index EPU EPU index 100 100 50 50 0 0 0.000 0.010 0.020 0.030 0.040 90 100 110 120 130 Coefficient of variation of exchange rate Future expectation index Figure 5: EPU index and India )LJXUH (38LQGH[DQG,QÀDWLRQ VIX volatility 250 250 200 200 150 150 EPU index EPU EPU indexEPU 100 100 50 50 0 0 5 1015202530 0 0.5 1 1.5 2 VIX Standard deviation of inflation Figure 7: EPU index and Repo rate )LJXUH (38LQGH[DQG:3,LQÀDWLRQ 250 250 200 200 150 150 EPU index EPU 100 EPU index 100 50 50 0 0 456789 -10 -5 0 5 10 15 Repo rate (1-quarter lag) WPI inflation (%) 6RXUFH 5%,1,)7<&62DQGhttp://www.policyuncertainty.com/ (from Figure 3 to 8) 120 Economic Survey 2018-19 Volume 1 DECOUPLING OF ECONOMIC JURZWK Figure 9: Comparison of India’s and global EPU index 350 EPU-India EPU-Global 300 250 200 150 EPU index 100 50 0 Jul-06 Jul-13 Jan-17 Jan-03 Jan-10 Jun-09 Jun-16 Oct-11 Oct-18 Oct-04 Feb-07 Sep-07 Feb-14 Sep-14 Apr-08 Apr-15 Dec-05 Dec-12 Mar-18 Mar-11 Mar-04 Nov-08 Nov-15 Aug-17 Aug-10 Aug-03 May-12 May-19 May-05 Source: http://www.policyuncertainty.com/ How does Policy Uncertainty affect Investment? 121 Figure 10: Comparison of EPU index of India with United States 300 EPU-India EPU-US 250 200 150 EPU index 100 50 0 Jan-13 Jan-11 Jan-05 Jan-03 Jan-07 Jan-09 Jan-15 Jan-17 Jan-19 Sep-07 Sep-15 Sep-17 Sep-13 Sep-11 Sep-09 Sep-05 Sep-03 May-14 May-12 May-10 May-06 May-04 May-08 May-16 May-18 Source: http://www.policyuncertainty.com/ GREEN SHOOTS OF TURNAROUND ,QIDFWJURVV¿[HGFDSLWDOIRUPDWLRQ IN INVESTMENT ACTIVITY DVDSURSRUWLRQRI*'3FRPPRQO\UHIHUUHG 6.12 Figure 11 shows that after falling for WRDVWKH¿[HGLQYHVWPHQWUDWHIHOOIURP close to a decade since 2008, investment per cent in 2007-08 to 27 per cent in the activity has turned the corner since Q1 of following ten years but has since recovered Figure 11: Investment rate and GDP growth 41 14.0 GFCF as percentage of GDP (left scale) 39 Improvement in 12.0 investment rate GDP growth rate (right scale) Improvement in investment rate 37 10.0 35 8.0 33 6.0 31 4.0 GDP growth GDP growth (%) 29 Deceleration in 2.0 investment rate 27 0.0 GFCF as percentage of GDP (%) of GDP as percentage GFCF 25 -2.0 2005-06Q1 2005-06Q3 2006-07Q1 2006-07Q3 2007-08Q1 2007-08Q3 2008-09Q1 2008-09Q3 2009-10Q1 2009-10Q3 2010-11Q1 2010-11Q3 2011-12Q1 2011-12Q3 2012-13Q1 2012-13Q3 2013-14Q1 2013-14Q3 2014-15Q1 2014-15Q3 2015-16Q1 2015-16Q3 2016-17Q1 2016-17Q3 2017-18Q1 2017-18Q3 2018-19Q1 2018-19Q3 6RXUFH &HQWUDO6WDWLVWLFV2I¿FH Note: Quarterly GFCF rate from 2005-06 Q1 to 2010-11 Q4 has been calculated using the quarterly to annual ratio from 2004-05 series. 122 Economic Survey 2018-19 Volume 1 to approximately 28 per cent recently. period can be attributed to policy related While several factors led to the investment XQFHUWDLQW\ +DUGRXYHOLV HW DO ¿QG slowdown till 2017-18, inter-alia, including that shocks to economic policy uncertainty the twin balance sheet problem discussed in are associated with a subsequent decline detail in Economic Survey 2016-17, we show LQ LQYHVWPHQW LQGXVWULDO SURGXFWLRQ *'3 that a secular trend of reducing economic economic sentiment and the stock market. policy uncertainty may have helped to foster These shocks go a long way to explain not the turnaround in investment activity. only the direction but also the magnitude of 6.13 The continued resolution of the WKHFKDQJHVLQPDFURDQG¿QDQFLDOYDULDEOHV twin balance sheet problem following during the Greek economic crisis. implementation of Insolvency and Bankruptcy Code 2016 and recapitalization 6.15 The relationship of uncertainty in of banks helped to promote investment. economic policy with investment may be Focus on improvement in the business through two channels. First is the direct climate via measures to improve ease of relationship of economic policy uncertainty doing business, clarity in the policy for with investment growth and second is the )', OLEHUDOL]DWLRQ PD\ KDYH DOVR KHOSHG relationship of EPU with other variables in this regard by reducing economic policy which in turn affect investment. uncertainty. 6.16 Figure 12 shows that there is a strong RELATIONSHIP OF ECONOMIC negative relationship between EPU index and POLICY UNCERTAINTY WITH investment growth. There is a correlation of INVESTMENT IN INDIA (-)0.30 between these two variables (from Q1 of 2005-06 to Q4 of 2018-19). However, 6.14 Internationally, there are many studies the relationship was weaker for some time VKRZLQJ D VLJQL¿FDQW G\QDPLF UHODWLRQVKLS period i.e., Q3 of 2009-10 to Q4 of 2013-14, between economic policy uncertainty and real macroeconomic variables. Economic when the uncertainty in the economy was policy uncertainty as measured by EPU index declining and even the investment growth foreshadows a decline in economic growth, rate was declining. banking crisis (Baker et al. 2016). Anand et Figure 12: Investment growth and EPU index al. (2014) found that high uncertainty and GHWHULRUDWLQJ EXVLQHVV FRQ¿GHQFH SOD\HG D 20 role in the investment slowdown in India. Bloom et al. (2018) found that uncertainty 15 VKRFNVFDQJHQHUDWHGURSLQ*'3RIDURXQG SHU FHQW ZLWK KHWHURJHQHRXV ¿UPV 10 *OXHQDQG,RQ XVLQJ(38LQGH[¿QG 5 that policy related uncertainty is negatively (%) growth GFCF UHODWHGWR¿UPDQGLQGXVWU\OHYHOLQYHVWPHQW 0 and the economic magnitude of the effect 0 50 100 150 200 250 is substantial. Their estimates indicate EPU index that approximately two thirds of the 32 -5 per cent drop in corporate investments in Source: http://www.policyuncertainty.com/, US observed during the 2007-2009 crisis &62 How does Policy Uncertainty affect Investment? 123 6.17 Impulse response functions from the 6.18 Foreign investments are also expected 9HFWRU $XWRUHJUHVVLYH 5HJUHVVLRQ 9$5 to be negatively related to the economic model show after a shock i.e., higher policy certainty in the economy and the data uncertainty, the investment rate falls and then shows so as well (Figure 14 and Figure 15). the impact withers away with time (Figure %RWK)RUHLJQ'LUHFW,QYHVWPHQW )', ÀRZV 14). The impact of a one standard deviation and Foreign Institutional Investment (FII) shock to EPU index is about 1 percentage ÀRZVDUHQHJDWLYHO\FRUUHODWHGWR(38LQGH[ point and it remains for many quarters (Figure LPSO\LQJWKDWQRWRQO\WKHVKRUWWHUPLQÀRZV ,Q IDFW LW FDQ EH VDLG ZLWK VXI¿FLHQW EXWDOVRORQJWHUPFDSLWDOLQÀRZVDUHDIIHFWHG FRQ¿GHQFH WKDW WKH LPSDFW UHPDLQV IRU DW by higher uncertainty in economic policy. OHDVW¿YHTXDUWHUV WKH SHUFHQWFRQ¿GHQFH ,PSXOVH 5HVSRQVH )XQFWLRQ RI 9$5 DOVR EDQGUHPDLQVEHORZ]HURWLOO¿YHTXDUWHUV VKRZV D VLJQL¿FDQW QHJDWLYH LPSDFW RI WKH shock, which lingers on about three to four Figure 13: Impulse Response of GFCF quarters. However, another point to note is growth to EPU index WKDWWKHLQLWLDOLPSDFWLVVKDUSHUIRU)',ÀRZV (Figure 16 and 17). 6.19 There are various other factors affecting investment. First important factor that affects investment decision is cost of borrowing. Borrowing costs, with a lag, are expected to be negatively associated with &KDQJH LQSHUFHQWDJHSRLQWV LQYHVWPHQWDVWKH\UHÀHFWKLJKHULQSXWFRVWV $VH[SHFWHG¿[HGLQYHVWPHQWLVQHJDWLYHO\ 2 4XDUWHUVIROORZLQJWKHVKRFN correlated with repo rate , weighted average &, RUWKRJRQDOL]HGLUI lending rate and marginal cost of lending Source: Survey calculations. rates of SBI. Second important factor for Figure 14: FDI growth and EPU index Figure 15: FII growth and EPU index 100 100 75 75 50 50 25 25 0 (%) growth FII FDI growth(%) 0 0 50 100 150 200 250 -25 -25 -50 0 50 100 150 200 250 -50 EPU index EPU index 6RXUFH KWWS ZZZSROLF\XQFHUWDLQW\FRP5%, 2 %RUURZLQJFRVWVKHUHDUHUHSUHVHQWHGE\UHSRUDWHZKLFKLVWKHUDWHRILQWHUHVWFKDUJHGE\5%,WREDQNVIRUWKHLUERUURZLQJV IURP5%,$OWKRXJKWKHDFWXDOERUURZLQJFRVWRI¿UPV¶ZLOOEHGLIIHUHQWDQGVLJQL¿FDQWO\KLJKHUWKDQUHSRUDWHLWLVH[SHFWHG to move in the same direction. 124 Economic Survey 2018-19 Volume 1 Figure 16 : Impulse-response of FDI growth Figure 17 : Impulse-response of FII growth to to EPU index EPU index &KDQJH LQSHUFHQWDJHSRLQWV &KDQJH LQSHUFHQWDJHSRLQWV 4XDUWHUVIROORZLQJWKHVKRFN 4XDUWHUVIROORZLJQWKHVKRFN &, RUWKRJRQDOL]HGLUI &, RUWKRJRQDOL]HGLUI Source: Survey calculations. Source: Survey calculations. investment is the prices that producers get for of variation. This is because the returns that WKHLUSURGXFWV5LVHLQSULFHVDUHH[SHFWHGWR the foreign investors actually realize are in WULJJHUJUHDWHULQYHVWPHQWVDVEXVLQHVVHV¿QG foreign currency terms, which depend on LWSUR¿WDEOHWRGRVRDVORQJDVFRQVXPSWLRQ the exchange rate. If the volatility of the GHPDQG LV VXI¿FLHQWO\ VWURQJ WR RYHUFRPH exchange rate is higher, it may decrease the WKH LPSDFW RI LQÀDWLRQ7KLV LV VHHQ DV WKH JURZWK RI IRUHLJQ LQÀRZV ,W LV VHHQ WKDW investment growth is positively correlated WKHUHODWLRQVKLSEHWZHHQJURZWKLQ)',DQG WR ZKROHVDOH SULFH LQÀDWLRQ EXW QHJDWLYHO\ volatility of exchange rate is weak suggesting WR FRQVXPHU SULFH LQÀDWLRQ 7KLV PD\ EH that foreign investors in projects have other due to the fact the producers would realize FRQVLGHUDWLRQV DV ZHOO 2Q WKH RWKHU KDQG producer prices which are closer to wholesale a negative relationship, is seen between prices upon selling any product, whereas ),, LQÀRZV DQG YRODWLOLW\ RI H[FKDQJH UDWH consumers have to pay consumer prices The negative relationship suggests that the and higher prices may dampen the demand. portfolio investments which are generally Third important factor affecting investment short term investments are more affected by is capacity utilization. The utilization of the volatility in exchange rate, as compared capacity in any quarter is expected to have a WR)',ÀRZVZKLFKDUHJHQHUDOO\IRUORQJHU positive relationship with investment growth duration (details in annex of the Chapter). in the following quarter, as excess unutilized capacity in the previous quarter may lower 6.21 Can EPU index proxy for all variables the need for new investment in the current H[DPLQHG IRU LPSDFWLQJ ¿[HG LQYHVWPHQW TXDUWHU 'DWD VKRZV D SRVLWLYH FRUUHODWLRQ in the economy? It can, if it is strongly between investment growth and capacity correlated with these variables and results utilization in previous quarter (details in in previous section indicate that it is indeed annex of the Chapter). correct. EPU is positively correlated to all 7KH IRUHLJQ FRPSRQHQW RI ¿[HG the factors discussed above- repo rate, WPI LQYHVWPHQW)',DQG),,ÀRZVDUHH[SHFWHG LQÀDWLRQ YRODWLOLW\ RI H[FKDQJH UDWH DQG to be negatively related to the volatility of Capacity Utilization (as shown in Figure H[FKDQJH UDWH PHDVXUHG E\ LWV FRHI¿FLHQW 3 to 8). How does Policy Uncertainty affect Investment? 125 CONCLUSION AND POLICY policy certainty. The Government could RECOMMENDATIONS DOVR XVH ODEHOV VXFK DV ³6WDQGVWLOO´ YHUVXV ³5DWFKHW XS´ WR FDWHJRUL]H 6.22 While economic uncertainty stemming various categories of policies according from uncontrollable factors remains beyond to the level of commitment about future the control of policymakers, they can control certainty that it can provide. HFRQRPLF SROLF\ XQFHUWDLQW\ 5HGXFLQJ economic policy uncertainty is critical 2. Second, following the adage that because both domestic investment and foreign ³ZKDW JHWV PHDVXUHG JHWV DFWHG XSRQ´ investment are strongly deterred by increases economic policy uncertainty index in domestic economic policy uncertainty. must become an important index that 6.23 India has secularly decreased domestic policymakers at the highest level economic policy uncertainty since 2012 PRQLWRURQDTXDUWHUO\EDVLV5HODWHGO\ and has been exceptional in reducing this following the evolved academic uncertainty since 2015 amidst a global literature in this area, government must environment of increases in the same. encourage construction of economic However, policymakers need to double policy uncertainty sub-indices to capture down on reducing domestic economic policy economic policy uncertainty stemming uncertainty. IURP ¿VFDO SROLF\ WD[ SROLF\ PRQHWDU\ policy, trade policy, and banking policy. 6.24 We outline a few steps in this regard: Tracking these sub-indices would enable 1. First, top-level policymakers must ensure monitoring and control over economic that their policy actions are predictable, policy uncertainty. provide forward guidance on the stance 3. Quality assurance of processes in of policy, maintain broad consistency in SROLF\ PDNLQJ ZKLFK UHÀHFW WKH DGDJH actual policy with the forward guidance, and reduce ambiguity/arbitrariness RI ³'RFXPHQW ZKDW \RX GR EXW PRUH in policy implementation. To ensure FULWLFDOO\GRZKDW\RXGRFXPHQW´PXVW predictability, the horizon over which be implemented in the government. The policies will not be changed must be actual implementation of policy occurs PDQGDWRULO\VSHFL¿HGVRWKDWLQYHVWRUFDQ at the lower levels, where ambiguity be provided the assurance about future gets created and exacerbates economic policy certainty. While this will generate policy uncertainty. As organizations in some constraints in policy making, such the private sector compete and seek the YROXQWDU\ W\LQJ RI SROLF\PDNHUV¶ KDQGV KLJKHVW OHYHO RI TXDOLW\ FHUWL¿FDWLRQV is undertaken in several cases including Government departments must be WKH )LVFDO 5HVSRQVLELOLW\ DQG %XGJHW mandated to similarly seek quality 0DQDJHPHQW $FW WKH 0RQHWDU\ 3ROLF\ FHUWL¿FDWLRQV7KLVSURFHVVRIFHUWL¿FDWLRQ )UDPHZRUNRIWKH5HVHUYH%DQNRI,QGLD will require training of personnel in A similar constraint placed on ensuring following quality assurance processes QR FKDQJHV LQ SROLF\ IRU D VSHFL¿HG DQG ZLOO VLJQL¿FDQWO\ UHGXFH HFRQRPLF horizon would go a long way to ensuring policy uncertainty. 126 Economic Survey 2018-19 Volume 1 CHAPTER AT A GLANCE ¾ (FRQRPLF3ROLF\8QFHUWDLQW\KDVUHGXFHGVLJQL¿FDQWO\LQ,QGLDRYHUWKHODVWGHFDGH ¾ Continued decline in economic policy uncertainty in India post 2015 is exceptional because it contrasts sharply with the increase during this period in economic policy uncertainty in major countries, especially the U.S. ¾ $QLQFUHDVHLQHFRQRPLFSROLF\XQFHUWDLQW\GDPSHQVLQYHVWPHQWJURZWKLQ,QGLDIRUDERXW¿YH quarters. ¾ Unlike generic economic uncertainty, which cannot be controlled, policymakers can reduce economic policy uncertainty to foster a salutary investment climate in the country. ¾ Forward guidance, consistency of actual policy with forward guidance, and quality assurance FHUWL¿FDWLRQ RI SURFHVVHV LQ *RYHUQPHQW GHSDUWPHQWV FDQ KHOS WR UHGXFH HFRQRPLF SROLF\ uncertainty. REFERENCES &DEDOOHUR5LFDUGR-DQG5REHUW63LQG\FN 8QFHUWDLQW\ LQYHVWPHQW DQG LQGXVWU\ . .QLJKW)UDQN+5LVNXQFHUWDLQW\DQGSUR¿W HYROXWLRQ. No. w4160. National Bureau of Courier Corporation, 2012. (FRQRPLF5HVHDUFK 3LQG\FN 5REHUW 6 DQG $QGUHV 6ROLPDQR ³(FRQRPLF LQVWDELOLW\ DQG DJJUHJDWH %ORRP 1LFKRODV 0D[ )ORHWRWWR 1LU LQYHVWPHQW´ NBER macroeconomics Jaimovich, Itay Saporta `Eksten, and annual 8 (1993): 259-303. 6WHSKHQ-7HUU\³5HDOO\XQFHUWDLQEXVLQHVV F\FOHV´ Econometrica 86, no. 3 (2018): &KHQ ANNEX Figure A1: Investment growth and repo rate Figure A2: Investment growth and WPI LQÀDWLRQ 25 25 20 20 15 15 10 10 5 5 GFCF growth (%) GFCF growth GFCF growth (%) growth GFCF 0 0 45678910 -10 -5 0 5 10 15 -5 -5 Repo rate (1-quarter lag) WPI inflation (%) Figure A3: Investment growth and capacity Figure A4 : FDI growth and exchange rate utilization volatility 16 150.0 14 12 100.0 10 8 50.0 6 4 0.0 FDI growth(%) 0.000 0.010 0.020 0.030 0.040 GFCF growth (%) GFCF growth 2 0 -50.0 70 75 80 85 -2 -4 -100.0 Capacity Utilization (1 quarter lag) Coefficient of variation of exchange rate Figure A5: FII growth and exchange rate volatility 200 150 100 50 FII growth (%) growth FII 0 0.000 0.010 0.020 0.030 0.040 -50 -100 Coefficient of variation of exchange rate Source: 5%,&62Note: Capacity Utilization data is available only from 2008-09 onwards India's Demography at 2040: Planning Public Good Provision for 07 CHAPTER the 21st Century India is set to witness a sharp slowdown in population growth in the next two decades. Although the country as a whole will enjoy the “demographic dividend” phase, some states will start transitioning to an ageing society by the 2030s. It will surprise many readers to learn that population in the 0-19 age bracket has already peaked due to sharp declines in total fertility rates (TFR) across the country. The southern states, Himachal Pradesh, Punjab, West Bengal and Maharashtra now have fertility rates well below the replacement rate. TFR in Bihar, Uttar Pradesh, Jharkhand, Chhattisgarh, Rajasthan and Madhya Pradesh are above the replacement rate but are also experiencing significant declines. As a result, the national TFR is expected to be below replacement level by 2021 (adjusted for the skewed gender ratio, it may already be there). The age distribution, however, implies that India's working-age population will grow by roughly 9.7mn per year during 2021-31 and 4.2mn per year in 2031-41. Meanwhile, the proportion of elementary school-going children, i.e. 5-14 age group, will witness significant declines. Contrary to popular perception, many states need to pay greater attention to consolidating/merging schools to make them viable rather than building new ones. At the other end of the age scale, policy makers need to prepare for ageing. This will need investments in health care as well as a plan for increasing the retirement age in a phased manner. I. RECENT DEMOGRAPHIC this period; the slowdown in states with TRENDS historically high population growth such as Bihar, Uttar Pradesh, Rajasthan and Haryana 7.1 Population growth in India has been is particularly noteworthy. Population is now slowing in recent decades from an annual growing below 1 per cent in the southern growth rate of 2.5 per cent during 1971-81 to states as well as West Bengal, Punjab, an estimated 1.3 per cent as of 2011-16 (Figure Maharashtra, Odisha, Assam and Himachal 1). All major states have witnessed a marked Pradesh1 (Figure 2). deceleration in population growth during ______1 ,QWKH¿JXUHVDEEUHYLDWLRQVXVHGIRUVWDWHVDUHDVIROORZV$3 $QGKUD3UDGHVK$6 $VVDP%5 %LKDU&* &KKDWWLVJDUK '/ 'HOKL*- *XMDUDW+3 +LPDFKDO3UDGHVK+5 +DU\DQD-+ -KDUNKDQG-. -DPPX .DVKPLU.$ .DUQDWDND./ .HUDOD0+ 0DKDUDVKWUD03 0DGK\D3UDGHVK25 2GLVKD3% 3XQMDE5- 5DMDVWKDQ7/ 7HODQJDQD71 7DPLO1DGX 8. 8WWDUDNKDQG83 8WWDU3UDGHVK:% :HVW%HQJDO India's Demography at 2040: Planning Public Good Provision for the 21st Century 129 Figure 1: Annual Population Growth Rate in India (per cent) 2.5 2.0 1.5 1.0 0.5 0.0 1941-51 1951-61 1961-71 1971-81 1981-91 1991-01 2001-11 2011-16 6RXUFH &HQVXV,QWHUQDWLRQDO,QVWLWXWHIRU3RSXODWLRQ6FLHQFHV ,,36 HVWLPDWHV Figure 2: Annual Population Growth Rate by State during 2011-16 (per cent) 2.0 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 RJ JK GJ JH PB TL AS HP AP UP DL TN KL BR OR CG HR KA UK MP WB MH 6RXUFH &HQVXV,,36HVWLPDWHV 7.2 A key driver of this trend has been halved from 4.5 in 1984 to 2.3 as of 2016 the steady decline in India’s total fertility (Figure 3 and Figure 4). rate2 7)5 VLQFH WKH PLG V 7KRXJK 3 WKH GHFOLQH LQ ,QGLD¶V 7)5 KDV EHHQ PRUH 7KH UHSODFHPHQW OHYHO IHUWLOLW\ is gradual when compared to the experience of usually marked at 2.1 but, as discussed in other emerging economies, it has nonetheless WKH QH[W VHFWLRQ ,QGLD¶V 7)5 PD\ DOUHDG\ ______2 7RWDOIHUWLOLW\UDWHUHIHUVWRWKHWRWDOQXPEHURIFKLOGUHQERUQRUOLNHO\WREHERUQWRDZRPDQRIFKLOGEHDULQJDJHLQKHU lifetime. 3 7)5RIFKLOGUHQSHUZRPDQLVFDOOHGWKHUHSODFHPHQWOHYHOIHUWLOLW\ZKLFKLVWKHDYHUDJHQXPEHURIFKLOGUHQDZRPDQ would need to have in order for the population to replace itself 130 Economic Survey 2018-19 Volume 1 Figure 3: Number of Years Taken for TFR to Decline from over 4.0 to India’s TFR of 2.3 25 20 15 10 5 0 India China Brazil Turkey S.Korea Thailand Sri Lanka Singapore Bangladesh Hong Kong 6RXUFH :RUOG%DQN6DPSOH5HJLVWUDWLRQ6\VWHP Figure 4: TFR in India 5.5 5.0 4.5 4.0 3.5 3.0 2.5 2.0 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016 6RXUFH 6DPSOH5HJLVWUDWLRQ6\VWHP be close to the HৼHFWLYH replacement level is now below replacement level fertility in 13 fertility after accounting for its skewed out of the 22 major states (Figure 6). In fact, sex ratio. Interestingly, India has reached 7)5KDVUHDFKHGDVORZDVLQVWDWHV WKH FXUUHQW 7)5 RI DW D UHODWLYHO\ ORZ VXFK DV 'HOKL :HVW %HQJDO 7DPLO 1DGX per capita income when compared to the $QGKUD 3UDGHVK 7HODQJDQD 3XQMDE DQG experience of major developed economies Himachal Pradesh. Even high fertility states but similar to that of other Asian countries VXFKDV%LKDU-KDUNKDQG5DMDVWKDQ0DGK\D (Figure 5). 3UDGHVK &KKDWWLVJDUK 8WWDU 3UDGHVK DQG 1RWH WKDW WKHUH LV D ZLGH YDULDWLRQ LQ Uttarakhand have seen a sharp decline in WKHH[SHULHQFHRIGLIIHUHQW,QGLDQVWDWHV7)5 7)5RYHUWKH\HDUV India's Demography at 2040: Planning Public Good Provision for the 21st Century 131 Figure 5: Real Per Capita GDP when TFR Reached 2.3 25000 US Australia 20000 Canada France New Zealand Belgium UK 15000 Italy Turkey Austria Hong Kong 10000 Brazil Singapore India 5000 S.Korea Thailand Sri Lanka Bangladesh China real per capita GDP (PPP, 2011 $) real per capita GDP (PPP, 2011 0 1960 1970 1980 1990 2000 2010 2020 year when TFR reached 2.3 6RXUFH :RUOG%DQN3HQQ:RUOG7DEOH Figure 6: TFR by State in 2016 3.4 3.2 3.0 2.8 2.6 2.4 2.2 Replacement level fertility = 2.1 2.0 1.8 1.6 1.4 1.2 1.0 RJ JK GJ JH TL PB AS HP AP UP DL TN KL BR OR HR CG UK KA MP WB MH 6RXUFH 6DPSOH5HJLVWUDWLRQ6\VWHP 7KHVHGHYHORSPHQWVVXJJHVWWKDW,QGLD age-structure, and the ageing phenomenon has entered the next stage of demographic DOUHDG\ XQGHUZD\ LQ VRPH VWDWHV 7KH transition with population growth set to slow southern states, Himachal Pradesh, Punjab, markedly in the next two decades along with West Bengal and Maharashtra are already DVLJQL¿FDQWLQFUHDVHLQWKHVKDUHRIZRUNLQJ quite advanced in the demographic transition, age population (the so-called “demographic ZLWK L 7)5DOUHDG\ZHOOEHORZUHSODFHPHQW dividend” phase). level fertility; (ii) population growth mainly 7.6 However, national-level population due to momentum; (iii) more than 10 per cent WUHQGV PDVN WKH VLJQL¿FDQW KHWHURJHQHLW\ of the population over the age of 59; and (iv) across states in terms of fertility, mortality, at most one-third of the population below the 132 Economic Survey 2018-19 Volume 1 age of 20. In contrast, states such as Bihar, chapter. However, as an illustrative exercise, 8WWDU 3UDGHVK -KDUNKDQG &KKDWWLVJDUK 6HFWLRQ,,,ORRNVDWVRPHSROLF\LPSOLFDWLRQV Rajasthan and Madhya Pradesh are still in the for health care provision, elementary school early stages of demographic transition. facilities and retirement age. 7.7 In light of continued urbanization, II. PROJECTING NATIONAL AND improvements in health care, increase in STATE LEVEL POPULATION female education, and other socio-economic GULYHUV RI GHPRJUDSKLF FKDQJH 6HFWLRQ ,, 7.8 Population and its age structure are forecasts demographic metrics at the national projected at the national and state level up to DQGVWDWHOHYHOXSWR6XFKDQH[HUFLVH 2041 following the methodology outlined in would enable us to understand the pace of %R[)RUWKHSXUSRVHRIDQDO\VLV6HFWLRQ,, demographic transition at the national and and III focus on 22 major states, which account state level and assess which states are likely to for 98.4 per cent of India’s population as per H[SHULHQFHVLJQL¿FDQWDJHLQJ7KHSURMHFWHG &HQVXV population and age-structure over the next two (i) Declining Fertility Rates decades has several implications for policy, inter-alia for the (i) provision of health care, 7.9 Projected values for 2021-41 suggest (ii) provision of old-age care, (iii) provision WKDW7)5DWWKHQDWLRQDOOHYHOZLOOFRQWLQXHWR of school facilities, (iv) access to retirement- decline rapidly and will lie below replacement UHODWHG¿QDQFLDOVHUYLFHV Y SXEOLFSHQVLRQ OHYHOIHUWLOLW\DWDVHDUO\DV 7DEOH funding, (vi) income tax revenues, (vii) In line with the fertility patterns witnessed in labour force and labour participation rates, RWKHU FRXQWULHV 7)5 LV H[SHFWHG WR VWDELOL]H and (viii) retirement age. Detailed analysis WKHUHDIWHU IRU VRPH WLPH DURXQG 6XFK of these issues is beyond the scope of this IHUWLOLW\ OHYHOV ZRXOG EH FORVH WR WKH 7)5 Table 1: TFR for India and Major States, 2001-2041 States 2001 2011 2016 2021 2031 2041 ,1',$ 3.1 2.4 2.3 1.8 1.7 1.7 Andhra Pradesh 2.3 1.8 1.7 1.5 1.5 1.5 Assam 3.0 2.4 2.3 1.8 1.8 1.8 Bihar 4.4 3.6 3.3 2.5 2.0 1.8 &KKDWWLVJDUK 3.9 2.7 2.5 1.8 1.8 1.8 Delhi 2.1 1.9 1.6 1.5 1.5 1.5 *XMDUDW 2.9 2.4 2.2 1.9 1.8 1.8 Haryana 3.1 2.3 2.3 1.8 1.8 1.8 Himachal Pradesh 2.2 1.8 1.7 1.6 1.6 1.6 -DPPX .DVKPLU 2.5 1.9 1.7 1.5 1.5 1.5 -KDUNKDQG 4.4 2.9 2.6 1.8 1.8 1.8 .DUQDWDND 2.4 1.9 1.8 1.5 1.5 1.5 India's Demography at 2040: Planning Public Good Provision for the 21st Century 133 .HUDOD 1.8 1.8 1.8 1.8 1.8 1.8 Madhya Pradesh 3.9 3.1 2.8 2.0 1.8 1.8 Maharashtra 2.4 1.8 1.8 1.5 1.5 1.5 Odisha 2.6 2.2 2.0 1.8 1.8 1.8 Punjab 2.4 1.8 1.7 1.6 1.6 1.6 Rajasthan 4.0 3.0 2.7 1.9 1.8 1.8 7DPLO1DGX 2.0 1.7 1.6 1.5 1.5 1.5 7HODQJDQD 2.3 1.8 1.7 1.6 1.6 1.6 Uttar Pradesh 4.5 3.4 3.1 2.0 1.8 1.8 Uttarakhand 4.5 3.4 1.9 1.6 1.6 1.6 West Bengal 2.4 1.7 1.6 1.5 1.5 1.5 6RXUFH &HQVXV6DPSOH5HJLVWUDWLRQ6\VWHP,,36SURMHFWLRQV 1RWH 3URMHFWHGYDOXHVIRUDUHEDVHGRQ¿WWHGPRGHOYDOXHVIURP\HDUWUHQGVRI7)5EDVHGRQHVWLPDWHV IURP6DPSOH5HJLVWUDWLRQ6\VWHP%HIRUHWKHYDOXHVRI$QGKUD3UDGHVKDUHDVVLJQHGWR7HODQJDQD Box 1: Methodology for Population Projections 8VLQJ WKH &HQVXV GDWD DV EDVHOLQH SRSXODWLRQ LV SURMHFWHG E\ DJHVWUXFWXUH XS WR 7KHVHSURMHFWLRQVDUHXQGHUWDNHQERWKDWWKHQDWLRQDOOHYHODQGIRUVWDWHVDQG8QLRQ7HUULWRULHV 87V 7KHcohort-componentPHWKRGRORJ\ &DQQDQ DQG*HRUJHHWDO LVIROORZHGIRU population projections at the national level and for 22 major states that account for 98.4 per cent of India’s population using assumptions for fertility, mortality, life expectancy and sex ratio at birth. 7KHVHDVVXPSWLRQVDWWKHQDWLRQDOOHYHODUHGHULYHGXVLQJWKHDVVXPSWLRQVIRUVWDWHVZHLJKWHGE\ WKHLUVKDUHLQQDWLRQDOSRSXODWLRQ1RLQWHUVWDWHPLJUDWLRQLVDVVXPHGVLQFHWKH&HQVXVGDWD on net inter-state migration by age-structure has not been published. International migration is not WDNHQLQWRFRQVLGHUDWLRQ7KHDJHVH[SRSXODWLRQLVVPRRWKHQHGDQGDGMXVWHGIRUWKHSRSXODWLRQ category of “age not stated” using a point formula similar to the methodology used in government’s RI¿FLDOSURMHFWLRQV 2I¿FHRI5HJLVWUDU*HQHUDORI,QGLD Population Projections for Smaller States and UTs: 7KH HLJKW VPDOOHU VWDWHV $UXQDFKDO 3UDGHVK *RD 0DQLSXU 0HJKDOD\D 0L]RUDP 6LNNLP 1DJDODQGDQG7ULSXUD DQGVL[87V &KDQGLJDUK3XGXFKHUU\'DPDQ 'LX'DGUD 1DJDU+DYHOL /DNVKDGZHHSDQG$QGDPDQ 1LFREDU DFFRXQWRQO\SHUFHQWRI,QGLD¶VSRSXODWLRQ'XHWR constraints in obtaining reliable estimates for long-term trends in mortality and fertility, the ratio method 3LWWHQJHU DQG86&HQVXV%XUHDX LVXVHGIRUSRSXODWLRQSURMHFWLRQ7KHUDWLR of the small area (say a small state) to the larger area (say India) is calculated and assumed to remain constant up to 2041. For each year, this ratio is multiplied by the projected population of the larger area, as derived using the cohort-component methodology, to obtain the population projections for WKHVHVWDWHVDQG87V 134 Economic Survey 2018-19 Volume 1 Mortality Rate: A log-linear model is used to project mortality using life expectancy at birth for 1970-2016 IURPWKH6DPSOH5HJLVWUDWLRQ6\VWHP¶V/LIH7DEOHV¿WWHGVHSDUDWHO\IRUPDOHDQGIHPDOH4 for females , for males Life expectancy is projected to continue to rise during the projection period from 67.2 years in 2016 WR\HDUVLQIRUPDOHVDQGPRUHVLJQL¿FDQWO\IURP\HDUVLQWR\HDUVLQ 2041 for females5. Fertility Rate: 7)5LVSURMHFWHGXSWRXVLQJWKHGompertz method *RPSHUW] EDVHGRQWKHORZHU / DQGXSSHU 8 OLPLWVRI7)5DQGWKHEDVHSHULRG7)5ZKHUHWKHODWHVWDYDLODEOH7)5LVLQVHUWHG 7KHORZHUOLPLW / RI7)5LVWDNHQEHWZHHQIRUGLIIHUHQWVWDWHVDQGWKHXSSHUOLPLW 8 RI7)5LVWDNHQWREHWKHYDOXHRI7)5LQWKHEDVHSHULRGJLYHQWKDW7)5DFURVVVWDWHVLVRQD GRZQZDUGWUHQGFXUUHQWO\7)5IRUWLPHSHULRGt is projected using the estimated parameters a and b XVLQJWKH2UGLQDU\/HDVW6TXDUHV 2/6 UHJUHVVLRQ Sex Ratio: Both sex ratio at birth and sex differentials in survival probability are taken into consideration to GHWHUPLQHWKHVH[UDWLRRIWKHSRSXODWLRQ6H[UDWLRDWELUWKLVDVVXPHGWRUHPDLQFRQVWDQWDWWKH 2014-16 levels since it already stands below 1.10 in 12 out of the 22 major states and is not expected WRGHFOLQHVLJQL¿FDQWO\LQWKHQH[WWZRGHFDGHVLQWKHUHPDLQLQJVWDWHV FXUUHQWO\ VHHQ LQ FRXQWULHV VXFK DV &KLQD Maharashtra and Himachal Pradesh, are %HOJLXP1HWKHUODQGVDQG%UD]LO H[SHFWHGWRVHH7)5GHFOLQHIXUWKHUE\ reaching as low as 1.5-1.6 and stabilizing 7.10 At the state level, those already thereafter. Even states lagging behind in the below replacement level fertility, including IHUWLOLW\ WUDQVLWLRQ DUH H[SHFWHG WR VHH 7)5 the southern states, West Bengal, Punjab, IDOO VLJQL¿FDQWO\ EHORZ UHSODFHPHQW OHYHO ______4 6LQFH /LIH 7DEOHV IRU 'HOKL DQG +LPDFKDO 3UDGHVK DUH QRW DYDLODEOH IRU ORQJHU SHULRGV DSSURSULDWH LQFUHPHQW LQ OLIH H[SHFWDQF\DWELUWKIRUPDOHDQGIHPDOHDUHDSSOLHGWRWKH81 IRUHFDVWVWRSURMHFWOLIHH[SHFWDQF\DWELUWKXSWR 5 6LQFH.HUDODDOUHDG\KDVKLJKOLIHH[SHFWDQF\DWELUWKWKHPD[LPXPOLIHH[SHFWDQF\DWELUWKLVDVVXPHGWREHHTXDOWRWKH FXUUHQWOLIHH[SHFWDQF\DWELUWKRI-DSDQ India's Demography at 2040: Planning Public Good Provision for the 21st Century 135 WR 7KLV ZRXOG EH DV HDUO\ DV LQ (ii) Population Growth Trajectory -KDUNKDQG +DU\DQD DQG &KKDWWLVJDUK DQG by 2031 in Uttar Pradesh, Rajasthan and 7.13 Demographic projections show that Madhya Pradesh. In fact, by 2031, all states India’s population growth will continue to would see below replacement level fertility. slow rapidly over the next two decades, growing less than 1 percent during 2021- 7KLV LV LQ OLQH ZLWK H[SHFWDWLRQV RI 31 and under 0.5 per cent during 2031-41 further decline in fertility for females in the 7DEOH 6XFK SRSXODWLRQ JURZWK UDWHV 20-30 age-group, driven by rising female would be close to the trend currently seen education, postponement of marriage, access LQ FRXQWULHV VXFK DV *HUPDQ\ DQG )UDQFH to family planning methods, and continued ,Q IDFW ZLWK 7)5 SURMHFWHG WR IDOO ZHOO decline in infant mortality. While family below replacement level fertility by 2021, planning programs have played a major positive population growth in the next role in reducing fertility in India in the past two decades will be due to population decades, these socio-economic changes have momentum and the continued rise in life manifested over the last 10-15 years. expectancy. 7KH SURMHFWLRQV IRU 7)5 LQ 7DEOH *LYHQ VWDWHOHYHO GLIIHUHQFHV LQ LQLWLDO are based on the assumption that sex ratio at fertility levels, mortality and age composition, birth will remain at current levels over the both the trajectory of population and population next two decades. As of 2014-16, sex ratio JURZWKZLOOFRQWLQXHWRYDU\DFURVVVWDWHV6WDWHV at birth remains higher than the normal range ahead in the demographic transition will see a of 1.02-1.076 at the national level and in 17 continued deceleration in population growth RXWRIPDMRUVWDWHV7KXVWKHUHDUHPRUH and reach near-zero growth rates by 2031-41. men than women in the population when :LWKSRSXODWLRQSHDNLQJE\7DPLO1DGX¶V FRPSDUHG WR WKH QDWXUDO OHYHO7KLV LPSOLHV population growth will start declining during that the required replacement level fertility 2031-41 unless offset by inward migration. at the national and state level is higher than Population growth will be close to zero in the usual benchmark of 2.1, i.e., due to the Andhra Pradesh and as low as 0.1-0.2 per cent skewed sex ratio, a woman would have to give LQ .DUQDWDND .HUDOD 7HODQJDQD +LPDFKDO birth to more than 2.1 children in order for Pradesh, West Bengal, Punjab and Maharashtra. the population to replace itself. Our estimates suggest that the HৼHFWLYH replacement level 6WDWHV ODJJLQJ EHKLQG LQ WKH fertility after taking into account the skewed demographic transition will also witness sex ratio could be around 2.15-2.2 for India a marked slowdown in population growth with a sex ratio of 1.11; around 2.2-2.25 for during 2021-41. Population growth will halve states such as Haryana, Uttarakhand and RYHU WKH QH[W WZR GHFDGHV LQ &KKDWWLVJDUK Uttar Pradesh, Rajasthan and Madhya *XMDUDW ZLWK WKH VH[ UDWLR DV KLJK DV 1.20; and between 2.1-2.2 for the remaining Pradesh. Bihar alone will have a population states with the sex ratio around 1.07-1.14. JURZWK UDWH RI SHU FHQW 1RQHWKHOHVV ,QWHUHVWLQJO\WKHFXUUHQW7)5LQRXWRIWKH WRJHWKHU ZLWK -KDUNKDQG WKHVH VWDWHV ZLOO account for nearly two-thirds of the increase 22 major states is already below the HৼHFWLYH replacement level fertility. in India’s population during 2021-41, with ______6 7KHDYHUDJHYDOXHRIVH[UDWLRDWELUWKLVDURXQGLHER\VERUQSHUHYHU\JLUOV 136 Economic Survey 2018-19 Volume 1 Table 2: Annual Population Growth Rate (in per cent) for India and Major States States 2001-11 2011-21 2021-31 2031-41 ,1',$ 1.77 1.12 0.72 0.46 Andhra Pradesh 1.10 0.65 0.31 0.02 Assam 1.71 0.74 0.77 0.48 Bihar 2.54 1.82 1.34 1.00 &KKDWWLVJDUK 2.26 1.17 0.76 0.57 Delhi 2.12 1.00 0.62 0.30 *XMDUDW 1.93 1.12 0.71 0.44 Haryana 1.99 1.08 0.70 0.44 Himachal Pradesh 1.29 0.64 0.57 0.24 -DPPX .DVKPLU 2.36 0.88 0.82 0.49 -KDUNKDQG 2.24 1.39 0.97 0.82 .DUQDWDND 1.56 0.75 0.36 0.10 .HUDOD 0.49 0.66 0.45 0.18 Madhya Pradesh 2.03 1.36 0.81 0.64 Maharashtra 1.60 0.73 0.42 0.15 Odisha 1.40 0.82 0.63 0.38 Punjab 1.39 0.71 0.42 0.11 Rajasthan 2.13 1.47 0.96 0.75 7DPLO1DGX 1.56 0.56 0.25 -0.05 7HODQJDQD 1$ 0.80 0.53 0.21 Uttar Pradesh 2.02 1.48 0.93 0.73 Uttarakhand 1.88 1.30 0.70 0.50 West Bengal 1.38 0.71 0.50 0.14 6RXUFH &HQVXV,,36SURMHFWLRQV just Uttar Pradesh and Bihar accounting for to decline and is projected to drop from as RYHUSHUFHQWRIWKHLQFUHDVH 7DEOH high as 41 per cent in 2011 to 25 per cent by 7DEOH 2QWKHRWKHUKDQGWKHVKDUH (iii) Changing Age Composition of elderly, 60 years and above, population :LWK 7)5 UHDFKLQJ ORZ OHYHOV DQG will continue to rise steadily, nearly doubling longevity continuing to increase, India’s from 8.6 per cent in 2011 to 16 per cent by population at the national level and in several 2041. India’s demographic dividend will peak VWDWHVZLOOEHJLQDJHLQJVLJQL¿FDQWO\LQMXVWD around 2041, when the share of working-age, GHFDGHIURPQRZ7KHVKDUHRI,QGLD¶V\RXQJ i.e. 20-59 years, population is expected to i.e. 0-19 years, population has already started hit 59 per cent. With changing demographic India's Demography at 2040: Planning Public Good Provision for the 21st Century 137 Table 3: Population (in millions) for India and Major States, 2011- 2041 Projected growth States 2011 2016 2021 2031 2041 during 2021-41 (%) ,1',$ 1210.6 1286.1 1346.9 1443.2 1510.2 12.1 Andhra Pradesh 49.4 51.2 52.6 54.2 54.3 3.4 Assam 31.2 32.2 33.5 36.1 37.9 12.9 Bihar 104.1 113.8 123.0 139.5 153.4 24.7 &KKDWWLVJDUK 25.5 27.3 28.5 30.7 32.4 13.8 Delhi 16.8 17.7 18.5 19.6 20.2 9.4 *XMDUDW 60.4 64.1 67.2 72.0 75.2 11.8 Haryana 25.4 26.9 28.1 30.0 31.4 11.7 Himachal Pradesh 6.9 7.1 7.3 7.7 7.9 8.2 -DPPX .DVKPLU 12.5 13.1 13.6 14.8 15.5 13.4 -KDUNKDQG 33.0 35.7 37.6 41.2 44.6 18.8 .DUQDWDND 61.1 63.7 65.7 68.1 68.7 4.7 .HUDOD 33.4 34.6 35.6 37.2 37.9 6.4 Madhya Pradesh 72.6 78.1 82.5 89.2 94.9 15.0 Maharashtra 112.4 117.0 120.6 125.7 127.6 5.8 Odisha 42.0 43.8 45.4 48.2 50.1 10.3 Punjab 27.7 28.8 29.7 31.0 31.3 5.3 Rajasthan 68.5 74.1 78.6 86.1 92.6 17.8 7DPLO1DGX 72.1 74.5 76.2 78.1 77.7 2.0 7HODQJDQD 35.2 36.7 38.0 40.0 40.9 7.4 Uttar Pradesh 199.8 216.2 229.3 250.7 269.0 17.3 Uttarakhand 10.1 10.9 11.4 12.2 12.8 12.3 West Bengal 91.3 94.8 97.8 102.7 104.2 6.5 6RXUFH &HQVXV6DPSOH5HJLVWUDWLRQ6\VWHP,,36SURMHFWLRQV composition, India’s age-structure by 2041 states, would have less than one-fourth of the ZLOOUHVHPEOHWKDWRI&KLQDDQG7KDLODQGDV population under the age of 20 but about one- seen during the current decade. ¿IWKRUPRUHSRSXODWLRQRYHUWKHDJHRI by 2041. 7.17 All major states are projected to witness a decline in the share of young population 7.18 Even states in earlier stages of and an increase in the share of elderly demographic transition, such as Bihar, Uttar population over the next two decades. 3UDGHVK -KDUNKDQG &KKDWWLVJDUK 0DGK\D 6WDWHV DKHDG LQ WKH GHPRJUDSKLF WUDQVLWLRQ 3UDGHVKDQG5DMDVWKDQZLOOVHHDVLJQL¿FDQW such as Himachal Pradesh, West Bengal, decline in the share of young population, Maharashtra, Punjab and most of the southern though these shares will remain relatively 138 Economic Survey 2018-19 Volume 1 Table 4: Population by Age Structure (per cent share of population) for India and Major States, 2011-2041 0-19 years 20-59 years 60 years and above States 2011 2021 2031 2041 2011 2021 2031 2041 2011 2021 2031 2041 ,1',$ 40.9 34.5 28.8 25.2 50.5 55.8 58.8 58.9 8.6 9.7 12.4 15.9 Andhra 34.8 28.4 24.4 21.4 55.1 59.6 60.2 58.6 10.1 12.0 15.4 20.0 Pradesh Assam 42.7 35.4 29.1 26.8 50.6 56.7 60.1 58.8 6.7 7.9 10.9 14.4 Bihar 49.4 43.5 35.1 30.1 43.2 48.9 55.9 58.3 7.4 7.7 9.1 11.6 &KKDWWLVJDUK 42.3 36.0 30.5 27.2 49.9 55.0 58.0 58.5 7.9 8.9 11.6 14.4 Delhi 37.2 29.2 23.5 20.2 56.0 61.1 61.9 58.5 6.8 9.7 14.6 21.2 *XMDUDW 38.7 33.2 28.6 25.1 53.3 56.8 58.2 57.9 8.0 9.9 13.2 17.0 Haryana 40.3 33.5 28.4 24.9 51.0 57.1 59.5 59.3 8.7 9.5 12.1 15.8 Himachal 35.3 29.0 24.5 22.0 54.5 58.8 59.3 56.9 10.3 12.2 16.1 21.1 Pradesh -DPPX 43.7 33.8 24.5 23.0 48.9 57.1 62.9 59.8 7.4 9.1 12.6 17.2 .DVKPLU -KDUNKDQG 45.9 38.8 31.0 28.0 46.9 52.8 58.5 58.7 7.2 8.4 10.6 13.4 .DUQDWDND 35.8 29.8 25.0 21.7 54.7 59.0 60.5 59.3 9.5 11.1 14.5 19.0 .HUDOD 31.3 27.6 24.9 23.3 56.2 56.2 54.7 52.8 12.6 16.2 20.5 23.9 Madhya 43.8 38.0 31.8 27.3 48.4 53.7 57.6 59.3 7.9 8.3 10.6 13.4 Pradesh Maharashtra 36.2 29.5 24.1 21.2 53.9 59.0 60.9 59.0 9.9 11.5 14.9 19.7 Odisha 38.2 32.6 28.3 26.1 52.3 56.7 58.2 57.3 9.5 10.8 13.4 16.6 Punjab 35.8 28.2 23.8 21.0 53.9 59.5 60.2 58.4 10.4 12.3 16.0 20.6 Rajasthan 45.5 38.3 31.5 27.3 47.1 53.4 58.0 59.5 7.5 8.2 10.4 13.3 7DPLO1DGX 32.3 27.0 23.2 20.6 57.3 59.7 59.2 56.9 10.4 13.3 17.6 22.6 7HODQJDQD 37.0 30.0 26.0 23.0 53.8 59.4 60.5 58.8 9.2 10.6 13.5 18.2 Uttar Pradesh 47.6 39.4 32.6 27.7 44.6 52.7 57.9 60.3 7.8 7.9 9.5 12.0 Uttarakhand 42.2 35.2 29.4 24.1 48.8 55.1 58.6 60.6 9.0 9.7 12.1 15.3 West Bengal 37.1 29.1 24.2 21.9 54.4 59.8 60.6 58.4 8.5 11.1 15.2 19.7 6RXUFH &HQVXV,,36SURMHFWLRQV India's Demography at 2040: Planning Public Good Provision for the 21st Century 139 high and as large as 30 per cent in Bihar rise through 2041 in states lagging behind by 2041. Meanwhile, the share of elderly in the demographic transition, particularly population in these states will still be below Bihar, Uttar Pradesh, Madhya Pradesh and 15 per cent through 2041. Rajasthan. In principle, the latter states with rising working-age population could meet the (iv) Implications for Working-Age Population ODERXUGH¿FLWLQPDQ\RIWKHIRUPHUDJHLQJ VWDWHV &XUUHQW PLJUDWLRQ WUHQGV EURDGO\ 7.19 While most of the discussion on follow this pattern, and a study of this demographic dividend revolves around the phenomenon will be the subject of a future share of working-age population, changes (FRQRPLF6XUYH\ in the size of working-age population plays a key role in determining the size of labour III. POLICY IMPLICATIONS force and direction of inter-state labour OF AGEING migration. (i) Elementary Schools *LYHQ FKDQJLQJ DJH FRPSRVLWLRQ 7.22 As of 2016, population in the 5-14 India’s working-age population will continue age-group, which roughly corresponds to the to increase through 2041, rising by 96.5 number of elementary school-going children, million during 2021-31 and by 41.5 million has already begun declining in India and GXULQJ 7DEOH 7KLV ZLOO KDYH DFURVV DOO PDMRU VWDWHV H[FHSW -DPPX implications for the required rate of job .DVKPLU3RSXODWLRQSURMHFWLRQVVXJJHVWWKDW FUHDWLRQ LQ WKH HFRQRP\$V SHU WKH 1662 WKLVWUHQGZLOOFRQWLQXHWKURXJK 7DEOH 3HULRGLF /DERXU )RUFH 6XUYH\ India’s labour force participation rate for the 7KH VL]H RI WKH \HDUV SRSXODWLRQ will drop sharply in Himachal Pradesh, age-group 15-59 years is around 53 per cent (80 per cent for males, 25 per cent for females). 8WWDUDNKDQG 7DPLO 1DGX 0DKDUDVKWUD Depending on the trajectory of labour force 3XQMDE $QGKUD 3UDGHVK DQG .DUQDWDND E\ participation during 2021-41, additional jobs 1RWH WKDW LW ZLOO GHFOLQH HYHQ LQ WKH will need to be created to keep pace with the laggard states such as Bihar, Uttar Pradesh, projected annual increase in working-age Rajasthan and Madhya Pradesh. Overall, the population of 9.7 million during 2021-31 and number of school-going children in India will 4.2 million during 2031-41. Projecting labour decline by 18.4 per cent between 2021 and force participation is beyond the scope of this 7KLV ZLOO KDYH YHU\ LPSRUWDQW VRFLDO study, but this will be impacted by changes in and economic consequences. schooling years, age distribution and female 7RXQGHUVWDQGWKHLPSOLFDWLRQVIRUWKH labour force participation. provision of elementary schools, we examine 7.21 7KH HYROXWLRQ RI ZRUNLQJDJH the number of government and private population, moreover, will vary across states. schools per capita of 5-14 years population 7KHVL]HRIZRUNLQJDJHSRSXODWLRQZLOOVWDUW and school enrolment at the national and to decline in 11 out of the 22 major states state level. In light of the projected decline in during 2031-41, including in the southern elementary school-going children, the number states, Punjab, Maharashtra, West Bengal RIVFKRROVSHUFDSLWDZLOOULVHVLJQL¿FDQWO\LQ and Himachal Pradesh. On the other hand, India across all major states even if no more working-age population will continue to schools are added (Figure 7 and Figure 8). 140 Economic Survey 2018-19 Volume 1 Table 5: Population by Age Structure (in millions) for India and Major States, 2011-2041 0-19 years 20-59 years 60 years and above States 2011 2021 2031 2041 2011 2021 2031 2041 2011 2021 2031 2041 ,1',$ 494.7 464.2 415.8 381.0 611.7 751.6 848.2 889.7 104.2 131.1 179.3 239.4 Andhra 17.2 14.9 13.3 11.6 27.2 31.3 32.6 31.9 5.0 6.3 8.3 10.9 Pradesh Assam 13.3 11.9 10.5 10.2 15.8 19.0 21.7 22.2 2.1 2.6 3.9 5.5 Bihar 51.4 53.5 48.9 46.2 45.0 60.1 77.9 89.4 7.7 9.4 12.7 17.8 &KKDWWLVJDUK 10.8 10.3 9.4 8.8 12.7 15.7 17.8 19.0 2.0 2.6 3.5 4.7 Delhi 6.2 5.4 4.6 4.1 9.4 11.3 12.1 11.8 1.1 1.8 2.9 4.3 *XMDUDW 23.4 22.3 20.6 18.9 32.2 38.2 41.9 43.5 4.8 6.7 9.5 12.8 Haryana 10.2 9.4 8.5 7.8 12.9 16.0 17.9 18.6 2.2 2.7 3.6 5.0 Himachal 2.4 2.1 1.9 1.7 3.7 4.3 4.6 4.5 0.7 0.9 1.2 1.7 Pradesh -DPPX 5.5 4.6 3.6 3.6 6.1 7.8 9.3 9.3 0.9 1.2 1.9 2.7 .DVKPLU -KDUNKDQG 15.2 14.6 12.8 12.5 15.5 19.8 24.1 26.2 2.4 3.2 4.4 6.0 .DUQDWDND 21.9 19.6 17.0 14.9 33.4 38.8 41.2 40.8 5.8 7.3 9.9 13.0 .HUDOD 10.5 9.8 9.3 8.8 18.8 20.0 20.3 20.0 4.2 5.8 7.6 9.0 Madhya 31.8 31.3 28.4 25.9 35.1 44.3 51.4 56.2 5.7 6.9 9.4 12.7 Pradesh Maharashtra 40.7 35.6 30.4 27.1 60.5 71.2 76.6 75.4 11.1 13.9 18.8 25.2 Odisha 16.0 14.8 13.7 13.1 21.9 25.7 28.1 28.7 4.0 4.9 6.5 8.3 Punjab 9.9 8.4 7.4 6.6 15.0 17.7 18.6 18.3 2.9 3.7 4.9 6.4 Rajasthan 31.2 30.1 27.2 25.3 32.3 42.0 50.0 55.1 5.1 6.5 9.0 12.3 7DPLO1DGX 23.3 20.6 18.1 16.0 41.3 45.5 46.3 44.2 7.5 10.1 13.7 17.5 7HODQJDQD 13.0 11.4 10.4 9.4 18.9 22.6 24.2 24.0 3.2 4.0 5.4 7.4 Uttar Pradesh 95.1 90.3 81.8 74.5 89.1 120.9 145.0 162.2 15.6 18.1 23.8 32.3 Uttarakhand 4.3 4.0 3.6 3.1 4.9 6.3 7.1 7.7 0.9 1.1 1.5 2.0 West Bengal 33.8 28.5 24.9 22.8 49.7 58.5 62.2 60.9 7.8 10.8 15.6 20.5 6RXUFH &HQVXV,,36SURMHFWLRQV India's Demography at 2040: Planning Public Good Provision for the 21st Century 141 Table 6: Population for 5-14 years (in millions) for India and Major States, 2011-41 Projected change States 2011 2016 2021 2031 2041 during 2021-41 (%) ,1',$ 260.54 243.60 234.64 202.96 191.51 -18.38 Andhra Pradesh 8.72 7.88 7.44 6.52 5.82 -21.78 Assam 7.04 6.60 5.90 5.14 5.22 -11.47 Bihar 29.07 28.25 26.95 24.46 23.10 -14.28 &KKDWWLVJDUK 5.65 5.33 5.28 4.45 4.46 -15.60 Delhi 3.19 2.94 2.71 2.26 2.06 -24.07 *XMDUDW 12.03 11.41 11.29 10.11 9.42 -16.57 Haryana 5.17 4.88 4.76 4.16 3.91 -17.87 Himachal Pradesh 1.23 1.14 1.05 0.95 0.88 -16.59 -DPPX .DVKPLU 2.83 2.86 2.35 1.77 1.86 -20.65 -KDUNKDQG 8.27 7.92 7.63 5.90 6.44 -15.60 .DUQDWDND 10.99 10.34 9.95 8.32 7.46 -25.00 .HUDOD 5.38 5.12 4.89 4.64 4.42 -9.56 Madhya Pradesh 16.85 15.87 15.99 13.74 12.90 -19.34 Maharashtra 20.63 19.43 17.99 14.85 13.67 -24.02 Odisha 8.45 7.83 7.37 6.75 6.60 -10.43 Punjab 4.96 4.49 4.11 3.69 3.27 -20.35 Rajasthan 16.49 15.59 15.41 13.09 12.70 -17.57 7DPLO1DGX 11.74 10.94 10.31 8.98 8.00 -22.40 7HODQJDQD 6.64 6.01 5.64 5.17 4.70 -16.57 Uttar Pradesh 51.35 46.06 45.62 39.36 37.45 -17.91 Uttarakhand 2.21 2.00 2.11 1.65 1.54 -26.98 West Bengal 17.43 15.78 14.05 12.38 11.55 -17.79 6RXUFH &HQVXV6DPSOH5HJLVWUDWLRQ6\VWHP,,36SURMHFWLRQV 142 Economic Survey 2018-19 Volume 1 Figure 7: Number of Elementary Schools in India per 1 million of 5-14 Years Population under Status Quo 8000 250 240 7500 230 Schools per 1 million 7000 of 5-14 yrs population 220 5-14 yrs population in 210 6500 million (RHS) 200 6000 190 5500 180 2016 2021 2031 2041 6RXUFH 8QL¿HG'LVWULFW,QIRUPDWLRQRQ6FKRRO(GXFDWLRQ6DPSOH5HJLVWUDWLRQ6\VWHP,,36 1RWH &DOFXODWLRQV DUH EDVHG RQ SURMHFWHG \HDUV SRSXODWLRQ IRU IURP ,,36 DQG number of elementary schools at 2016 levels. Figure 8: Number of Elementary Schools 6WDWHV VXFK DV +LPDFKDO 3UDGHVK per 1 million of 5-14 Years Population Uttarakhand, Andhra Pradesh and Madhya under Status Quo Pradesh have more than 40 per cent of elementary schools with fewer than 50 HP JK VWXGHQWV HQUROOHG )LJXUH 6LPLODU WUHQGV UK AS Figure 9: Per cent of Elementary Schools CG MP with Less Than 50 Students Enrolled AP HP OR JK TL UK PB AP WB AS KA OR RJ 2016 MP MH CG 2041 MH TN KA JH TL UP WB HR JH 2005-06 GJ RJ KL PB 2016-17 BR TN KL DL GJ 0 3000 6000 9000 12000 15000 18000 21000 HR UP BR 6RXUFH 8QL¿HG 'LVWULFW ,QIRUPDWLRQ RQ 6FKRRO DL (GXFDWLRQ6DPSOH5HJLVWUDWLRQ6\VWHP,,36 0 1020304050607080 1RWH &DOFXODWLRQV DUH EDVHG RQ SURMHFWHG \HDUVSRSXODWLRQIRUIURP,,36DQGQXPEHURI 6RXUFH 8QL¿HG 'LVWULFW ,QIRUPDWLRQ RQ 6FKRRO elementary schools at 2016 levels. Education. India's Demography at 2040: Planning Public Good Provision for the 21st Century 143 H[LVW LQ &KKDWWLVJDUK $VVDP DQG 2GLVKD emphasis from quantity towards quality and with large number of schools per capita and HI¿FLHQF\RIHGXFDWLRQ small school size. In fact, the number of (ii) Health Care Facilities elementary schools with less than 50 students has increased over the past decade across all 7.26 Access to health care is still a major major states except Delhi. challenge in India. If India’s hospital facilities remain at current levels, rising population 7KH ³RSWLPDO´ VFKRRO VL]H YDULHV over the next two decades (even with slowing widely according to terrain and urban population growth rates) will sharply reduce clustering, but this sharp increase in number the per capita availability of hospital beds of elementary schools per capita needs to be in India across all major states (Figure 10). FDUHIXOO\VWXGLHG7KHWLPHPD\VRRQFRPHLQ India already fares poorly relative to other PDQ\VWDWHVWRFRQVROLGDWHPHUJHHOHPHQWDU\ emerging and developed economies in terms VFKRROVLQRUGHUWRNHHSWKHPYLDEOH6FKRROV of per capita availability of hospital beds located within 1-3 kms radius of each other (Figure 11). can be chosen for this purpose to ensure no VLJQL¿FDQW FKDQJH LQ DFFHVV 7KLV ZRXOG 6WDWHV ZLWK KLJK SRSXODWLRQ JURZWK also be in line with the experience of other 7DEOH DUHDOVRWKHRQHVZLWKWKHORZHVWSHU major economies witnessing a decline in capita availability of hospital beds (Figure elementary school-going population, such as 12). Hence, there is a straightforward case -DSDQ &KLQD 6RXWK .RUHD 6LQJDSRUH DQG for expanding medical facilities in these &DQDGDZKLFKKDYHLPSOHPHQWHGSROLFLHVWR states. For states in the advanced stage of PHUJHRUFORVHGRZQVFKRROV1RWHWKDWWKLVLV demographic transition, however, the rapidly not about reducing investment in elementary FKDQJLQJ DJH VWUXFWXUH 7DEOH ZLOO PHDQ education, but an argument for shifting policy that the type of health care services will have Figure 10: Number of Government Hospital Beds in India per 1 million Population under Status Quo 500 Hospital beds per 1 million population 1550 Total Population in million (RHS) 1500 475 1450 450 1400 1350 425 1300 400 1250 2016 2021 2031 2041 6RXUFH &HQWUDO%XUHDXRI+HDOWK,QWHOOLJHQFH6DPSOH5HJLVWUDWLRQ6\VWHP,,36 1RWH &DOFXODWLRQV DUH EDVHG RQ SURMHFWHG SRSXODWLRQ IRU IURP ,,36 DQG QXPEHU RI government hospital beds at 2016 levels. 144 Economic Survey 2018-19 Volume 1 Figure 11: Number of Hospital Beds per 10,000 Population 150 125 100 75 50 25 0 U.S. U.K. India Japan China Brazil France Canada Mexico S.Korea Malaysia Germany 6RXUFH :+2 1RWH 'DWDLVDVRIIRU,QGLDIRURWKHUFRXQWULHV Figure 12: Number of Government to adapt towards greater provision of geriatric Hospital Beds per 1 million Population care. A major problem with planning for the under Status Quo provision of medical facilities is the paucity of DL VSHFL¿FGDWDHVSHFLDOO\RQSULYDWHKRVSLWDOV HP Available data on government hospitals have KL been used here but it is clear even from basic WB JK research that it does not provide a true picture TN of the quality or quantity of health care in the KA country. UK AS (iii) Retirement Age GJ AP MH 7.28 India’s healthy life expectancy at the age PJ 2016 of 60, which is the average number of years a TL 2041 60-year old person is expected to live in OR RJ full health taking into account the impact of MP diseases and injuries, has continually increased CG over the years for both men and women. HR JH Healthy life expectancy at the age of 60 now UP stands at 12.9 years (12.5 years for males; BI 13.3 years for females), though it is still much 0 200 400 600 800 1000 1200 1400 lower than that for other major developed and 6RXUFH &HQWUDO%XUHDXRI+HDOWK,QWHOOLJHQFH6DPSOH emerging economies (Figure 13). 5HJLVWUDWLRQ6\VWHP,,36 7.29 Due to ageing population and increasing 1RWH &DOFXODWLRQVDUHEDVHGRQSURMHFWHGSRSXODWLRQ IRUIURP,,36DQGQXPEHUof government hospital pressure on pension funding, many countries beds at 2016 levels. have begun raising the pensionable retirement India's Demography at 2040: Planning Public Good Provision for the 21st Century 145 Figure 13: Healthy Life Expectancy at Age of 60 (years) 22 20 2000 2016 18 16 14 12 10 U.S. U.K. India Japan China Brazil France Turkey Canada Mexico S.Korea Thailand Malaysia Australia Germany Indonesia Singapore Philippines Switzerland South Africa New Zealand 6RXUFH WHO. DJH&RXQWULHVVXFKDV*HUPDQ\)UDQFHDQG Table 7: Retirement Age Reforms Being 86KDYHLQFUHDVHGWKHUHWLUHPHQWDJH6RPH Implemented or Under Consideration in FRXQWULHV VXFK DV $XVWUDOLD DQG 8. XVHG Major Economies to allow women to retire earlier than men Country Retirement Age Reforms but have changed the rules to bring them at Retirement age to increase SDU0DQ\FRXQWULHVVXFKDV*HUPDQ\8. *HUPDQ\ gradually to 66 by 2023 and to DQG86KDYHVLJQDOOHGWKDWWKH\ZLOONHHS 67 by 2029 increasing the retirement age according to a 3HQVLRQEHQH¿WDJHWRULVH SUHVHW WLPHOLQH 7DEOH ,Q WKH 8. IRU 86 gradually to reach 67 for those example, the state pension age will increase born in 1960 or later for both men and women to 66 by October 6WDWHSHQVLRQDJHWRLQFUHDVH 7KH 8. JRYHUQPHQW LV SODQQLQJ for both men and women to 66 further increases in the retirement age to 67 8. by October 2020, and further to spanning the years 2026-28 and to 68 during 67 between 2026-28 and to 68 2044-46. between 2044-46 Pensionable age scheduled to *LYHQ WKDW OLIH H[SHFWDQF\ IRU ERWK Australia increase gradually to 67 by 2023 males and females in India is likely to continue rising, increasing the retirement age Under consideration to raise the retirement age for women by 1 for both men and women going forward could year every three years and for be considered in line with the experience &KLQD men by 1 year every six years so RI RWKHUFRXQWULHV )LJXUH 7KLVZLOOEH that by 2045, the retirement age key to the viability of pension systems and for both men and women would would also help increase female labour force be 65 SDUWLFLSDWLRQ LQ WKH ROGHU DJHJURXSV 6LQFH Under consideration to raise the -DSDQ an increase in the retirement age is perhaps retirement age to 70 inevitable, it may be worthwhile signalling 6RXUFH &RXQWU\VSHFL¿F SHQVLRQ GRFXPHQWV DQG this change well in advance – perhaps a government press releases. 146 Economic Survey 2018-19 Volume 1 Figure 14: Retirement Age (years) 70 Male Female 65 60 55 50 45 40 U.S. U.K. India Japan China France Canada Mexico Turkey S. Korea Thailand Australia Malaysia Germany Singapore 6RXUFH &RXQWU\VSHFL¿FSHQVLRQGRFXPHQWV2(&' decade before the anticipated shift – so that WLPH 7KLV LV HYHQ WUXH IRU D FRPPRQO\ WKH ZRUNIRUFH FDQ EH SUHSDUHG IRU LW 7KLV discussed topic such as the demographic will also help plan in advance for pensions dividend. It is important, therefore, that and other retirement provisions. working assumptions and projections are constantly revised in light of new evidence IV. CONCLUSION (especially in the age of big data) for areas 7KLVFKDSWHULVQRWPHUHO\DQDWWHPSW such as urbanization, energy requirements, to look at the changing population dynamics forest cover, water availability, climate of the country but is meant as an illustration change and other long-term factors that have of how several of the common working a large impact on the socio-economic context assumptions of economists and policy- in which government policy interventions makers need to be revisited from time to play out. CHAPTER AT A GLANCE ¾ India is set to witness a sharp slowdown in population growth in the next two decades. Although the country as a whole will enjoy the “demographic dividend” phase, some states will start transitioning to an ageing society by the 2030s. ¾ A surprizing fact is that population in the 0-19 age bracket has already peaked due to sharp GHFOLQHVLQWRWDOIHUWLOLW\UDWHV 7)5 DFURVVWKHFRXQWU\7KHQDWLRQDO7)5LVH[SHFWHGWREH below replacement rate by 2021. ¾ Working-age population will grow by roughly 9.7mn per year during 2021-31 and 4.2mn per year in 2031-41. ¾ 7KH SURSRUWLRQ RI HOHPHQWDU\ VFKRROJRLQJ FKLOGUHQ LH DJH JURXS ZLOO ZLWQHVV VLJQL¿FDQWGHFOLQHV&RQWUDU\WRSRSXODUSHUFHSWLRQPDQ\VWDWHVQHHGWRSD\JUHDWHUDWWHQWLRQWR FRQVROLGDWLQJPHUJLQJVFKRROVWRPDNHWKHPYLDEOHUDWKHUWKDQEXLOGLQJQHZRQHV ¾ $WWKHRWKHUHQGRIWKHDJHVFDOHSROLF\PDNHUVQHHGWRSUHSDUHIRUDJHLQJ7KLVZLOOQHHG investments in health care as well as a plan for increasing the retirement age in a phased manner. India's Demography at 2040: Planning Public Good Provision for the 21st Century 147 REFERENCES Transactions of the Royal Society of London (1825). %UDVV:LOOLDP$QVOH\-&RDOH3DXO'HPHQ\ Don F. Heisel, Frank Lorimer, Anatole &DQQDQ ( ³7KH SUREDELOLW\ RI D FHVVDWLRQ 5RPDQLXNDQG(WLHQQH9DQ'H:DOOH³7KH of the growth of population in England 'HPRJUDSK\RI7URSLFDO$IULFD´Princeton and Wales during the next century”, The University Press (1968). Economic Journal (1895). “Population Projections for India and *HRUJH 09 6WDQOH\ . 6PLWK 'DYLG $ 6WDWHV ´ Report of the Technical 6ZDQVRQ DQG -HII 7D\PDQ ³3RSXODWLRQ *URXSRQ3RSXODWLRQ3URMHFWLRQVFRQఅLWXWHG 3URMHFWLRQV´ &KDSWHU LQ -DFRE 6LHJHO by the National Commission on Population. DQG 'DYLG 6ZDQVRQ HGV The Methods 2I¿FH RI WKH 5HJLVWUDU *HQHUDO &HQVXV and Materials of Demography. San Diego: &RPPLVVLRQHURI,QGLD Elsevier Academic Press (2004). “Revision of World Population Prospects”, ³3URMHFWLRQV RI WKH 3RSXODWLRQ E\ 6WDWHV UN Population Division (2017). DQG ´&XUUHQW3RSXODWLRQ5HSRUWV 6HULHV 3 1R US Census Bureau, *RPSHUW]%³2QWKH1DWXUHRIWKH)XQFWLRQ (1952). Expressive of the Law of Human Mortality, DQG RQ D 1HZ 0RGH RI 'HWHUPLQLQJ WKH 3LWWHQJHU ' ³3URMHFWLQJ 6WDWH DQG /RFDO 9DOXHRI/LIH&RQWLQJHQFLHV´Philosophical Populations”, Cambridge: Ballinger (1976). From Swachh Bharat to Sundar Bharat via Swasth Bharat : An Analysis of the 08 Swachh Bharat Mission CHAPTER olq/kdhVlikZ[kqeylanwf"krksndk%A fØfeya fDyUua i.kZ'kSokydneSaA foo.kZ fojla lkUæa nqxZU/a u fgra tye~AA p-lw- “The river having water polluted with soil and faeces, insects, snakes and rats and carrying rainwater will aggravate all doshas. Slimy, having insects, impure, full of leaves, moss and mud, having abnormal color and taste, viscous and foul smelling water is not wholesome.” — Charaka Samhita Aligning with the ideals of Mahatma Gandhi, the Swachh Bharat Mission (SBM) was initiated in WRDFKLHYHXQLYHUVDOVDQLWDWLRQFRYHUDJHE\2FWREHU 7KLVÀDJVKLSSURJUDPPHLV SHUKDSVWKHODUJHVWFOHDQOLQHVVGULYHDVZHOODVDQDWWHPSWWRHIIHFWEHKDYLRXUDOFKDQJHLQWKH ZRUOGHYHU(YHQ\HDUVDIWHU,QGLD¶VLQGHSHQGHQFHLQDURXQGPLOOLRQUXUDODQGDERXW 10 million urban households in India were without a sanitary toilet; over 564 million, i.e. close WRKDOIWKHSRSXODWLRQVWLOOSUDFWLFHGRSHQGHIHFDWLRQ7KURXJK6%0 SHUFHQWRIUXUDO,QGLD has been covered in the last four years. Since October 2014, over 9.5 crore toilets have been built DOORYHUWKHFRXQWU\DQGYLOODJHVKDYHEHHQGHFODUHG2SHQ'HIHFDWLRQ)UHH 2') $VRQ -XQH 6WDWHV87VDUHSHUFHQWFRYHUHGZLWK,QGLYLGXDO+RXVHKROG/DWULQH ,++/ 6%0KDVVLJQL¿FDQWO\LPSURYHGKHDOWKRXWFRPHV7RKLJKOLJKWWKHLPSDFWRI6%0RQKHDOWKQHZ HYLGHQFHLVSURYLGHGWKDW6%0KDVKHOSHGUHGXFHGLDUUKRHDDQGPDODULDDPRQJFKLOGUHQEHORZ ¿YH\HDUVVWLOOELUWKDQGORZELUWKZHLJKW QHZERUQZLWKZHLJKWOHVVWKDQNJV 7KLVHIIHFWLV SDUWLFXODUO\SURQRXQFHGLQGLVWULFWVZKHUH,++/FRYHUDJHZDVORZHULV)LQDQFLDOVDYLQJV IURPDKRXVHKROGWRLOHWH[FHHGWKH¿QDQFLDOFRVWVWRWKHKRXVHKROGE\WLPHVRQDYHUDJHDQG WLPHV IRU SRRUHVW KRXVHKROGV$V VDQLWDWLRQ JDLQHG RYHU WKH ODVW IRXU \HDUV FRQWULEXWHV WR 6XVWDLQDEOH'HYHORSPHQW*RDOV 6'*V HVSHFLDOO\WKH6'*WKHPRPHQWXPPXVWEHVXVWDLQHG WRPDNHFOHDQOLQHVVDQLQWHJUDOSDUWRI,QGLD¶VFRQVFLRXVQHVV INTRODUCTION into town planning. Although sanitation and hygiene are considered to be virtues 8.1 Mahatma Gandhi once said, “Sanitation in all cultures and religions of the world, is more important than independence.” Proper sanitation and hygiene are essential inputs prevalence of unsanitary conditions have not only for healthy and disease free living been a problem faced by most of the countries EXW DOVR IRU D GLJQL¿HG OLIH DV D KXPDQ at some point of time in the process of their being. The ancient Indus valley civilisation economic development. Many have alluded accorded prime importance to sanitation by to the unhygienic conditions that prevailed in meticulously integrating sanitation systems the industrial towns of 19th century Europe. From Swachh Bharat to Sundar Bharat via Swasth Bharat 149 8.2 Lack of access to basic sanitation quality of life by promoting cleanliness, hygiene services continues to be a major problem in and eliminating open defecation. The targets of many parts of the world. In 2015, 2.3 billion the mission are to be met by 2 October, 2019, people, globally, lacked basic sanitation coinciding with the 150th birth anniversary of the services (JMP, 2017). Lack of sanitation has Father of the Nation. been recognised as a major problem in India. 8.5 SBM adopts a multi-faceted approach Even after 67 years of India’s independence, including: in 2014, around 10 crore rural and about one crore urban households in India were without x &RPPXQLW\ SDUWLFLSDWLRQ: Ensuring a sanitary toilet and over 55 crore – about half appropriate participation of the the country’s population – still practiced open EHQH¿FLDU\FRPPXQLWLHV ¿QDQFLDOO\ RU GHIHFDWLRQ,QIDFWDQXQÀDWWHULQJQDWLRQDOIDFW otherwise, in the setting up of the toilets was that open defecation in India represented to promote ownership and sustained use. 60 per cent of open defecation globally. Poor x )OH[LELOLW\ LQ &KRLFH: SBM offers sanitation costs India around 5.2 per cent ÀH[LELOLW\ E\ EXLOGLQJ LQ D PHQX RI of its GDP (LIXIL, Water Aid and Oxford RSWLRQV VR WKDW WKH SRRUGLVDGYDQWDJHG Economics, 2016). families can subsequently upgrade 8.3 The Government’s emphasis on their toilets depending upon their working towards a clean India in mission UHTXLUHPHQWVDQGWKHLU¿QDQFLDOSRVLWLRQ PRGHZDVUHÀHFWHGLQWKHVSHHFKRIWKH3ULPH This is done to ensure that sanitary Minister, Narendra Modi from Rajghat at the toilets are constructed, which ensures Swachh Bharat Mission launch on 2 October, VDIHFRQ¿QHPHQWDQGGLVSRVDORIIDHFHV 2014, when he declared: “If people of India An illustrative list of technology options, can reach Mars with minimal expenditure, with cost implications is provided to why can they not keep their streets and meet the user preferences and location- colonies clean.” The Swachh Bharat Mission VSHFL¿FQHHGV (SBM) was launched as a multi-pronged x &DSDFLW\ %XLOGLQJ: SBM augments the approach to enhance the level of sanitation in institutional capacity of districts to change the country. The focus under this mission has behaviour at the grassroots level and not just been on construction of toilets but strengthen the capacities of implementing also on effecting a behavioural change in the agencies so that the programme could communities. The result has been substantial be rolled in a time-bound manner and gains in health parameters as shown by collective outcomes could be measured. various studies. The gains from a cleaner India are important inputs, directly as well x Instil Behaviour change: Incentivizing as indirectly, for achieving broader economic the performance of State-level development objectives. institutions to implement activities for behavioural change among communities. SWACHH BHARAT MISSION- Emphasising on awareness generation, GRAMIN (SBM) triggering mind-set changes, leading 8.4 Recognising the need for urgent action on to community behaviour change and the sanitation front, on 2 October, 2014, the birth demand generation for sanitary facilities anniversary of Mahatma Gandhi, Prime Minister, in houses, schools, anganwadis, places Narendra Modi announced India’s Swachh of community congregation and for solid Bharat (Clean India) Mission to enhance the and liquid waste management activities. 150 Economic Survey 2018-19 Volume 1 x Broad-based Engagement: SBM set up Household Latrines (IHHL) to eligible the Swachh Bharat Kosh to encourage EHQH¿FLDULHV LQ UXUDO DUHDV DQG FRYHUV IRU Corporate Social Responsibility and accept provision of water storage. The central contributions from private organizations, share for the incentive provided for IHHLs individuals and philanthropists. is 60 per cent and the State share is 40 per cent. For North Eastern States, Jammu and x Use of Technology: Information Kashmir and Special Category States, the technology and social media is central share is 90 per cent and the State imperative to this program as it share is 10 per cent. Additional contributions allows citizens to keep a check on the from other sources are also permitted. availability of toilets for every rural A total of `51,314.3 crore has been household in India. Nearly 90 per cent allocated since 2014-15 for SBM, out of of all SBM toilets have already been which, `48,909.2 crore has been released geo-tagged. Many mobile applications (95.3 per cent). Additionally, a provision have been launched by not only the was made for Extra Budgetary Resources government but also by few citizens, of `15,000 crore of which `8,698.20 crore which direct the municipal corporations’ has already been drawn. Details of the funds attention towards unclean areas. allocated for SBM and the funds released to 8.6 Under SBM, an incentive of `12,000 WKH 6WDWHV87V VLQFH DUH JLYHQ LQ is provided for construction of Individual Table 1. Table 1: Details of funds allocated and the funds released for SBM (2015-19) ` (in Crore) Years Funds Allocated Funds Released Fund Utilization (per cent) 2014-15 2850.0 2730.3 95.8 2015-16 6525.0 6363.0 97.51 2016-17 10513.0 10272.0 97.70 2017-18 16948.27 16610.9 98.0 2018-19 (RE) * 14478.1 12932.96 89.3 * (up to 31.03.2019) Source: Ministry of Drinking Water and Sanitation 8.7 As a result of the efforts of the the termination of faecal-oral transmission, Government, as on date, 98.9 per cent of India GH¿QHG E\ D QR YLVLEOH IDHFHV IRXQG has been covered under SBM. Since October LQ WKH HQYLURQPHQWYLOODJH DQG E HYHU\ 2014, over 9.5 crore toilets have been built all KRXVHKROGDVZHOODVSXEOLFFRPPXQLW\ over the country (till 14.06.2019). The total institution(s) using safe technology option number of household toilets constructed from for disposal of faeces. The number of ODF 2014 till 2018 shows a rapid progress over the YLOODJHV KDYH VLJQL¿FDQWO\ LQFUHDVHG VLQFH last few years starting from less than 50 lakh 2015 (Figure 1). As on 29.05.2019, 5,61,014 household toilets per year and reaching up to villages (93.41 per cent), 2,48,847 gram over 3 crore toilets per year. A major focus panchayats (96.20 per cent)- 6,091 blocks of SBM has been on making villages Open (88.60 per cent) and 618 districts (88.41 per Defecation Free (ODF). ODF would mean cent) have been declared ODF. From Swachh Bharat to Sundar Bharat via Swasth Bharat 151 Figure 1: Number of household toilets constructed and ODF villages (2015-19) 35 2.5 30 30.3 2.1 2 Lakhs Millions 25 25.0 1.7 22.0 1.5 20 1.4 15 1 12.6 10 0.5 0.5 5 0 0 2015-16 2016-17 2017-18 2018-19 No. of Household toilets constructed (in Millions) ODF Villages (in Lakhs) Source: Ministry of Drinking Water and Sanitation 0RVWRIWKHVWDWHVVKRZHGVLJQL¿FDQWO\ achieve their targets (Figure 2). Goa has the greater access to IHHL in 2018-19 as lowest IHHL coverage followed by Odisha compared to 2014-15 (Figure 2). Most of the and Telangana. Karnataka and Arunachal states have achieved the status of 100 per cent Pradesh are very close to achieving 100 per IHHL coverage and only few states are yet to cent IHHL coverage. Figure 2: Individual Household Latrines in 2014-15 and 2018-19 (in per cent) Individual Household Latrines (IHHL) Individual Household Latrines (IHHL) 2014-15 (in per cent) 2018-19 (in per cent) Source: Ministry of Drinking Water and Sanitation 152 Economic Survey 2018-19 Volume 1 8.9 A comparison of some of the states in coverage is yet to achieve 90 per cent level, IHHL coverage and their neighbouring states whereas the neighbouring states of Andhra has been depicted in Figure 3. Goa, in spite of Pradesh, Jharkhand and Chhattisgarh have starting from a very high baseline has shown VKRZQ VLJQL¿FDQW LPSURYHPHQWV :HVW a saturation of IHHL coverage to around Bengal continues to increase the coverage 70 per cent only, whereas the neighbouring from its high base in 2012-13, whereas the states of Maharashtra and Karnataka have neighbouring States of Bihar and UP have VKRZQVLJQL¿FDQWLPSURYHPHQWV,Q2GLVKD also shown momentum since 2015-16. Figure 3: IHHL Coverage of some States in comparison to its neighbouring States IHHL Coverage (%) in Goa & nearby States IHHL Coverage (%) in Bihar & nearby States IHHL Coverage (%) in Gujarat & nearby States IHHL Coverage (%) in Odisha & nearby States Source: Ministry of Drinking Water and Sanitation COMPARISON ACROSS STATES targets (Figure 4). Goa has the lowest ODF FOR ODF STATUS (IN PER CENT) coverage declared followed by Odisha, 8.10 Most of the states have achieved Telangana and Bihar. West Bengal and the status of 100 per cent ODF coverage Sikkim are very close to achieving 100 per and only few states are yet to achieve their cent ODF coverage. From Swachh Bharat to Sundar Bharat via Swasth Bharat 153 Figure 4: ODF status across States (in per cent) West Bengal 99.55 Uttarakhand 100 Uttar Pradesh 100 Tripura 100 Telangana 73.99 Tamil Nadu 100 Sikkim 97.06 Rajasthan 100 Punjab 100 Puducherry 100 Odisha 45.36 Nagaland 100 Mizoram 100 Meghalaya 100 Manipur 100 Maharashtra 100 Madhya Pradesh 100 Lakshadweep 100 Kerala 100 Karnataka 100 Jharkhand 100 Jammu & Kashmir 100 Himachal Pradesh 100 Haryana 100 Gujarat 100 Goa 5.84 Daman & Diu 100 D & N Haveli 100 Chhattisgarh 100 Chandigarh 100 Bihar 82.95 Assam 100 Arunachal Pradesh 100 Andhra Pradesh 100 A & N Islands 100 0 20406080100 Source: SBM Dashboard as on 14th June 2019 154 Economic Survey 2018-19 Volume 1 8.11 The success of a scheme like the SBM (SLWM) is another major component of depends not only on the infrastructure created 6%0 0LVVLRQ $V VFLHQWL¿F GLVSRVDO RI but also on the resultant behavioural change waste has a noticeable impact on social and the associated changes in the patterns development, there is an urgent need for of toilet usage by individuals. The National VHWWLQJ XS WKH V\VWHP IRU WKH HI¿FLHQW Annual Rural Sanitation Survey (NARSS) disposal of waste in various states, especially 2018-19, conducted by an Independent 9HUL¿FDWLRQ$JHQF\ ,9$ KDVIRXQGWKDW rural villages. In light of this, many states per cent of households had access to toilets have undertaken various activities such as during the survey period. Further, 96.5 per construction of waste collection centres, cent of the households in rural India that had menstrual hygiene management activities, access to a toilet, used them. The NARSS also installation of bio-gas plants, construction of UHFRQ¿UPHGWKH2')VWDWXVRI SHUFHQW compost pits, installation of dustbins, system of villages, which were previously declared for collection, segregation and disposal of DQG YHUL¿HG DV 2') E\ YDULRXV GLVWULFWV garbage, construction of drainage facility States. It is also interesting to note that 95.4 and leach pits and construction of soak pits per cent of the villages surveyed were found to have minimal litter and minimal stagnant and stabilization ponds. These activities water. require huge disbursement of funds from Central and State governments. Figure 5 SOLID AND LIQUID WASTE highlights the Central share expenditure MANAGEMENT XQGHU6/:0GXULQJODVWIRXU\HDUVLQ6WDWHV 8.12 Solid and Liquid Waste Management UTs. Figure 5: Central share expenditure under SLWM during last 4 years in States/UTs (` Lakh) 8000 7000 6000 5000 4000 3000 2000 1000 0 &HQWUDOVKDUHH[SHQGLWXUHXQGHU6/:0GXULQJODVW\HDUVLQ6WDWHV87V 5V/DNK 2014-15 2015-16 2016-17 2017-18 Source: Ministry of Drinking Water and Sanitation ANALYSIS OF SBM ON HEALTH ISSUES scheme had on the various socio-economic outcomes of the rural populace. A direct 8.13 The success of SBM can be assessed impact of improved sanitation should from the gains that the actions under the manifest on the health indicators. Diarrhoea, From Swachh Bharat to Sundar Bharat via Swasth Bharat 155 DOHDGLQJFDXVHRIGHDWKDPRQJWKHXQGHU¿YH of diarrhoea and malaria cases in children children in India, accounted for around 11 below 5 years, still birth and low birth weight per cent of deaths in 2013. Diarrhoea cases cases in these two groups between March among children below 5 years in India have 2015, when SBM begin its implementation UHGXFHGVLJQL¿FDQWO\RYHUWKHSDVW\HDUV and March 2019, when most districts in 8.14 As of March 2014, 50 per cent of the India had IHHL coverage of 100 per cent. districts in India had IHHL Coverage less 7KH ¿UVW JURXS LH GLVWULFWV ZLWK ORZ ,++/ than 33.5 per cent (median value). In order to coverage suffered more from diarrhoea, gauge the impact of SBM on health indicators, malaria, still births and low birth weight we estimated a Difference-in-Difference. For than the second group i.e. districts with high this purpose, we separate districts into two IHHL coverage–indicating that sanitation JURXSVWKH¿UVWJURXSZKHUH,++/FRYHUDJH and hygiene is the primary reason for these was low (below medium) and the second KHDOWKSUREOHPVLQWKHFRXQWU\7KLV¿QGLQJ group where IHHL coverage was high points to the fact that adequate sanitation (above medium) as of 2015. Because IHHL plays a key role in reducing diarrhoea, coverage become almost universal as of 2019 malaria, still births and low birth weight cases (Figure 2), the increase in IHHL coverage )LJXUHV 7KH PDMRU ¿QGLQJ RI WKLV ZDV VLJQL¿FDQWO\ PRUH LQ WKH ¿UVW JURXS RI districts than in second group. Therefore, it is analysis was that all these health indicators expected the impact on health to be larger for including diarrhoea and malaria cases WKH¿UVWJURXSWKDQIRUWKHVHFRQGJURXS7R LPSURYHG VLJQL¿FDQWO\ LQ ERWK JURXSV DIWHU examine this thesis, we tracked the number the implementation of SBM. Figure 6: Impact of IHHL Coverage on Diarrhoea and Malaria cases in children below 5 years Source: Health Management Information System, Ministry of Health & Family Welfare; IHHL data from SBM Dashboard-Swachh Bharat Mission – Gramin, Ministry of Drinking Water and Sanitation Note: 7RWDORIGLVWULFWVRI,QGLDDUHGLYLGHGLQWRWZRSDUWV ¿UVWWKDWKDG,++/FRYHUDJHEHORZSHUFHQWLQ0DUFK and second that had IHHL coverage above 33.5 per cent in March 2014. 156 Economic Survey 2018-19 Volume 1 Figure 7: Impact of IHHL Coverage on Still Births and New-borns with weight less than 2.5 kg Source: Health Management Information System, Ministry of Health & Family Welfare; IHHL data from SBM Dashboard-Swachh Bharat Mission – Gramin, Ministry of Drinking Water and Sanitation 8.15 Diarrhoea cases reduced from around cases declined from 3,890 and 3,230 in 2015 6,968 and 5,262 in 2015 to 5,683 and 4,550 in WR DQG LQ LQ WKH ¿UVW DQG LQWKH¿UVWDQGVHFRQGJURXSUHVSHFWLYHO\ second group respectively. While this study Malaria cases also dropped from around 761 shows that sanitation has an important role and 273 in 2015 to 222 and 113 in 2019 to play in reducing diarrhoea and malaria, LQ WKH ¿UVW DQG VHFRQG JURXS UHVSHFWLYHO\ there may be other factors like distribution Still births came down from 540 and 403 in of mosquito nets, fogging machines and WRDQGLQ LQWKH¿UVWDQG FRQVWUXFWLRQ RI *DPEXVLD ¿VK KDWFKHULHV second group respectively. Low birth-weight under the National Vector Borne Disease Figure 8: Diarrhoea in Indian States Figure 9: Malaria in Indian States Source: Health Management Information System, Ministry of Health & Family Welfare From Swachh Bharat to Sundar Bharat via Swasth Bharat 157 Figure 10: Still Births in Indian States Figure 11: Low Birth Weight Cases in Indian States Source: Health Management Information System, Ministry of Health & Family Welfare Note: Low birth weight cases indicate new borns with weight less than 2.5 kgs. Control Programme and provision of safe Non-ODF districts were selected to ensure drinking water, Oral rehydration solutions socio-cultural and regional similarity across (ORS) and zinc, hand washing and personal geographies within the state. Becoming ODF hygiene under Integrated Action Plan for had a positive impact on the child health and Prevention and Control of Pneumonia and nutrition, evident from the fact that the health Diarrhoea that have also played an important and nutritional indicators of the children and role in reduction of malaria and diarrhoea, mothers belonging to the ODF areas were but are not in the scope of this study. comparatively better than their non-ODF counterparts (Figure 12). 8.16 With improved sanitation and 100 per cent ODF, diarrhoea cases reduced Figure 12: Prevalence of diarrhoea in ODF VLJQL¿FDQWO\ LQ PDQ\ VWDWHV OLNH *XMDUDW and Non –ODF areas in 2017 (in per cent) Tamil Nadu, West Bengal & Bihar (Figure 8). Similarly, improvements are evident in 20 18.1 malaria, still births and low birth weight 18 cases (Figures 9, 10 & 11). 16 15.2 14 12.1 12 IMPACT OF SBM: FEW 10.2 10 8.5 INDEPENDENT STUDIES 8 6.9 8.17 The Sanitation Health Impact 6 4 Assessment study was conducted by Ministry 2 of Drinking Water and Sanitation (MoDWS), 0 ODF Non -ODF Overall to understand the impact of ODF status on Children less than or equal to 2 years Children age is greater than 2 years the key child health and nutritional indicators in ¿YH states- Karnataka, Madhya Pradesh, Base (All children): 4985 Rajasthan, Uttar Pradesh and West Bengal. Source: Ministry of Drinking Water and Sanitation 158 Economic Survey 2018-19 Volume 1 8.18 Another study, “Swachh Bharat Mission that in 2014, i.e. before the start of the SBM, – Preliminary estimations of potential health there were an estimated 140,000 deaths from impacts from increased sanitation coverage” diarrhoeal disease attributable to unsafe conducted by World Health Organization sanitation; about 39,000 of those attributable (WHO) to estimate health gains based on the GHDWKVRFFXUUHGLQFKLOGUHQ\RXQJHUWKDQ¿YH latest available evidence linking sanitation years. Since the start of the SBM, mortality and mortality from diarrhoeal disease, from unsafe sanitation is estimated to have showcased initial estimates of expected declined to about 50,000 deaths in 2017-2018. health gains from reduced diarrhoeal disease The study shows that there is a clear relation due to increased sanitation coverage with between progress on sanitation coverage and the SBM initiative. The study results show health gains (Figure 13). Figure 13: The Assessed and Projected Progress on Sanitation Coverage and Health Gains 140000 120 120000 100 100000 80 80000 60 60000 40000 40 Baseline 20000 20 0 0 cent) Facilities(per Coverage withCoverage basic 2014 2015-16 2017-18 Jan-19 Oct-19 Household Sanitation Deaths Avoided compared to Deaths Avoided compared Deaths avoided compared to baseline(2014) Household sanitation coverage with basic facilities(%) Source: World Health Organization (WHO) 8.19 Prior studies have shown how important behaviour change communication costs sanitation and hygiene are in economic associated with programme delivery, while terms in India, as well as what it would cost the remaining 92 per cent is required to be India to implement. For example, the World spent on incentivising household toilets and Bank estimated the economic impacts of hand washing stations. inadequate sanitation in India in the year 2006 – showing an annual economic impact 8.20 A recent study conducted by UNICEF of `2.4 trillion (US$ 53 billion), implying a on behalf of MoDWS assessed the economic per capita annual loss of `2,180 (US$ 48) LPSDFWV EHQH¿WV RI6%07KHVWXG\IRFXVHG or 6.4 per cent of the GDP in the same year RQWKHKRXVHKROGDQGFRPPXQLW\¿QDQFLDODQG (World Bank 2011). Hence, the costs of HFRQRPLFEHQH¿WVDVZHOODVFRVWVRILPSURYHG inadequate sanitation and the expected gains sanitation and hygiene.The study found that from improved sanitation, are considerable. on an average, every household in an open The majority of SBM interventions and defecation free village saved about `50,000 their associated costs occur at community SHU\HDURQDFFRXQWRI¿QDQFLDOVDYLQJVGXH and household level. Approximately 8 per to lower likelihood of disease from using a cent of the national government’s overall toilet and practicing hand washing and the contribution is allocated to social and value of time saved due to a closer toilet. Cost- From Swachh Bharat to Sundar Bharat via Swasth Bharat 159 EHQH¿W UDWLRV ZHUH SUHVHQWHG XQGHU GLIIHUHQW households in a community use a toilet, the perspectives, thus allowing conclusions to be ¿QDQFLDOVDYLQJVH[FHHGWKH¿QDQFLDOFRVWVWR drawn about the impact of the intervention the household by 1.7 times, on average. For on households, each with different policy the poorest households, the value is higher conclusions. On the other hand, costs included at 2.4 times. When household time savings investment and operational costs for toilet and (from closer toilet access and less sickness) hand washing station, including subsidies or and the time for cleaning and maintaining the resources provided by government or non- WRLOHWDUHYDOXHGWKHEHQH¿WVH[FHHGFRVWVE\ VWDWH DFWRUV DV ZHOO DV ¿QDQFLDO DQG QRQ WLPHV:KHQEHQH¿WVRIOLYHVVDYHGDUH ¿QDQFLDOFRVWVWRKRXVHKROGV LQFOXGHG WKH EHQH¿WV H[FHHG FRVWV E\ times. If the government contribution to the 7KH¿QGLQJVRIWKHVWXG\VXJJHVWWKDW WRLOHW FRVW LV LQFOXGHG UHÀHFWLQJ D EURDGHU ZKHQFRVWVDQGEHQH¿WVDUHFRPSDUHGRYHUD VRFLHWDOSHUVSHFWLYHWKHEHQH¿WVH[FHHGFRVWV 10-year time period and when 100 per cent of by 4.3 times (Table 2). 7DEOH %HQH¿WFRVWUDWLRVIURPGLIIHUHQWSHUVSHFWLYHVDW rate of toilet use of 100 per cent Household Household Household ¿QDQFLDO Social perspective(includes Financial ¿QDQFLDO perspective + perspective + government subsidy) Perspective time impacts+ time impacts lives saved All 1.7 3 4.7 4.3 Poorest 2.4 4 7 5.8 Q2 1.4 3.3 5.4 4.7 Q3 1.6 2.9 4.5 4 Q4 1.7 2.9 4.3 3.9 Richest 2.1 2.8 4 3.7 Source: Financial and Economic Impacts of Swachh Bharat Mission in India- UNICEF 8.22 In terms of the impact of SBM on the x 11.25 times less likely to have their physical environment, a very recent study groundwater sources contaminated (12.7 by UNICEF, in association with MoDWS times less from contaminants traceable indicates considerable impact on combating to humans alone). contamination of water, soil and food. The x 1.13 times less likely to have their soil study was conducted on the basis of a list of contaminated, 1.48 times less likely to ten ODF and ten non-ODF villages each in have food contaminated and 2.68 times the states of Odisha, Bihar and West Bengal less likely to have household drinking (total of 20*3=60 villages). Four villages of water contaminated. HDFK FODVVL¿FDWLRQ 2') YHUVXV QRQ2') 7KH¿QGLQJVIURPWKHVWXG\LQGLFDWHWKDW were randomly selected from the shortlisted these substantial reductions may potentially villages in each of these states (total of be attributed to the improvement in sanitation 8*3=24 villages). Overall, in terms of faecal and hygiene practices, as well as supportive contamination, ODF villages were, on average: systems such as regular monitoring. 160 Economic Survey 2018-19 Volume 1 WAY FORWARD individual houses, cleaning water bodies, VFLHQWL¿F ZDVWH PDQDJHPHQW GHDOLQJ ZLWK 8.24 SBM has brought in a remarkable plastic menace, controlling air pollution, etc. WUDQVIRUPDWLRQ DQG WUDFHDEOH EHQH¿WV WR WKH society as a whole. It is one of the largest 8.27 To sustain the momentum created and cleanliness drives in the world. Many States behavioural change, a number of actions have achieved the status of 100 per cent ODF would have to be taken on a continuous basis and IHHL coverage, thereby has led to a sea such as motivation of “agents of change” at the change in the dignity of people, especially JURXQGOHYHOLPSDUWWUDLQLQJWR¿HOGDJHQWV women. This mission acts as a driver for appointment of sanitation Ambassadors to eliminating the gender disparity through the campaign and create awareness especially on FRQVWUXFWLRQ RI JHQGHUVSHFL¿F ODWULQHV LQ KHDOWK EHQH¿WV REWDLQ V\VWHPDWLF IHHGEDFN public areas such as schools, roads and parks. from users. Attention must also be accorded to This public movement will have indirect the sewer construction and water availability. positive impact on society by increasing 8.28 Going forward, SBM should focus on the enrolment ratio of girls in schools and achieving 100 per cent disposal of solid and improving health standards. liquid waste. Currently, many states are not 8.25 Through SBM, 99.2 per cent of the concentrating enough on this aspect which rural India has been covered. Since October could pull us back to where we were a few 2, 2014 over 9.5 crore toilets have been built \HDUVEDFN6FLHQWL¿FWHFKQLTXHVIRUWKHVDIH all over the country and 564,658 villages and effective disposal of waste should be the have been declared ODF. India’s phenomenal next on the agenda for this mission. As Indian journey towards sanitation for all has ensured economy grows, people are also on the move the social, environmental and economic gains for various activities- for better education, for by ensuring that the behavioural change gets accessing better health, transport, hospitals, rooted in people’s consciousness. The Mission and tourism purposes- imparting strongly has brought one of the largest behavioural the culture of swachhata at public places and changes in its citizenry. The mission mirrors maintaining it should be an important part of the National Developmental priorities by clean India. focusing on the gender equality and women 8.29 The cleaning of rivers should be an empowerment. Importantly, it is also aligned integral part of clean India, along with with the 2030 global sustainable development coordinated activities between Centre agenda and SDGs especially the SDG 6.2 – and States such as treatment of industrial “By 2030, achieve access to adequate and HIÀXHQFH GUDLQ ELRUHPHGLDWLRQ ULYHU equitable sanitation and hygiene for all, and surface cleaning, rural sanitation, river front end open defecation, paying special attention development, afforestation and biodiversity to the needs of women and girls and those in conservation etc. vulnerable situations”. 8.30 To continue the momentum created by 8.26 Yet, India’s challenge is an enormous 6%0WKHDYDLODELOLW\RI¿QDQFLDOUHVRXUFHV one. Construction of toilets is one part of the intermixed with changing mind-sets have to solution for a clean India. There are various be ensured. Annual monitoring of the various facets for a clean India. The dream of clean rural villages of different states has to be India can only be realized by addressing guaranteed for the effective formulation of these multiple facets – maintaining a culture different policies and their implementation. of swachhata at public places beyond As the resource requirements are large, there From Swachh Bharat to Sundar Bharat via Swasth Bharat 161 is a need to facilitate and sustain innovative surroundings clean and maintaining hygiene ¿QDQFLQJ PHFKDQLVPV E\ H[SORULQJ WKH would have tremendous environmental VXLWDELOLW\ RI YDULRXV ¿QDQFLDO LQVWUXPHQWV EHQH¿WV 6%0 QHHGV WR LQFRUSRUDWH LQ VSHFL¿F FRQWH[WV DQG LQWHUYHQWLRQV )RU environmental and water management issues H[DPSOH PLFUR¿QDQFLQJ FRQFHVVLRQDO for long term sustainability and improvements. loans, corporate social responsibility and The issues relating to water availability are crowd funding align with local government expected to be exacerbated by the effects of ¿QDQFLQJ3ULYDWH3DUWQHUVKLSDQG&RUSRUDWH climate change and incidence of extreme 6RFLDO5HVSRQVLELOLW\FDQHQVXUHLQVSHFL¿F weather events. Investment in the toilet and FRQWH[WV D VPRRWK ÀRZ RI IXQGV IRU WKH sanitation infrastructure in future, therefore, SURFXUHPHQWRIYDULRXVVFLHQWL¿FWHFKQRORJLHV demands incorporation of principles of for waste disposal and awakening masses. sustainability, circular economy, and adoption However, Governments must assign sig- of eco-friendly sanitation technologies. QL¿FDQWZHLJKWWRWKHDOORFDWLRQRIDGHTXDWH Finally, all these efforts together endeavour resources as improvement in sanitation is into culminating a Swachh (Clean), Swasth one of the key determinants for the wider (Healthy) and Sundar (Beautiful) Bharat economic development of the economy. that we dreamt for us and future generations to inherit which will be a real tribute to the 8.31 A clean India should also lead to 'Father of the Nation'. environment friendly green India. Keeping the CHAPTER AT A GLANCE ¾ SBM, one of the largest cleanliness drives in the world, has brought in a remarkable transformation DQGWUDFHDEOHKHDOWKEHQH¿WV ¾ Even 67 years after India’s independence, in 2014, around 10 crore rural and about 1 crore urban households in India were without a sanitary toilet; over 56.4 crore, i.e. close to half the population, still practiced open defecation. Through SBM, 99.2 per cent of the rural India has been covered. Since October 2, 2014 over 9.5 crore toilets have been built all over the country and 564,658 villages have been declared ODF. ¾ %HFRPLQJ2')KDVUHGXFHGGHDWKVGXHWRGLDUUKRHDPDODULDHVSHFLDOO\LQXQGHU¿YHFKLOGUHQ still births and new-borns with weight less than 2.5 kg and thereby improved child health and nutrition. This effect is particularly pronounced in districts where IHHL coverage was lower. ¾ )LQDQFLDOVDYLQJVIURPDKRXVHKROGWRLOHWH[FHHGWKH¿QDQFLDOFRVWVWRWKHKRXVHKROGE\ times, on average and 2.4 times for poorest households. ¾ Going forward, SBM needs to incorporate environmental and water management issues for sustainable improvements in the long-term. 162 Economic Survey 2018-19 Volume 1 REFERENCES Water Aid and Oxford Economics. (2016). “The True Cost of Poor Sanitation.” Dalberg. 2019. “6XPPDU\ 5HSRUW $VVHVVPHQWRI2')(QYLURQPHQWVRQ)DHFDO WHO UNICEF. 2017. “Joint Monitoring &RQWDPLQDWLRQRI:DWHU6RLODQG)RRG” 3URJUDPPH IRU :DWHU 6XSSO\ 6DQLWDWLRQ DQG +\JLHQH 3URJUHVV RQ 'ULQNLQJ :DWHU Ministry of Drinking Water and Sanitation. 6DQLWDWLRQDQG+\JLHQH” Government of India. 2017. “The Sanitation +HDOWK,PSDFW$VVHVVPHQW6WXG\” World Bank. 2011. New Delhi. Water and Sanitation Program “(FRQRPLF ,PSDFWV RI UNICEF. 2019. “Assessment of IEC Activity- Inadequate Sanitation in India.” Swachh Bharat Mission (Gramin) 2014-19.” Enabling Inclusive Growth through Affordable, Reliable and Sustainable 09 Energy CHAPTER ¶lw;ZvkRektxrLrLFkq"kÜÓ¸ Sun is the soul of all animate and inanimate -Rig Veda Energy is vital for development and prosperity of any economy. India, however, ODJVEHKLQGVLJQL¿FDQWO\LQHQHUJ\XVDJH GHVSLWHDFFRXQWLQJIRUSHUFHQWRI ZRUOG¶VSRSXODWLRQ,QGLDXVHVRQO\DURXQGSHUFHQWRIWKHZRUOG¶VSULPDU\ HQHUJ\(QHUJ\SRYHUW\KDVEHHQPRUHSHUYDVLYHLQ,QGLDWKDQLQFRPHSRYHUW\ SHU FHQW RI RXU SRSXODWLRQ FRXOG QRW DFFHVV FOHDQ FRRNLQJ LQ ZKHQ FRPSDUHGWRSHUFHQWIRU&KLQDIRXUSHUFHQWIRU%UD]LODQGOHVVWKDQRQH SHUFHQWIRU0DOD\VLD:LWKDQLQFUHDVHRISHUFDSLWDHQHUJ\FRQVXPSWLRQE\ WLPHV,QGLDZLOOEHDEOHWRLQFUHDVHLWVUHDOSHUFDSLWD*'3E\86 LQSULFHV $GGLWLRQDOO\LI,QGLDKDVWRUHDFKWKH+',OHYHORILWKDV WRLQFUHDVHLWVSHUFDSLWDHQHUJ\FRQVXPSWLRQE\IRXUWLPHV,QGLD¶VHPSKDVLV RQ HQHUJ\ HI¿FLHQF\ RYHU WKH GHFDGHV KDV KHOSHG VLJQL¿FDQWO\ LQ VHUYLQJ WKH FRXQWU\¶V HQHUJ\ QHHGV (QHUJ\ HI¿FLHQF\ SURJUDPPHV KDYH JHQHUDWHG FRVW savings worth more than `FURUHVDQGDUHGXFWLRQRIDERXWPLOOLRQWRQV RI&2HPLVVLRQLQ:KLOHWKHVKDUHRIUHQHZDEOHVLQWRWDOJHQHUDWLRQ KDVLQFUHDVHGIURPSHUFHQWLQWRSHUFHQWLQ ,QGLDVWLOO QHHGVLQYHVWPHQWLQUHQHZDEOHHQHUJ\RIPRUHWKDQ86ELOOLRQRYHUWKH QH[WGHFDGH$VHOHFWULFYHKLFOHVUHSUHVHQWWKHQH[WJHQHUDWLRQLQVXVWDLQDEOH PRELOLW\,QGLDPXVWHPSKDVL]HRQWKHP&XUUHQWO\WKHPDUNHWVKDUHRIHOHFWULF FDUVLVRQO\SHUFHQWZKHQFRPSDUHGWRSHUFHQWLQ&KLQDDQG SHUFHQW LQ1RUZD\$FFHVVWRIDVWFKDUJLQJIDFLOLWLHVPXVWEHIRVWHUHGWRLQFUHDVHWKH PDUNHWVKDUHRIHOHFWULFYHKLFOHV INTRODUCTION unevenly distributed spatially in rural vis-à- vis urban areas and socio-economically when 9.1 As witnessed over the past two seen across income groups. India, therefore, centuries, energy has been the driving needs to quadruple its per-capita energy force behind the process of economic consumption to meet the rising aspirations development: greater access to energy has of its citizens. This will also enable India to fostered economic growth as well as other achieve the human development status of an indicators of human development. India has a per-capita energy consumption of only upper-middle-income country. about one-third of the global average. Within 9.2 India’s energy needs have been this consumption, access to clean fuel is complemented by efforts to use energy 164 Economic Survey 2018-19 Volume 1 HI¿FLHQWO\ LQ WKH ODVW WKUHH GHFDGHV 7KH charging infrastructure. overall electricity savings due to adoption of ENERGY FOR PROSPERITY WKHVHHQHUJ\HI¿FLHQF\PHDVXUHVLVHVWLPDWHG at 7.21 per cent of the net electricity 9.4 Energy is an integral component of consumption in 2017-18. Total thermal the growth process for any economy. The energy saved is 2.7 per cent of the net thermal present day developed countries pursued a energy consumption and 2.0 per cent of the path of energy-intensive industrial growth net energy supply during the same period. to reach the standards of living witnessed by them today. The upper-middle-income 9.3 Further, India has also strived to countries have also seen per capita energy increase the share of energy from sustainable consumption rise with their rise in per capita sources. The share of renewables in total incomes. Though India accounts for around generation has increased from 6 per cent in 18 per cent of world’s population, it uses 2014-15 to 10 per cent in 2018-19. Electric only around 6 per cent of the world’s primary vehicles (EVs) represent the next generation energy. India’s per capita energy consumption in sustainable mobility and need to be equals 0.6 tonnes of oil equivalent (toe) as encouraged. The adoption rate of electric compared to the global per capita average vehicles has been slow, largely due to the of 1.8 toe. India’s per capita primary energy lack of charging infrastructure in the country consumption lags that of the upper-middle- and the time taken for completely charging income countries by a considerable margin the EVs. A policy push is therefore required (Figure 1). to devise universal charging standards for the country as a whole and to provide adequate 9.5 Historical experience across countries Figure 1: Per Capita Primary Energy Consumption (1965-2017) 3 2 (tonnes of oil equivalent) 1 Primary energy consumption per capita Primary energy 0 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 Year Mexico Turkey China Country Brazil Malaysia India Source: Data on primary energy consumption from BP Energy Statistics, Population and Per-capita real GDP from World Bank Data ȱ ȱ ȱȱěǰȱȱȱȱ¢ 165 shows that in the initial years of economic intensity of GDP started declining at a much development, increase in per capita GDP lower level of per capita GDP as compared to requires a large increase in primary energy per the developed world. India’s primary energy capita. A comparison can be made between intensity of GDP started declining since 1991 India and China, both of which started from at per capita GDP of around US$ 578 whereas low levels of per capita primary energy US primary energy intensity of GDP started consumption as well as per capita GDP. declining since 1970 at per capita GDP of However, we can see that China was able around US$ 23,309 (at constant 2010 US$). to quickly increase its energy consumption 9.6 Figure 3 shows the relationship and grew rapidly (Figure 2). In the medium- between per capita energy consumption term, for India to achieve per capita GDP and corresponding real per capita GDP for comparable to that of the upper-middle- around 170 countries for the year 2017. income countries, we require greater energy A simple linear regression between the resources and that too at a rapidly increasing two variables indicates that one Gigajoule rate. Energy intensity of India’s GDP has increase in energy consumption per capita been declining in the recent past, which is corresponds to an increase of US$ 145 UHÀHFWLYH RI LQFUHDVHV LQ WKH HI¿FLHQF\ RI per capita in 2010 prices. Thus, India will energy use. However, India cannot become have to increase its per capita consumption an upper-middle-income country without (i) from the current 24 Gigajoules by 2.5 rapidly raising its share of the global energy times to increase its real per capita GDP by consumption commensurate with its share US$ 5000 in 2010 prices, which will also of the global population, and (ii) ensuring enable it to enter the upper-middle income universal access to adequate modern group. This will require huge energy resources commercial energy at affordable prices. It that would also need to increase with time. is also important to note that India’s energy Figure 2: Per Capita Primary Energy Consumption and Per Capita GDP (1965-2017) Mexico Turkey China Brazil Malaysia India 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 Primary energy consumption per capita (tonnes of oil equivalent) Primary energy 0 2000 4000 6000 8000 10000 12000 GDP per capita (constant 2010 US$) Source: Data on primary energy consumption from BP Energy Statistics, Population and Per-capita real GDP from World Bank Data 166 Economic Survey 2018-19 Volume 1 Figure 3: Per capita energy consumption and per capita GDP for various countries (2017) 90000 60000 30000 GDP per capita (Constant 2010 US$) 0 0 100 200 300 400 500 Per capita energy consumption (Gigajoules) Source: Data on Per capita energy consumption from BP Energy Outlook 2019 and per capita GDP at constant 2010 US$ from World Bank Data. 9.7 Access to energy is important not development. India would have to quadruple just in its own right but also due to its its per capita energy consumption to reach a linkages with other social indicators. The HDI of 0.8 and enter the group of countries Sustainable Development Goal (SDG) No.7 with high human development. on Affordable and Clean Energy is closely related to all other SDGs. This is highlighted ACCESS TO ENERGY – ENERGY by the strong relationship between Human POVERTY Development Index (HDI) and Per capita 9.8 There is wide disparity between urban energy consumption (Figure 4). At low levels and rural areas in access to energy. A large of energy consumption, increases in per capita proportion of the population especially in energy consumption leads to considerable rural areas relies on non-commercial biomass increases in human development. The curve VXFK DV ¿UHZRRG DQG GXQJ FDNHV IRU WKHLU ¿WWHGWRWKHGDWDLQGLFDWHVWKDWIRUFRXQWULHV in the sub 100 Gigajoules per capita energy cooking/heating needs, thereby exacerbating consumption region, small increases in energy health concerns due to poor indoor air quality. consumption correspond to large increases in :KLOHWKHVKDUHRI/LTXH¿HG3HWUROHXP*DV HDI. A country with 100 Gigajoules of per (LPG) as a cooking fuel has increased over capita energy consumption has, on an average, the years, the share of households reporting HDI of around 0.8 which is considered to be it to be as the primary source of energy for very high human development (http://hdr. cooking has been low in the rural areas when undp.org/en/composite/HDI). India had a per compared with the urban areas (Figure 5). capita energy consumption of 24 Gigajoules It is heartening to see a wide acceptance of and a HDI of 0.64 in 2017 i.e., medium human LPG as the cooking fuel in urban areas. ȱ ȱ ȱȱěǰȱȱȱȱ¢ 167 Figure 4: Human Development and Per Capita Energy Consumption for a cross-section of countries (2017) 1.0 0.8 HDI 2017 India 0.6 0.4 60 0 100 200 300 400 500 Gigajoules/capita Source: Data from BP Energy Outlook 2019 Figure 5: Distribution of households by primary source of energy used for cooking: all-India, 1993-94 to 2011-12 Rural Urban 100 100 75 75 50 50 Per cent of households Per cent of households 25 25 0 0 Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Year Year coke/ coal LPG kerosene other sources# Fuel firewood & chips dung cake no cooking arrangement Source: Data from NSSO Report No.567: Energy Sources of Indian Households for Cooking and Lighting, 2011-12 Note: # includes gobar gas, charcoal, electricity, others 168 Economic Survey 2018-19 Volume 1 )LJXUH 3HUFHQWDJHRIKRXVHKROGVUHSRUWLQJµ¿UHZRRGDQGFKLSV¶DVSULPDU\VRXUFHRI energy for cooking (2011-12) Rural Urban 80 80 60 60 40 40 Per cent Per cent 20 20 0 0 Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Percentile Class of MPCE Percentile Class of MPCE Source: Data from NSSO Report No.567: Energy Sources of Indian Households for Cooking and Lighting, 2011-12 Note: # includes gobar gas, charcoal, electricity, others MPCE=Monthly Per Capita Expenditure 9.9 While there is a large gap in energy years, especially through the efforts of the access between the rural and urban areas, Government of India such as the Ujjwala there remains a wide variation in the energy scheme (Figure 7). As per IEA-1(2018), in access between the households at various 2017, 53 per cent of the population in India economic strata. Using the data from latest did not have access to clean cooking when available consumer expenditure round of compared with 68 per cent in 2010. However, 1DWLRQDO6DPSOH6XUYH\LHZH¿QG this remains low when compared with other that around 81 per cent of rural households upper-middle-income countries such as 30 and 59 per cent of urban households in lowest per cent for China, 4 per cent for Brazil and ¿YHSHUFHQWLOHFODVVHVRIH[SHQGLWXUHUHSRUWHG less than 1 per cent for Malaysia. ¿UHZRRG FKLSVDVWKHLUSULPDU\VRXUFHRI 9.10 Government has been taking conscious energy for cooking (Figure 6). As we move efforts to make clean cooking fuel available XSWKHH[SHQGLWXUHFODVVHVZH¿QGWKDWWKH to households. Pradhan Mantri Ujjwala UHOLDQFH RQ ¿UHZRRG DQG GXQJ FDNHV NHHSV Yojna was launched in 2016, with the aim to falling and the use of LPG gains importance. safeguard the health of women and children +RZHYHU HYHQ DW WKH WRS ¿YH SHUFHQWLOH by providing them with clean cooking fuel. classes in the rural areas, around 34 per cent Around 7 crore LPG connections have been of households in 2011-12, which is the latest provided till April 2019 under the Scheme. year for which this data is available, reported 'LUHFW %HQH¿W 7UDQVIHU IRU /3* FRQVXPHU ¿UHZRRGDQGFKLSVWREHWKHSULPDU\VRXUFH '%7/ VFKHPH QDPHO\ ދ3$+$/¶ LQ of energy for cooking while only around 50 districts of the country on 15 November, per cent of these households reported LPG 2014 has also been launched to rationalize as their primary energy source for cooking. subsidies based on approach to cut subsidy This indicated that the problem of energy leakages. As on 5 March, 2019, 24.39 crore poverty has been more pervasive than LPG consumers have joined the scheme. income poverty. The access to clean cooking LPG consumers, who join the PAHAL fuel has increased considerably in the recent scheme, will get the LPG cylinders at non- ȱ ȱ ȱȱěǰȱȱȱȱ¢ 169 Figure 7: Percentage of population without access to clean cooking 80 70 60 50 ŚŝŶĂ 40 /ŶĚŝĂ Per cent 30 ƌĂnjŝů 20 10 0 2000 2005 2010 2017 Source: Data from IEA World Energy Outlook 2018 subsidized price and receive LPG subsidy (as delivers sustainable development and protect per their entitlement) directly into their bank the environment. A large part of India’s accounts. PAHAL has been recognized by energy story also comes from the various the “Guinness Book of World Record” as the HQHUJ\HI¿FLHQF\PHDVXUHVWKDWWKHFRXQWU\ :RUOG¶V/DUJHVW'LUHFW%HQH¿W6FKHPH has implemented over the years. ENERGY EFFICIENCY 9.12 The primary energy intensity of India’s 9.11 While India focuses in increasing GDP has followed a falling trend over the its energy production and consumption, years (Figure 8). India’s primary energy ensuring access to electricity for all and intensity of GDP has fallen from 0.0004 toe in improving living standards, it also strives 1990 to 0.0002 toe in 2017. India understood to ensure that it follows a growth path that WKHLPSRUWDQFHRIHQHUJ\HI¿FLHQF\PHDVXUHV )LJXUH ,QGLD¶V3ULPDU\(QHUJ\,QWHQVLW\RI*'3 Primary energy Primary consumption (TOE)/GDP($) 0.0003 0.00035 0.0004 1990 1995 2000 2005 2010 2015 Year Source: Data on primary energy consumption from BP Energy Statistics, real GDP from World Bank Data 170 Economic Survey 2018-19 Volume 1 reasonably early in its economic development 9.14 The institutional and legal framework path and has embraced a number of energy LQ WKH FRXQWU\ IRU HQHUJ\ HI¿FLHQF\ KDV HI¿FLHQF\PHDVXUHVLQWKHODVWWKUHHGHFDGHV been strengthened through the Energy The aim of this section is to provide the reader Conservation Act in 2001, which created DQDQDO\VLVRIWKHLPSDFWRIHQHUJ\HI¿FLHQF\ WKH %XUHDX RI (QHUJ\ (I¿FLHQF\ %(( measures in terms of energy saved, emissions 7KH RYHUDOO VL]H RI WKH HQHUJ\ HI¿FLHQF\ avoided, cost savings realized. market in India is estimated to be US$ 22.81 7KH WHUP HQHUJ\ HI¿FLHQF\ EURDGO\ ELOOLRQ (QHUJ\ (I¿FLHQF\6HUYLFHV /LPLWHG means using lesser amount of energy to (EESL’s Business Plan, 2016-2021). produce a given amount of output. For Realizing the potential, Government of India example, a light-emitting diode (LED) light with BEE in the lead undertook a number of bulb requires less energy than an incandescent VFKHPHVIRUSURPRWLQJHQHUJ\HI¿FLHQF\LQ light bulb to produce the same amount of various sectors across India (Figure 9 and OLJKWLHLWLVPRUHHQHUJ\HI¿FLHQW Box 1). )LJXUH 6HFWRU6SHFL¿F(QHUJ\(I¿FLHQF\6FKHPHV Sector Specific Energy Efficiency Schemes /LJKWLQJ Industry Appliances Building Agriculture Municipal Large Standard Energy Agriculture Municipal MSME Conservation Demand Side Demand Side Industry /DEHO Building Code Management Management BEE SME PAT scheme UJALA BEE Star Rating Pumping Street Lighting programme GEF- UNIDO- BEE BEEP- EESL programme GEF- World Bank-BEE Green Building programme programmes %R[ (QHUJ\(I¿FLHQF\3URJUDPPHV $%ULHI Standards & Labelling Programme was launched in May, 2006 with an objective of providing the consumer an informed choice about the energy and cost saving potential of the labelled appliances/ equipment being sold commercially. This scheme entails laying down minimum energy performance norms for appliances/equipment, rating the energy performance on a scale of 1 to 5 with 5 being the PRVWHQHUJ\HI¿FLHQWRQH7KHSURJUDPPHFRYHUVDSSOLDQFHVRXWRIZKLFKDSSOLDQFHVDUHXQGHU the mandatory regime while the remaining 13 appliances are under the voluntary regime. Buildings: The Energy Conservation Building Code (ECBC), which sets minimum energy standards for new commercial buildings having a connected load of 100 KW or contract demand of 120 KVA or more, has been updated by BEE in 2017. BEE has also launched the Eco-Niwas Samhita (Part 1: Building Envelope) for residential buildings in December, 2018. Hotels have also been assigned mandatory targets for reducing their energy consumption. ȱ ȱ ȱȱěǰȱȱȱȱ¢ 171 Small & Medium Scale Industries:%((KDVLPSOHPHQWHGYDULRXVHQHUJ\HI¿FLHQF\GHPRQVWUDWLRQ projects in Textile, Bricks and Food Clusters. Post implementation energy audits have also been FRQGXFWHGLQWKHVHFOXVWHUVWRPHDVXUHWKHVDYLQJVDFKLHYHGE\LPSOHPHQWDWLRQRI(QHUJ\(I¿FLHQW Technologies. Transport:&RUSRUDWH$YHUDJH)XHO(I¿FLHQF\ &$)( QRUPVIRUSDVVHQJHUFDUVKDYHEHHQQRWL¿HG LQ$SULODQGWKHIXHOHI¿FLHQF\QRUPVIRU+HDY\'XW\9HKLFOHVIRU*URVV9HKLFOH:HLJKWJUHDWHU WKDQWRQQHVZHUHQRWL¿HGLQ$XJXVW)XUWKHUWKHIXHOHI¿FLHQF\QRUPVIRUOLJKWDQGPHGLXP FRPPHUFLDOYHKLFOHVDUHXQGHU¿QDOL]DWLRQDQGDUHEHLQJGHYHORSHGIRUWUDFWRUV%((LVDOVRZRUNLQJ towards faster adoption of electric vehicles and labelling program for vehicles. Demand Side Management (DSM) Programmes: BEE had launched its demand side management schemes covering the areas on Agriculture, Municipal, and Distribution Companies (DISCOMs). Under the Agriculture DSM (AgDSM), MoU has been signed between Indian Council of Agricultural 5HVHDUFK ,&$5 DQG %(( WR FUHDWH DZDUHQHVV IRU HQHUJ\ HI¿FLHQW SXPS VHWV DQG LWV RSHUDWLRQDO practices. In order to tap the energy savings potential of municipalities, BEE undertook nation-wide DZDUHQHVV SURJUDPPHV WR DGGUHVV HQHUJ\ HI¿FLHQF\ LQ ZDWHU SXPSLQJ VHZDJH SXPSLQJ VWUHHW lighting and public buildings across Urban Local Bodies (ULBs) in the country. BEE is carrying out preparation of DSM Action Plan, load research study of DISCOMs and capacity building of DISCOM RI¿FLDOVDFURVVWKHFRXQWU\ Industries: Perform Achieve and Trade (PAT) scheme has been launched for industries, in which mandatory targets are assigned to energy intensive industries for reducing the energy consumption. This is followed by conversion of excess energy savings into tradable instruments called Energy Saving &HUWL¿FDWHV (6&HUWV 3$7F\FOH,ZDVFRPSOHWHGLQZLWKDVDYLQJRI0LOOLRQ7RQQHRI2LO Equivalent (MTOE) and mitigation of about 30 million tonne of CO2 emission. Platform for trading of ESCerts was launched in September, 2017. In total, about 12.98 lakh ESCerts were traded at a cost of about `100 crore. PAT Cycle II commenced from April, 2016 in which 621 Designated Consumers '& ZHUHQRWL¿HG3$7VFKHPHLVEHLQJLPSOHPHQWHGRQDUROOLQJF\FOHEDVLVLHLQFOXVLRQRIQHZ VHFWRUV'&VHYHU\\HDU3$7F\FOH,,,ZDVQRWL¿HGZLWKHIIHFWIURP$SULODQG3$7F\FOH² ,9ZDVQRWL¿HGZLWKHIIHFWIURP$SULODQG3$7F\FOH9KDVFRPPHQFHGIURP$SULO Presently under PAT scheme, there are over 800 units participating and by 2020 it is expected that they will be able to achieve energy savings of about 20 MTOE and mitigation of about 70 million tonnes of CO2 emission. Lighting: With a view to tap the immense potential of LED lamps in reducing the energy requirement the Unnati Jyoti by Affordable LEDs for All (UJALA) programme was launched on 5th January, 2015 with a target to replace 770 million incandescent bulbs with LED bulbs. It was estimated that this would OHDGWRDQQXDOHQHUJ\VDYLQJVRIELOOLRQN:KE\0DUFK (QHUJ\(I¿FLHQF\6HUYLFHV/LPLWHG (EESL) has been designated as the implementing agency for this programme. LED bulbs under UJALA are distributed at subsidized rates through special counters set up at designated places in different cities across the country. For domestic lights, EESL service model enables domestic households to procure LED lights at an affordable price, with the option of paying the cost of procurement through easy instalments from their electricity bill. Outreach: The partnership and involvement of consumers is equally important, through behavioural FKDQJH LQ VXVWDLQLQJ HI¿FLHQW XVH RI HQHUJ\ DQG DYRLGDQFH RI ZDVWDJH $ FDPSDLJQ KDV EHHQ initiated to educate people for conserving energy in air-conditioning application by maintaining optimum temperature settings. BEE has already issued guidelines to large commercial establishment recommending temperature setting between 24° C-26° C without compromising comfort levels. These simple actions have the potential to save energy up to 20 per cent apart from rendering associated KHDOWKDQGHQYLURQPHQWEHQH¿WV 172 Economic Survey 2018-19 Volume 1 ,PSDFW RI (QHUJ\ (I¿FLHQF\ Figure 10: Energy Saved in 2017-18 Programmes 9.15 The implementation of various energy HI¿FLHQF\ SURJUDPPHV KDV ZLWQHVVHG exceptional performance in terms of reducing energy consumption thereby leading to lower greenhouse gas (GHG) emissions and cost savings. According to a BEE study, overall, this saving has resulted in total cost savings worth `53,000 crore (approximately) in 2017- 18 and contributed in reducing 108.28 Million Tonnes of CO2 emission. The contribution is largely from three major programmes – PAT, 8-$/$ DQG 6WDQGDUG /DEHOOLQJ )LJXUHV 10 and 11). The overall electricity savings GXH WR HQHUJ\ HI¿FLHQF\ PHDVXUHV LV per cent of the net electricity consumption in 2017-18, total thermal energy saved is 2.7 per cent of the net thermal energy consumption and 2.0 per cent of the net energy supply. 6RXUFH %XUHDXRI(QHUJ\(I¿FLHQF\ Note: BU-Billion Units Figure 11: Impact of Energy Savings in 2017-18 Reduction in CO2 emission (MtCO2) Monetary Savings (`Crore) 6RXUFH %XUHDXRI(QHUJ\(I¿FLHQF\ Energy Saving Potential of Various estimated for effective policy and programme interventions to realize the potential savings. Sectors The energy saving potential in various 9.16 Going forward, the sectors with possible demand sectors has been estimated by BEE HQHUJ\ VDYLQJV QHHG WR EH LGHQWL¿HG DQG using three scenarios (Table 1). ȱ ȱ ȱȱěǰȱȱȱȱ¢ 173 Table 1: Three Scenarios for estimating energy saving potential Assumptions by 2031 Technological Policy/program/ Change in Fuel mix Improvement & scheme initiatives penetration Scenario 1: Least effort No technological No further Current fuel mix change and no new implementation of technology penetration Programs Scenario 2: Moderate Moderate/Business Successful achievement Moderate/BAU fuel effort as Usual (BAU) of program targets mix shift from fossil technological fuel to Renewable improvements and Energy(RE)/electricity technology penetration based consumption as per govt./other agencies target Scenario 3: Aggressive Aggressive Over achievement of Aggressive fuel mix effort technological program targets shift towards RE based improvements and consumption in sector penetration over govt./ (if applicable) other agencies target 9.17 In light of the above scenarios, the table sector stands out with maximum energy below shows India’s energy saving potential saving potential (Table 2). in various demand sectors in 2031. Industrial 7DEOH ,QGLD¶VHQHUJ\VDYLQJSRWHQWLDOLQYDULRXVGHPDQGVHFWRUVLQ Sector Energy Consumption Moderate Savings- Aspirational Savings - – 2031 (Least Effort) 2031 2031 Mtoe Mtoe per cent Mtoe per cent Agriculture 64.4 5.7 9 9.9 15 Transport 232.9 15.8 7 23.8 10 Domestic 98.6 12.1 12 15.1 15 Commercial 29.5 4.9 17 6.4 22 Municipal 8.0 0.9 12 1.5 19 Industries 443.4 47.5 11 72.3 16 Total (mtoe) 10 15 Total (TWh) 10198 1010 10 1500 15 6RXUFH %XUHDXRI(QHUJ\(I¿FLHQF\ Note: TWh=Terawatt-hour 174 Economic Survey 2018-19 Volume 1 It is vividly clear that there is still great shifting to non-fossil fuel sources for potential to be realized in terms of energy electricity generation. Despite this, coal HI¿FLHQF\ LQ YDULRXV GHPDQG VHFWRUV $V D remains the largest source of electricity country committed to implement the Paris generation mix globally, with 38 per cent Agreement on Climate Change and SDGs, market share in 2018 (IEA, 2019). In terms of it is necessary to prepare and plan strategies generation capacity, at the end of 2018, global to unlock the potential to achieve the energy renewable generation capacity amounted to HI¿FLHQF\ SRWHQWLDO ZKLFK VKRXOG LQFOXGH 2351 GW that constituted around a third of favourable regulatory structures, strengthened total installed electricity capacity (IRENA, LQVWLWXWLRQDOIUDPHZRUNLQQRYDWLYH¿QDQFLDO 2019). A look at India’s installed capacity for VWUXFWXUHV IRU DIIRUGDEOH ¿QDQFLQJ XVH the last decade can tell us the importance that of technology, and increased stakeholder thermal energy has played in meeting India’s engagement. The existing approaches must electricity needs (Figure 12). be reviewed and a new portfolio of strategies SODQQHG WR VWUHQJWKHQ HQHUJ\ HI¿FLHQF\ 9.19 Almost 60 per cent of India's installed across all sectors in the country. capacity is in thermal power out of which the main component is the coal based SUSTAINABILITY OF ENERGY thermal power plants. India’s Nationally GENERATION Determined Contribution (NDC) under 9.18 Globally, focus has been gradually the Paris Agreement states that India will Figure 12: Share of various energy sources in total Installed capacity in India 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% ϮϬϬϳ ϮϬϬϴ ϮϬϬϵ ϮϬϭϬ ϮϬϭϭ ϮϬϭϮ ϮϬϭϯ ϮϬϭϰ ϮϬϭϱ ϮϬϭϲ ϮϬϭϳ ϮϬϭϴ ϮϬϭϵ Thermal Nuclear Hydro Renewables Source: Central Electricity Authority ȱ ȱ ȱȱěǰȱȱȱȱ¢ 175 achieve 40 per cent installed capacity of been arguably a transformation in the energy power from non-fossil fuels by 2030. While mix in India. Renewable energy sources are there has been tremendous increase in the a strategic national resource. Harnessing renewable energy capacity, fossil fuels, these resources is a part of India’s vision to especially coal, would continue to remain achieve social equity and energy transition an important source of energy. Further, it with energy security, a stronger economy, may not be advisable to effect a sudden and climate change mitigation. Union abandonment of coal based power plants Budget 2018-19 announced zero import without complete utilisation of their useful duty on components used in making solar lifetimes as it would lead to stranding of panels to give a boost to domestic solar panel manufacturers. Government has also assets that can have further adverse impact RIIHUHG YDULRXV ¿QDQFLDO LQFHQWLYHV IRU RII on the banking sector. Further, considering grid and decentralized renewable energy the intermittency of renewable power supply, systems and devices for meeting energy XQOHVVVXI¿FLHQWWHFKQRORJLFDOEUHDNWKURXJK needs for cooking, lighting and productive in energy storage happens in the near future, purposes. Thus, progressively declining it is unlikely that thermal power can be easily FRVWV LPSURYHG HI¿FLHQF\ DQG UHOLDELOLW\ replaced as the main source of energy for a have made renewable energy an attractive growing economy such as India. As such, option for meeting the energy needs in a base load power would have to be continued sustainable manner and helping India pursue to be provided by the thermal power plants. its low carbon development pathway. Given the sustainable energy objectives of 9.22 In this regard, India has been the country and the importance that coal undertaking one of the world’s largest based power plants entail, there is a need renewable energy expansion programmes in for building capacity for cleaner and more the world. The share of renewable energy HI¿FLHQW FRDO WHFKQRORJLHV $OVR LPSRUWDQW is progressively increasing in the Indian is the economy’s ability to generate greater electricity mix. The share of renewables output from available energy resources and (excluding hydro above 25 MW) in total its resource endowments. generation was around 10 per cent in the 9.20 A comprehensive energy policy should year 2018-19 compared to around 6 per take into consideration the economies cent in 2014-15. Now globally India stands th th of both coal and renewables as they are 4 in wind power, 5 in solar power and th interdependent. They are substitutes for 5 in renewable power installed capacity. each other as a source of energy but are The cumulative renewable power installed capacity (excluding hydro above 25 MW) FRPSOHPHQWDU\LQNHHSLQJWKHÀRZWRWKHJULG has more than doubled from 35 GW on 31 stable as coal generation represents a stable March 2014 to 78 GW on 31 March 2019. source of power while renewable energy may In addition, around 27 GW renewable power be variable. capacity is under installation and over 38 GW POTENTIAL OF RENEWABLE ENERGY under bidding. The target is to achieve an 9.21 While increasing access to energy is installed capacity of renewable based power important, it is also imperative that this comes of 175 GW by the year 2022. at much lower costs to the environment than 9.23 Government has been taking a slew of it has happened historically in advanced measures for the renewable energy sector. economies. As observed above, there has Traditionally, renewable energy has been 176 Economic Survey 2018-19 Volume 1 VXSSRUWHGWKURXJKYDULRXV¿VFDODQG¿QDQFLDO investment in renewable plants for upto the incentives. As the viability of renewable year 2022 (without transmission lines) would energy has improved drastically in the recent be about US$ 80 billion at today’s prices and times, tariff discovery is made through reverse an investment of around US$ 250 billion auctioning process. The solar tariff has come would be required for the period 2023-2030. down from around `18/kWh in 2010 to `2.44/ Thus, on an annualized basis, investment kWh in bids conducted in 2018. Similarly for opportunity for over US$ 30 billion per year wind power, the tariff has declined from an is expected to come up for the next decade average of `4.2/kWh in 2013-14 to `2.43/ and beyond. kWh in December 2017. Therefore, the wind 9.28 India has great potential for hydro power cumulative capacity has exceeded power generation. However, the utilisation of 35.6 GW. hydro power for meeting the power generation 9.24 Recent years have seen rapid growth needs have been limited. India has a hydro in installed solar generating capacity along potential of around 145320 MW, out of ZLWKVLJQL¿FDQWLPSURYHPHQWVLQWHFKQRORJ\ which 45400 MW have been utilised. As we price, and performance. Moreover, creative move towards greater energy requirements in business models have spurred investment in future, this source of energy, which is climate this sector. The initial target of the National friendly compared to traditional sources Solar Mission upto the year 2022, was to of power, can play a major role. However, install 20 GW solar power, which was further high tariffs have been a major obstacle. To enhanced to 100 GW in early 2015. The encourage the hydro sector, a new Hydro solar power installed capacity has increased Policy has been approved which includes around 1000 times from 25 MW as on 31 recognising large hydropower projects March, 2011 to 28.18 GW as on 31 March, as a renewable energy source. Further, 2019. tariff rationalization measures have been XQGHUWDNHQLQFOXGLQJSURYLGLQJÀH[LELOLW\WR 9.25 Priority has been accorded to seamless the developers to determine tariff by back integration of renewables into the grid and loading of tariff after increasing project better grid stability. In order to facilitate life to 40 years, increasing debt repayment smooth integration of increasing share of period to 18 years and introducing escalating renewables into the national grid, Green tariff of 2 per cent, budgetary support for Energy Corridor project continues to be IXQGLQJ ÀRRG PRGHUDWLRQ FRPSRQHQW RI in operation. Eleven Renewable Energy hydropower projects on a case-to-case basis, Management Centres are already at different and budgetary support for funding cost of stages of installation. enabling infrastructure i.e. roads and bridges 9.26 Kisan Urja Suraksha Evam Utthaan on a case-to-case basis. Mahabhiyan (KUSUM) scheme has been 9.29 While access to greater and cleaner ODXQFKHG IRU SURYLGLQJ ¿QDQFLDO DQG ZDWHU HQHUJ\UHVRXUFHVDQGLQFUHDVLQJWKHHI¿FLHQF\ security to farmers and for de-dieselization of energy resources are important, another of the farm sector. The scheme envisages area that has tremendous potential is electric around 2.75 million solar pumps and, on a mobility. pilot basis, 1 GW decentralized solar power plants in uncultivable lands of farmers to ELECTRIC VEHICLES (EVs) IN enhance income of farmers. INDIA 9.27 Broad estimates suggest that additional 9.30 With the world’s second largest ȱ ȱ ȱȱěǰȱȱȱȱ¢ 177 population and an area of 3.3 million square emerge as a hub for manufacturing of such NLORPHWHUV LW LV QRW GLI¿FXOW WR XQGHUVWDQG vehicles. With this view, a “National Electric how important the transport sector is for the Mobility Mission Plan 2020 (NEMMP)” was Indian economy. In India, transport sector conceived with an objective to achieve sales is the second largest contributor to CO2 of 60-70 lakh units of total EVs by 2020. In emissions after the industrial sector. Road 2015, the Faster Adoption and Manufacturing transport accounts for around 90 per cent of of Electric vehicles (FAME) scheme was the total emissions in the transport sector in launched to fast-track the goals of NEMMP ,QGLD 02() && ,QFUHDVLQJYHKLFOH with an outlay of `795 crore. The initial outlay ownership, as is evident from Figure 13, has was for a period of 2 years, commencing also meant that the demand for the fossil fuels from 1 April 2015, which was extended up for these vehicles has also increased. Given to 31 March, 2019. FAME India Phase II has the large import dependence of the country been launched, with effect from 1 April 2019, for petroleum products, it is imperative that with a total outlay of `10,000 Crore over the there be a shift of focus to alternative fuels to period of three years. Emphasis in this phase support our mobility in a sustainable manner. LVRQHOHFWUL¿FDWLRQRISXEOLFWUDQVSRUWDWLRQ 9.31 While the government has given an 9.32 In addition to the initiatives of impetus to the promotion of quality public the Government of India, several states, transport, especially through the introduction including Karnataka, Kerala, Telangana, of metro projects in various major cities, a Maharashtra and Andhra Pradesh, Uttar shift to electric mobility in road transport can Pradesh, Uttarakhand, have drafted EV OHDG WR EHQH¿FLDO UHVXOWV ,QGLD FRXOG DOVR policies to complement the national policy Figure 13: Domestic passenger vehicle sales in India 3250000 3000000 Sales 2750000 2500000 Ŧ Ŧ Ŧ Ŧ Ŧ Ŧ Years Source: Data from SIAM Note: Only Aug 2018 -March 2019 data is available for 2018-19 178 Economic Survey 2018-19 Volume 1 DQG DGGUHVV VWDWHVSHFL¿F QHHGV $QGKUD China accounted for a major part of these Pradesh has set a target of 10 lakh EVs by sales. Charging infrastructure has also kept 2024 while Kerala has set a target of 10 lakh pace with almost 30 lakh chargers at homes EVs by 2022. Maharashtra has announced its and workplaces and about 430,151 publicly draft EV Policy, 2018 to increase the number accessible chargers worldwide in 2017. of registered EVs in the state to 5 lakh. However, only around 25 per cent of these Telangana has targeted 100 per cent electric were fast chargers (IEA-2, 2018). buses for intracity, intercity and interstate 9.34 In India, electric two wheelers have transport for its state transport corporation. been the major part of EV sales with sales Uttarakhand’s EV policy has focused on of around 54,800 in 2018 (NITI Aayog, the manufacturing of EVs in the state with 2019). Compared to this, sales of electric cars incentives for manufacturers of EVs in the have been only around 2000 in 2017 (IEA- MSME sector (NITI Aayog, 2019). 2, 2018). Indian market share of electric 9.33 Globally, the sales of electric cars have cars is a meagre 0.06 per cent. According been rising at a fast pace from just over 2000 to the Society of Manufacturers of Electric units being sold in 2008 to over 10 lakh in Vehicles (SMEV), Uttar Pradesh topped the 2017. More than half of the sales were in China list of the states with highest EV sales of (IEA-2, 2018). The market share of electric around 6878 units in 2017-18, followed by cars is around 2 per cent in China while it is Haryana at 6,307 units and Gujarat at 6,010 DURXQG SHUFHQWLQ1RUZD\(OHFWUL¿FDWLRQ electric vehicles. Maharashtra reported sales of two-wheelers and buses has also picked up of around 4,865 EV units, while West Bengal pace in the recent years. In 2017, global sales FDPHLQ¿IWKZLWKVDOHVRIXQLWV)LJXUH of electric buses were about 1 lakh and sales 14 showcases the sales of electric cars which of two-wheelers are estimated at 3 crore. includes Battery Electric Vehicles (BEVs) and Figure 14: Electric Car (BEV and PHEV) sales in India 2000 1500 Sales 1000 500 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Year Source: Data from Global EV Outlook 2018 ȱ ȱ ȱȱěǰȱȱȱȱ¢ 179 Plug-in Hybrid Electric Vehicles (PHEVs) in through producing or importing NEVs or India. through the purchase of NEV credits from 9.35 Various incentives have been provided other manufacturers who have excess credits. to the buyers and users of electric vehicles Additionally, the subsidy program- with a in different countries to encourage their consistent focus on the investment intensity uptake. Norway, which has the highest of the charging and battery infrastructure - share of electric cars has provided generous seems to have driven the increasing Chinese incentives to EV buyers and disincentives market share in EVs. to the use of conventional vehicles. These 9.36 Given the various incentives given in include exemption from VAT, tax incentives the different countries, it is only natural to on import and purchase of EVs, waiver of ask whether these incentives have had any toll and ferry fees, free parking, etc. Closer impact on the uptake of electric vehicles. home, Chinese government has issued a new While a number of studies seem to indicate energy vehicle (NEV) credit mandate that that incentives have been effective, some sets a minimum requirement regarding the studies have indicated their ineffectiveness production of new energy vehicles (PHEVs, and have shown that charging infrastructure %(9V DQG )&(9V ZLWK VRPH ÀH[LELOLW\ is a more important determinant of EV uptake offered through a credit trading mechanism (Hardman et al., 2017). Figure 15 presents the in the car industry. Every manufacturer is density of publicly accessible chargers and required to earn minimum NEV credits either the corresponding market shares of electric Figure 15: Market share of electric cars and charger density in selected countries in 2017 Market share in 2017 (per cent) Market Number of publicly accessible fast and slow chargers per 1000 population in 2017 Source: Data from Global EV Outlook 2018 180 Economic Survey 2018-19 Volume 1 cars for some countries for which the data was be in the form of electric vehicles. According available. Fitting a line through the scatter, we to NITI Aayog (2019), if India reaches an EV ¿QGWKDWWKHPDUNHWVKDUHRI(9VLVSRVLWLYHO\ sales penetration of 30 per cent for private related to the availability of chargers and a cars, 70 per cent for commercial cars, 40 per larger availability of chargers corresponds to cent for buses, and 80 per cent for 2 and 3 a greater adoption of EVs. The market share wheelers by 2030, a saving of 846 million of EVs increases with increasing availability tons of net CO2 emissions and oil savings of of charging infrastructure. This is primarily 474 MTOE can be achieved. It also provides due to the limited driving range of batteries in us an opportunity to grow as a manufacturing the EVs. It, therefore, becomes important that hub for EVs, provided policies are supportive. adequate charging stations are made available While various incentives have been provided throughout the road networks. In India, the by the government and new policies are limited availability of charging infrastructure being implemented, it is important that seems to be a major impediment to increased these policies not only focus on reducing the adoption of EVs. upfront costs of owning an EV but also reduce 9.37 Another major impediment is that of the overall lifetime costs of ownership. time taken for completely charging EVs, WAY FORWARD compared to conventional vehicles. Even fast 9.39 Energy is the mainstay of the chargers can take around half an hour to charge development process of any economy. The an electric car while slow chargers could take priority for the government is ensuring access even 8 hours. It is, therefore, an important to sustainable and clean energy sources. Given policy issue to come up with universal the close link between energy consumption charging standards for the country as a whole and various social indicators, this attains even to enable increased investment in creation of greater importance. Compared to the income such infrastructure. It is equally important dimension of poverty, its energy dimension to provide information on public chargers is even more severe. Government of India to the users of EVs through online maps and initiated a big step in the form of the Pradhan other means such as physical signage. This Mantri Ujjwala Yojana, providing access to will encourage increased ease of adoption of around 7 crore households under the scheme. EVs. Also, since the battery is the heart of The task now is to ensure that households any EV, development of appropriate battery with LPG continue to use the clean fuel for WHFKQRORJLHVWKDWFDQIXQFWLRQHI¿FLHQWO\LQ the high temperature conditions in India need FRRNLQJSXUSRVHVWKURXJKFRQWLQXHGUH¿OOLQJ to be given utmost importance (NITI Aayog, ,Q WHUPV RI KRXVHKROG HOHFWUL¿FDWLRQ ,QGLD has achieved almost 100 per cent with 2018). HOHFWUL¿FDWLRQ RI FURUH KRXVHKROGV 9.38 The country’s economy is growing Not only does India have to meet the energy and would continue to grow at a rapid pace needs of the future, it has to do so in a more in the coming years. This presents a great sustainable manner. While renewable energy opportunity for the automobile industry as capacity has been expanded manifold, fossil the demand for automobiles would only fuel based energy is likely to continue to be increase. Given the commitments that India an important source of power. has made on the climate front as a nation and the increasing awareness of the consumers on 2YHUDOOHQHUJ\HI¿FLHQF\LVDVWUDWHJ\ that can lead to a win-win situation through environmental aspects, it is likely that larger better utilisation of energy resources. Future and larger share of automobile sector would policy direction should orient itself to ȱ ȱ ȱȱěǰȱȱȱȱ¢ 181 HQKDQFHG HQHUJ\ HI¿FLHQF\ SURJUDPPHV LQ the Detroit of EVs in the future. Appropriate different sectors of the economy as well as policy measures are needed to lower the technological solutions to better utilise the overall lifetime ownership costs of EVs natural resource endowments of the country for greater prosperity. EVs hold enormous and make them an attractive alternative to potential for India not only because it is conventional vehicles for all consumers. environment friendly but also because India 9.41 To conclude, India’s economic future can emerge as a hub of manufacturing of EVs generating employment and growth and prosperity is dependent on her ability to opportunities. It may not be unrealistic to provide affordable, reliable and sustainable visualise one of the Indian cities emerging as energy to all her citizens. CHAPTER AT A GLANCE ¾ India with a per-capita energy consumption of about one-third of the global average will have to increase its per capita energy consumption at least 2.5 times to increase its real per capita GDP by $5000 per capita, in 2010 prices, to enter the upper-middle income group. ¾ Additionally, if India has to reach the HDI level of 0.8, which corresponds to high human development, it has to quadruple its per capita energy consumption. ¾ India has set ambitious targets for renewable energy and has been undertaking one of the world’s largest renewable energy expansion programmes in the world. Now, globally India stands 4th in wind power, 5th in solar power and 5th in renewable power installed capacity. ¾ (QHUJ\HI¿FLHQF\SURJUDPPHVLQ,QGLDKDYHJHQHUDWHGFRVWVDYLQJVZRUWKPRUHWKDQ`50,000 crore and a reduction in about 11 crore tonnes of CO2 emission. ¾ The share of renewables in total electricity generation has increased from 6 per cent in 2014-15 to 10 per cent in 2018-19 but thermal power still plays a dominant role at 60 per cent share. ¾ The market share of electric vehicles is only 0.06 per cent in India when compared to 2 per cent in China and 39 per cent in Norway. Access to fast charging facilities must be fostered to increase the market share of electric vehicles. REFERENCES ". Retrieved from International Energy Agency: https://www.iea.org/weo2018/ Ghaniet. al (2014). Ejaz Ghani, Arti Grover Goswami and William R. Kerr: "6SDWLDO (QHUJ\ (I¿FLHQF\ 6HUYLFHV /LPLWHG '\QDPLFV RI (OHFWULFLW\ 8VDJH LQ ,QGLD "(QHUJ\(I¿FLHQF\0DUNHW,Q,QGLD35*)(( 3ROLF\ 5HVHDUFK :RUNLQJ 3DSHU ", 6XFFHVVIXO (6&2 0RGHO": https://www. World Bank Group aeee.in/wp-content/uploads/2018/04/EESL_ Ashish-Jindal.pdf Hardman et. al. (2017). "The effectiveness RI ¿QDQFLDO SXUFKDVH LQFHQWLYHV IRU EDWWHU\ IEA-2. (2018). "*OREDO (9 2XWORRN". HOHFWULFYHKLFOHV±$UHYLHZRIWKHHYLGHQFH Retrieved from International Energy 5HQHZDEOHDQG6XVWDLQDEOH(QHUJ\" Reviews Agency: https://webstore.iea.org/global-ev- Vol 80, pages 1100-1111. outlook-2018 IEA-1. (2018). ":RUOG (QHUJ\ 2XWORRN IEA (2019). "*OREDO(QHUJ\DQG&26WDWXV 182 Economic Survey 2018-19 Volume 1 5HSRUW": www.iea.org/geco/electricity/ Government of India. IRENA (2019). ",5(1$ $QQXDO 5HQHZDEOH 1,7,$D\RJ 1,7,$D\RJ :RUOG &DSDFLW\6WDWLVWLFV " Energy Council. "=HUR (PLVVLRQ 9HKLFOHV " 0R() && 6HFRQG%LHQQLDO8SGDWH =(9V 7RZDUGVD3ROLF\)UDPHZRUN 5HSRUW WR WKH 8QLWHG 1DWLRQV )UDPHZRUN NITI Aayog. (2019). "1,7,$D\RJ 5RFN\ &RQYHQWLRQ RQ &OLPDWH &KDQJH". Ministry 0RXQWDLQ ,QVWLWXWH ,QGLD¶VHOHFWULF PRELOLW\ of Environment, Forest and Climate Change, WUDQVIRUPDWLRQ " Effective Use of Technology for Welfare Schemes – Case of 10 MGNREGS CHAPTER mn~;esu fg flè;fUr dk;kZf.k u euksjFkS%A Work gets accomplished by putting in effort, and certainly not by mere wishful thinking While MGNREGS was made effective from 2006, the streamlining of the programme RFFXUUHGLQZKHQWKHJRYHUQPHQWKDUQHVVHGWKHEHQH¿WVRIWHFKQRORJ\7KLVLQWHUDOLD LQFOXGHGWKHLPSOHPHQWDWLRQRI'LUHFW%HQH¿W7UDQVIHU '%7 DQGOLQNLQJLW$DGKDUOLQNHG 3D\PHQWV $/3 ,WOHYHUDJHGWKH-DQ'KDQ$DGKDDUDQG0RELOH -$0 WULQLW\WRFUHGLW ZDJHVGLUHFWO\LQWR0*15(*6ZRUNHUV¶EDQNDFFRXQWVWKHUHE\UHGXFLQJVFRSHIRUGHOD\VLQ SD\PHQW7KLVFKDSWHUKLJKOLJKWVWKHEHQH¿WVRIFDUHIXODQGHIIHFWLYHWDUJHWLQJRIJRYHUQPHQW SURJUDPPHVE\GHPRQVWUDWLQJWKDW'%7HQDEOHG0*15(*6KDVLQGHHGKHOSHGWRDOOHYLDWH GLVWUHVVRIZRUNHUV3RVW'%7SD\PHQWGHOD\VLQWKHSD\PHQWRIZDJHVXQGHU0*15(*6KDV UHGXFHGVLJQL¿FDQWO\WKHUHE\SURYLGLQJOLYHOLKRRGVHFXULW\WRSHRSOHLQGLVWUHVV%RWKGHPDQG DQGVXSSO\RIZRUNXQGHU0*15(*6LQFUHDVHGHVSHFLDOO\LQGLVWULFWVVXIIHULQJIURPGLVWUHVV 7KHLQFUHDVHLQWKHQXPEHURI¿OOHGPXVWHUUROOVDOVRLPSOLHVWKDWGLVWUHVVHGZRUNHUVLQGHHG WXUQXSPRUHIUHTXHQWO\IRUZRUN7KHLPSRUWDQFHRI$/3HQDEOHG0*15(*6LQDOOHYLDWLQJ GLVWUHVVLVSDUWLFXODUO\SURQRXQFHGIRUWKHYXOQHUDEOHVHFWLRQVRIVRFLHW\LQFOXGLQJZRPHQ SHUVRQVZLWKGLVDELOLW\6FKHGXOHG&DVWHVDQG6FKHGXOHG7ULEHV$VGDWDRQGHPDQGIRUZRUN XQGHU0*15(*6LVDYDLODEOHDOPRVWUHDOWLPHLWFDQEHGHYHORSHGLQWRDUHDOWLPHPHDVXUH WRWUDFNGLVWUHVVDWWKHOHYHORIDGLVWULFWSDQFKD\DW7KLVHYLGHQFHKLJKOLJKWVWKDWVNLOIXOXVH RIWHFKQRORJ\ZKHQFRPELQHGZLWKDQXQZDYHULQJFRPPLWPHQWWRPRQLWRULQJHIIHFWLYHQHVV RIJRYHUQPHQWVFKHPHVFDQPDNHDVXEVWDQWLDOGLIIHUHQFHRQWKHJURXQG INTRODUCTION workers were employed during daytime to 10.1 Today’s workforce programs, which are construct the Imambara. Others were hired at popularly used across the world to alleviate night to demolish part of what was constructed distress and poverty, owe their intellectual during the day time. The Mahatma Gandhi origins to “food for work” programs during National Rural Employment Guarantee Act the rule of Chandragupta Maurya (320 BC (MGNREGA), which was enacted through to 298 BC). In fact, as acknowledged by an Act of Parliament in 2005, represents 'UHNPHLHU ³IRRG IRU ZRUN´ LV ¿UVW the modern version of such “food for work” referred in Kautilya’s Arthashastra. Much programmes in India. later in 1784, but more than a century before Keynes (1909), Nawab Asaf-ud-Daula started 10.2 The programme was operationalized a “food for work” programme to help the through the Mahatma Gandhi National famine-stricken people of Lucknow. Some Rural Employment Guarantee Scheme 184 Economic Survey 2018-19 Volume 1 (MGNREGS) with effect from February of wages is critical. To conceptually 2, 2006. The programme was initiated to understand the importance of the same, ameliorate rural distress by providing at least consider two farmers, A and B. Suppose for 100 days of manual labour at minimum wages the purpose of the illustration, MGNREGS to anyone who seeks employment under ZDJHV DUH ¿[HG DW `100 per day of work. the program. Creation of productive assets Due to bad monsoon, A’s crop failed and in for prescribed quality and durability, social order to survive, he seeks work for 100 days inclusion, gender parity, social security and under MGNREGS and receives `10,000 but equitable growth form the founding pillars of after a delay of several months. Thus, A’s the programme. FDVK LQÀRZ GXULQJ KLV WLPH RI HFRQRPLF 10.3 The Act states that “the objective of adversity, is actually zero. Anticipating such the legislation is to enhance the livelihood delay, farmer A would prefer to work in a security of poor households in rural areas”. place where the wages might be lower than For the rural poor, even slightest economic MGNREGS but are disbursed on time. This distress can be a threat to their livelihood. choice enables him to generate the liquidity The programme was, therefore, designed that he desperately needs in distress. But it such that rural poor could turn to it in times is evident that the programme did not meet of need and that it could mitigate distress by his needs as the wage payments were not providing adequate work in times of distress. timely. In contrast to farmer A, say farmer B This chapter shows that the effective use KDGDQRUPDOKDUYHVW7RHDUQH[WUDPRQH\ of technology enhanced the effectiveness, B also enrols for 100 days of work under design and targeting of the programme. MGNREGS. He also receives `10,000 MGNREGS wages after a delay of several ,Q WKH ¿UVW GHFDGH RI LWV H[LVWHQFH months. However, as farmer B is not under MGNREGS had been saddled with several duress, he would choose to avail the higher LQHI¿FLHQFLHV LQFOXGLQJ ZLGHVSUHDG wages under the programme. corruption, political interference, leakage, DQG VLJQL¿FDQW GHOD\ LQ ZDJH SD\PHQWV 10.6 In contrast, in a regime where the (Niehaus and Sukhtankar, 2013a,b; MGNREGS payments are made on time, the Ravallion, 2012; Agarwal et al., 2016). The distressed farmer AZLOOGH¿QLWHO\FKRRVHWR programme was reviewed in 2015 and the enrol for work under MGNREGS instead government initiated major reforms using of seeking alternative avenues to alleviate technology and emphasised on bringing in his distress. If farmers A and B work under more transparency and accountability, robust MGNREGS, both receive their wages in a planning and creation of durable productive timely and systematic manner. Working for assets. The scheme was also integrated 0*15(*6EHFRPHVEHQH¿FLDOIRUIDUPHUA with the Aadhaar Linked Payments (ALP) as it provides him with the necessary liquidity system. The ALP leveraged the Jan Dhan, for survival when he needs it most. Thus, Aadhaar and Mobile (JAM) trinity to provide XQGHUHI¿FLHQWWDUJHWLQJLQFUHPHQWDOGHPDQG 'LUHFW %HQH¿W 7UDQVIHUV '%7 WR WKH for MGNREGS work would be greater from EHQH¿FLDU\ DFFRXQWV$V D UHVXOW WKH ZDJH distressed workers than from non-distressed payment system underlying MGNREGS was workers. streamlined, thereby reducing the scope for 7KH VLPSOH H[DPSOH DERYH LOOXVWUDWHV delays in payment (Agarwal et al., 2019). how: (i) delays in payments can materially 10.5 For a workforce programme to drive genuinely distressed farmers away effectively alleviate distress, timely payment from MGNREGS; and (ii) improvements ěȱȱȱ¢ȱȱȱȱȮȱȱȱ 185 in the targeting of MGNREGS to genuine 10.9 Various government initiatives have EHQH¿FLDULHV FDQ LQFUHDVH WKH GHPDQG IRU facilitated overcoming these structural work from distressed workers, thereby constraints. By December, 2015, the total effectively realising the objective of the number of Aadhaar enrolments in the country programme. A person undergoing economic H[FHHGHGFURUHWKHUHE\FRYHULQJDPDMRU distress needs immediate and certain portion of the adult population. Linking the liquidity. Working for uncertain promised Aadhaar Number to an active bank account wages, which are likely to be realised with was the key to implementing income transfers. a substantial lag, presents an unattractive In 2015, the Pradhan Mantri Jan DhanYojana proposition for a person in distress as delayed (PMJDY) was launched to ensure universal payments effectively imply zero wages in access to banking facilities with at least one adverse times. Consistent with this thesis, basic banking account for every household. WKLVFKDSWHUKLJKOLJKWVWKHEHQH¿WVRIFDUHIXO PMJDY addressed the issue of banking the targeting of Government programmes by use unbanked population in the country and of technology. Aadhaar provided a credible identity source to whoever wanted to open a bank account. USE OF TECHNOLOGY The bank accounts of people, including those IN IMPLEMENTATION OF opened under PMJDY, were linked to their MGNREGS unique Aadhaar numbers, which facilitated FURVVYHUL¿FDWLRQRILGHQWLWLHV%\H[SDQGLQJ 10.8 Before the implementation of DBT, the mobile payment options, the Government MGNREGS wages were transferred to the was able to ease the connectivity issue as SDQFKD\DW EDQN DFFRXQWV DQG D VLJQL¿FDQW people could get access to banking facilities number of workers had to collect wages in using their mobile phones. So, the JAM trinity FDVKIURPWKHJUDPSDQFKD\DWRI¿FH7KRXJK enabled the roll-out of DBT by streamlining attempts were made to implement a system of WKHYDOLGDWLRQYHUL¿FDWLRQRIEHQH¿FLDULHVDV DBT, two structural constraints limited these well as the process for release of funds. This attempts. As per a World Bank report1, until ensured timely transfer of funds to the right 2015, close to 50 per cent of the country’s EHQH¿FLDU\ DQG HQDEOHG HIIHFWLYH WDUJHWLQJ population did not have bank accounts. The under welfare schemes. proportion of unbanked population was National electronic Fund Management VLJQL¿FDQWO\KLJKHUIRUUXUDOSHRSOHZKRDUH System (NeFMS) the target group for MGNREGS. In rural ,QGLD EDQNLQJ SHQHWUDWLRQ ZDV H[WUHPHO\ 10.10 In order to streamline the system of low. According to the Reserve Bank of India IXQG ÀRZ DQG WR HQVXUH WLPHO\ SD\PHQW RI (RBI)2 ,total banking outlets in villages as of wages, NeFMS was implemented in the year March, 2014 was 1,15,350. This has increased 2016 (Figure 1). Under the system, the Central E\ DURXQG ¿YH WLPHV VLQFH WKHQ ZLWK WRWDO Government directly credits the wages of the banking outlets in villages at 5,69,547 as of MGNREGS workers, on a real time basis, to March, 2018. Second, verifying the identity DVSHFL¿FEDQNDFFRXQWRSHQHGE\WKH6WDWH RI JHQXLQH EHQH¿FLDULHV DQG WUDQVIHUULQJ *RYHUQPHQWV $OO WKH 3URJUDPPH 2I¿FHUV wages directly into their bank accounts posed debit this state-level single account for problems. authorization of wage payment. Currently, 1 KWWS GDWDWRSLFVZRUOGEDQNRUJ¿QDQFLDOLQFOXVLRQFRXQWU\LQGLD 2 RBI annual reports for years 2014 and 2018 186 Economic Survey 2018-19 Volume 1 NeFMS is implemented in 24 States and 1 )LJXUH )XQGÀRZ3UH'%7DQG3RVW Union Territory wherein payment of wages '%7 is being credited directly to the bank/post RI¿FH DFFRXQWV RI 0*15(*6 ZRUNHUV 3UH'%7XQGHUH)06 by the Central Government. This initiated the implementation of DBT in the Scheme. As a result of this initiative, the e-payment under MGNREGS has increased from 77.34 per cent in FY 2014-15 to 99 per cent in FY 2018-19. Aadhar Linked Payments (ALP) 10.11 In 2015, the Government introduced 3RVW'%7XQGHU1H)06 ALP in MGNREGS in 300 districts that had a high banking penetration. Remaining districts were covered under ALP in 2016. Conceptually, ALP could speed up the wage payment cycle in the following two ways. First, due to stringent biometric requirements, an Aadhaar linked account is unlikely to EHORQJ WR D µJKRVW¶ EHQH¿FLDU\ +HQFH *RYHUQPHQW RI¿FLDOV UHTXLUH OHVV WLPH WR verify and audit claims from such accounts. Second, the Central Government, which Source: Ministry of Rural Development ultimately foots the bill for the program, can numbers of 10.16 crore workers (87.51 transfer wages directly to the bank accounts per cent) have been collected and seeded. RI WKH EHQH¿FLDULHV WKHUHE\ FXWWLQJ WKH Almost 55.05 per cent of all the payments bureaucratic red tape. Out of the 11.61 crore under MGNREGS are through Aadhaar active workers under MGNREGS, Aadhaar Based Payment Systems (ABPS). As shown %R[ 3HUFHLYHG%HQH¿WVRI'%7 x Providing timely release of payments. x (QVXULQJFRUUHFWIXQGVDUHWUDQVIHUUHGWRFRUUHFWEHQH¿FLDULHVUHGXFLQJFRUUXSWLRQ OHDNDJHVLQ system. x Reduction in delays in system for funds transfer (improving programme performance and LQVWLOOLQJWUXVWDQGFRQ¿GHQFHLQV\VWHPE\EHQH¿FLDULHV x Strong focus on security, tracking and monitoring of funds (through use of digital sign/signatures and convergence/interoperability), x Reconciliation process during payments between intermediate agencies involved in funds transfer (near real time tracking, accountability and transparency). x 6WUHDPOLQHWKHYHUL¿FDWLRQSURFHVVDQGHQGWRHQGIXQGVUHOHDVHSURFHVVLQDOOWKHEHQH¿FLDU\ oriented schemes ěȱȱȱ¢ȱȱȱȱȮȱȱȱ 187 )LJXUH &RYHUDJHRI0*15(*6E\'%7 ͷͲͲ ͳʹ ͶͲͲ ͺ ͵ͲͲ ʹͲͲ ('00 crore) Ͷ ͳͲͲ Total Fund Transferred under DBT under Transferred Fund Total Ͳ Ͳ data seeded with Aadhar (in crore) (in with Aadhar seededdata Total Number of Benficiaries whose Total Number of ʹͲͳͷǦͳ ʹͲͳǦͳ ʹͲͳǦͳͺ ʹͲͳͺǦͳͻ Source: DBT Bharat portal %R[ 6RPH,QLWLDWLYHVWRVWUHDPOLQH0*15(*6 NREGAsoftLVDORFDOODQJXDJHHQDEOHGZRUNÀRZEDVHGH*RYHUQDQFHV\VWHPWRFDSWXUHDOOWKH activities under MGNREGS at Center/State/District/Block and Panchayat level. It makes available all the documents like Muster Rolls, registration application register, job card/employment register/ muster roll issue register, muster roll receipt register that are inaccessible to the public otherwise. GeoMGNREGA uses space technology to develop a database of assets created under MGNREGS using technological interventions like mobile based photo geo-tagging and a GIS based information system for online recording and monitoring. As on 10th June 2019, it has been implemented in 31 States and UTs. A total of 3.58 crore projects out of 4.44 crore completed projects are already geo- tagged. The entire data is in public domain and ensures transparency and public disclosure. Annual Master Circular: A master circular was issued in 2016, which consolidated 1039 advisories that had been issued since the inception of the programme. This Master Circular is amended and issued every year subsequently. This has helped to streamline the implementation of the programme and bringing in clarity. Tweaking the wage & material ratio: Durable and productive assets are essential for the sustainable livelihood of the poor people in rural areas. The 60:40 wage and material ratio was mandated at Gram Panchayat (GP) level. This often leads to non-productive assets being created simply because 60 per cent has to be spent on unskilled wage in a GP. To address this without diluting 60:40 principles, the wage and material ratio of 60:40 was allowed at the district level rather the GP level. (PSKDVLV RQ ,QGLYLGXDO %HQH¿FLDU\ 6FKHPHV $ YHU\ ODUJH QXPEHU RI ,QGLYLGXDO %HQH¿FLDU\ Schemes (IBS) like goat sheds, dairy sheds, 90-95 days’ work in Pradhan Mantri Awaas Yojana- Gramin (PMAY-G), wells, farm ponds, vermi-compost pits, water soak pits etc have been taken up RYHUWKHODVW¿YH\HDUV7KHHPSKDVLVRQ,%6KDVUHVXOWHGLQHQKDQFHGLQFRPHVRIWKHEHQH¿FLDULHV 188 Economic Survey 2018-19 Volume 1 DQGDOVRLPSURYHGWKHTXDOLW\RIDVVHWVDVWKHEHQH¿FLDULHVRIWHQSXWLQWKHLUVDYLQJVWRVXSSOHPHQW the contribution of MGNREGS. The share of IBS has increased from 21.4 per cent in 2014-15 to 66.1 per cent in 2018-19. Natural Resource Management (NRM) – Mission Water Conservation (MWC): Planned and systematic development of land to improve its productivity and harnessing of water through development of watersheds have become the central focus of MGNREGS work across the country. Guidelines were drawn up in partnership with the Ministry of Water Resources, River Development *DQJD5HMXYHQDWLRQDQG'HSDUWPHQWRI/DQG5HVRXUFHVWRIRFXVRQWKHGDUNDQGJUH\UHJLRQV where the ground water was falling rapidly. It was made mandatory to spend 65 per cent of total 0*15(*6 H[SHQGLWXUH RQ 150 ZRUNV LGHQWL¿HG LQ ZDWHU VWUHVVHG EORFNV7HFKQRORJLFDO support from National Remote Sensing Centre, ISRO using GIS Technology (BHUVAN Portal)has HQDEOHGV\VWHPDWLFSODQQLQJPRQLWRULQJDQGH[HFXWLRQRIVWUXFWXUHVLPSDFWLQJVXUIDFHDQGJURXQG water resources. The major works taken up under NRM include check dams, trenches, ponds, UHQRYDWLRQ RI WUDGLWLRQDO ZDWHU ERGLHVWDQNV GXJ ZHOOV HWF 'XULQJ WKH ODVW ¿YH \HDUV ODNK KHFWDUHVRIODQGKDVEHQH¿WWHGWKURXJKWKHVHLQWHUYHQWLRQV 6XSSRUW IRU 'URXJKW 3URR¿QJ: In 2015-16, provision of additional employment of 50 days in drought affected areas over and above 100 days per household under MGNREGS was approved. 7KHPDMRUGURXJKWSURR¿QJZRUNVXQGHUWDNHQXQGHU0*15(*6DUHSODQWDWLRQVDIIRUHVWDWLRQODQG GHYHORSPHQWFKHFNGDPVZHOOVWUHQFKHVEXQGVDQGSRQGVSHUFRODWLRQWDQNV'XULQJWKHODVW¿YH \HDUVH[SHQGLWXUHRQVXFKSURMHFWVKDVPRUHWKDQGRXEOHGIURP`1753 crore to `4089 crore. Increased accountability: Various citizen centric mobile Apps like Gram Samvaad Mobile App and JanMnREGA (an asset tracking and feedback app for MGNREGS assets) have been developed, which aim to empower the rural citizens by providing direct access to information and improve accountability to the people. LQ)LJXUHWKHQXPEHURIEHQH¿FLDULHVDQG also higher in the post DBT years as compared the funds transferred under DBT under the to pre-DBT years indicating that employment Scheme has jumped manifold from 2015-16 generated is higher post implementation of to 2018-19. DBT. It is also heartening to note that more WKDQ SHUFHQWRIWKHSHUVRQGD\VEHQH¿WWKH ,03$&72)'%721 vulnerable sections. EFFECTIVENESS OF MGNREGS Timely Payment of Wages Coverage 10.13 DBT focused on directly transferring 10.12. Muster rolls are a form of an IXQGV LQWR WKH EHQH¿FLDU\ EDQN DFFRXQW DWWHQGDQFHUHJLVWHU+LJKHUQXPEHURI¿OOHG The NREGASoft monitors generation of muster rolls represent higher worker turnout payment of wages within 15 days. Sustained RQVLWH)LJXUHVKRZVWKDWWKH¿OOHGPXVWHU efforts and intensive engagement with all UROOVKDYHVKRZQDVLJQL¿FDQWLQFUHDVHDIWHU stakeholders has enabled vast improvements implementation of DBT indicating that more in the timely payment of wages. In 2014-15, people are reporting for work. Figure 4 shows 26.9 per cent of the payments were generated that total person days and total person days of within 15 days, which has now risen to 90.4 vulnerable sections (women, SCs and STs)3 is per cent in 2018-19 (Figure 5). 37KHVHJURXSVDUHQRWPXWXDOO\H[FOXVLYHDQGWKHUHIRUHGRXEOHFRXQWLQJLVSRVVLEOH ěȱȱȱ¢ȱȱȱȱȮȱȱȱ 189 Figure 3: Filled muster rolls under MGNREGS Source: Adapted from data from MGNREGA portal Figure 4: Share of Vulnerable Sections in Person Days under MGNREGS ϰϬϬϬϬϬ ϯϲϬϬϬϬ ϯϮϬϬϬϬ ϮϴϬϬϬϬ ϮϰϬϬϬϬ EƵŵďĞƌŽĨƉĞƌƐŽŶĚĂLJƐ ϮϬϬϬϬϬ ϮϬϭϭ ϮϬϭϮ ϮϬϭϯ ϮϬϭϰ ϮϬϭϱ ϮϬϭϲ ϮϬϭϳ ϮϬϭϴ dŽƚĂůƉĞƌƐŽŶĚĂLJƐ;ǀƵůŶĞƌĂďůĞƐĞĐƚŝŽŶƐͿ dŽƚĂůƉĞƌƐŽŶĂLJƐ;KƚŚĞƌƐͿ Source: Adapted from data from MGNREGA portal 10.14. In the pre-ALP period, the average the proportion of total amount of wage amount disbursed to bank accounts almost payments that were received with a lag doubles from `1.82 crore per block per year of more than 90 days before and after the in pre-ALP period to `3.98 crore per block implementation of ALP, it is found that the per year. This indicates that more funds delay in payments reduced by almost one- ÀRZHGWKURXJK'%7DIWHU$/3ZDVLQVWLWXWHG third from 35 per cent to less than 10 per ,I $/3 LPSURYHV WKH HI¿FLHQF\ RI WKH cent in the post-ALP period (Figure 6). SURJUDPPHWKHQWKHUHVKRXOGEHDVLJQL¿FDQW Thus, implementation of ALP has positively reduction in the delay in wage payments. LPSDFWHG WKH ÀRZ RI SD\PHQWV XQGHU WKH When a comparison is made between scheme. 190 Economic Survey 2018-19 Volume 1 Figure 5: Share of Payments done within 15 days under MGNREGS ͳͲͲ ͻͲǤͶ ͺͶǤͷ ͺͲ Ͳ Ͷ͵ǤͶ ͵Ǥͻ ȋΨȌ ͶͲ ʹǤͻ ʹͲ ͳͷ Ͳ ʹͲͳͶǦͳͷ ʹͲͳͷǦͳ ʹͲͳǦͳ ʹͲͳǦͳͺ ʹͲͳͺǦͳͻ Source: Ministry of Rural Development %R[ 'DWDDQGYDULDEOHVXVHG The data for MGNREGS is collected from the MGNREGS Public Data Portal for the period FY2012 to FY2017. Public data portal provides information on all the scheme’s variables from FY2012 onwards at various administrative subdivision levels. Delayed payments are available at a district level from FY2015 onwards. This data provides information on the number of transactions delayed at various intervals. As MGNREGS targets rural poor, whose primary occupation is agriculture, drought is used as a SUR[\IRUHFRQRPLFGLVWUHVV7KHSUHFLSLWDWLRQGDWDLVFROOHFWHGIURPWKH&OLPDWLF5HVHDUFK8QLW University of East Anglia. As the eastern-most longitudes in India span beyond the scope of the GDWDWKHEORFNVLQWKHVWXG\DUHOLPLWHGDW (7KHGDWDLVH[WUDFWHGDQGPDSSHGWRWKHEORFNVLQ the country. Since the climate data is available only till FY2017, the time period of the sample is UHVWULFWHGWR)<7KXVWKHVDPSOHH[DPLQLQJGURXJKWDVDSUR[\IRUGLVWUHVVXVHVGDWDZKHUH both MGNREGS and precipitation data are simultaneously available. The Schedule 1.5 of NSSO VXUYH\ RQ +RXVHKROG ([SHQGLWXUH RQ 6HUYLFHV DQG 'XUDEOH *RRGV 5RXQG KDV EHHQ XVHG WR REWDLQGDWDRQFRQVXPSWLRQH[SHQGLWXUHDWWKHGLVWULFWOHYHO7RGH¿QHEORFNVDIIHFWHGE\GURXJKW WKHGH¿QLWLRQSURYLGHGE\,QGLDQ0HWHRURORJLFDO'HSDUWPHQW ,0' LVXVHG ,0'GH¿QHVDQDUHD to be affected by drought if it receives less than 75 per cent of its normal precipitation. A panel that contains weather and MGNREGS information of each block for every year from FY2012 to FY2017 is constructed. It takes value 1 if annual rainfall in a block is less than 75 per cent of normal rainfall, RWKHUZLVHLWWDNHVYDOXH)RUWKHSXUSRVHRIWKHDQDO\VLVDSRVW$/3SHULRGLVDOVRGH¿QHGDVSHUWKH staggered implementation of ALP – 300 districts from FY2015 and remaining districts from FY2016. 7KHVXPPDU\VWDWLVWLFVRIWKHDQDO\VLVXQGHUWDNHQLVJLYHQLQWKHDSSHQGL[ Demand for MGNREGS Work GHOD\HG SD\PHQWV LW LV H[SHFWHG WKDW WKHUH 10.15 Given that there has been an increase will be an increase in demand for work under in amount disbursed to bank accounts post the programme in distressed areas (Agarwal implementation of ALP and a decline in et al., 2019). ěȱȱȱ¢ȱȱȱȱȮȱȱȱ 191 Figure 6: Delay in Payment of Wages under MGNREGS Sharp fall in Delay in Payments after ALP Proportion of Wages Delayed by 90+ days by Delayed Wages of Proportion 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 Pre-ALP period Post-ALP period Source: Survey Calculations. 10.16 Figure 7 displays the difference -in that effective implementation of MGNREGS -difference estimate of the effect of ALP on should increase demand for work in the persons demanding work. In the blocks not GLVWUHVVHG DUHDV WKLV ¿QGLQJ LV FRQVLVWHQW affected by drought, there is no effect of ALP with the thesis. The difference -in -difference on the number of persons demanding work. estimate, i.e. the before- after difference in the Crucially, however, in blocks that are affected blocks affected by drought versus the same by drought, the persons demanding work difference in blocks not affected by drought, increases by 20.7%. As we argued above HTXDOVDQGLVVWDWLVWLFDOO\VLJQL¿FDQW Figure 7: Demand for work under MGNREGS 16000 Demand for work in distress areas increases after ALP 14000 12000 10000 8000 per year 6000 4000 Number of persons per Block Block per of persons Number 2000 0 Drought-affected Districts Districts not affected by drought Pre-ALP Post-ALP Source: Survey Calculations. 192 Economic Survey 2018-19 Volume 1 10.17 It appears, therefore, that before the blocks affected by drought. implementation of ALP, the rural poor treated MGNREGS as an option to earn additional 10.19 It can be inferred that the increased income during good times rather than a shock state capacity to implement anti-poverty absorber during bad times. This actually programmes brought about by ALP can defeated the purpose of the programme. Post potentially bridge the demand supply gap implementation of ALP, there is a reversal in MGNREGS (Dutta et al., (2012)). With of trend, wherein an increase in demand reliable data, it is possible that the Central and for work under MGNREGS is observed in State governments will be able to effectively drought affected areas. The change post ALP monitor the implementation of MGNREGS implementation suggests that reduction in the DQG QXGJH WKH RI¿FLDOV WR SURYLGH MREV delay of payments has an immediate positive wherever and whenever they are needed the effect on the demand for work in distressed most. times. Work Done under MGNREGS Supply of MGNREGS work 10.20 Muster rolls are a form of 10.18 Figure 8 similarly displays the attendance register signed by workers. It acts difference-in-difference estimate for the as a preliminary check in the sense that, if effect of ALP on the supply of work under demand and supply of work increases, but MGNREGS. As in Figure 7, we observe WKHUHLVQRFKDQJHLQPXVWHUUROOV¿OOHGWKHQ very little change due to the implementation it means that there may be a false reporting of ALP on supply of work in the blocks not of numbers. Figure 9 shows that the muster affected by drought. In contrast, we observe a rolls increased by 19% in the blocks that 20% increase in the supply of work in blocks were not affected by drought, In contrast, that are affected by drought. This suggests muster rolls increased by an enormous 44% that the supply of work under MGNREGS in the blocks that were affected by drought. also responds to the increase in demand in the Thus, the evidence in Figure 9 shows that Figure 8: Supply of Work under MGNREGS 16000 Increase in Supply of Work in distress areas after ALP 14000 12000 10000 8000 per year 6000 4000 2000 Number of persons allotted work per Block per work allotted of persons Number 0 Drought-affected Districts Districts not affected by drought Pre-ALP Post-ALP Source: Survey Calculations. ěȱȱȱ¢ȱȱȱȱȮȱȱȱ 193 )LJXUH $PRXQWRIZRUNGRQHLQ0*15(*6 7RWDOPXVWHUUROOV¿OOHG 8000 Higher increase in filled muster rolls in distress areas after ALP 7000 6000 5000 4000 year 3000 2000 1000 Number of muster rolls filled per Block per Block per filled rolls of muster Number 0 Drought-affected Districts Districts not affected by drought Pre-ALP Post-ALP Source: Survey Calculations. the actual work done under MGNREGS also UHJUHVVLRQ DUH SORWWHG RQ WKH \D[LV 7KH LQFUHDVHGVLJQL¿FDQWO\LQEORFNVDIIHFWHGE\ [D[LV VKRZV WKH \HDU EHIRUH DQG DIWHU WKH drought due to the use of ALP. This increase implementation of ALP with 0 corresponding was more than double the increase in blocks to the year of implementation. We observe that were unaffected by drought. that absent ALP, there is either no change or a decline in total person days worked Impact on Vulnerable Sections of by vulnerable sections of the society. In the Society the pre-ALP period, represented to the left of year zero, the gap between person days 10.21 As economic shocks affect vulnerable worked by vulnerable sections of the society sections of society (women, persons with disability, SCs and STs) the most, there are ZDV LQVLJQL¿FDQW ,Q WKH SRVW $/3 SHULRG represented to the right of zero, there has concerns that they might not be able to adapt been a large increase in person days worked easily to the use of technology under DBT and by the vulnerable sections of the society in KHQFHPD\JHWH[FOXGHG .KHUD 7KHUH blocks affected by drought. This means that is also reason to believe that such people are after implementation of ALP, women, SC and more likely to be unaware of technological ST workforce increased under MGNREGS changes that occur in implementation of during times of economic distress (Figure 10). social welfare programs. If that is true, then there should not be any change in MGNREGS USE OF DATA ON CONSUMPTION work by these individuals in distressed areas TO PROXY DISTRESS post implementation of ALP (Agarwal et al., 2019). Figure 10 shows the differential 10.22 While drought is the primary source effects of ALP for vulnerable sections of of rural distress, there is a possibility of the society and others. The residuals after VRPH H[WUHPHO\ ORFDO XQREVHUYHG GLVWUHVV controlling for other determinants using a which is not related to drought such as pest 194 Economic Survey 2018-19 Volume 1 Figure 10: Total person days worked by vulnerable sections of the society in drought and QRQGURXJKWDIIHFWHGDUHDVEHIRUHDQGDIWHUWKHLPSOHPHQWDWLRQRI$/3 Source: Survey Calculations. attacks, disease outbreak, sale of land for to distinguish localized distress from large infrastructure development etc. Such distress crises because large-scale distress will be VKRXOGUHGXFHFRQVXPSWLRQH[SHQGLWXUHRIWKH common across neighbouring regions. Once local areas affected by it. Therefore, monthly ALP district-neighbour pairs and non-ALP FRQVXPSWLRQ H[SHQGLWXUH IURP 166 URXQG GLVWULFWQHLJKERXUSDLUVKDYHEHHQLGHQWL¿HG VXUYH\ GDWD FDQ EH XVHG DV D SUR[\ IRU the ratio of MGNREGS demand for each pair distress. The hypothesis is that there should is calculated. This ratio is called MGNREGS be an increase in demand for MGNREGS demand factor. Similarly, the ratio of work in areas with decline in consumption FRQVXPSWLRQ H[SHQGLWXUH IRU HDFK SDLU LV H[SHQGLWXUH 8VLQJ 166 GDWD WR LGHQWLI\ calculated. This ratio is called consumption unobservable distress, this test is performed IDFWRU $ QHJDWLYH UHODWLRQVKLS H[LVWV WRVHHLILPSURYHPHQWVLQ0*15(*6H[WHQG between MGNREGS demand factor and to all kinds of distress that may or may not be monthly consumption factor for each district as easily observable as drought. neighbour pair (Figure 11). This means that DUHDV ZLWK ORZ FRQVXPSWLRQ H[SHQGLWXUH 10.23 NSSO does not include block level have higher MGNREGS demand as LGHQWL¿FDWLRQ VR WKH GDWD LV DJJUHJDWHG DW compared to areas with higher consumption the district level. Since the survey data is H[SHQGLWXUH available only for FY2015, the sample is restricted to one year. To perform this test, 10.24 Therefore, for the purpose of this geographical neighbours of each district are test, consumption factor of less than one LGHQWL¿HG ¿UVW 7KHQ WKH GLVWULFW QHLJKERXU is used to identify distressed areas. It is pairs are divided such that ALP districts are evident from Table 1 that the MGNREGS matched with their ALP neighbours and non- demand factor is 1.45 for non-distressed ALP districts are matched with their non- districts and 1.56 in distressed districts in ALP neighbours in FY2015. This also helps the pre ALP period. Even though there is an ěȱȱȱ¢ȱȱȱȱȮȱȱȱ 195 Figure 11: Relationship between WAY FORWARD MGNREGS demand and consumption H[SHQGLWXUH 7KLV FKDSWHU KLJKOLJKWV WKH EHQH¿WV of using technology in welfare schemes to improve end to end governance, create a robust evidence based implementation framework in partnership with the States, streamline the processes, timely transfer of funds to implementing agencies and EHQH¿FLDULHVSOXJJLQJRIOHDNDJHVRSWLPXP utilization of public funds and improving overall performance (outputs/outcomes) RI WKH SURJUDPPHV ,W DOVR VLJQL¿FDQWO\ improves transparency and accountability DQG DERYH DOO HQVXULQJ WKDW ULJKW EHQH¿WV UHDFKWKHULJKWEHQH¿FLDU\DWWKHULJKWWLPH Source: NSS, Round 72, MGNREGA portal 10.26 DBT through Electronic Fund Management Systems in MGNREGS has increase in MGNREGS demand in districts VWUHDPOLQHG WKH IXQG ÀRZ SURFHVV DQG ZLWK OHVV FRQVXPSWLRQ H[SHQGLWXUH WKH helped in better targeting, reduction in delay increase is marginal. After implementation of ALP, in non-distressed districts, the LQ SD\PHQWV WR EHQH¿FLDULHV PLQLPL]HG MGNREGS demand factor is 1.18 i.e., the leakages and above all led to substantial saving MGNREGS demand for these districts is of funds. More importantly, it has enabled like their neighbours’. In distressed districts MGNREGS to be effective in alleviating it increases to 1.76. For distressed districts, distress of workers. Both demand and demand for MGNREGS work is almost twice supply of work under the Scheme increased, of their neighbours’ in the post ALP period. It especially in blocks suffering from distress is interesting to see that not only has the gap and from the vulnerable sections of society, between MGNREGS demand of distressed including women, persons with disability, and non-distressed areas widened but also SCs and STs. The increase in the number there is greater increase in the demand for RIPXVWHUUROOVWKDWZHUH¿OOHGDOVRLPSOLHV MGNREGS in distressed areas in the post that distressed workers indeed turn up more ALP period. frequently for work. The positive outcomes in MGNREGS are based on the revealed Table 1: Proportionate change in demand in preferenceRIWKHXOWLPDWHEHQH¿FLDULHVZKR DUHDVZLWKKLJKFRQVXPSWLRQH[SHQGLWXUHYV are not only at the bottom of the pyramid, DUHDVZLWKORZFRQVXPSWLRQH[SHQGLWXUHLQ i.e. the rural poor, but are also distressed. $/3DQGQRQ$/3GLVWULFWV As enrolment in the Scheme is voluntary, High Low EHQH¿FLDULHVKDYHVWURQJLQFHQWLYHVWRUHYHDO Consumption Consumption their preference by “voting with their feet” factor factor ZKHQ SURJUDPPH GHOLYHU\ LV LQHI¿FLHQW RU No ALP 1.45 1.56 HI¿FLHQW ALP 1.18 1.76 10.27 The above analysis has the following policy implications: 196 Economic Survey 2018-19 Volume 1 Probable Indicator of distress: Demand ([SDQVLRQRIµZRUNV¶XQGHU0*15(*6 for work under MGNREGS may be used to To further increase the effectiveness of the develop a real-time indicator of distress at the 6FKHPH WKH GH¿QLWLRQ RI µZRUNV¶ XQGHU granular district/ panchayat level. Distress at the Scheme should be regularly reviewed WKHOHYHORIDGLVWULFWRUSDQFKD\DWLVGLI¿FXOW and amended in light of the requirements. to identify in real-time using the current Inclusion of de-silting of canals and water datasets. While employment related NSS bodies in the Water Conservation Mission surveys are carried out once in 5-6 years, would enhance their storage capacity and district-level GDP is released irregularly. PLWLJDWHWKHIUHTXHQF\RIÀRRGV Both these datasets are released with lags. The NSSO surveys, though they are available 8SVNLOOLQJWKH0*15(*6:RUNHUV: The at the household level, are released after objective of the scheme to enhance livelihoods a gap of almost two years from the date for households can be reinforced by enabling of the surveys. As an adverse economic them to acquire suitable skills, which in turn VKRFN VLJQL¿FDQWO\ UHGXFHV FRQVXPSWLRQ will help them increase incomes and provide H[SHQGLWXUHRIWKHKRXVHKROGLWLVLPSRUWDQW horizontal and vertical mobility to them. The to provide assistance to the household at convergence of MGNREGS with Deen Dayal the right time. By utilizing information on Upadhyaya Grameen Kaushalya Yojana demand for work under MGNREGS and (DDU-GKY) and involvement with women correlating it with other real-time measures Self-Help Groups needs to be strengthened so of weather etc., that lead to rural distress, a that supply for skilled wage labour increases. dashboard (Figure 12) can be created which 7KHIRFXVQHHGVWREHRQWKHGLYHUVL¿FDWLRQ ÀDVKHVµDOHUWV¶IURPDUHDVXQGHUORFDOGLVWUHVV of the livelihoods with multiple sources of to enable policymakers to act in a timely income for them to come out of poverty. manner to alleviate such distress. As demand for MGNREGS work is also affected by the ([SDQGLQJ XVH RI -$0 WR RWKHU :HOIDUH governance capacity in the state, this indicator Schemes 7KH H[SHULHQFH RI LQFUHDVLQJ of real-time distress can be constructed after the effectiveness of MGNREGS by using accounting for the effect of the same. DBT and ALP lends immense credibility to adoption of this strategy in other programmes. The adoption of DBT in programmes which )LJXUH 'LVWUHVVPDSRI%LKDU LQYROYHWUDQVIHURIFDVKEHQH¿WV VFKRODUVKLSV or pensions) and price subsidies (such as WKRVHJLYHQIRUNHURVHQHOLTXH¿HGSHWUROHXP gas (LPG), public distribution system (PDS), fertilisers and other input subsidies needs WR EH VWUHQJWKHQHG WR PLQLPLVH H[FOXVLRQ and inclusion errors. This will make public VSHQGLQJ PRUH HI¿FLHQW DQG HIIHFWLYHO\ targeted. 8VH RI 'LJLWDO ,QIUDVWUXFWXUH IRU PLFUR EHQH¿WV: A huge digital infrastructure, linking Aadhaar, bank accounts and mobiles has been Source: Generated as a sample created and effectively used for MGNREGS Note: Orange areas indicate distress areas - the largest welfare programme. This can be XVHGWRH[SDQGWKHUHDFKRIWKHSURJUDPPHV ěȱȱȱ¢ȱȱȱȱȮȱȱȱ 197 through provision of micro-insurance, micro- ¿QDQFLDODQGHFRQRPLFLQFOXVLRQEHQH¿WWLQJ pensions and micro-credit to people in every the vulnerable and marginalized sections of corner of the country. Its wide use can lead to the society. CHAPTER AT A GLANCE ¾8VHRIWHFKQRORJ\LQVWUHDPOLQLQJ0*15(*6KDVKHOSHGLQFUHDVHLWVHI¿FDF\ ¾Adoption of NeFMS and DBT in MGNREGS helped to reduce delays in the payment of ZDJHVVLJQL¿FDQWO\ ¾Both demand and supply of work under MGNREGS increased, especially in districts suffering from distress. ¾The vulnerable sections of the society viz., women, SC and ST workforce increased under MGNREGS during times of economic distress. ¾Skilful use of technology when combined with an unwavering commitment to monitoring effectiveness of government schemes can make a substantial difference on the ground. REFERENCES Khera, Reetika. 2011. “The UID project and welfare schemes.” Economic and Political Agarwal, Sumit, Shashwat Alok, Yakshup :HHNO\, 38-43. Chopra, and Prasanna L Tantri. 2016. “Government Employment Guarantee, Labor Muralidharan, Karthik, Paul Niehaus, Supply and Firms’ Reaction: Evidence from and Sandip Sukhtankar. 2016. “Building the Largest Public Workfare Program in the state capacity: Evidence from biometric World.” Working Paper. smartcards in India.” American Economic Review, 106(10): 2895-2929. Agarwal, Sumit, Shradhey Prasad, Nishka Muralidharan, Karthik, Jishnu Das, Alaka Sharma, and Prasanna L Tantri. 2019. +ROODDQG$DNDVK0RKSDO³7KH¿VFDO “A Friend Indeed: Does The Use of Digital cost of weak governance: Evidence from Identity Make Welfare Programs Truly teacher absence in India.” -RXUQDORI3XEOLF Counter-Cyclical?” Working Paper. Economics, 145: 116-135. Drekmeier, Charles. 1962. “Kingship Niehaus, Paul, and Sandip Sukhtankar. and Community in Early India", Stanford 2013a. “Corruption dynamics: The golden 8QLYHUVLW\3UHVV. goose effect.” $PHULFDQ(FRQRPLF-RXUQDO Dutta, Puja, Rinku Murgai, Martin Ravallion, (FRQRPLF3ROLF\, 5(4): 230-69. and Dominique Van de Walle. 2012. “Does Niehaus, Paul, and Sandip Sukhtankar. India’s employment guarantee scheme 2013b. “The marginal rate of corruption guarantee employment?” Economic and in public programs: Evidence from India.” 3ROLWLFDO:HHNO\, 55-64. -RXUQDORI3XEOLF(FRQRPLFV, 104: 52-64. Keynes, J. M. 1909. “Recent Economic Ravallion, Martin. 2012. “Corruption in the Events in India,” 7KH(FRQRPLF-RXUQDO, 19 0*15(*6 $VVHVVLQJDQ,QGH[´Economic (73), pp. 51-67. DQG3ROLWLFDO:HHNO\, 13-15. 198 Economic Survey 2018-19 Volume 1 A $SSHQGL[ 6XPPDU\6WDWLVWLFVRIWKH$QDO\VLV Variables Observations Mean SD Min 0D[ Total person days 23022 326019.3 367448.3 0 4724609 Total households reached 100 days 23022 620.95 1122.978 0 22877 Total households demanded work 23022 7593.07 7526.75 0 67951 Total persons demanded work 23022 12630.9 13699.18 0 150125 Total households allotted work 23022 7578.99 7522.68 0 67951 Total persons allotted work 23022 12596.87 13668.93 0 149927 7RWDOPXVWHUUROOV¿OOHG 23022 5727.20 6342.09 0 85312 Total households worked 23022 7248.92 7043.5 0 66490 Total persons worked 23022 11726.19 12273.58 0 147080 Amount disbursed to bank account 23022 27.3 41.9 0 672 (Rs crore) Total pers on days worked by SCs 23022 71673.49 105123.4 0 1405991 Total person days worked by STs 23022 56170.62 154782.9 0 3566409 Total person days worked by women 23022 169081.5 247204.3 0 3296483 Redesigning a Minimum Wage 11 System in India for Inclusive Growth CHAPTER Despite India’s outstanding growth in the last two decades, low pay and wage inequality remain serious obstacles towards achieving inclusive growth. An effective minimum wage policy that targets the vulnerable bottom rung of wage earners can help in driving up aggregate demand and building and strengthening the middle class, and thus spur a phase of sustainable and inclusive growth. However, the present minimum wage system in India is extremely complex with PLQLPXPZDJHVGH¿QHGIRUYDULRXVVFKHGXOHGMREFDWHJRULHVIRUXQVNLOOHG ZRUNHUVDFURVVYDULRXVVWDWHV'HVSLWHLWVFRPSOH[VWUXFWXUHDQGSUROLIHUDWLRQ of scheduled employments over time, the Minimum Wages Act,1948 does not FRYHUDOOZDJHZRUNHUV2QHLQHYHU\WKUHHZDJHZRUNHUVLQ,QGLDKDVIDOOHQ WKURXJKWKHFUDFNDQGLVQRWSURWHFWHGE\WKHPLQLPXPZDJHODZ*LYHQWKLV situation, this chapter reviews the situation pertaining to minimum wages in India and suggests the way forward for rationalising and streamlining the policy for minimum wages. INTRODUCTION he shall give six grains of silver per diem. From the sixth month until the end of the year 11.1 Minimum wages for labour rendered has KHVKDOOJLYH¿YHJUDLQVRIVLOYHUSHUGLHP´ been a feature of society since ancient times. For instance, the famous Indian treatise from 11.2 In recent years, minimum wage 2nd Century BCE, Arthashastra, ordained systems have been strengthened by many “the lowest wages for state employees was countries to lift workers out of poverty and 60 panas per year for unskilled workers such to reduce levels of inequality. The renewed as servants, guards, valets, palanquin bearers, interest in minimum wage arises as recent and labourers.” Similarly, the minimum literature and evidence suggests that wages for agricultural labourers, watchmen, minimum wages can promote social justice cowherds and other unskilled workers in the without any major negative implication for private sector was effectively set at 60 panas employment if wages are set at an adequate a year1 (Chapter-3, Book V:"The Conduct level. of Courtiers"). Similarly, the Code of ,QWKHODVW¿YH\HDUVGXULQJDSHULRG Hammurabi, which is often cited as the oldest of global economic slowdown, sluggish written laws on record, mentions minimum global trade and export growth, India’s wages: “If a man hires a workman, then from growth story has been powered by private WKHEHJLQQLQJRIWKH\HDUXQWLOWKH¿IWKPRQWK consumption. Therefore, with 93 per cent 1 One pana was a punch-marked silver/copper coin of the Maurya period. 200 Economic Survey 2018-19 Volume 1 workers in the informal economy, a well persons to advise the Government in designed minimum wage system can reduce ¿[LQJPLQLPXPZDJHV inequalities in incomes, bridge gender gaps • The Indian Labour Conference (ILC) in wages and alleviate poverty. of 1957 recommended determining the 11.4 Wage levels and distribution of wages minimum wage based on the principle of DUHWRDODUJHH[WHQWLQÀXHQFHGQRWRQO\E\ a household’s needs. skills and productivity levels, but also by the • In 1988, the Labour Minister’s role of labour market institutions, particularly Conference made recommendations for minimum wages and collective bargaining. linking minimum wage with the cost of But for the minimum wage system to play a living index, which became mandatory meaningful role in aligning protection with in 1991. the promotion of sustainable growth, it must EHSURSHUO\GHVLJQHGLWVJRDOVFODUL¿HGDQG • In 1992, the Supreme Court of India its enforcement made effective. However, the ruled that minimum wage should also minimum wage system in India is extremely be linked with aspects such as children’s complex with a plethora of minimum wages. education, medical requirements etc. Given this situation, this chapter reviews NATIONAL LEVEL MINIMUM the situation pertaining to minimum wages WAGE in India and suggests the way forward for rationalising and streamlining the policy for 11.6 The idea of a national level minimum minimum wages. wage has been debated since the enactment of the Minimum Wages Act in India. The main MINIMUM WAGE SYSTEM IN argument against a national minimum wage INDIA has been the existence of wide disparities in 11.5 The Indian Minimum Wage System economic development and large variations has been quite a debated and dynamic issue. in cost of living between regions and states. Box 1 portrays the time-line involved in ,QGLD ZDV RQH RI WKH ¿UVW GHYHORSLQJ arriving at a National Floor Level Minimum countries to introduce minimum wages Wage (NFLMW) in India. with the enactment of the Minimum Wages Act way back in 1948. The Act COMPLEX MINIMUM WAGE protects both regular and casual workers. SYSTEM IN INDIA Minimum wage rates are set both by 11.7 Over the last 70 years, the minimum the Central and the State governments wage system in India has expanded and for employees working in selected has become complex. The ¿UVW VHW RI ‘scheduled’ employment2. Minimum complexities arises from issues relating to wages have been set for different its coverage. Today, there are nearly 429 categories of workers according to skill scheduled employments and 1,915 scheduled levels, location and occupations. The job categories for unskilled workers. This $FWGLGQRWSUHVFULEHQRUPVIRU¿[LQJWKH massive expansion in job categories and level of the minimum wage. However, it wage rates has led to major variations not provided for tripartite advisory boards only across states but also within states. consisting of employers, employees of scheduled employments, and independent 11.8 A second set of complexities arises 2 (PSOR\PHQWVQRWL¿HGXQGHUWKH0LQLPXP:DJHV$FWE\WKH&HQWUHDQG6WDWHV Redesigning a Minimum Wage System in India for Inclusive Growth 201 Box 1: Timeline of adoption of National Minimum Wage • First National Commission on Labour. • Recommendation: National Mimimum Wage is neither ‘feasible nor desirable’. 1969 • Bhoothalingam Committee • Argued for adoption of National Floor Level Minimum Wage to ensure a uniform wage for all workers and enhance protection of the most vulnerable workers and 1978 eliminate arbitariness in the determination of level of minimum wages for different States and occupations. Recommendations were mainly for the organized sector. • Unorganized sector and agriculture were left out. • National Commision on Rural Labour • Recommended for a National Floor Level Minimum Wage as wide disparites were prevalent in minimum wages across States. 1991 • Central Government adopted non-statutory National Floor Level Minimum (NFLMW)- `SHUGD\ZDVQRWL¿HG • This NFLMW is updated regularly as per CPI. 1996 • NFLMW is `176 per day w.e.f. 01.06.2017 IURP WKH ODFN RI XQLIRUP FULWHULD IRU ¿[LQJ to ` 538 in Delhi. The range (difference the minimum wage rate. In some states or in between highest and lowest minimum wages) VSHFL¿F VFKHGXOHG HPSOR\PHQWV PLQLPXP in each state varies from ` 16 in Nagaland to wages are linked to the cost of living, through ` 905 in Kerala. a variable dearness allowance (VDA) 11.10 The third set of complexities arises whereas other states do not include the VDA from the fact that Minimum Wages Act component. All this affects the level and does not cover all wage workers. One in variation of wage rates that can be observed every three wage workers in India has fallen across and within States. through the crack and is not protected by the 11.9 The variation of scheduled minimum wage law (ILO, 2018). Some major employments and minimum wage rates vulnerable categories – such as domestic within and across states is shown in Figure workers – are presently covered only in 18 1. The number of scheduled employments States and Union Territories. Further, the varies from 3 in Mizoram to 102 in Assam revision of minimum wage rates has often with the number of scheduled employments been delayed (Anant and Sundaram, 1998). being in the high double digits in most states. 11.11 India has taken a number of steps to 6LPLODUO\WKHQRWL¿HGORZHVWPLQLPXPZDJH improve overall coherence, for example, by rate (per day) varies from `115 in Nagaland GHFODULQJ D QDWLRQDO PLQLPXP ZDJH ÀRRU 202 Economic Survey 2018-19 Volume 1 Figure 1: Range of Minimum Wages in India (Rs. per day) 1800 1600 1192 1400 710 772 658 1200 651 581 1000 596 510 478 430 483 455 417 396 411 800 436 415 460 364 458 381 428 310 365 329 400 329 310 419 410 283 600 350 273 240 271 244 538 400 411 451 376 135 311 312 327 336 340 401 255 268 280 287 294 294 295 304 325 235 239 261 300 200 202 213 225 240 270 166 196 200 206 225 115 132 170 171 ϳϲ ϵϬ ϭϬϮ ϴϴ ϴϴ ϴϬ ϳϱ 0 ϱϰ ϲϭ Ϯϰ ϭϵ Ϯϴ ϯϬ ϲϳ Ϯϵ ϲϮ ϭϱ ϰϲ ϳϬ ϰϲ ϱϴ ϯ ϳϯ ϱϲ ϳϮ Ϯϲ ϱϲ ϳϭ ϳϯ ϮϬ ϳϯ ϰϱ ϱϬ ϰϰ ϵ ϳ Ϯϵ 1RWH )LJXUHVRQWKHKRUL]RQWDOD[LVLQGLFDWHVWKHQXPEHURIVFKHGXOHGHPSOR\PHQWVQRWL¿HGXQGHUWKH0LQLPXP Wage Act by the Central Government and all the States/Union Territories. 6RXUFH 7KHGDWDSHUWDLQLQJWRWKHVFKHGXOHGHPSOR\PHQWVDQGPLQLPXPZDJHUDWHVQRWL¿HGE\WKH6WDWH&HQWUDO *RYHUQPHQWKDYHEHHQFROODWHGIURPWKHODWHVWPLQLPXPZDJHQRWL¿FDWLRQVLVVXHGE\WKHUHVSHFWLYH*RYHUQPHQWV 7KHVHQRWL¿FDWLRQVKDYHEHHQLVVXHGDWGLIIHUHQWSRLQWVRIWLPHUDQJLQJIURP'HFHPEHUWR$SULO and strengthening the coordination of the ZDJHVIRUXQVNLOOHGZRUNHUVQRWL¿HGE\WKH Central Advisory Board with State Advisory more advanced and industrialised states Boards, and by promoting states to determine and vice versa. minimum wage rates through consultations REFLECTION OF GENDER ZLWKLQ ¿YH EURDGHU UHJLRQDO FRPPLWWHHV However, a simple system covering as many DISCRIMINATION THROUGH workers as possible, understood by all, and MINIMUM WAGE PROVISIONS easily enforceable is the key to improve the 11.13 While the Minimum Wages Act does effectiveness of minimum wage. not discriminate between women and men, DIFFERENT MINIMUM an analysis of minimum wages for different WAGE ACROSS STATES: IS IT occupations shows persistence of systematic bias. For instance, women dominate in the JUSTIFIED? category of domestic workers while men 7KH PDLQ MXVWL¿FDWLRQ IRU SHUVLVWLQJ dominate in the category of security guards. with different levels of minimum wages While both these occupations fall within the DFURVV VWDWHV LV WKDW WKH\ UHÀHFW GLIIHUHQW category of unskilled workers, the minimum levels of economic development. In Figure wage rate for domestic workers within a 2, the per capita Net State Domestic Product state is consistently lower than that for the (NSDP) for 2016-17 is plotted against the minimum wage rates for security guards PRVW UHFHQWO\ QRWL¿HG ORZHVW PLQLPXP (Figure 3). Furthermore, the differences in ZDJH UDWHV 6HYHUDO VWDWHV DUH VLJQL¿FDQW their minimum wage rates are quite large with outliers with some of the lowest minimum the minimum wage rates for security guards Redesigning a Minimum Wage System in India for Inclusive Growth 203 Figure 2: Per Capita Net State Domestic Product 2016-17 (at current prices) and /DWHVW1RWL¿HG/RZHVW0LQLPXP:DJH5DWHVLQ,QGLD 600.00 Delhi 500.00 A & N Islands Karnataka 400.00 ) Chandigarh C Telangana Haryana Andhra Pradesh Goa Uttar Pradesh Punjab Gujarat Sikkim 300.00 Odisha Bihar Mizoram Kerala AssamChhattisgarh Jharkhandd Uttarakhand MP Minimum Wages(in Manipur Rajasthan Maharashtra Puducherry 200.00 Meghalaya Arunachal J&K Westt Pradesh Himachal Pradesh Bengal Tamil Nadu Nagaland 100.00 0.00 0 50000 100000 150000 200000 250000 300000 350000 400000 Per Capita Net State Domestic Product (in CͿ 6RXUFH 3HU&DSLWD16'3IURP&62'DWDSHUWDLQLQJWRWKHORZHVWPLQLPXPZDJHUDWHVQRWL¿HGE\WKH 6WDWH&HQWUDO*RYHUQPHQWKDYHEHHQFROODWHGIURPWKHODWHVWPLQLPXPZDJHQRWL¿FDWLRQVLVVXHGE\WKHUHVSHFWLYH *RYHUQPHQWV7KHVHQRWL¿FDWLRQVKDYHEHHQLVVXHGDWGLIIHUHQWSRLQWVRIWLPHUDQJLQJIURP'HFHPEHUWR$SULO 2019. Figure 3: Comparison of Minimum Wages for Domestic Workers (Female Dominated) and Security Guards (Male Dominated) Domestic Workers Security Guard 450 412 400 350 319 328 300 286 250 233 200 171 150 100 50 0 Andhra Pradesh Assam Himachal Pradesh 6RXUFH %DVHGRQWKHODWHVWPLQLPXPZDJHQRWL¿FDWLRQVLVVXHGE\WKHUHVSHFWLYHVWDWHJRYHUQPHQWV 204 Economic Survey 2018-19 Volume 1 in Assam being 44 per cent higher than that prevailing minimum wage rates are below for domestic workers. Such large differences the NFLMW as of 2018-19 (Figure 4). can only be attributed to gender bias as is 11.16 A second measure of compliance obvious from the disparity across states. could be to compare actual wages received COMPLIANCE WITH THE by various categories of workers with the MINIMUM WAGE ACT QRWL¿HGPLQLPXPZDJH7RJHWDQDJJUHJDWH SLFWXUHWKH1)/0:LVXVHGDVWKHQRWL¿HG 11.14 The proliferation of minimum wage minimum wage. By this measure, the rates and scheduled employments is a strong proportion of vulnerable workers receiving deterrent for compliance. Different statutory wages below the NFLMW can be an index of minimum wage rates for the same occupation non-compliance. Using this measure, Kannan between states combined with the wide range and Papola (2017) show that 39 per cent of between the lowest and highest minimum the male casual workers and 56 per cent of wages can trigger migration of the industry women casual workers in rural areas, and to lower wage regions/state. As the impact of 28 per cent of male casual workers and 59 minimum wage levels on employment and per cent of women casual workers in urban poverty depends on the level of compliance areas received wages below the NFLMW in and enforcement (Soundararajan, 2014), it is ,QWKHVDPH¿JXUHVZHUHSHU of paramount importance to rationalise the cent (male rural), 96 per cent (female rural) minimum wage policy. and 49 per cent (male urban) and 88 per 11.15 Currently NFLMW is non-statutory. cent (female urban). This indicates a trend Yet, the NFLMW can provide a useful towards increasing compliance and that there benchmark for assessing the spread of the is a gender gap in compliance similar to the UDQJHRIPLQLPXPZDJHV¿[HGIRUXQVNLOOHG gender gap in level of minimum wages. Using workers across states. Over the years, most of the NSSO Employment-Unemployment WKHQRWL¿HGPLQLPXPZDJHUDWHVLQGLIIHUHQW Survey (EUS) data, a comparison was made states have moved above the NFLMW between the wages of regular and casual rate, though there are still a few states and workers with NFLMW. It was observed that occupations/job categories for which the FRPSOLDQFH OHYHOV ZHUH VLJQL¿FDQWO\ KLJKHU Figure 4: Lowest Minimum Wages for Unskilled Workers and NFLMW (INR per day) 600 National Floor Level Minimum Wage (C176) 500 400 300 538 451 200 411 401 376 340 336 327 325 312 311 304 300 295 294 294 287 280 270 268 261 255 240 239 235 225 225 100 213 206 202 200 196 171 170 166 132 115 0 Goa Bihar Delhi Kerala Assam Punjab Odisha Sikkim Gujarat Tripura Haryana Manipur Mizoram Nagaland Rajasthan Karnataka Jharkhand Telangana Meghalaya Puducherry Chandigarh Tamil Nadu Tamil Uttarakhand Maharashtra Chhattisgarh West Bengal A&N Islands Central Govt. Uttar Pradesh Lakshadweep D & N Haveli Daman & Diu Daman Andhra PradeshAndhra Madhya Pradesh Himachal Pradesh Arunachal Pradesh Jammu & Kashmir Jammu 6RXUFH 7KHGDWDSHUWDLQLQJWRORZHVWOHYHORIPLQLPXPZDJHUDWHVIRUXQVNLOOHGZRUNHUVQRWL¿HGE\WKH6WDWH &HQWUDO*RYHUQPHQWDQG1)/0:QRWL¿HGE\WKH&HQWUDO*RYHUQPHQWKDYHEHHQFROODWHGIURPWKHODWHVWPLQLPXP ZDJHQRWL¿FDWLRQVLVVXHGE\WKHUHVSHFWLYHJRYHUQPHQWV7KHVHQRWL¿FDWLRQVKDYHEHHQLVVXHGDWGLIIHUHQWSRLQWVRI time ranging from December 2014 to April 2019. Redesigning a Minimum Wage System in India for Inclusive Growth 205 Figure 5: Percentage of Regular Workers Receiving Wages over the NFLMW, 2012 INDIA - 80.6 100.00 90.00 80.00 70.00 60.00 50.00 40.00 30.00 20.00 10.00 0.00 Source: Based on unit level data of the NSS Employment-Unemployment Survey, 2011-12. Figure 6: Percentage of Casual Workers Receiving Wages over the NFLMW, 2012 100.00 90.00 INDIA-58.05 80.00 70.00 60.00 50.00 40.00 30.00 20.00 10.00 0.00 Source: Based on unit level data of the NSS Employment –Unemployment Survey, 2011-12 206 Economic Survey 2018-19 Volume 1 for regular wage workers when compared to that for 2009-10, the marginal effects of the casual wage earners, as indicated in Figures 5 effective minimum wage increases gradually & 6. as we move towards the 80th quantile, i.e., IMPACT OF MINIMUM WAGES the marginal wage pushes up the wages disproportionately more on the lower side of 11.17 What has been the impact of minimum the wage distribution. This is quite different wage on the labour market in India? To what from the marginal effects observed in 2004- H[WHQWKDVLWEHHQVXFFHVVIXOLQIXO¿OOLQJWKH 05, when the marginal effects of an increase goal of protecting the vulnerable workers, in the minimum wage were greater at the improving general wage levels, and reducing higher levels of the income distribution than inequality and poverty? In this context, it at lower levels (Figure 7). must be remembered that a well-designed minimum wage system is only one of the Figure 7: Effect of minimum wages on wage several institutional mechanisms necessary distribution in India for a meaningful impact on all these factors. Impact on wage levels 11.18 Rani, Belser and Ranjbar (2013) demonstrate that minimum wage in India GRHV QRW RSHUDWH DV D FRQYHQWLRQDO ÀRRU wage to protect the lowest paid workers. Nevertheless, the study shows the presence of a “lighthouse effect”, i.e., the minimum wage acts as a benchmark that pulls up wages in the low-paid and informal sector by enhancing Source: Rani and Ranjbar (2015) the bargaining power of vulnerable workers. Impact on Wage Inequality 11.19 Menon and Rodgers (2017) use household survey data from 1982-83 and 11.21 International experience suggests that 2008 to show a marked increase in compliance greater compliance with minimum wages has between these two periods with a stronger led to reduction in wage inequality. India’s impact on male wages compared to female experience regarding the impact of minimum wages and on regular wages compared to wages on wage inequality needs to be casual wages during this period. Using data evaluated keeping in mind the segmentation for workers in the construction industry, in the labour market and variations across Soundararajan (2018) shows the presence of various categories of workers. the “lighthouse effect” of minimum wage. 11.22 Between 1993 and 2011, the average 6SHFL¿FDOO\ PLQLPXP ZDJH VHHPV WR KDYH real wages increased in India, with the fastest shaped wage bargaining, thereby leading to growth recorded for casual labour, women’s rise in actual wages. labour, and rural/agricultural labour (ILO 11.20 Rani and Ranjbar (2015) show 2018). Despite these increases, the existing that the minimum wage does impact the wage inequality measured by the Gini distribution of actual wages, with the impact FRHI¿FLHQWUHPDLQVYHU\KLJKE\LQWHUQDWLRQDO 3 depending on wage quantile. They show standards (Figure 8) . Going deeper, it is seen 3 7KH*LQLFRHI¿FLHQWLVDFRPPRQO\XVHGPHDVXUHRILQFRPHLQHTXDOLW\WKDWFRQGHQVHVWKHHQWLUHLQFRPHGLVWULEXWLRQIRUD country into a single number between 0 and 1: the higher the number, the greater the degree of income inequality. Redesigning a Minimum Wage System in India for Inclusive Growth 207 )LJXUH *LQL&RHI¿FLHQWIRU5HJXODUDQG&DVXDO:RUNHUV WR 1993-94 2004-05 2011-12 0.60 0.49 0.49 0.50 0.50 0.46 0.47 0.41 0.40 0.30 0.28 0.30 0.26 0.20 0.10 0.00 Regular Casual All Source: ILO, 2018. that this inequality has increased amongst compared to the wage rate of the bottom 10 regular workers while it has decreased among per cent of wage earners (P90/P10) declined casual workers. among casual workers and increased among regular workers, except regular male rural 11.23 A similar trend is visible when we workers. The ratio of the wage rate of the measure wage inequality through wage middle 10 per cent of wage earners (50th dispersion ratios (Tables 1 and 2). The ratio decile or P50) to the bottom 10 per cent of the average wage rate of the top 10 per cent declined consistently during 1993-2011 for Table 1: Rural Wage Inequality Dispersion Ratios: 1993-94 to 2011-12 1993-94 2004-05 2011-12 (P90/ (P90/ (P50/ (P90/ (P90/ (P50/ (P90/ (P90/ (P50/ P10) P50) P10) P10) P50) P10) P10) P50) P10) Male 7.6 2.3 3.3 9 3.5 2.6 7.1 3.6 2.0 Regular Female 12 4.3 2.8 15 5.8 2.6 12.5 5.0 2.5 Rural Male 3.3 2.0 1.7 2.9 1.7 1.7 2.9 1.7 1.7 Casual Female 3.1 1.7 1.8 2.8 1.8 1.5 2.5 1.5 1.7 Table 2: Urban Wage Inequality Dispersion Ratios 1993-94 to 2011-12 1993-94 2004-05 2011-12 (P90/ (P90/ (P50/ (P90/ (P90/ (P50/ (P90/ (P90/ (P50/ P10) P50) P10) P10) P50) P10) P10) P50) P10) Male 7.0 2.3 3.0 8.6 3.2 2.7 8.9 3.5 2.5 Regular Female 12.9 2.6 5.0 18.7 5.6 3.3 15.6 5.0 3.1 Urban Male 3.7 1.8 2.0 3.1 1.8 1.8 3.0 1.9 1.6 Casual Female 3.8 1.8 2.1 3.5 1.8 2.0 4.0 2.0 2.0 Source: ILO, 2018. 208 Economic Survey 2018-19 Volume 1 regular and casual workers, both for males inequality especially at lower levels. This and females in urban and rural areas. Thus, EHFRPHVDOOWKH PRUH VLJQL¿FDQWDV ZRPHQ there is a ‘catching up’ process because of the constitute the majority of the bottom rungs of faster increase of wages of casual workers, the wage distribution. This also shows how which substantiates the ‘lighthouse effect’ of compliance of the statute is imperative for minimum wages. increasing welfare. 11.24 This mixed trend of wage inequality Impact on Employment – increasing amongst regular workers and %URHFNH ¿QGVLQDPHWDVWXG\ declining amongst the bottom and middle on employment across Brazil, Chile, China, level of all workers – can perhaps be explained Colombia, India, Indonesia, Mexico, the by the rise of average minimum wages, in Russian Federation, South Africa and Turkey consonance with the increase in Mahatma that minimum wages have only a minimal Gandhi National Rural Employment (or no) impact on employment in emerging Guarantee Scheme (MGNREGS) wages, economies. which were benchmarked to minimum wages (Berg et al., 2018). It is, therefore, 11.26 Rani, Belser and Ranjbar (2013), established that well-designed and effective LQDVWXG\RIGLVWULFWVRI,QGLD¿QG WKDW implementation of minimum wages will there was no impact of minimum wages strengthen the trend towards decreasing wage on employment between 2005 and 2010. BOX 2: MINIMUM WAGE SYSTEM IN BRICS BRICS countries have varied systems in terms of coverage, degree of tripartite consultation, criteria for setting the minimum wage and adjustment procedure. However, in all these countries, minimum wages are explicitly embedded within a larger wage policy aimed at balancing needs of the workers with overall economic factors. Table 3: Minimum Wage System in BRICS countries China Russia Brazil South Africa India Coverage National Minimum Regional A national Minimum wages minimum wage rates are minimum wages minimum wage are limited wage, covering established by that coexist with a was approved in to Scheduled all workers. province. national minimum 2018, covering Employments, Regions can also wage. The all groups of diff. skills & GH¿QHPLQLPXP regional minimum wage earners. occupations. wages above the ZDJHVDUH¿[HG national level. above the federal rate. Redesigning a Minimum Wage System in India for Inclusive Growth 209 Consultation ‘Quadripartite Administrative Russian Tripartite The tripartite Minimum Wages commission’ in authorities, in Committee- the Employment are set through 2005, composed charge of labour Employers’ Conditions 1RWL¿FDWLRQRU of federal issues prepare a association, trade Commission Consultation, government, programme to unions and the (ECC) advises based on state ¿[DQGDGMXVW Government the Minister of the tripartite government, minimum wages. of the Russian Labour on the Advisory Board employers Federation determination and Committees and unions, decides. of the minimum set for this formulates wage. purpose. a long-term minimum wage policy - until 2019. Criteria Minimum wage Cost of living Regions choose Cost of living Adopted need- is increased of workers and different criteria and minimum based norms from by the sum of their dependents; for their minimum living levels, the 1957, 15th LQÀDWLRQLQWKH the consumption wages but the poverty ILC Session and previous year price index; the subsistence alleviation, wage 1992 Supreme plus the GDP average wages of minimum is differentials Court Judgment growth of 2 years workers; labour a need-based & inequality, before (if >0) productivity; the income level that OSH, conditions urban economic is the benchmark and level of situation; and the that guarantees employment, level of economic minimum LQÀDWLRQ*'3 development. consumption productivity, requirements. collective bargaining. Adjustment Adjusted on an At least every 1RVSHFL¿F Regular annual Adjusted at least annual basis two years, periodicity adjustment. HYHU\¿YH\HDUV and whenever appropriate when the indicators change. Source: ILO, 2018 However, Menon and Rogers (2017) report a potent tool for protecting workers and a positive effect of minimum wages on alleviating poverty, if set at an appropriate employment levels for both men and women. level that ensures compliance. International 7KH\¿QGWKDWDSHUFHQWULVHLQPLQLPXP experience has shown that relatively simple wages raised the employment level by 6.34 systems are more effective and usually percentage points in rural areas while it had complex systems are least effective. D VWDWLVWLFDOO\ LQVLJQL¿FDQW LPSDFW RQ XUEDQ Cunningham (2007) and Ghose (1997) show employment levels for both men and women. that a complex system of minimum wages shows lack of coherence about wage levels WAY FORWARD and wages being set in an arbitrary fashion. 11.27 It is evident from above that a well- United Kingdom, for example, abolished its designed minimum wage system can be system of industry-wide trade boards in the 210 Economic Survey 2018-19 Volume 1 1980s and replaced it with a simple national design of minimum wages system are as PLQLPXP ZDJH 7KLV WUHQG LV UHÀHFWHG LQ follows: evolution of ILO standards as well, which y 6LPSOL¿FDWLRQ DQG 5DWLRQDOLVDWLRQ earlier encouraged the adoption of a select Rationalisation of minimum wages as system of minimum wages to groups of proposed under the Code on Wages workers who are in a weak bargaining position Bill needs to be supported. This code in the labour market, but later promoted a amalgamates the Minimum Wages Act, comprehensive approach that covers as many 1948, the Payment of Wages Act, 1936, workers as possible. the Payment of Bonus Act, 1965 and the 11.28 Multiple minimum wages usually exist Equal Remuneration Act, 1976 into a to take care of the needs of a heterogeneous VLQJOHSLHFHRIOHJLVODWLRQ7KHGH¿QLWLRQ labour force. For example, this is the case of wage in the new legislation should in India and the Latin American Countries subsume the present situation of 12 that have a high diversity of labourers. Some GLIIHUHQWGH¿QLWLRQVRIZDJHVLQGLIIHUHQW policy recommendations for an effective Labour Acts. Figure 9: Geographical regions as determined by the Expert Committee on determining WKHPHWKRGRORJ\IRU¿[LQJWKH1DWLRQDO0LQLPXP:DJH 6RXUFH ([SHUW&RPPLWWHHRQGHWHUPLQLQJWKHPHWKRGRORJ\IRU¿[LQJWKH1DWLRQDO0LQLPXP:DJH Redesigning a Minimum Wage System in India for Inclusive Growth 211 y Setting a National Floor Level of the last revision in the minimum Minimum Wage: Central Government wage adjunct to the mandated period. VKRXOGQRWLI\D³QDWLRQDOÀRRUPLQLPXP This would enable dissemination of ZDJH´ WKDW FDQ YDU\ DFURVV WKH ¿YH information and increased transparency geographical regions (Figure 9). in the system. 7KHUHDIWHU VWDWHV FDQ ¿[ WKH PLQLPXP y Role of Technology: The concept of wages, which shall not be less than the ‘bounded rationality’ in behavioural ³ÀRRU ZDJH´ 7KLV ZRXOG EULQJ VRPH economics is that there are restrictions uniformity in the minimum wages across to human information processing, due country and would make all states almost to limits in knowledge (or information) equally attractive from the point of view and computational capacities of labour cost for investment as well as (Kahneman, 2003). A complex system reduce distress migration. with multiplicity of wages across states y Criteria for setting minimum wage: and across occupations sets limits on Further, the Code on Wages Bill should how workers process the information FRQVLGHU ¿[LQJ PLQLPXP ZDJHV EDVHG DYDLODEOH DQG XVH LW WR WKHLU EHQH¿W on either of the two factors viz; (i) the Technology can help in overcoming this skill category i.e unskilled, semi-skilled, behavioural bias by making information skilled and highly skilled; and (ii) the available in a simple and clear manner. geographical region, or else both. This Use of a variety of online, mobile phone key change would substantially reduce and networking technologies have the the number of minimum wages in the potential to facilitate the collection and country. For instance, Madhya Pradesh analysis of labour statistics, assist with KDV QRWL¿HG PLQLPXP ZDJHV EDVHG RQ the dissemination of information about just four skill levels of unskilled, semi- labour laws and policies, reduce costs and skilled, skilled and highly skilled across improve transparency. A national level occupations and regions. The state has dashboard can be created at the Centre just four basic minimum wages for the with access to the state governments four skill categories. whereby the states can regularly update WKH QRWL¿FDWLRQV UHJDUGLQJ PLQLPXP Coverage: The proposed Code on y wages. This portal must be made Wages Bill should extend applicability available at Common Service Centres of minimum wages to all employments/ (CSCs), rural haats etc., with the workers in all sectors and should required mass media coverage so that cover both the organized as well as the the workers are well-informed and their unorganized sector. bargaining skills and decision-making y Regular adjustment: A mechanism power are strengthened. Uniformity in should be developed to adjust minimum minimum wages would also encourage wages regularly and more frequently, industries to move towards interior areas similar to countries like Montenegro, and thereby reduce labour migration. Nicaragua, Netherlands, Uruguay, Information on various combinations of and Costa Rica, where the minimum wages, occupations/skills and states can wage adjustment takes place every six be made available so that workers can months (ILO, 2014). A dashboard needs get easy access to whatever combination to be set up by the Ministry of Labour of minimum wages they want to know. & Employment, which shows the date The system should be built in a way that 212 Economic Survey 2018-19 Volume 1 Box 3 : Use of Technology for Minimum Wage Enforcement- Cross Country Experiences y In UAE, all enterprises have been legally required to pay wages for both national and migrant ZRUNHUV WKURXJK EDQNV DQG RWKHU ¿QDQFLDO VHUYLFH SURYLGHUV7KLV V\VWHP DOORZV WKH 0LQLVWU\ of Labour to have a comprehensive wage database and an electronic wage payment monitoring mechanism for enterprises within the country. y In South Africa a system, called ‘Impimpi Alive’, enables workers to send anonymous SMS messages to the Department of Labour (DOL) after which an inspector is dispatched to the employer’s place of business within 48 hours. y In U.S. an app – The Wage & Hour Guide for Employers App – puts federal and state wage and KRXUODZVDWWKH¿QJHUWLSVRIHPSOR\HUVDVZHOODVODZPDNHUVIRUEHWWHUWUDQVSDUHQF\ y U.S. also has an app – GovDocs Minimum Wage app that provides the most up-to-date minimum wage rate data for all company locations. ÀDVKHV µUHG¶ DOHUWV LI WKH VWDWXWH LV QRW 11.29 To sum up, the world of work is in being followed in any state or occupation a churn as technology is heralding major LQWKHQRWL¿HGDUHD transformations both in the workplace as well as in work and employment y Grievance redressal: There should be an easy to remember toll-free number relations. The impact is being felt for anybody to register his grievance on both in the developed and developing non-payments of the statutory minimum countries. For India, undergoing a delayed wages. This number should be given structural and demographic transition, the wide publicity to make people aware challenges posed by the technology driven of this avenue for grievance redressal. changes are enormous. Expanding decent Swift action should be taken against employment to young aspirants in the labour the offenders and this action should be markets is a major concern. Establishing an effective minimum wage system that will ÀDVKHGRQWKHGDVKERDUGZLWKRXWJRLQJ lead to inclusive growth is therefore an urgent LQWR VSHFL¿F GHWDLOV 7KH LPSUHVVLRQ of action being taken would act as a necessity. GHWHUUHQWWRHPSOR\HUVWRÀRXWWKHVWDWXWH CHAPTER AT A GLANCE ¾ 7KHSUHVHQWPLQLPXPZDJHV\VWHPLQ,QGLDLVFRPSOH[ZLWK PLQLPXPZDJHVGH¿QHGIRU various scheduled job categories across various states. ¾ One in every three wage workers in India is not protected by the minimum wage law. ¾ 0LQLPXPZDJHVVKRXOGEH¿[HGIRUIRXUFDWHJRULHVQDPHO\XQVNLOOHGVHPLVNLOOHGVNLOOHGDQG highly skilled based on the geographical region and should cover all workers, irrespective of any wage ceilings. ¾ A simple, coherent and enforceable Minimum Wage System should be designed with the aid of WHFKQRORJ\DVPLQLPXPZDJHVSXVKZDJHVXSDQGUHGXFHZDJHLQHTXDOLW\ZLWKRXWVLJQL¿FDQWO\ affecting employment. ¾ An effective minimum wage policy is a potential tool not only for the protection of low- paid workers but is also an inclusive mechanism for more resilient and sustainable economic development. Redesigning a Minimum Wage System in India for Inclusive Growth 213 REFERENCES Kahneman, Daniel. 2003. “Maps of Bounded Anant, T.C.A., and K. 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A Review of technologies and the transition to formality: Consequences of the Indian Minimum The trend towards e–formality, Employment Wage on Indian Wages and Employment. 3ROLF\ 'HSDUWPHQW (PSOR\PHQW :RUNLQJ Geneva: forthcoming as a Publication of the Paper No. 247. Geneva: ILO. International Labour Organisation.