ESTIMATION OF DISTRICT LEVEL POVERTY IN

Rajendra P. Mamgain M.H. Suryanarayana

Submitted to Directorate of Economics and Statistics Department of Planning Government of Uttarakhand

GIRI INSTITUTE OF DEVELOPMENT STUDIES (An Autonomous Institute Funded by ICSSR and Govt. of )

Sector - O, Aliganj Housing Scheme LUCKNOW - 226024, (U.P.)

Phones: (0522) 2321860, 2325021 Telefax: (0522) 2373640 E-mails: [email protected]; [email protected] November 2017

PREFACE

Measurement of poverty and its elimination has been a core strategy of the development planning process in India since the beginning of its plan process. However, measuring poverty and its eradication has been a daunting challenge. Despite significant progress in the methodology of the measurement of , the poverty estimates suffer due to paucity of data at more disaggregated level for effective policy interventions. In recent periods, with the availability of large data sets from NSSO quinquennial rounds on consumption expenditure both for central and state samples, it is possible to make robust estimates of poverty at district level for most Indian states. Keeping this in view, we have attempted to estimate district-wise poverty and inequality in Uttarakhand on the request of Directorate of Economics and Statistics (DES), Government of Uttarakhand.

The study brings out several interesting features of poverty and inequality in Uttarakhand, which may be useful in prioritising action plans and resource allocations to eradicate poverty and promote inclusive development. The study has observed remarkable economic progress and resultant reduction in poverty in Uttarakhand particularly after its formation on November 9, 2000. However, high economic growth stands accompanied with widening regional disparities over the years. This is also reflected in significant variations in average per capita consumption expenditure acrossthe districts of the state. The incidence of poverty in the state declined by almost three times from 32.7 per cent in 2004-05 to 11.3 per cent in 2011-12, which has been much faster than its neighbouring state and parent state, Uttar Pradesh. Among social groups, the incidence of absolute poverty was the least among the Other Social Groups (OSGs), followed by the Other Backward Classes (OBCs) and highest for Scheduled Castes (SCs) in 2004-05. The percentage point reduction in poverty in Uttarakhand between 2004-05 and 2011-12 was the maximum among SCs (30.34) followed by OBCs (29.06), the Scheduled Tribes (STs) (20.52) and OSGs (18.88). There was a more or less uniform reduction (around 65 per cent) in incidence of poverty among all the social groups in rural Uttarakhand.

Our estimates show significant variations in the incidence of poverty across districts in Uttarakhand ranging as high as 28.5 per cent in Garhwal and lowest 9.2 per cent in . In most of the hill districts the incidence of poverty is above the state average. The incidence of rural poverty is generally the lowest in the richest quartile group of districts, namely Dehradun, Udham Singh Nagar and . The marginal distribution of incidence of rural poverty across districts is nearly symmetrical while those pertaining to extent of inequality and cost of living are highly negatively skewed ones. This would mean that at least half of the districts are densely located with respect to high extent of relative inequality and cost of living. Rural-urban disparity in mean monthly per capita expenditure (MPCE) is the lowest in Nainital (108.45) --- the richest in terms of rural mean MPCE but poorest fourth in terms urban mean MPCE. Such disparity is the highest in (212.13), which is the third poorest rural district but second poorest urban district. The median disparity is highest in Uttarakashi (172.10), which falls in the rural upper middle and urban lower middle quartile group. These patterns show a failure of urban development to catch up with rural prosperity leading to a development process far removed from the Kuzents’ inverted-U postulate. Relative rural-urban spatial cost of living too throws up a picture different from the conventional perception. In a majority of the districts, the rural spatial cost of living exceeds the urban one.

The study points out that since most of the economic opportunities are concentrated in plain areas of the state, hill areas are almost lagging on various indicators of economic progress. Work opportunities are marred with seasonality and low levels of productivity particularly in hill region of the state. The growth in non-farm employment opportunities has been largely concentrated in the plain districts of the state. Due to lack of economic opportunities and quality employment, the hill areas of the state have been experiencing accelerated pace of long term exodusto plain areas of the state and other parts of the country. It further warns that neglecting productive employment opportunities at the cost of redistributive measures would not prove beneficial in the long run as it has serious economic and political consequences particularly emanating from large scale job related exodus from hill districts of the state.

The study states that creation of gainful employment opportunities with reasonable social safety measures are critical in eradication of poverty and reduction in vulnerabilities of population belonging to various regions and sub-groups of population in Uttarakhand. Thus, along with creation of employment opportunities, skill development of both men and women is crucial for various trades and occupations to improve their employability and productivity.

The study could be possible due to generous financial support from Directorate of Economics and Statistics (DES), Government of Uttarakhand. We would like to specially thank DES for its valuable support. We are grateful to Dr. Manoj Pant, Joint Director, DES for extending his cooperation and support at various stages of the study. Our sincere thanks are due to Shri Shushil Kumar, Director, DES and Shri Pankaj Naithani, Additional Director, DES for their valuable suggestions and encouragement in completing the study. We are also thankful to Shri G.S. Pande, Deputy Director and other officers of DES for their inspiring support.

The Giri Institute of Development Studies (GIDS) provided unstinted support in the smooth conduct of the study. We express our gratitude to Prof. S.R. Hashim, Chairman, Giri Institute of Development Studies (GIDS), Lucknow for his valuable guidance. We are also grateful to Dr. Himanshu and Prof. Amitabh Kundu for their valuable inputs. We acknowledge the vital research support provided by Shri Vachaspati Shukla during the initial stages of the study.

We are also grateful to Professor Surendra Kumar, Director, GIDS for extending his full cooperation during the entire duration of the study. We express our gratitude to all our colleagues in GIDSCol. (Retd.) D.P. Singh, Finance and Administrative Officer, Mr. R.S. Bisht, Office Superintendent, and Mr. Sunil Srivastava, Accountant- for efficient project management services. We also thank Mr. K.K. Verma for typesetting and formatting the study report.

We hope the findings of the study would be useful to policy planners and line department organisations of Government of Uttarakhand, and NGOs in prioritising their strategies and actions towardsquicker eradication of poverty and minimising vulnerabilities of population in Uttarakhand. It would also be useful to researchers and students interested in the issues of poverty, inequality and regional development in India.

Rajendra P. Mamgain M.H. Suryanarayana

CONTENTS

Preface Contents List of Tables List of Figures List of Abbreviations Chapter I: Introduction The Context 1 Why is Poverty Estimation Required? 2 Approaches of Estimation of Poverty at District Level 3 Policy Initiatives 7 Objectives of the Study 9 Chapter Plan 9 Chapter II: Uttarakhand Economy: An Overview Introduction 11 Growth and Regional Inequalities 12 Demographic Changes in Uttarakhand 17 Education Development in Uttarakhand 23 Health and Basic Amenities 28 Summing Up 30 Chapter III: Levels of Living in Uttarakhand: Select Dimensions Introduction 39 Population Composition: Social Groups 39 Distributional Profiles 40 Relative Profiles of Consumption Distributions 43 Absolute Deprivation 49 Mainstreaming/Marginalization 54 Summary 68 Chapter IV: Deprivation in Uttarakhand: A District-wise Profile Introduction 71 Data Base and Methodology 72 Inter-district Disparities in Consumption 72 Relative Inequality: District-wise Nominal Consumption 80 Distribution District-wise Estimates of Poverty 83 Rural-Urban Profile 89 Incidence of Poverty across Hills and Plains 91 Deprivation and its Determinants 92 Findings and Recommendations 93 Chapter V: Explaining Poverty in the Framework of Employment and its Quality Introduction 97 Employment in Uttarakhand 98 Structure and Quality of Employment 102 Demand Side Dynamics of Employment 112 Correlates of Poverty and Employment 114 Summing Up 115 Chapter VI: Summary and Conclusions 121 Deprivation and Inequality-A Comparative Picture 122 District-wise Poverty and Inequality in Uttarakhand 125 Eradicating Poverty and Reducing Vulnerability through Creating 127 Quality Employment References 133 List of Tables

Table 2.1 Distribution of Rural Households by Monthly Income of Highest 16 Earning Member (Rs.) 2.2 Select Demographic Features of Uttarakhand and India, 2011 18 2.3 Share of Migrant Population in Uttarakhand 21 2.4 Literacy Rate in Uttarakhand, 2011 25 2.5 Educational Level of Population, 2011 26 2.6 Select Indicators of Health, 2015-16 29 3.1 (a) Distribution (%) of Population across Social Groups: Rural Sector 40 for Select States 3.1 (b) Distribution (%) of Population across Social Groups: Urban Sector 40 for Select States 3.2 (a) Measures of Average MPCE and Inclusion/Exclusion in/from the 41 National Mainstream: Rural Sector 3.2 (b) Measures of Average MPCE and Inclusion/Exclusion in/from the 41 National Mainstream: Urban Sector 3.3 (a) Levels of Average MPCE in Uttarakhand relative to Select State 44 Averages (Percentage difference): Rural Sector 3.3 (b) Summary Statistics on NSS Per Capita Consumer Expenditure 44 Distribution: Rural Sector (2004/05 & 2011/12) 3.3 (c) Extent of Inequality in the Rural Sector: 2004/05 &2011/12 45 3.4 (a) Levels of Average MPCE in Uttarakhand relative to Select State 46 Averages (Percentage difference): Urban Sector 3.4 (b) Summary Statistics on NSS Per Capita Consumer Expenditure 47 Distribution: Urban Sector (2004/05 & 2011/12) 3.4 (c) Extent of Inequality in the Urban Sector: 2011/12 48 3.5 Extent of Mainstream Inclusion: Rural and Urban Sectors 49 3.6 Estimates of Poverty Lines by State and Method (Rs MPCE) 51 3.7 Estimates of Poverty by Sector, State and Method 53 3.8 (a) Estimates of Deprivation in the Rural Sector: Incidence, Depth and 54 Severity (2004/05 vs. 2011/12) 3.8 (b) Estimates of Deprivation in the Urban Sector: Incidence, Depth and 54 Severity (2004/05 vs. 2011/12) 3.9 (a) Summary Statistics on Per Capita Monthly Consumer Expenditure 58 Distribution by Social Groups: Rural Uttarakhand 3.9 (b) Summary Statistics on Per Capita Monthly Consumer Expenditure 59 Distribution by Social Groups: Urban Uttarakhand 3.10 (a) Estimates of Deprivation: Incidence, Depth and Severity by Social 60 Group: Rural Sector (2004/05 & 2011/12) 3.10 (b) Estimates of Deprivation: Incidence, Depth and Severity by Social 62 Group: Urban Sector (2004/05 & 2011/12) 3.11 (a) Measures of Inter-Group Inclusion/Exclusion: Rural Uttarakhand 64 3.11 (b) Measures of Inter-Group Inclusion/Exclusion: Urban Uttarakhand 64 3.12 (a) Extent of Mainstreaming/Marginalization by social groups: Rural 66 Sector 3.12 (b) Extent of Mainstreaming/Marginalization by Social Groups: Urban 67 Sector 4.1 (a) Summary Profiles of District-wise Consumer Expenditure 74 Distribution: Rural Uttarakhand 2011/12 (At current local prices) 4.1 (b) Summary Profiles of District-wise Consumer Expenditure 75 Distribution: Rural Uttarakhand 2011/12 (At average state level rural prices) 4.2 (a) Summary Profiles of District wise Consumer Expenditure 78 Distribution: Urban Uttarakhand 2011/12 (At current local prices) 4.2 (b) Summary Profiles of District wise Consumer Expenditure 79 Distribution: Urban Uttarakhand 2011/12 (At average state level urban prices) 4.3 (a) Extent of Inequality in MPCE Distribution: Districts wise - Rural 81 Uttarakhand (2011/12) (At current local prices) 4.3 (b) Extent of Inequality in MPCE Distribution: District wise - Urban 82 Uttarakhand (2011/12) (At current local prices) 4.4 District wise Estimates of Price-adjusted Poverty Lines: 84 Uttarakhand 2011/12 (Rs.) 4.5 District-wise Estimates of Poverty: Uttarakhand (2011/12) (%) 85 4.6 District-wise Estimates of Poverty: Uttarakhand (2011/12) (%) 86 4.7 Poverty Profiles across Districts: Rural and Urban Uttarakhand 88 (2011/12) 4.8 Rural-Urban Disparities in Economic Profiles 90 4.9 Estimates of Poverty by Hills and Plains: Uttarakhand: 2011/12 91 4.10 Estimates of Poverty (Incidence, depth and severity) across social 92 groups by Hills and Plains: Uttarakhand: 2011/12 4.11 Poverty and its Determinants 93 5.1 Gender-wise Work Participation Rates in Uttarakhand, 2011 (in %) 99 5.2 District-wise Percentage Share of Marginal Workers in Uttarakhand 102 5.3 Occupational Distribution of Workers (Main+Marginal), 2011 103 5.4 Sector-wise Composition of Employment in Rural Areas of Hilly 106 Districts of Uttarakhand, 2005 5.5 Per Capita GSDP in Uttarakhand by Sector, 2004-05 (at 1999-2000 111 constant prices) 5.6 Growth in Number of Enterprises* and Employment between 2005 113 and 2013 (% change) 5.7 Correlation Matrix 117 List of Figures Figure 2.1 Per capita NSDP at Constant Prices (Rs.) 13

2.2 Sectoral Composition of GSDP in Uttarakhand (2002-14) at 2004- 14 05 Prices 2.3 Per capita NDDP, 2012-13 (at 2004-05 prices), (Rs. ‘00) 15 2.4 % SC/ST Population, 2011 19 2.5 District-wise Age Composition of Population, 2011 20 2.6 Literacy Rates (%), 2011 20 2.7 Literacy Rates, 2011 24 2.8 District-wise Literacy Rates, 2011 24 2.9 Percentage of Persons with Secondary and above Education among 27 Youth (15-29 yrs), 2011 3.1 Incidence of Poverty (%) across Social Groups: Rural Uttarakhand 61 3.2 Incidence of Poverty (%) across Social Groups: Urban Uttarakhand 62 4.1 Mean Levels of Living across Rural and Urban Districts: 76 Uttarakhand 4.2 Extent of Inequality across Districts: Uttarakhand (2011/12) 83 4.3 Incidence of Poverty across Districts: Uttarakhand (2011/12) 85 4.4 Spatial Cost of Living Indices across Districts: Uttarakhand 87 (2011/12) 5.1 % share of Workers in Population, 2011 99 5.2 District-wise WPRs (%) 100 5.3 Workforce Participation Rates, 2011-12 101 5.4 Sctoral Composition of Employment, 2011-12 (%) 104 5.5a Nature of Employment, 2011-12--Rural 107 5.5b Nature of Employment, 2011-12--Urban 107 5.6 Nature of Employment across Social Group of Workers in 108 Uttarakhand, 2011-12 5.7 % Rural Households with Salaried Workers, 2011 110 5.8 Relative Index of Productivity of Foodgrains per hectare, 2014-15 112 ABBREVIATIONS

BPL Below Poverty Line CSO Central Statistical Office DES Directorate of Economics and Statistics GoI Government of India GoUK Government of Uttarakhand GSDP Gross State Domestic Product IC Inclusive Coefficient ICIMOD International Centre for Integrated Mountain Development ICP Inclusive Coefficient in a Plural Society MGNREGA Mahatma Gandhi National Rural Employment Guarantee Act MPCE Monthly per Capita Consumer Expenditure NDDP Net District Domestic Product NFHS National Family & Health Survey NLM National Livelihood Mission NSSO National Sample Survey Organisation OBCs Other Backward Classes OSGs Other Social Groups PLBs Poverty Level Baskets SAS Small Area Statistics SCs Scheduled Castes SEC Sixth Economic Census SECC Socio-Economic Caste Census SGSY Swarnjayanti Gram SwarojgarYojana STs Scheduled Tribes ToR Terms of Reference WPR Work Participation Rate

Chapter - I INTRODUCTION

I. THE CONTEXT

Measurement of poverty and its elimination has been a core strategy of the development planning process in India since its First Five Year Plan. Household surveys for consumption expenditure have been the main instruments of poverty measurement. The debate on methodological issues for measurement of poverty has passed through many critical stages. The first systematic attempt to measure poverty began in India after the recommendations of Planning Commission Expert Committee under the chairmanship of Prof. Y. K. Alagh in 1979. The Committee set the rural and urban poverty lines at Rs. 49.09 and Rs. 56.64 per capita per month at 1973-74 prices, respectively (Planning Commission, 2009). These lines were based on the assumption of different calorie requirements and related poverty level baskets (PLBs) for rural and urban consumption. Subsequently, the Lakdawala methodology of the estimation of poverty lines formed the basis of poverty estimates nationally and across states until 2004-05. The Planning Commission appointed another committee to look into the matter under the chairmanship of Prof. Suresh Tendulkar, popularly known as Tendulkar Committee in December 2005. The Tendulkar Committee recommended the adoption of the consumption basket underlying the Alagh-Lakdawala national urban poverty line in 2004-05 as the PLB and aligned it with the national rural poverty line by using an appropriate price index. In this way the rural and urban poverty lines got fully aligned around a common PLB. Such change led to an upward adjustment of the national rural poverty line and correspondingly the national rural poverty estimate. The Tendulkar Committee estimates also invited public uproar over poverty estimates that led the Planning Commission to appoint yet another committee under the chairmanship of Professor C. Rangarajan to estimate poverty. The Rangarajan Committee submitted its report in June 2014. It recommended separate consumption baskets for rural and urban areas which include food items that ensure recommended calorie, protein and fat intake, and non-food items like clothing, education, health, housing and transport. The Rangarajan Committee once again de- linked the rural and urban poverty lines. Based on its methodology, the Rangarajan

1 Committee raised the Tendulkar national rural poverty line from Rs. 816 per-capita per month at 2011-12 prices to Rs. 972 and that of the national urban poverty line up from Rs. 1000 per capita per month at 2011-12 prices to Rs. 1407 (Planning Commission, 2014). As is well known, poverty estimates are based on monthly per capita expenditure data collected systematically by NSSO in its quinquennial surveys on consumption expenditure since 1972-73. The sample size allows one to estimate poverty at state level, separately for rural and urban areas, and at NSSO region level with certain degree of confidence. The sample size does not allow estimation of poverty at district and sub-district level. Thus, due to the lack of district level poverty estimates based on NSSO consumption expenditure, the state governments are handicapped in directing their welfare and development programmes to eradicate poverty at household and area levels.

II. WHY IS POVERTY ESTIMATION REQUIRED?

A recent (March 2016) document of NITI Ayog underscores the importance of measuring poverty due to the following three mainreasons:

a. Identification of the poor through a comparison of the poverty line with household (or individual) expenditure; b. Tracking poverty in a region over time and comparing it across regions at a point in time; and c. Estimation of the required expenditure on anti-poverty programmes and their allocation across regions.

The present method of poverty estimation only helps in assessing the number of poor and the progress made in poverty reduction at the national and state levels over a period of time based on poverty level basket (PLB) of household per capita consumption expenditure. It becomes rather irrelevant for household level interventions for poverty redressal. For this state governments have been using a variety of alternative criteria to identify below poverty line (BPL) households through periodic censuses of households. The Socio-economic Caste Census 2011 (SECC-2011) is expected to be one of the leading sources of data for identification of poor households and helping them under various welfare schemes of central and state governments. However, such censuses cannot be undertaken on quinquennial basis

2 due to time and costs. These, however, can be made the basis for government interventions towards the well-being of households only for few years butcertainly not for a long period of one decade. This makes the job of policy makers all the more difficult in addressing the question of poverty due to lack of an authentic database on a yearly or biannual basis. The periodic NSSO surveys on consumption expenditure with relatively larger sample size sufficient for capturing patterns at disaggregated levels, say at district/zonal level can bridge the gap between poverty estimation and related resource allocations. However, there are many issues related to sample size and its adequacy to capture regional and social diversities, poverty estimation procedures and resource allocation for eradication of poverty.

III. APPROACHES OF ESTIMATION OF POVERTY AT DISTRICT LEVEL

1. Calculating poverty on pooled sample by using Tendulkar Committee Method

With the initiatives of Central Statistical Office (CSO), Government of India, various state governments have started compilation and pooling of both central and state samples of NSSO rounds on consumption expenditure (Schedule 1.0) and employment and unemployment (Schedule 10.0). With the help of pooled samples it is possible to make a robust estimation at a more disaggregated level, such as regional or district levels. The Department of Statistics, Government of Uttarakhand has pooled the census and state sample data of NSSO for 68th Round (2011-12). Keeping in view the available methods of poverty estimation, we have estimated district-wise poverty in Uttarakhand by broadly following the Tendulkar Committee approach. However, we can also provide alternative estimates of poverty by using the method of latest Rangarajan Committee (2014). This would require a reasonably larger sample size of households in each district of Uttarakhand. Experts have argued that for a large number of districts in the country it is possible to make district level poverty estimates (Sastry, 2003). The NSSO’s central sample size for Uttarakhand in its 68thRound on Household Consumption Expenditure was 1048 households in rural areas and 736 households in urban areas of the state. The state sample size was almost similar to the central sample size. Thus, double sample size definitely helps in estimation of poverty and its reliability at least at the district level. The details of district-wise sample size of 68th NSSO Round (central, state and pooled) are given in Chapter 5 on district-wise estimation of poverty.

3 One of the major limitations of the Tendulkar Committee method, particularly in the context of hill areas, is that by taking urban poverty line basket of household per capita consumption to estimate poverty in rural areas, it fails to capture the high cost of living for rural population in hill areas (Papola, 2002).

2. Calculating poverty by using Tendulkar Committee approach through small area estimation approach Small area typically refers to the part of a population for which reliable statistics of interest cannot be produced due to small sample sizes. Demands for reliable small area statistics (SAS) are increasing with growing governments’concerns over issues relating to distribution, equity and disparity. One can apply this (Tendulkar Committee) method also for obtaining district level poverty estimates for area level models and provide the estimation procedure, along with the method of obtaining the estimates of Mean Square Error (MSEs) of estimated parameters. However, such methods suffer from several limitations and are generally not helpful in implementing poverty alleviation programmes at household and sub-regional levels within a district.

3. Calculating multidimensional poverty by using Socio-economic Caste Census data The estimation of poverty based on calorie intake and then converting it into monetary value has been criticised for its inadequacy in capturing various forms of drudgeries, vulnerabilities of livelihoods and higher cost of living in mountain areas (Papola, 2002). For example, while using urban consumption expenditure basket for estimation of rural poverty by Tendulkar Committee, the estimates of percentage of poor in rural areas of Uttarakhand turned out to be substantially low at 32.2 per cent during the year 2004-05 as compared to earlier estimates by the Planning Commission using Lakdawala method (39.6 per cent). This was mainly due to the fact that cost of living in rural as well as urban areas in hill regions is comparatively much higher than in plain urban areas. Due to lack of price adjustment for cost of living separately for hill areas, poverty levels generally come down, and, thus could provide misleading conclusions.

It is now a well established fact that poverty is largely multi-dimensional in its nature (Radhakrishna et. al., 2010; Alkrine, 2009, Papola, 2002). Apart from low levels of consumption (calorie intake), a household may face severe deprivations in terms of

4 ownership of productive assets, availability and quality of employment, education, health, communication, accessibility to facilities and geographic conditions. A sizeable number of households in mountain areas including Uttarakhand suffer from such deprivations, more so in hill regions (Papola, 2002). The estimates of multi-dimensional poverty could provide useful insights on poverty in Uttarakhand.

4. Limitations of consumption-based approach of estimation of poverty in mountain areas Calorie intake based poverty estimates are generally criticized for their limitations to capture various forms of poverty, particularly in the context of hill/mountain regions. It is well known that for populations living in mountain areas it is absolutely necessary to have a higher minimum energy and calorie intake apart from requirement of minimum clothing, including warm clothing and permanent shelter, to protect themselves from the extremities of weather and climate as compared to those living in plain areas (Papola, 2002). For example, energy requirement for traveling a distance of one km in hill areas is far more than in plain areas. Thus, the use of common consumption norms to measure the well-being of people along these parameters generally places many people in hills/mountains above the poverty line even without fulfilling their basic needs (Papola, 2002). Papola (2002) shows how a poverty line taking into account (i) higher energy/calorie intake, (ii) greater non-food needs such asclothing and shelter for survival, and (iii) higher prices prevalent in mountain areas, jumps up by about 70 per cent compared to plain areas. The poverty ratios based on state price index are alsoproblematic as they do not capture the local cost of living, particularly in hill areas. This is simply associated with the high cost of transportation of goods and services to mountain areas as compared to plain areas.

Calculation of poverty based on multidimensional approach too is not free from its limitations. It ignores the quality of productive assets such as land. Although landlessness is not a major issue in hill areas such as in Uttarakhand, yet the quality of land differs in terms of its size and spread. More than one-tenth of land holdings in the hill districts of Uttarakhand are less than 0.25 hectare size, which could be termed almost landless; another half of the land holdings are between 0.25 to 0.5 hectare sizes (Mamgain, 2004). Similarly, the productivity of agricultural land is abysmally low (less than half) in hill areasas compared to plain areas (Mamgain, 2004). Thus, the condition of most people engaged in agriculture in

5 the hill districts is not much different than those working as agricultural labour in the plain districts.

Malnutrition is generally high among population residing in hill areas as compared to those living in plain areas. Hilly terrain imposes an additional burden on people’s health and nutrition, and aggravates the problem of under-nutrition (ICIMOD, 2016). A study by International Centre for Integrated Mountain Development (ICIMOD) (2016) estimated lower calorie intake among hill population in the north-eastern region of India (for rural areas 2,098 kcal/day per capita in hill areas vs. national rural average of 2,147 kcal/ day; for urban areas 2092 vs. 2123, respectively). Using the child malnutrition parameterfor estimation of poverty inIndian states, Radhakrishna et.al., (2010) show a jump in the percentage of poor households to over 71 per cent in rural areas and 48 per cent in urban areas of Uttarakhand during the year 2004-05. These ratios are very high as compared to Himachal Pradesh (57.7 per cent for rural areas and 30.7 per cent in rural areas) but marginally lower than national average. However, the nutritional norm of poverty measurement is not free from criticism. It is argued how per capita calorie intake among richer sections of population has been decreasing and that for poor sections improving over the years though not substantially, both in rural and urban areas. This requires a broader approach as calorie norm may no longer be relevant nowadays for defining the minimum subsistence (Suryanarayana, 2010).

In brief, poverty is a multidimensional phenomenon that goes beyond inadequate income to include deprivation of basic human capability including education, health and living standards (Alkire, and Robles, 2015). In recent years asound body of literature has emerged in estimating poverty by using the multidimensional approach (see Alkire and Foster, 2011). Calculation of multidimensional poverty requires comprehensive data about households on their economic, social, and regional dimensions. However, availability of such detailed data and that too on reasonably short intervals at a more disaggregated level such as district-wise orCD Block-wise, is a major concern while making poverty estimates. Nonetheless, poverty estimates, as mentioned earlier, are very useful to understand the progress of an economy and society and act as a guiding principle in resource allocations and interventions.

6 IV. POLICY INITIATIVES1

Towards accelerating balanced regional development in the country, development of hill areas has been a policy priority in the national planning process since long. For the first time, a Special Hill Area Development Programme for the development of hill regions in the country was initiated in the Sixth Plan period and it has since continued in subsequent plans. Uttarakhand was accorded a special category status in 2002 by the Planning Commission. The state government undertook several policy measures and programmes for the development of Uttarakhand. Some of the state government’s initiatives are critically examined in the following sections.

Under its industrial policy, the state government provided several incentives in the form of tax concessions, concessional finance, industrial plots and other basic infrastructure to attract industries. These measures led to tremendous progress in industrial development in Uttarakhand albeit in the plains. The number of industries registered under the Factories Sector Act increased by over seven times from 698 in 2001-02 to 2843 in 2011-12. Employment in these factories jumped 8.4 times from 40880 to 342385 during this period (CSO, ASI data).

Unfortunately, the industrial development policy of the state remained skewed infavour of plain areas. Since the industrial policy could hardly benefit hill areas in terms of attracting industries therein, a separate Hill Industrial Development Policy was announced in 2008 to attract industries to the hill districts. However, this policy remained anon-starter till 2011, when Government of Uttarakhand amended the 2008 policy and extended special incentives like upto 90 per cent tax rebate, transport subsidy and rebate on power tariff till 2025. It also decided to set up 11 industrial hubs at district headquarters in hilly districts. Notwithstandinginitial hiccups, the policy picked up momentum and began attracting industries and investment in the state though not on the desired scale. The policy also facilitated creation of over 3000 small (mainly micro) units and provided employment for over 10500 people. MSMEs were mainly created in the herbal, floriculture, flour mills,

1 This section draws on Mamgain and Reddy, 2016.

7 handlooms, mineral water, pharmaceuticals, auto repair and steel fabrication. Between April 2012 and November 2013, 763 new units were set up, attracting investments of USD 11.6 million employing a total of 2,690 people (India Brand Equity Foundation, 2014). There are several issues related to creation of quality infrastructure such as roads, industrial plots, buildings and power supply which still need to be addressed.

The state government’s Veer Chandra Singh Garhwali Paryatan Swarozgar Yojana (Veer Garhwali Tourism self-employment scheme) for promoting tourism related enterprise development is a credit-cum-subsidy scheme under which assistance is given for fast food centres, setting up of retail outlets for local handicrafts, transport, motels, hotels, equipment for adventure sports, setting up of tourist information centres with PCs, restaurants, and so on. However, the potential of tourism and other related activities has yet to be harnessed fully for creation of employment and income in the hill districts of Uttarakhand. At present, most of the tourism is religious in nature, and itwas severely affected due to the disaster in Kedar valley in June 2013. There are several places and locations in hill districts which are yet to be explored and developed fully for attracting tourist inflows into the region. There isserious lack of quality road connectivity, suitable accommodation, drinking water and trained human resources. Little is known about state-sponsored skill development initiatives, particularly in the rural areas of the state.

The experience of implementation of public employment programmes, namely, Mahatma Gandhi National Rural Employment Guarantee Programme (MGNREGA) has been amixed one. Though employment was provided to almost all demanding households, it could provide only about 41 days of employment as against the guarantee of 100 days. In hill region, about half of employment generated was performed by women, whereas in plain region, the share of women was less than 23 per cent. Also, the implementation of MNREGA in Uttarakhand has been criticized by villagers due to irregular availability of work and delays in payment of wages.

The experience of Swarnjayanti Gram SwarojgarYojana (SGSY) or Golden Jubilee village self-employment scheme, and its recent format, National Livelihood Mission (also

8 called Aajivika Mission) in creation of self-employment has also been a mixed one. The State Rural Livelihood Mission was started with the primary objective of reducing poverty by enabling poor households to access gainful self-employment and skilled wage employment opportunities, resulting in appreciable improvement in their livelihoods on a sustainable basis, through building strong grassroots institutions for the poor.

However, there has been very little visible progress towards improving livelihoods, particularly in hill districts of the state, despite the existence of several development programmes aimed at improving income and reducing poverty and vulnerability. Mamgain and Reddy (2016) show how in their sample villages there was hardly any evidence of use of better farming practices in crop production, horticulture, poultry, dairy and fishery production. This is mainly due to lack of agricultural extension services available to villagers to improve their farm practices and productivity. Hardly any upscaling efforts are being made to improve farming practices and small enterprise development in a large part of Hill Region. This has resulted in an ever-increasing exodus from hill areas of Uttarakhand in recent years.

V. OBJECTIVES OF THE STUDY

Keeping in view the Terms of Reference (ToR) of Department of Economics and Statistics (DES), Government of Uttarakhand, the present study aims to generate district-wise poverty estimates, separately for rural and urban areas for Uttarakhand. It also aims to provide poverty estimates for various social groups across hill and plain areas in the state. The study also makes a critical analysis of poverty and inequality and offers few suggestions. Given the constraints of access to other data sources, such as SECC and NFHS-4, the present exercise of poverty estimation is largely based on NSSO 68th round pooled data on consumption expenditure for Uttarakhand for the year 2011-12.

VI. CHAPTER PLAN

Apart from the introductory chapter, an overview of the Uttarakhand economy is presented in Chapter II. It brings out significant regional disparities in various development indicators, particularly in the context of hill and plain areas of the state. Chapter III provides measures of absolute deprivation and inequality at the macro, sectoral and district levels. It deals with

9 the extent of inclusion of different social groups with reference to robust measures of average and extent of deprivation among them. Chapter IV gives the estimates of district-wise poverty and inequality based on the pooled data of central and state samples of NSSO 68th Round Consumption Expenditure Survey data for the year 2011-12. Chapter V analyses the nature and quality of employment in Uttarakhand and related income inequalities. It argues that due to poor quality of employment, most households resort to long duration migration which is not making any significant multiplier impact on the local economy, particularly in source areas (hill districts). The last Chapter VI provides summary and conclusions and related policy implications.

10 Chapter - II

UTTARAKHAND ECONOMY: AN OVERVIEW2

I. INTRODUCTION

Increase in income inequalities is a distinct feature of economic growth in India and its regions over the last six decades of its development planning (Planning Commission, 2013). The persistence of such inequalities is largely attributable to the slow pace of development of basic economic and social infrastructure across several regions and unequal access to income opportunities. This has fuelled demands for smaller states from time to time. The arguments in support of small states were linked to better governance and resulting economic efficiency in the use of state resources leading to improved income opportunities. The genesis of Uttarakhand on November 9, 2000,as a new state of the Indian Union from Uttar Pradesh is also largely linked with the economic backwardness of the region. The major aspirations of common people from the new state included, among others, creation of better employment opportunities to arrest the existing large scale out-migration of able-bodied youth, mainly educated males, from the Hill Regions3 of Uttarakhand. Other expectations included improved access to infrastructure facilities such as electricity, road, telecommunications, health, education, and better governance to lead to better living conditions for the peopleofthe state in general and in hill districts in particular (Mamgain, 2004).

The development experience of Uttarakhand over nearly one and half decade with respect to achieving high economic growth and reduction in the poverty has been quite encouraging. However, the economic growth is mainly centred in the three plainsdistricts while the ten hill districts remain far behind in this increasing economic prosperity (GoUK, 2013-14Annual Plan). Most of the economic opportunities have tended to concentrate in plain areas of the state. As a result, the population in Hill Region of the state has yet to struggle hard for eking out livelihoods largely from agriculture by involving large numbers of their household into the labour force (Mamgain, 2004). Consequently, the pace of out-

2 This chapter draws substantively from Mamgain and Reddy (2016). The first author is one of the authors of this report. 3Ten districts with hilly terrain namely, , , Chamoli, , Nainital, , Pauri Garhwal, , Tehri Garhwal and Uttarkashi are referred as Hill Region. the remaining three districts, namely, Dehradun, Hardwar and Udham Singh Nagar are in the plain areas of Uttarakhand.

11 migration could not slow down from the hill districts; rather it has accelerated during the recent years, as reflected in Population Census 2011. A very slow growth of population in most of the hill districts, and an absolute decline of 17,868 persons in the population of Almora and Pauri Garhwal districts between 2001 and 2011 is a testimony of huge out- migration (Mamgain and Reddy, 2016). Historically, these districts have had well developed social indicators in comparison to many other districts. The extent of out-migration has been so huge that many villages are left with single-digit populations in 2011. In brief, there are significant regional inequalities in Uttarakhand, which have perpetuated over the years.

In this chapter we present a brief overview of Uttarakhand economy with special focus on regional growth and inequalities on select indicators of development. After the brief introduction, Section II portrays growth and structure of income and regional inequalities in Uttarakhand. The demographic features and changes therein are analysedin Section III with a concern on distress-driven out-migration due to lack of opportunities for economic and social development in the ten hill districts. In Sections V and VI we examine the social progress in education, health and basic amenities in the state. The last Section VII sums up the major points emerging from our analysis.

II. GROWTH AND REGIONAL INEQUALITIES

In this section we have analysed the pattern and structure of economic growth and regional inequalities in Uttarakhand to understand the dynamics of growth, employment and poverty. Since its formation, Uttarakhand has witnessed an impressive growth of over 9 per cent in its gross state domestic product (GSDP) during the period 2001-02 to 2011-12 (at 2004-05 prices). As a result, real per capita income of the state almost increased 4.5 times from Rs. 19,164 in 2001-02 to Rs. 92,911 in 2011-12. The per capita income in Uttarakhand has bypassed the national level income since 2005-06 onwards and that in Himachal Pradesh, since 2008-2009. The per capita income in Uttarakhand is more than three times that of its parent state, Uttar Pradesh (Fig. 2.1) (Mamgain and Reddy, 2016).This progress definitely justifies the argument of formation of smaller states like Uttarakhand for faster development.

12 Note:For years 2000-2001 to 2004-2005, at 1999-2000 prices; for the period 2004-05 to 2011-12, at 2004-2005 prices; for the period 2011-12 to 2015-16, at 2011-12 prices.

Source:Calculated from CSO Data.

A look into the composition of the economic growth of the state shows that it is largely contributed by a rapid growth of GSDP in secondary and tertiary sectors. However, in recent years the growth of secondary sector hovered around 12 per cent and that of services sector at around 8 to 9 per cent. Growth in agriculture sector was low yet fluctuated over the years. As a result, the structure of GSDP has changed considerably in the state. The share of agriculture in GSDP declined substantially by about 17 percentage points-- from 27 per cent in 2000-01 to 9.8 per cent in 2013-14. The corresponding increase of about 17 percentage points was in the share of secondary sector and another 10 percentage points in case of service sector (Figure 2.2). The credit for this impressive growth largely goes to the Industrial Policy of Uttarakhand which provided several incentives to attract private industries in the state.

13 Fig. 2.2: Sectoral Composition % of GSDP in Uttarakhand (2002-14) at 2004-05 Prices

Source: Authors’ calculation based on CSO Data.

Regional Disparities in Per Capita Income

The impressive economic growth in Uttarakhand has been unevenly distributed across its districts. Income inequalities across the hill and plain districts are revealing:For example, per capita income (measured in terms of per capita net district domestic product) in is about 2.5 times less than that in Dehradun and Udham Singh Nagardistricts (Figure 2.3). All the hill districts except Nainital have per capita district domestic product much less than the state average. Surprisingly, , well known for its tourism, also has low income. One of the explanations for it could that income from services is not generally reflected in the district domestic product figures. Reasons for such income inequality could be easily explained with the pattern of enterprise development in Uttarakhand. According to the Sixth Economic Census, 2013, 41.7 per cent of income generating enterprises (excluding crop production, plantation, defence and compulsory social security activities) are located in three plains districts, whereas the population in hill districts is mainly dependent on

14 agriculture and allied activities and that too largely as subsistence with abysmally low levels of productivity (Mamgain, 2004).

Fig. 2.3: Per capita Net District Domestic Product, 2012-13 (at 2004-05 prices) (Rs. ‘00)

Source: Directorate of Economics and Statistics, Government of Uttarakhand.

The Socio-economic Caste Census-2011 data throws up an interesting picture about the monthly income of a highest earning member of a household in rural areas. Though such income data suffer with the limitations of under-reporting and intensive probe on the part of surveyors, however it brings out interesting patterns of income distribution of highest earning members among rural households. The data show a highest 80 per cent of rural households in Uttarakashi having less than Rs. 5000 monthly income of their highest earning members. Other districts with such low income of rural households are Almora, Champawat and Tehri Garhwal. The lowest proportion of such rural households was in Dehradun and Rudraprayag districts. While has the advantage of urbanization as well as tourism, Rudraprayag district has the advantage of tourism. As compared to India, the proportion of low earning member households is significantly lower in Uttarakhand (Table 2.1). Similarly, the proportion of rural households with a highest monthly income range of more than Rs. 10,000 was almost double in Uttarakhand as compared to the national average. The proportion of such high income rural households significantly varies across districts of the state with Dehradun on the top (27 per cent) and Tehri Garhwal at the bottom (9.6 per cent). Such variations in monthly income of highest earning members in rural households can partly be explained with the relatively higher proportion of rural population in salaried jobs in

15 districts having higher proportion of middle and high income range households. The variations in the range of monthly household income across districts also indicate the limitations of per capita income based on district domestic product.

Table 2.1: Distribution of Rural Households by Monthly Income of Highest Earning Member (Rs.) District Less than Rs. 5,000 Between Rs. 5,000 Rs. 10,000 or more and Rs 10,000 Uttarkashi 80.10 9.05 10.84 Chamoli 60.07 24.21 15.72 Rudraprayag 53.74 31.32 14.94 Tehri Garhwal 70.94 19.47 9.59 Dehradun 48.95 23.95 27.10 Pauri Garhwal 59.17 23.87 16.96 Pithoragarh 62.83 19.78 17.39 Bageshwar 66.37 20.99 12.64 Almora 73.30 16.24 10.47 Champawat 73.12 14.03 12.85 Nainital 61.78 20.90 17.31 Udham Singh Nagar 65.02 22.24 12.74 Hardwar 62.56 27.00 10.44 State Total 63.41 21.86 14.72 All India 74.52 17.18 8.25

Source: Socio-economic Caste Census, 2011.

Incidence of Poverty

The incidence of poverty declined significantly in Uttarakhand along with its high economic growth. The percentage of poor population in the state decreased to 11.3 per cent in 2011-12 from 31.8 per cent in 2004-05 (Planning Commission, 2007, 2014).This could be possible due to improved distribution of food grains through public distribution system in the state and partly due to improved incomes of rural households through public employment programmes. The state has definitely performed well in poverty reduction as compared to its parent state,

16 Uttar Pradesh (see Table 3.8 in chapter III. Poverty and inequality are analysed in details in Chapters III and IV).

III. DEMOGRAPHIC CHANGES IN UTTARAKHAND

Population Growth

With a population of 10.09 million in 2011, Uttarakhand ranked at 20th position among Indian states. Nearly 70 per cent of the state’spopulation lives in its rural areas. About 48.4 per cent of the population resides in ten hill districts (generally referred as Hill Region). Thus, more than half of the state’s population resides in the remaining three districts of Hardwar, Dehradun and Udham Singh Nagar (Table 2.2) The state has witnessed significant changes in its demographic structure, particularly during the decade of 2001-2011—a period of high economic growth. It has registered a moderate growth in its population (1.74 per cent per annum) during the decade 2001-11, which is comparatively higher than the national average. However, the Hill Regionwitnessed much lower growth in population (0.70 per cent) as compared to plains districts (2.74 per cent). Much of this growth in population in plains districts is contributed by migration from hill districts and also from the neighbouring Uttar Pradesh. In fact, there has been an absolute decline in population in two districts -- Almora and Pauri Garhwal during the period 2001-2011 (registering a negative compound annual growth of -0.13 and -0.14 respectively). Other hill districts with very low population growths are Tehri Garhwal, Bageshwar, Chamoli, Rudraprayag and Pithoragarh. Population growth of over 2.27 per cent in is largely centeredaround the area, falling in the plain areas of the district. Overall, the share of Hill Regionin the population of Uttarakhand has declined substantially by about five percentage points between 2001 and 2011 (Mamgain and Reddy, 2016). While population in Hill Region predominantly resides in rural areas, a sizeable 42 per cent of population in three plain districts of the state resides in urban areas. In other words, these three districts have emerged as predominant centres of economic activities in Uttarakhand.

There has been a notable change in the social composition of population across the hills and plain regions of the state. SCs and STs constitute over 21.6 per cent of total population of Uttarakhand (Table 2.2). The share of SCs in the population of the state has increased from 17.8 per cent in 2001 to 18.7 per cent in 2011. The opposite is true in case of STs. The proportion of SC population is comparatively more in hill region which increased

17 by almost one percentage point over 2001. The opposite is true for STs, whose share in hill region population declined substantially during the decade 2001-2011 (Mamgain and Reddy, 2016). SC/STs are proportionately low in Uttarakhand as compared to national average and much lower than the neighbouring Himachal Pradesh state (Fig. 2.4), implying lesser magnitude of vulnerable population in the state.

Table 2.2: Select Demographic Features of Uttarakhand and India, 2011 Sl. No. Variable Uttarakhand India Hill areas Plain areas Total 1. Population (in million) 48.50 52.36 100.86 1210.86 2. 0-6 years population (%) 13.18 13.68 13.44 13.60 3. Population growth rate 0.70 2.82 1.74 1.64 (2001-2011) 4. Sex ratio (all age 1037 900 963 943 groups) 5. Sex ratio (0-6 age 894 888 890 919 group) 6. SC population (%) 20.91 16.78 18.76 16.6 7. ST population (%) 1.05 4.60 2.89 8.6 8. Muslim population (%) 3.80 23.35 13.95 14.23 9. Urban population (%) 17.06 42.43 30.23 31.2 10. Literacy Rate (%) 80.87 76.90 78.82 73.0 11. %Workers (main plus 43.71 33.47 38.39 39.8 marginal) in total population (WPR) 12. WPR- Male 48.32 50.84 49.67 53.3 13 WPR-Female 39.26 14.16 26.68 25.5

Source: Calculated from Primary Census Abstract, India and Uttarakhand, 2011.

The proportion of SCs, STs and varies substantially across the districts of Uttarakhand. Over one-fourth of population in Bageshwar, Pithoragarh, Uttarkashi and Almora belong to SCs. Udham Singh Nagar, Tehri Garhwal and Pauri Garhwal districts have comparatively lesser proportion of SC population (Annexure Table 2.2). Thehighest percentage of ST population is in Udham Singh Nagar district (7.46%) followed by Dehradun (6.58%). Muslims constitute nearly 14 per cent of the total population in Uttarakhand. Their share is highest (over 34 per cent) in Hardwar district and lowest (0.55) in . Muslim population is largely concentrated in the plain areas of the state. Together, the SC, ST and Muslim population, is as high as 56 per cent of population in Hardwar district. In the three plains districts, the three groups constitute 44.7 per cent of population. Evidence shows a higher incidence of poverty among SCs and STs across the country (Thorat and Dube,

18 2013). It is also true in case of Uttarakhand and, it underlines the magnitude of vulnerability, particularly in districts with higher proportion of such population. In other words, a huge diversity in the socio-religious composition of population across various districts in Uttarakhand has implications for poverty and welfare measuresbe undertaken by the government in the state.

Note: UP=Uttar Pradesh, HP=Himachal Pradesh, UK=Uttarakhand. Source: Primary Census Abstract, 2011, Registrar General of India, New .

Age Composition and Dependency

The age-composition of the population varies across districts in Uttarakhand. Proportionately children (0-14 years) are more in Uttarakashi, Champawat, Hardwar and Udham Singh Nagar districts. The proportionof the aged population (above 60 years) is highest in Pauri Garhwal and Almora districts (over 12 per cent). The share of aged population is comparatively higher in hill region of the state. Nearly 60 per cent of the population is in the age-group 15-59 years and itsproportion does not vary significantly across various districts except in Dehradun (63.7 per cent) (Figure 2.5, Annexure Table 2.3). However, the proportion is comparatively low in hill districts as compared to plain districts. In other words, the higher proportion of children and older population reflects the high dependency ratio requiring more resources to support the dependent population.

19 Source:Census of India, 2011

Literacy Rate

With a literacy rate of over 78.8 per cent, Uttarakhand is much ahead of thenational average (73 per cent). Literacy level of population in hill areas ismuch higher than in plain areas of the state; however, such differences have significantly reduced over the last decade with a faster improvement in literacy levels in the plains districts too. Gender-wise, literacy level of females is lower than males both in hills and plains, but more so in plain areas (Fig. 2.6) (Annexure Table 2.4). However, the state still lags behindits neighbouring hill state, Himachal Pradesh in literacy levels.

Source:Census of India, 2011.

20 Outmigration and its Magnitude

Over one-fourth of population in Uttarakhand was migrant population in 2011. It did not include those who had migrated due to marriage. This ratio is quite high compared to the all- India figure of about 19 per cent. Gender-wise, the incidence of migration, excludingmarriage related, is high among males (nearly 28 per cent males are migrants) (Table 2.3). Empirical studies show that out-migration (i.e. people moving away from a given region to other regions for employment, education and better quality of life)is a widespread phenomenon in Uttarakhand, particularly in the Hill Region, and more so in the previous decade, 2001-2011.

Table 2.3: Share of Migrant Population in Uttarakhand@ State/Region Persons Males Females Uttarakhand Total 24.8 27.8 20.9 Rural 21.9 26.4 17.4 Urban 25.4 29.6 21.4 India Total 19.0 21.7 16.1 Rural 14.9 17.6 12.1 Urban 19.9 22.4 17.2

Note:@ Population Census defines migrants as those persons whose place of enumeration is different than their place of last residence. These migration figures exclude migration due to marriage. Among the total migrant population about 42.6 per cent migrated due to marriage. Source:Calculated from Population Census, 2011, D-5 series (provisional)

A net decline in population of Almora and Pauri Garhwal districts between 2001 and 2011, and a very slow growth of population in other hill districts is a testimony of oumigration from hill areas of the state (Mamgain and Reddy, 2016). A maximum absolute decline in population is witnessed in small villages, which inhibited a large share of population. The magnitude is so huge and widespread that about 375 villages representing 2.75 per cent of total villages in the Hill Region stand almost abandoned as a result of out- migration. These villages have nearly turned into “ghost villages” (Mamgain and Reddy, 2016). Although, there has been a history of high incidence of migration from Hill Region yet a large number of migrants tended to return to their villages at a later period. This process of return migration seems to have stopped now. A number of studies in the past show out-

21 migration as a widespread phenomenon among rural households in the Hill Region of Uttarakhand (Bora, 1996; Mamgain, 2004; Mamgain and Reddy, 2016; Mehta, 2016). More recently, Mamgain and Reddy (2015) show as high as 88 per cent of sample rural households reporting at least one member migrating for employment from the villages in Pauri Garhwal and Almora districts. Most of the migrants are educated young men belonging to higher castes in the hill districts of Uttarakhand. The percentage of SCs is proportionately less among migrants. This is mainly due to weak social networks of SCs at the place of destination. However, their proportion among migrants has substantially increased in recent years.

The reasons for migration excluding marriage largely include employment, education and better quality of life. According to Population Census, 2011, nearly 40 per cent of male population in Uttarakhand migrated for work and another 5.5 per cent for education. This proportion is much higher than the national average (31.3 per cent) (RGI, 2017). As muchas 64 per cent of females and 33.3 per cent of males moved along with their households within Uttarakhand, mainly to urban areas. This also reconfirms the findings of micro studies about a large number of households moving out of the villages to urban areas of the state or other parts of the country. Mehta (2016) has showedthat nearly three-fourths of migrants from the hill districts have migrated outside Uttarakhand.

Yet another dimension pertains to complete outmigration of households from villages. Mamgain and Reddy (2016) show how over half of the number of existing households in their sample villages had permanently out-migrated over the last decade. One can see a number of locked and depilated houses and barren parcels of erstwhile cultivated land in several villages in the hill districts of Uttarakhand. Almost half of the Brahmin households have out-migrated completely from their villages both in Pauri Garhwal and Almora districts. The trend is much less among SC households, mainly due to their poor incomes.

The impact of migration on local economy and society has been significant. Most of the migrants from hill region could get employment in low paid salaried jobs such as domestic helps, security guards, peons, office attendants, etc. Remittances by them contribute significantly (about 26 per cent) to migrant households’ incomes. These are particularly crucial in poor and relatively low income group households,contributing nearly 50 per cent and 38 per cent of household incomes in their native places. If we include the income from pension, which of course is income largely from return migration, the household income rises by nearly 40 per cent (Mamgain, et al. 2005). However, remittance income is largely spent on

22 daily consumption requirements. The other important heads under which remittance income is spent include education and health. Since the average amount of remittances are small, these are hardly able to generate any multiplier effect at the village economy level except opening up of a few grocery shops to serve the consumer demand. Moreover, the consumer items sold in such grocery shops are mostly procured from outside the hill region. Even vegetables and milk and milk products, which were earlier available within villages, are nowprocured from plain areas of the state. Thus, remittances used to finance such consumption are again ploughed back to plain areas and areunable to create any multiplier impact in the local village economy (Mamgain and Reddy, 2016).

IV. EDUCATION DEVELOPMENT IN UTTARAKHAND

Education is regarded as an important asset for the overall well-being of human beings. It significantly contributes to the economic growth (Shultz, 1961). Dreze and Sen (1986) argue that literacy is a basic tool of self-defence in a society where social interaction often involves the written media. Similarly, education and social change are closely inter-linked (Ramchandran, 1997). Education is also regarded as an important driver for attaining inclusive development (Planning Commission, 2007). This section presents the educational development of population in Uttarakhand from the perspective of its role in poverty eradication and income generation.

Literacy Levels

Uttarakhand has made tremendous progress in improving literacy levels during the past five decades. Literacy level in the state has jumped by more than four times from 18 per cent in 1961 to 78.8 per cent in 2011. The pace of improvement in literacy has been much faster in the state than the all India average. In 1961, literacy rate in Uttarakhand was 18 per cent compared to the all-India level of 28 per cent. This pattern has not only reversed butby 2011 the literacy rate in Uttarakhand stands six percentage points higher than the all India level. However, literacy in the state is much lower than in Kerala and Himachal Pradesh at 82.8 per cent, but ishigher than Uttar Pradesh (67.7) by 11 percentage points (Fig 2.7).

23 Source: Census of India, 2011

Region–wise, literacy rate in hill districts was higher by about six percentage points than plains districts (Table 2.4). Such difference has narrowed substantially over the last decade 2001-2011. District-wise, Dehradun ranks at top in literacy levelwhereas Udham Singh Nagar has the lowest literacy level, lagging behind Dehradun by about 10 percentage points. Gender gap in literacy rates is highest in Uttarkashi (26.4 percentage points), followed by Tehri Garhwal, Champawat, Rudraprayag and Chamoli (Figure 2.8).

24 Table 2.4: Literacy Rate in Uttarakhand, 2011 (7 years and above population)

Region Person Male Female

Hill 80.9 91.6 70.8

Plain 76.9 83.8 69.2

Total 78.8 87.4 70.0

Source: Census of India, 2011

Educational Attainments of Working Age Population

With the expansion of educational facilities the educational levels of Uttarakhand population has improved at a faster pace as compared to many Indian states, thereby placing it above the national average on this indicator of development. We have specifically considered here the 15-59 age-group of population for explaining their educational attainments and regional differences therein.

About one-fifth of working age population (15-59 yrs.) was illiterate in Uttarakhand in 2011. A fairly high 43 per cent of population had had secondary and above level education (Table 2.5). Over 14 per cent of the working age population had graduate and abovelevel education. As expected, the proportion of illiterate persons is much less among youth (15-29 yrs.) population as compared to those in higher age-group 30-59 years. About half of the youth population was educated as compared to nearly 36 per cent in the age-group 30-59 years. The proportion of persons with technical diploma was low but more so in the age-group 30-59 years. This also shows a need for expanding access to diploma level education for improving the employability of population in the state, particularly that of youth.

25 Table2.5: Educational Level of Population, 2011

Age-group (yrs.) Educational level 15-29 30-59 15-59 Illiterate 9.95 29.69 20.20 Literate without educational level 1.48 2.15 1.83 Below Primary 2.33 3.15 2.76 Primary 12.87 14.73 13.83 Middle 23.35 14.32 18.66 Secondary 21.00 11.08 15.85 Hr. Secondary 14.98 9.06 11.91 Non-tech diploma 0.07 0.07 0.07 Tech. diploma 0.69 0.41 0.55 Graduate and above 13.13 15.14 14.18 Unspecified 0.14 0.20 0.17 Educated (Secondary and above) 49.88 35.76 42.55 Source: Calculated fromPopulation Census-Uttarakhand, 2011

Let us look at the share of population with secondary and above education. This is important as after secondary level education, vistas are open for various educational streams. At this stage, education and its quality turns out to be a major determinant of occupational diversification and earnings of an individual in the labour market (Mamgain, 2017). Viewed from this perspective, about half of the youth population possessed secondary and above education in 2011. However, there are sizeable differences of such human capital among youth across the districts in Uttarakhand—ranging between the highest 63.3 per cent in Pauri Garhwal to lowest 40 per cent in Hardwar. The other plains district, Udham Singh Nagar also lags behind on this indicator by remaining second last in the ranking of districts (Fig 2.9). The proportion of graduates and above ranged from a highest 20.3 per cent in Dehradun tolowest 8.7 per cent in Bageshwar. There were only four districts-- Dehradun, Nainital, Chamoli and Pauri Garhwal -- lying above the state average of graduates among youth.

26 Fig. 2.9: Percentage of Persons with Secondary and above Education among Youth (15-29 yrs), 2011

Source : Population Census-Uttarakhand, 2011

Access to Quality Education: A Big Challenge

Uttarakhand has witnessed a huge growth in the number of higher and technical educational institutions in recent years. But such growth is concentrated in few areas. More so, the anecdotal experience shows that access to such higher professional and technical education institutions is extremely poor for students belonging to remote and less developed regions in Uttarakhand.. Educational development in Uttarakhand, like any other state in India, is facing thetough challenge of employability of its graduates (World Bank, 2011). There is a lack of quality technical institutions such as ITIs for providing job oriented education at the lower spectrum of skill training in the state. Thus, many students are forced to quit education in desperation. Further, many of the trades being taught in these institutions have hardly any market demand and region-specificity. This results in higher incidence of unemployment among the graduates of these institutions (Mathur and Mamgain, 2004).

There is a great gap in the quality of school education in government schools and private schools and between rural and urban areas. In many cases education in government schools has become a subject of neglect. These schools are generally criticized for deterioration in thequality of education. Many of the schools in remote areas face anacute

27 shortage of teaching resources. There is a rapid growth in private schools with most of them providing quality education, particularly in the urban areas. This has created a big gap in the output from these institutions and those run by government. Thus, the educational outcome particularly from rural areas of the state is facing a big challenge in finding place in competitive education and labour markets. As a result, many of the pass outs from these institutions are turning into lowly educated and trained individuals landing in low paid occupations.

In brief, apart from achieving 100 per cent literacy levels, Uttarakhand requires a massive expansion of its educational infrastructure for skill development so as to prepare its population for future skill demands. Since the state has a comparative advantage in terms higher educational levels of its youth, it would require lesser efforts to harness this advantage.

V. HEALTH AND BASIC AMENITIES

Health is one of the important dimensions of human well-being and measuring multidimensional poverty as well. It is well documented how poor health of household members perpetuates poverty, especially when they have to bear the burden of their health care due to lack of public health facilities (Sen and Dreze, 2013; Krishna, 2010) The condition of Uttarakhand on select health indicators is mixed when compared with neighbouring Himachal Pradesh and Uttar Pradesh, and India. For example, total fertility rate and infant mortality rate in the state are almost similar to the national average but quite higher than Himachal Pradesh. With regards to institutional births irrespective of public or private facility, Uttarakhand and Uttar Pradesh are at similar stage (about 68 per cent), which is much behind Himachal Pradesh and national average at 76.7 per cent and 78.9 per cent respectively (Table 2.6). As regards child health, the position of Uttarakhand is comparatively better than national average but substantially behind Himachal Pradesh. More worrisome is the high percentage of severely wasted children (weight-for-height) in Uttarakhand (9 per cent) as compared to Uttar Pradesh, necessitating targeted interventions on a larger and wider scale. Nonetheless, Uttarakhand has made significant progress in terms of access to improved drinking water and sanitation facilities.

28 Table 2.6: Select Indicators of Health, 2015-16

Himachal Uttar Indicator Uttarakhand India Pradesh Pradesh Total fertility rate (children per 2.1 1.9 2.7 2.2 woman) Infant mortality rate (IMR) 40 34 64 41 Under-five mortality rate (U5MR) 47 38 78 50 Mothers who had full antenatal care 11.5 36.9 5.9 21.0 (%) Institutional births (%) 68.6 76.4 67.8 78.9 Institutional births in public facility 43.8 61.6 44.5 52.1 (%) Children age 12-23 months fully immunized (BCG, measles, and 3 57.7 69.5 51.1 62.0 doses each of polio and DPT) (%) Children under 5 years who are 33.5 26.3 46.3 38.4 stunted (height-for-age) (%) Children under 5 years who are wasted 19.5 13.7 17.9 21.2 (weight-for-height) (%) Children under 5 years who are severely wasted (weight-for-height) 9.0 3.9 6.0 7.5 (%) Children under 5 years who are 26.6 21.2 39.5 35.7 underweight (weight-for-age) (%) Households with an improved 92.9 94.9 96.4 89.9 drinking-water source (%) Households using improved sanitation 64.5 70.7 35.0 48.4 facility (%) Source: NFHS-4 (2015-16).

District-wise, there are significant regional disparities in the health indicators in Uttarakhand. For example, the percentage share of institutional births in the state ranges between a highest 83.7 per cent in Dehradun and the lowest 53.3 per cent in Chamoli. This is largely due to the relatively inadequate access to health facilities in remote hill areas. Similarly, the proportion of wasted children under 5 years (weight-for-height) ranges between a lowest of 9 per cent in Nainital and a highest 46 per cent in Tehri Garhwal. The proportion of anemic women (15-49 years) was lowest in Pithoragarh (42.3 per cent) and highest in Hardwar (55.3 per cent) during 2015-16 (NFHS-4). The high values of standard deviation in case of malnutrition, institutional deliveries and sanitation speak about the disparities across districts in the state. Surprisingly, Hardwar district lags much behind others in most of the health development indicators despite having a fairly high per capita district domestic product (Annexure Table 2.7). Access and availability of drinking water is a major issue particularly in all hill districts. The micro studies show how lack of adequate drinking

29 water has perpetuated out-migration from many villages in hill districts (Mehta, 2016). This again shows that high income level of a given economy generally is not sufficient condition to eradicate multidimensional poverty.

VI. SUMMING UP Uttarakhand has achieved remarkable progress in attaining high economic growth after its formation in November 2000. The growth has been largely led by manufacturing sector and also by the construction and services sector. However, growth is not evenly spread across different regions of the state. Most of the hill districts severely lag behind the three plains districts including Dehradun in economic development. Like in other parts of the country, disparities in economic development have widened in Uttarakhand. This is also reflected in various other development indicators such as education, health and basic amenities. Although the situationin hill districts on educational development front is far better than two plains districts of Hardwar and Udham Singh Nagar, yet there are hardly any employment opportunities for the educated labour force in hill areas. As a result, most of the hilly districts have experienced a huge out-migration of able-bodied population in search of livelihood. Moreover, out-migration in terms of sending remittances has hardly made any multiplier impact on the economy in source areas of migration. Such significant regional disparities in development outcomes only reinforcethe need to understand poverty in Uttarakhand not simply based on income/consumption approach but it should be analysed in its multidimensional forms. Lastly, the general indicators of development used to assess progress in mountain economies may sometimes lead to confusing interpretations. For example, the availability of infrastructure per one lakh population would have little meaning if it is not linked with the distance and altitude in the context of hills. This is because travelling a distance of one kilometre would require altogether different time and energy in hill and plain areas. Thus, the available data used for calculation of poverty in the contexts of hill regions fall rather inadequate, and therefore need to be interpreted with utmost care.

30 Annexures Annexure Table 2.1: District-wise Population in Uttarakhand Share of Rural Population (in No.) population (%)

District 2001 2011 CAGR 2001 2011

Almora 630567 622506 -0.13 91.28 89.89

Bageshwar 249462 259898 0.41 97.19 96.54

Chamoli 370359 391605 0.56 86.49 84.69

Nainital 762909 954605 2.27 64.74 61.05

Champawat 224542 259648 1.46 84.89 85.00

Pauri Garhwal 697078 687271 -0.14 87.09 86.21

Pithoragarh 462289 483439 0.45 87.01 85.71

Rudraprayag 227439 242285 0.63 99.12 95.87

Tehri Garhwal 604747 618931 0.23 90.08 88.69

Uttarkashi 295013 330086 1.13 92.20 92.73

Hill region 4524405 4850274 0.70 85.63 83.27

Hardwar 762909 954605 2.27 69.18 63.33

Dehradun 1282143 1696694 2.84 47.04 44.49

U. S. Nagar 1235614 1648902 2.93 67.39 64.40

Plains region 3280666 4300201 2.74 61.46 57.56

Uttarakhand 8489349 10086292 1.74 74.33 69.77

Source:Primary Census Abstract, Population Census, 2001 and 2011.

31 Annexure Table 2.2: Proportion of SC/ST/Muslim Population in Uttarakhand, 2011

District %SC %ST %Muslims %SC/ST/Muslim

Uttarkashi 24.41 1.06 1.08 26.55

Chamoli 20.25 3.13 1.12 24.51

Rudraprayag 19.68 0.16 0.61 20.45

Tehri Garhwal 16.5 0.14 1.19 17.83

Dehradun 13.49 6.58 11.91 31.98

Pauri Garhwal 17.8 0.32 3.34 21.47

Pithoragarh 24.9 4.04 1.24 30.18

Bageshwar 27.73 0.76 0.55 29.04

Almora 24.26 0.21 1.25 25.71

Champawat 18.25 0.52 3.35 22.11

Nainital 20.03 0.79 12.65 33.46

Udham Singh Nagar 14.45 7.46 22.58 44.49

Hardwar 21.76 0.33 34.28 56.37

Hill region 20.91 1.05 3.80 25.76

Plain region 16.78 4.6 23.35 44.73

Uttarakhand 18.76 2.89 13.95 35.61

Source: Primary Census Abstract, Population Census of India, 2011.

32 Annexure Table 2.3: Age-wise Distribution of Population in Uttarakhand, 2011 District 0-14 15-29 30-59 60+ 15-59

Uttarkashi 33.1 28.2 29.9 8.7 58.14

Chamoli 30.7 27.9 31.4 9.9 59.37

Rudraprayag 31.4 27.2 30.2 11.2 57.40

Tehri Garhwal 32.4 27.1 29.8 10.7 56.98

Dehradun 27.3 29.8 33.9 9.1 63.68

Pauri Garhwal 29.3 26.1 31.9 12.7 58.05

Pithoragarh 30.1 26.5 32.5 10.9 59.00

Bageshwar 31.0 25.7 31.6 11.7 57.28

Almora 30.3 26.2 31.1 12.4 57.32

Champawat 33.4 27.0 30.5 9.1 57.52

Nainital 29.6 29.3 32.8 8.3 62.11

Udham Singh Nagar 32.7 30.5 29.8 7.0 60.30

Hardwar 33.6 30.2 28.9 7.3 59.08

Hill region 30.7 27.3 31.4 10.5 58.72

Plains region 31.3 30.2 30.8 7.8 60.95

Uttarakhand 31.0 28.8 31.1 9.1 59.88

Source: Primary Census Abstract, Population Census of India, 2011.

33 Annexure Table 2.4: District-wise Literacy Rates in Uttarakhand

District 2001 2011

Person Male Female Person Male Female

Almora 73.64 89.2 60.56 80.47 92.86 69.93

Bageshwar 71.29 87.65 56.98 80.01 92.33 69.03

Chamoli 75.43 89.66 61.63 82.65 93.4 72.32

Champawat 70.39 87.27 54.18 79.83 91.61 68.05

Nainital 63.75 73.83 52.01 73.43 81.04 64.79

Pauri Garhwal 77.49 90.91 65.7 82.02 92.71 72.6

Pithoragarh 75.95 90.06 62.59 82.25 92.75 72.29

Rudraprayag 73.65 89.81 59.57 81.3 93.9 70.35

Tehri Garhwal 66.73 85.33 49.42 76.36 89.76 64.28

Uttarkashi 65.71 83.6 46.69 75.81 88.79 62.35

Hardwar 78.36 86.32 69.55 83.88 90.07 77.29

Dehradun 78.98 85.87 71.2 84.25 89.4 78.54

U. S. Nagar 64.86 75.22 53.35 73.1 81.09 64.45

Uttarakhand 71.6 83.3 59.6 78.8 87.4 70.00

Source: Primary Census Abstract, Population Census, 2001 and 2011.

34 35 Annexure Table 2.5a: District-wise Educational Level of Youth (15-29 Yrs.), 2011 Literate without educational Below Primar Hr. Non-tech Tech. Graduate Unsp- District Illiterate level Primary y Middle Secondary Secondary diploma diploma and above ecified Educated Uttarkashi 9.29 1.48 1.70 10.53 27.84 21.41 15.61 0.02 0.67 11.30 0.15 49.01 Chamoli 3.57 1.79 0.92 8.69 28.25 24.96 17.75 0.05 0.55 13.35 0.11 56.67 Rudraprayag 3.19 1.60 0.83 7.82 27.09 26.94 20.33 0.04 0.46 11.55 0.15 59.32 Tehri Garhwal 7.13 1.60 1.39 9.99 27.52 24.90 17.13 0.04 0.61 9.51 0.18 52.18 Dehradun 7.95 1.83 2.11 10.28 18.32 20.63 17.56 0.08 0.78 20.34 0.13 59.39 Pauri Garhwal 4.00 1.27 1.00 7.75 22.63 28.21 21.02 0.06 0.76 13.23 0.07 63.28 Pithoragarh 4.57 1.79 1.79 11.47 30.64 23.71 14.92 0.01 0.34 10.67 0.10 49.64 Bageshwar 4.27 1.56 1.50 12.60 31.01 25.34 14.68 0.01 0.26 8.66 0.10 48.96 Champawat 6.68 0.79 2.03 14.88 30.62 19.93 13.39 0.02 0.47 11.13 0.06 44.94 Nainital 7.71 1.03 2.13 11.79 23.52 20.83 16.25 0.07 0.80 15.77 0.11 53.72 Udham Singh Nagar 16.23 1.46 3.31 15.71 21.14 18.36 12.49 0.06 0.49 10.54 0.21 41.94 Hardwar 16.29 1.49 3.59 17.99 20.82 16.75 10.53 0.14 1.01 11.25 0.14 39.68 Almora 3.21 1.09 1.10 11.16 31.50 24.85 15.72 0.04 0.53 10.68 0.12 51.82 Hill 5.59 1.35 1.49 10.57 27.21 23.99 16.87 0.04 0.60 12.18 0.12 53.68 Plain 13.60 1.59 3.03 14.80 20.12 18.50 13.41 0.10 0.77 13.93 0.16 46.71 Uttarakhand 9.95 1.48 2.33 12.87 23.35 21.00 14.98 0.07 0.69 13.13 0.14 49.88 Source: Population Census, 2011

36 Annexure Table 2.5b: District-wise Educational Level of Population (30-59 Yrs.), 2011 Literate without educational Below Primar Hr. Non-tech Tech. Graduate Unsp- District Illiterate level Primary y Middle Secondary Secondary diploma diploma and above ecified Educated Uttarkashi 37.41 2.92 3.21 13.05 15.82 7.37 7.74 0.02 0.24 11.93 0.30 27.29 Chamoli 25.30 2.67 3.41 19.38 17.79 10.46 7.69 0.03 0.24 12.94 0.08 31.37 Rudraprayag 27.19 2.66 2.97 18.72 17.93 10.43 8.50 0.03 0.20 11.17 0.20 30.32 Tehri Garhwal 36.85 4.36 2.65 12.77 13.31 9.51 8.76 0.02 0.27 10.87 0.64 29.43 Dehradun 20.81 2.46 2.53 11.34 11.98 13.07 11.71 0.08 0.54 25.34 0.14 50.75 Pauri Garhwal 22.29 1.66 2.73 16.94 16.27 14.11 10.78 0.04 0.36 14.72 0.09 40.01 Pithoragarh 23.42 2.24 5.38 19.68 19.93 10.47 8.25 0.02 0.23 10.25 0.13 29.22 Bageshwar 28.28 2.44 4.81 18.91 17.59 11.75 9.05 0.01 0.14 6.83 0.18 27.78 Champawat 30.38 1.58 4.91 19.33 17.49 9.30 7.15 0.03 0.33 9.37 0.12 26.19 Nainital 21.70 1.39 3.52 15.05 14.48 12.05 11.45 0.06 0.46 19.68 0.15 43.70 Udham Singh Nagar 39.72 1.80 3.29 13.89 12.22 9.78 7.16 0.05 0.26 11.59 0.23 28.86 Hardwar 37.99 1.82 2.30 13.22 12.99 10.07 7.09 0.16 0.73 13.44 0.19 31.49 Almora 26.86 1.89 4.06 18.73 17.21 11.29 9.17 0.02 0.21 10.36 0.20 31.05 Hill 26.83 2.27 3.65 16.82 16.35 11.11 9.37 0.03 0.30 13.06 0.21 33.87 Plains 32.39 2.04 2.68 12.76 12.40 11.05 8.76 0.10 0.52 17.12 0.18 37.55 Uttarakhand 29.69 2.15 3.15 14.73 14.32 11.08 9.06 0.07 0.41 15.14 0.20 35.76 Source: Population Census, 2011

37 Annexure Table 2.6: Estimates of Human Development Index (HDI) and Inequality adjusted HDI State HDI IHDI Ratio Loss (%)

Andhra Pradesh 0.485 0.332 0.685 31.546

Assam 0.174 0.341 0.718 28.174

Bihar 0.447 0.303 0.679 32.055

Chhattisgarh 0.449 0.291 0.649 35.142

Gujarat 0.514 0.363 0.705 29.495

Haryana 0.545 0.375 0.688 31.180

Himachal Pradesh 0.558 0.403 0.722 27.810

Jharkhand 0.464 0.308 0.663 33.665

Karnataka 0.508 0.353 0.696 30.443

Kerala 0.625 0.520 0.832 16.781

Madhya Pradesh 0.451 0.290 0.643 35.735

Maharashtra 0.549 0.397 0.722 27.750

Odisha 0.442 0.296 0.669 33.107

Punjab 0.569 0.410 0.720 28.035

Rajasthan 0.468 0.308 0.660 34.019

Tamil Nadu 0.544 0.396 0.727 27.275

Uttar Pradesh 0.468 0.307 0.655 34.473

Uttarakhand 0.515 0.345 0.670 33.025

West Bengal 0.509 0.360 0.707 29.302

India 0.504 0.343 0.680 31.996

Source: Surayanarayana, et al. 2015

38 Annexure Table 2.7: District-wise Select Indicators of Health in Uttarakhand, 2015-16

Bagesh Cham Champ Dehra Garh Harid Naini Pithora Rudrapr US Uttarkash Select indicators of health Uttarakhand Almora Tehri war oli awat dun wal war tal garh ayag nagar i Mothers who had full antenatal 11.5 18.7 10.7 5.9 11.1 18.9 11.9 7.6 20.5 14.7 5.7 7.2 5.8 9.6 care (%) Institutional births (%) 68.6 66.3 55.9 53.3 73.3 83.7 74.5 62.8 64.7 73 66.5 71.1 67.5 65.1 Institutional births in public 43.8 57.8 49.6 49.4 54.1 49.5 59.7 23.8 41.2 65.3 59.8 59.4 39.5 58.9 facility (%) Children age 12-23 months fully immunized (BCG, measles, and 3 57.7 60.6 60.2 62.2 68.4 60.7 61.2 55.3 59 74.2 70.3 51.1 47.4 72 doses each of polio and DPT) (%) Children under 5 years who are 33.5 32.9 25.1 33.7 30.5 28.5 22.9 39.1 32.1 30.6 29.9 30.1 37.8 35.2 stunted (height-for-age) (%)

Children under 5 years who are 19.5 14.4 26.3 18 17.4 30.1 27.4 12.3 9 20.6 18.4 46.9 12 39.4 wasted (weight-for-height) (%)

Children under 5 years who are severely wasted (weight-for- 9 7.7 13.5 7.2 6.1 12 18.1 5.3 3.7 9.2 7.5 28.1 3.5 23.6 height) (%)

Children under 5 years who are 26.6 22.5 27.2 22.3 21.2 30.7 27.9 24.7 17 16.6 25.9 44.2 27.1 40.3 underweight (weight-for-age) (%)

Households with an improved 92.9 83.9 83 93.2 89.5 99.5 88.1 99.1 95.9 83.9 86.5 77.4 97.6 75.1 drinking-water source (%) Households using improved 64.5 65 67.4 62.4 59.5 75.6 66.2 56.9 73 62.7 67.6 65.8 56.2 48.5 sanitation facility (%) Women whose BMI below 18.4 24.8 24.9 15.2 20.6 16.2 16.6 20.7 17.2 13.5 14.8 18.1 19.1 16.9 normal (BMI <18.5kg/m) (%) Children age 6-59 months who 59.8 48.6 49 53.6 46.1 50.6 58.1 71.1 58 42.3 58.6 59.9 64.6 76.2 are anaemic (<11.0g/dl.) (%) Anaemic women (15-49 yrs) (%) 45.2 32.9 41.3 37.6 35.6 41.9 42.4 55.3 38.4 34.5 38.4 44.6 52.3 52.6 Source:NFHS-IV, 2015-16, National Family and Health Survey, International Institute of Population Sciences, Mumbai.

39 Chapter - III

LEVELS OF LIVING IN UTTARAKHAND: SELECT DIMENSIONS

I. INTRODUCTION Estimates of household consumer expenditure are widely used as a critical measure of standard of living and welfare in developing countries whereas estimates of income fraught with conceptual and methodological issues. Hence, this chapter seeks to examine welfare related issues in the context of development of Uttarakhand with reference to estimates of per capita household consumer expenditure, its distribution and extent of deprivation as reflected in different statistical measures. This chapter presents comparative profiles of the NSS (National Sample Survey) estimates of distribution of household monthly per capita consumer expenditure for Uttarakhand (the state under review) and Uttar Pradesh (its parent state), Himachal Pradesh (an adjacent hilly state to its northwest), and all-India which present the general background for macro-economic policies.

The chapter is organised into seven sections. After a brief introduction in Section I, Section II provides the context with reference to the composition of the population in terms of social groups and their implications for sample estimates. Section III provides estimates of the distributional profiles and their interpretations. Section IV analyses measures of absolute deprivation at the macro and sector levels. Section V deals with the extent of inclusion of different social groups with reference to robust measures of average, and the extent of deprivation amongthem (Section VI). The final Section VII summarizes the chapter.

II. POPULATION COMPOSITION: SOCIAL GROUPS

The social composition of households is generally defined in terms of (i) the Scheduled Tribes (STs); (ii) the Scheduled Castes (SCs); (iii) the Other Backwards Classes (OBCS); and (iv) ‘others’(Other Social Groups (OSGs). Unlike the all-India profile, the fourth category of ‘others’ constitutes the dominant section of the population in both rural and urban sectors of the hilly states of Uttarakhand and Himachal Pradesh; they account for about half the population (Table 3.1). The STs constitute about five per cent of the population while the SCs about a quarter and the OBCs about one-sixth of the population in these two states. The STs constitute less than one per cent of the population in rural and urban Uttar Pradesh (UP). The OBCs, on the other hand, account for half of the rural and urban populationin Uttar Pradesh

40 and India as a whole. The SCs account for a quarter of the rural UP population. Statistically, the implications would be as follows. The estimates of different variables for the ST population in Uttar Pradesh in particular would be less robust and hence less reliable in a statistical sense. Hence the discussion on Uttar Pradesh would not touch upon the estimates for the STs.

Table 3.1 (a): Distribution (%) of Population across Social Groups: Rural Sector for Select States 2004-05 2011-12 Social Himachal Uttar All Himachal Uttar All Group Uttarakhand Pradesh Pradesh India Uttarakhand Pradesh Pradesh India ST 5.92 5.09 0.49 10.57 4.73 7.64 1.29 11.12 SC 22.93 26.98 25.42 20.93 24.43 23.51 26.57 20.8 OBC 17.74 15.48 54.7 42.77 16.05 19.81 55.5 45.04 OSGs 53.4 52.46 19.39 25.72 54.79 49.04 16.63 23.04 Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00

Table 1 3.1(b): Distribution (%) of Population across Social Groups: Urban Sector for Select States

2004-05 2011-12 Social Himachal Uttar Himachal Uttar All Group Uttarakhand Pradesh Pradesh All India Uttarakhand Pradesh Pradesh India ST 1.23 2.67 0.45 2.92 1.79 3.85 0.72 3.47 SC 16.34 18.85 13.65 15.65 13.23 19.03 13.56 14.62 OBC 18.71 9.19 45.37 35.61 26.27 11.61 50.14 41.62 OSGs 63.72 69.3 40.53 45.82 58.72 65.51 35.58 40.29 Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 Source: Authors’ estimates based on the NSS 61st and 68th round central sample unit record data (Schedule Type I).

III. DISTRIBUTIONAL PROFILES

1. Uttarakhand: Inclusion in the National Mainstream

Every distribution could be examined with reference to its statistical properties like measures of location as well as dispersion. Income/consumption distributions are highly skewed. An order based average like the median would be an ideal measure of location. However, it is a convention in economic policy papers to report levels of living in terms of mean based estimates as they are simple to understand and interpret. A major limitation of these estimates is that they could provide misleading relative profiles at times. However, for reasons like convention and statistical robustness, we report both mean-based and order-based estimates of averages of monthly per capita consumer expenditure (MPCE) in Uttarakhand, Himachal

41 Pradesh, Uttar Pradesh and all-India (Table 3.2). As could be expected for skewed distributions, mean-based estimates are higher than the order-based estimates of average consumption expenditure in all the states under review.

Table 3.2a: Measures of Average MPCE and Inclusion/Exclusion in/from the National Mainstream: Rural Sector Disparity 2004-05 2011-12 measure Uttara Himachal Uttar All Uttara Himachal Uttar khand Pradesh Pradesh India khand Pradesh Pradesh All India Mean (Rs.) 648.94 835.57 539.29 579.18 1551.41 1800.60 1072.93 1287.17 Disparity w.r.t. national mean MPCE (ηinter%) 12.04 44.27 -6.89 0.00 20.53 39.89 -16.64 0.00 Median (Rs.) 555.72 688.25 465.84 486.16 1282.70 1495.91 931.15 1072.97 Disparity w.r.t. national median MPCE (ηinter%) 14.31 41.57 -4.18 0.00 19.55 39.42 -13.22 0.00

Table 3.2b: Measures of Average MPCE and Inclusion/Exclusion in/from the National Mainstream: Urban Sector

Disparity 2004-05 2011-12 measure Uttara Himachal Uttar All Uttara Himachal Uttar khand Pradesh Pradesh India khand Pradesh Pradesh All India 1104.6 Mean (Rs.) 1027.58 1422.17 879.67 0 2451.97 3173.232 1942.242 2477.00 Disparity w.r.t. national mean MPCE (ηinter%) -6.97 28.75 -20.36 0.00 -1.01 28.11 -21.59 0.00 Median (Rs.) 828.40 1201.10 662.68 838.66 1829.39 2639.11 1270.63 1865.54 Disparity w.r.t.national median MPCE (ηinter %) -1.22 43.22 -20.98 0.00 -1.94 41.47 -31.89 0.00 Notes: MPCE = Monthly per capita consumer expenditure(Mixed Reference Period). w.r.t.= with reference to

Source: Authors’ estimates at current prices based on the NSS 61st and 68th round central sample unit record data.

A pertinent question in this context would be to examine the extent of inclusion/exclusion of Uttarakhand in the national mainstream in terms of both mean-based and order-based measure of MPCE. This could be carried out in terms of estimates of inter- group median disparities. For this purpose, one may define the following

measures.Letμndenote national mean/median and μsstate-specific mean/median. Disparity

42 between state-specific and the nation-specific averages could be examined by comparing the respective estimates of median consumption MPCE as follows: 4

ηinter = [(μs/ μn)-1] … (1)

ηinter> 0 =>inclusion in the national mainstream and ηinter < 0 =>exclusion from the national mainstream.The salient features of the estimates in Table 3.2 are as follows:

(i) Uttarakhand stands second among the three states under review in terms of estimates of measures of average consumer expenditures for both rural and urban sectors.

(ii) Both mean and order-based estimates exceed corresponding national averages in the rural sectors of Uttarakhand and Himachal Pradesh; hence they indicate their inclusion in the national mainstream. As regards the urban sector, only Himachal Pradesh stands above the national average.

(iii) Uttarakhand has improved while both Himachal Pradesh and Uttar Pradesh have declined in terms of percentage difference with respect to the national average in both ruraland urban sectors. This would suggest that Uttarakhand’s pace of progress is better than that of the rest of India; but it is not so for Himachal Pradesh and Uttar Pradesh.

(iv) Himachal Pradesh seems to be doing exceptionally well wherein its averages exceed the corresponding all India ones in the range between 28 to 40 per cent. Conversely, the disparity estimates for Uttar Pradesh indicate its exclusion. In other words, Uttarakhand is doing better than Uttar Pradesh in terms of economic status relative to that of the nation as a whole.

It may be noted these estimates of average MPCEs are at local current prices and not adjusted for inter-state price differences. Hence, the disparity estimates are in nominal terms only. The relative profiles would differ to the extent the spatial cost of living differs across these states.

4 One may also consider the following modification for the measure of disparity: ηinter = [(μs/ αμm)-1] where 0 <α< 1

43 IV. RELATIVE PROFILES OF CONSUMPTION DISTRIBUTIONS

Economic welfare depends not only on the average, however measured, but also on the salient distributional profiles. Hence, this sub-section would summarize the salient distributional profiles of Uttarakhand vis a vis Himachal Pradesh, Uttar Pradesh and All India.

1. Rural sector

i. On an average, rural Uttarakhand is doing much better than rural Uttar Pradesh: Its mean monthly per capita consumer expenditure (MPCE) exceeded that of Uttar Pradesh by 20 per cent in 2004/05, which increased to about 45 per cent in 2011/12 (Table 3.3a). However, it does not compare well with Himachal Pradesh; it fell short of the mean MPCE in Himachal Pradesh by 22 per cent in 2004/05 but has improved its relative status since then as the percentage shortfall of Uttarakhand mean MPCE with respect to that of Himachal Pradesh declined to 14 per cent in 2011/12. In the national context, the mean MPCE of Uttarakhand exceeded that of all-India by 12 per cent in 2004/05 and 21 per cent in 2011/12.

ii. The estimates of all percentiles of consumption distribution for Uttarakhand are less than the corresponding estimates for Himachal Pradesh in both 2004/05 and 2011/12 (Table 3.3b). Barring the 99 the percentile for the rural sector in 2004/05, every percentile in Uttarakhand exceeds its counterpart in all-India. Every percentile in Uttarakhand is uniformly higher than the corresponding percentile in Uttar Pradesh in the two years under review (Table 3.3b). iii. The estimates of price-adjusted changes in percentiles between 2004/05 and 2011/12 reveal broadly the same extent of change across percentiles of all the states under review; the only exception is Uttarakhand wherein the percentiles in the 90s have increased by larger percentage points. This would be a clear indication of an increase in the extent of inequality in rural Uttarakhand.

Table 3.3a: Levels of Average MPCE in Uttarakhand relative to Select State Averages (Percentage difference): Rural Sector

44 2004-05 2011-12 Disparity Uttara Himachal Uttar All Uttara Himachal Uttar measure khand Pradesh Pradesh India khand Pradesh Pradesh All India Mean(Rs) 648.94 835.57 539.29 579.18 1551.41 1800.60 1072.93 1287.17 Uttarakhand mean disparity w.r.t. different state mean estimates (ηinter%) 0.00 -22.34 20.33 12.04 0.00 -13.84 44.60 20.53 Median 555.72 688.25 465.84 486.16 1282.70 1495.91 931.15 1072.97 Uttarakhand median disparity wrt different state median estimates (ηinter%) 0.00 -19.26 19.29 14.31 0.00 -14.25 37.75 19.55 Notes:MPCE = Monthly per capita consumer expenditure (Mixed Reference Period). wrt = with reference to

Table 3.3b: Summary Statistics on NSS Per Capita Consumer Expenditure Distribution: Rural Sector (2004/05 & 2011/12)

2004/05 2011/12 Percentage real change Perc Himacha Himacha Himacha Uttar All entil Uttara l Uttar All Uttara l Uttar All Uttara l Prades es khand Pradesh Pradesh India khand Pradesh Pradesh India khand Pradesh h India 1 296.40 314.85 208.53 197.42 681.39 704.26 399.16 424.65 48.82 48.10 14.87 32.55 5 344.24 372.68 266.50 259.74 791.37 823.91 524.30 554.54 48.82 45.50 20.19 30.95 10 372.23 421.41 297.09 295.00 848.39 931.32 586.71 639.10 46.85 45.42 20.94 34.09 25 449.13 520.46 364.89 369.73 1024.42 1156.16 723.39 808.64 47.02 46.56 21.70 36.16 50 555.72 688.25 465.84 486.16 1282.70 1495.91 931.15 1072.97 49.75 41.77 23.34 38.15 75 751.25 942.12 614.21 661.42 1739.92 2078.19 1217.02 1495.92 50.53 45.01 21.60 43.62 90 996.54 1325.54 845.64 924.47 2373.71 2910.71 1686.41 2089.60 57.13 44.01 22.87 43.48 95 1191.26 1707.11 1047.80 1175.59 3256.17 3832.85 2079.54 2651.95 92.27 48.94 21.92 43.03 99 1860.27 3042.87 1685.56 2013.84 5499.20 6289.03 3253.19 4361.08 114.54 31.10 16.45 34.01 Smal lest 115.75 209.31 73.74 14.11 517.69 611.89 139.92 44.11 - - - - Larg est 9254.31 18998.28 18202.83 37838.91 19662.56 26622.37 20705.45 94253.73 - - - - Rang e 9138.56 18788.97 18129.09 37824.80 19144.87 26010.48 20565.53 94209.62 - - - - IQR 302.12 421.66 249.32 291.69 715.50 922.03 493.63 687.28 - - - - Mean 648.94 835.57 539.29 579.18 1551.41 1800.60 1072.93 1287.17 58.00 39.91 22.40 39.69 Std. Devi ation 366.77 635.41 329.25 410.13 917.57 1230.70 650.80 962.86 - - - - Skew ness 6.43 8.50 10.40 8.93 3.85 6.32 6.50 13.54 - - - - Kurt osis 101.17 164.87 379.76 278.81 36.29 82.67 98.44 564.58 - - - - Note:Percentage real changes are worked out with adjustment for changes in the cost of living index implicit in the state-specific poverty lines estimates using Tendulkar methodology.

Source: Authors’ estimates at current prices based on the NSS 61stand 68th round central sample unit record data (Mixed reference Period). iv. The extent of inequality in consumption distribution, however measured, was the least in Uttarakhand in 2004/05 (Table 3.3c). The extent of relative nominal

45 consumption inequality increased in Uttarakhand by 2011/12; the percentage pointsincrease was the highest inUttarakhand among the four cases under review.Similar increase in the extent of inequality, though to a lesser extent, was seen in rural all India. Uttar Pradesh too has experienced a marginal increase in inequality by majority of the measures. Himachal Pradesh is the onlystate which has experienced a reduction in inequality between these two points in time.

Table 3.3c: Extent of Inequality in the Rural Sector: 2004/05 &2011/12 20045-05 2011-12 Inequality measures Uttarakha Himachal Uttar All Uttarak HP UP All India Rural nd Pradesh Pradesh India hand Rural Relative mean 0.172 0.206 0.179 0.199 0.187 0.200 0.179 0.204 deviation Coefficient of 0.565 0.760 0.611 0.708 0.591 0.683 0.607 0.748 variation Standard deviation 0.402 0.478 0.428 0.473 0.433 0.463 0.432 0.485 of logs 0.239 0.289 0.252 0.281 0.261 0.279 0.254 0.287 Gini coefficient 0.317 0.376 0.335 0.369 0.339 0.365 0.337 0.379 Mehran measure 0.201 0.246 0.211 0.237 0.221 0.236 0.212 0.242 Piesch measure 0.054 0.079 0.060 0.074 0.064 0.072 0.061 0.076 Kakwani measure Theil index (GE(a), 0.109 0.169 0.121 0.155 0.128 0.150 0.124 0.161 a = 1) Mean Log 0.110 0.126 0.106 0.135 Deviation (GE(a), a 0.093 0.138 0.104 0.130 = 0) Entropy index 0.090 0.135 0.103 0.130 0.105 0.124 0.106 0.138 (GE(a), a = -1) Half (Coeff.Var. 0.175 0.234 0.184 0.280 squared) (GE(a), a 0.160 0.289 0.186 0.251 = 2) Source:Authors’ estimates at current prices based on the NSS 61st and 68th round central sample unit record data (Mixed Reference Period).

2. Urban Sector

i. Urban Uttarakhand too is doing relatively better than other counterparts under review (Table 3.4a). The shortfall of urban mean consumption in Uttarakhand vis a vis that of Himachal Pradesh declined from 28 per cent in 2004/05 to 23 per cent in 2011/12; the shortfall with respect to the all India mean MPCE declined from seven per cent to just one per cent between these two years. On the other hand, Uttarakhand is doing better than its parent state Uttar Pradesh in both the yearsunder review.

46 Table 3.4a: Levels of Average MPCE in Uttarakhand relative to Select State Averages (Percentage difference): Urban Sector 2004-05 2022-12 Uttara Himachal Uttar All Uttara Himachal Uttar All Disparity measure khand Pradesh Pradesh India khand Pradesh Pradesh India 2477.0 Mean (Rs) 1027.58 1422.17 879.67 1104.60 2451.97 3173.232 1942.242 0 Uttarakhand mean disparity wrt different state mean estimates

(ηinter%) 0.00 -27.75 16.81 -6.97 0.00 -22.73 26.24 -1.01 1865.5 Median 828.40 1201.10 662.68 838.66 1829.39 2639.11 1270.63 4 Uttarakhand median disparity wrt different state median estimates ( ηinter%) 0.00 -31.03 25.01 -1.22 0.00 -30.68 43.98 -1.94 Notes: MPCE = Monthly per capita consumer expenditure (Mixed Reference Period). wrt = with reference to Source: Authors’ estimates at current prices based on the NSS 68th round central sample unit record data.

ii) All percentiles of the consumption distribution for urban Himachal Pradesh are clearly higher than the corresponding percentiles for Uttarakhand, Uttar Pradesh and all India (Table 3.4b). Only the upper percentiles (greater than or equal to the 50th percentile) of all India are higher than those for Uttarakhand; finally only the 99th percentile of Uttar Pradesh is greater than that for Uttarakhand in 2004/05. The profile differs marginally for the year 2011/12. The 99-th percentile of Uttarakhand exceeds those of Himachal Pradesh, all India, and Uttar Pradesh reflecting possible rapid urban growthat the top (Table 3.4b). iii) The price-adjusted estimates of changes in percentiles generally indicate higher values at the upper ends indicating an increase in the extent of real consumer expenditure inequality between the two points in time, more so in Uttarakhand.

47 Table 3.4b: Summary Statistics on NSS Per Capita Consumer Expenditure Distribution: Urban Sector (2004/05 & 2011/12)

2004/05 2011/12 Percentage real change Uttara Himachal Uttar All Uttara Himachal Uttar All Uttara Himachal Uttar All Percentiles khand Pradesh Pradesh India khand Pradesh Pradesh India khand Pradesh Pradesh India 1 338.72 371.15 240.18 267.92 700.83 864.32 512.78 578.05 27.18 57.30 36.62 43.05 5 418.61 660.12 324.19 361.89 957.92 1122.72 637.98 770.75 49.10 -5.50 19.91 40.27 10 467.64 713.71 372.65 423.54 1075.22 1273.48 723.21 908.93 50.20 2.85 17.19 41.90 25 598.26 889.19 473.45 571.32 1302.67 1734.78 924.65 1254.85 38.01 19.52 18.42 46.93 50 828.40 1201.10 662.68 838.66 1829.39 2639.11 1270.63 1865.54 41.10 44.14 14.86 49.73 75 1246.72 1690.81 1003.66 1303.39 2863.38 3786.63 2031.40 2869.45 49.94 48.37 25.52 47.44 90 1843.59 2375.15 1524.64 2034.42 4012.96 5574.70 3522.45 4511.92 37.94 59.13 54.16 49.07 95 2412.22 2907.65 2128.15 2699.61 5625.18 7657.05 6604.11 6282.13 53.46 87.76 133.44 60.00 99 3539.76 6050.12 4048.86 4788.85 13730.12 12493.44 10188.42 11358.83 208.15 30.92 74.76 64.48 Smallest 188.78 258.36 68.53 19.77 553.23 535.39 373.64 53.00 - - - - Largest 8195.85 7025.75 11880.27 29156.71 20563.76 59818.32 67458.10 70132.97 - - - - Range 8007.07 6767.39 11811.74 29136.95 20010.53 59282.93 67084.46 70079.97 - - - - IQR 648.47 801.62 530.21 732.07 1560.71 2051.85 1106.75 1614.60 - - - - Mean 1027.58 1422.17 879.67 1104.60 2451.97 3173.23 1942.24 2477.00 58.89 47.55 43.91 51.53 Std. Deviation 714.27 852.22 770.96 926.93 2109.38 2656.58 2232.04 2333.75 - - - - Skewness 3.37 2.79 4.67 4.21 3.99 7.14 10.40 6.84 - - - - Kurtosis 22.99 15.26 38.05 39.39 24.45 105.75 260.62 115.87 Note: Percentage real changes are worked out with adjustment for changes in the cost of living index implicit in the state-specific poverty lines estimates using Tendulkar methodology.

Source: Authors’ estimates at current prices based on the NSS 61st and 68th round central sample unit record data (Mixed reference Period).

iv) The extent of relative inequality as measured by different inequality measures increased between 2004/05 and 2011/12 (Table 3.4c). In general, the percentage increase was the highest in Himachal Pradesh followed by Uttar Pradesh, Uttarakhand and All-India respectively

3. Mainstream Inclusion We define inclusion with reference to the order measure of average, that is, median (Suryanarayana, 2008). We identify mainstream with an interval specified by a fraction, say, from 60 per cent of the median up to its 140 per cent. Since median is an order-based average and is the 50th percentile of the variable under review, we define an inclusion coefficient in terms of the proportion of ‘bottom half of the population falling in the mainstream interval’. Thus, we have a relative perspective on deprivation, that is, anyone whose income is less than the threshold, that is, 60 per of the median is considered excluded and if their consumer expenditure exceeds this threshold, that is considered included in the mainstream. An

48 improvement in the fraction of the bottom half of the population in the mainstream band would indicate progressive inclusion in the mainstream economic activity and vice versa. The complement of the inclusion coefficient would provide an estimate of the extent of exclusion for a homogenous society. Symbolically we have an ‘Inclusive Coefficient’ (IC) denoted by ‘’ is given by

.50   1  2  f (x)dx 0 … (1)

Where 0 << 1 and ξ.50 such that

 .50 1  f (x)dx   f (x)dx  2  0 .50

where 0 ≤ ≤ 1

Table 3.4c: Extent of Inequality in the Urban Sector: 2011/12 20045-05 2011-12 Inequality measures Uttara Himachal Uttar All Uttara HP UP All India khand Pradesh Prades India khand Urban h Rural 0.230 0.202 0.255 0.264 0.253 0.236 0.309 0.271 Relative mean deviation 0.695 0.599 0.876 0.839 0.860 0.837 1.149 0.942 Coefficient of variation 0.534 0.496 0.585 0.621 0.575 0.581 0.664 0.637 Standard deviation of logs 0.317 0.283 0.354 0.364 0.351 0.337 0.415 0.377 Gini coefficient 0.416 0.380 0.455 0.474 0.449 0.444 0.515 0.487 Mehran measure 0.267 0.235 0.304 0.309 0.302 0.283 0.366 0.322 Piesch measure 0.090 0.073 0.113 0.117 0.111 0.102 0.153 0.125 Kakwani measure 0.178 0.141 0.242 0.240 0.238 0.215 0.344 0.267 Theil index (GE(a), a = 1) Mean Log Deviation (GE(a), 0.160 0.131 0.203 0.215 0.199 0.188 0.279 0.232 a = 0) Entropy index (GE(a), a = - 0.167 0.142 0.211 0.239 0.203 0.206 0.290 0.256 1) Half (Coeff.Var. squared) 0.242 0.180 0.384 0.352 0.370 0.350 0.660 0.444 (GE(a), a = 2)

Source:Authors’ estimates at current prices based on the NSS 61st and 68th round central sample unit record data (Mixed Reference Period).

49 The extent of inclusion of the bottom half of the rural population in the mainstream was 93.40 per cent in Uttarakhand in 2004/05, which was the highest of the cases under review (Table 3.5). In 2011/12, the extent of mainstream inclusion in the rural sectors of the three states under review is higher than the corresponding estimate for rural All India (79.3%). Mainstream inclusion increased in Himachal Pradesh but declined in the remaining three cases by the year 2011/12.

The profile is different for the urban sector:The extent of inclusion in the mainstream was the least in India as a whole; minimum in Uttar Pradesh and maximum in Himachal Pradesh with Uttarakhand in between in 2004/05. Mainstream inclusion increased in Uttarakhand and Uttar Pradesh and declined in Himachal Pradesh and all-India. The reasons for such inclusion may be due to improved reach of government’s redistributive programmes in rural areas of these states.

Table 3.5: Extent of Mainstream Inclusion: Rural and Urban Sectors

Year 2004-05 2011-12 Uttar Uttar Uttarakhan Himacha Prades All Uttarakhan Himacha Prades All State d l Pradesh h India d l Pradesh h India Inclusion coefficient: 0.81 0.79 Rural 0.934 0.818 0.868 2 0.915 0.853 0.846 3 Inclusion coefficient: 0.63 0.62 Urban 0.729 0.746 0.713 9 0.770 0.568 0.745 3 Source: Authors’ estimates based on the NSS 61st and 68th round central sample unit record data (Mixed Reference Period).

V. ABSOLUTE DEPRIVATION This section presents official estimates of the extent of deprivation by rural and urban sectors in the states of Uttarakhand, Himachal Pradesh, Uttar Pradesh and all India (Table 3.8). The official estimates provide the extent of deprivation as measured by the percentage of population living below the subsistence norm called poverty line. The norms for defining the poverty lines could be different; depending upon the norm, we get different estimates of poverty line (Table 3.7).The official approach to defining and measuring poverty has evolved over time. Some salient features are as follows:

50 Lakdawala Approach

The conventional approach to measure poverty anchored the subsistence minimum in the calorie intake norm (Government of India, 1993). An individual, as observed in empirically estimated household consumption profiles, who cannot afford consumer expenditure that could provide for a calorie intake of 2400 calories in the rural sector and 2100 calories in the urban sector at the all-India level would be called poor. The corresponding consumer expenditure percentiles are called the poverty lines. Having identified the consumption basket that would ensure a subsistence minimum intake of calories and estimated its cost as a measure of poverty line, estimates of poverty ratios are obtained as cumulative population proportions less than the poverty line. Such poverty lines are obtained separately for rural and urban all-India. Their state-sector-specific equivalents are obtained using appropriate spatial cost of living indices. Poverty lines for subsequent years are obtained with price-adjustments in terms of Laspeyers’base-year-poverty-line-consumption-basket-weighted cost of living indices. One major limitation of this approach is that such price corrections make sense only in a stationary setting but not in the development context of structural changes in the economy involving changes in production and consumption patterns. Hence, there is no guarantee that the inflation-adjusted poverty lines would guarantee the underlying original calorie norm.This is precisely what several studies have found out for India and almost all the states in India. Further, available empirical evidences do not corroborate any association between calorie intake and health outcomes since calorie is only one of the critical determinants of health outcomes, however defined and measured.

Tendulkar Approach

In order to address the limitations of the conventional approach, the Tendulkar approach delinks the concept of poverty line from the calorie intake norm and bases it on some social perception of deprivation of basic human needs. Accordingly, the two approaches differ in terms of the information base, methods and interpretations (Government of India, 2009).

51 Rangarajan Approach

Even the Tendulkar approach is not devoid of conceptual and methodological inadequacies.5 Hence, the Government of India appointed the Rangarajan Committee which has defined deprivation with reference to three basic nutrient requirements (calorie, protein and fats) and other basic necessities. It too differs from the earlier approaches with respect to conceptual and methodological details (Government of India, 2014).

We have calculated official estimates of rural and urban poverty for the states under review. However, its own analysis would be based on MPCE estimates and poverty measures defined following the Tendulkar committee recommendation on poverty line.

Table 3.6: Estimates of Poverty Lines by State and Method (Rs MPCE) Rural Urban Uttara Uttar All Uttara Uttar Year khand HP Pradesh India khand HP Pradesh All India Method 2004-05 478.02 394.28 365.84 356.30 637.67 504.49 483.26 538.60 Lakdawala 2004-05 486.00 520.00 435.00 447.00 602.00 606 532.00 579.00 Tendulkar 2009-10 720.00 708.00 664.00 673.00 899.00 888 800.00 860.00 Tendulkar 2009-10 830.09 827.03 768.65 801.00 1169.82 1178.46 1130.76 1198.00 Rangarajan 2011-12 880.00 913.00 768.00 816.00 1082.00 1064 941.00 1000.00 Tendulkar 2011-12 1014.95 1066.60 889.82 972.00 1408.12 1411.59 1329.55 1407.00 Rangarajan Source: Government of India (2014)

For the conceptual and methodological reasons mentioned in the preceding bullet points, it would not make much sense to comment on the time series estimates of deprivation presented in Table 3.7. However, following good academic and policy convention, one may highlight some of the salient features as follows:

(i) As per the Lakdawala approach, the incidence of poverty was the highest in Uttarakhand, followed by Uttar Pradesh and Himachal Pradesh in the rural, urban and total economy as a whole in 2004/05. This profile is different from the one revealed by the Tendulkar Committee method for the same year, which shows the incidence of deprivation to be the highest in Uttar Pradesh followed by Uttarakhand and Himachal Pradesh in the same year.

5 For conceptual and methodological limitations of the Tendulkar approach, see Suranarayana (2011),

52 (ii) Both the Tendulkar and Rangarajan Committees’ approaches show similar profiles of deprivation across Uttarakhand, Himachal Pradesh and Uttar Pradesh. Deprivation is the highest in Uttar Pradesh and the least in Himachal Pradesh. As per their estimates, deprivation in Uttarakhand and Himachal Pradesh is less than the corresponding estimates at the national level in both rural and urban sectors; however, the extent of deprivation is more in Uttar Pradesh than in India as a whole in both rural and urban sectors.

(iii) In general, both Tendulkar and Rangarajan Committee approaches bring out a reduction in poverty in all the states at successive points of time under review (Table 3.7).

(iv) Table 3.8 presents estimates of incidence, depth and severity of poverty as measured

by the Pαclass of poverty measures. All these measures reveal identical profiles across the states under review: Deprivation is the highest in Uttar Pradesh followed by Uttarakhand and Himachal Pradesh. The extent of deprivation in Uttar Pradesh is higher than that in the nation as a whole in both rural and urban sectors.

(v) Our estimates of depth and severity show profiles similar to the ones revealed by the headcount measures for the following reason. They are estimated by making price- adjustments for the poverty line only. Estimates of depth and severity measures need to be adjusted for the differential impact of inflation across different expenditure groups because of changes in consumption basket profiles. Such adjustments have not been carried out for the estimates presented in Table 3.8. Hence, the estimates of incidence, depth and severity measures of deprivation show similar profiles across states.

(vi) Incidence of rural poverty declined by about 66 per cent in Himachal Pradesh and Uttarakhand, 39 per cent in India as a whole and by 29 per cent in Uttar Pradesh between 2004-05 and 2011-12.

(vii) As regards urban poverty, the reduction was much higher at the national level (47 per cent) than in Uttar Pradesh (23 per cent) followed by Uttarakhand (20 per cent) and Himachal Pradesh (5 per cent) respectively.

53 Table 3.7: Estimates of Poverty by Sector, State and Method

Rural Sector Uttarakhand Himachal Pradesh Uttar Pradesh All India Year % of No.of % of No. of % of No. of % of No. of Method persons persons persons persons persons persons persons persons (lakh) (lakh) (lakh) (lakh) 2004- 05 40.8 27.11 10.7 6.14 33.4 473 28.33 2209.24 Lakdawala 2004- 05 35.1 23.3 25 14.3 42.7 604.7 41.8 3266.6 Tendulkar 2009- 10 14.9 10.3 9.1 5.6 39.4 600.6 33.8 2782.1 Tendulkar 2009- 10 22.5 15.6 11.2 6.8 46.3 706.5 39.6 3259.3 Rangarajan 2011- 12 11.6 8.2 8.5 5.3 30.4 479.4 25.7 2166.6 Tendulkar 2011- 12 12.6 8.9 11.1 6.9 38.1 600.9 30.9 2605 Rangarajan Urban Sector 2004- 05 36.5 8.85 3.4 0.22 30.6 117.03 25.7 807.96 Lakdawala 2004- 05 26.2 6.4 4.6 0.3 34.1 130.3 25.7 807.6 Tendulkar 2009- 10 25.2 7.5 12.6 0.9 31.7 137.3 20.9 764.7 Tendulkar 2009- 10 36.4 10.9 22.5 1.5 49.6 215.1 35.1 1286.9 Rangarajan 2011- 12 10.5 3.4 4.3 0.3 36.4 10.9 13.7 531.2 Tendulkar 2011- 12 29.5 9.4 8.8 0.6 45.7 208.2 26.4 1024.7 Rangarajan Total 2004- 05 39.6 35.96 10 6.36 32.8 590.03 27.5 3017.2 Lakdawala 2004- 05 32.7 29.7 22.9 14.6 40.9 735.5 37.2 4076.1 Tendulkar 2009- 10 18 17.9 9.5 6.4 37.7 737.9 298 3546.8 Tendulkar 2009- 10 26.7 26.5 12.3 8.3 47 921.6 38.2 4546.2 Rangarajan 2011- 12 11.3 11.6 8.1 5.6 29.4 598.2 21.9 2697.8 Tendulkar 2011- 12 17.8 18.4 10.9 7.5 39.8 809.1 29.5 3629.9 Rangarajan Source: Government of India (2014)

54 Table 3.8a: Estimates of Deprivation in the Rural Sector: Incidence, Depth and Severity (2004/05 vs. 2011/12)

2004-05 2011-12 % reduction Uttara All Uttara All Uttara All Poverty Measures khand HP UP India khand HP UP India khand HP UP India Head-count ratio 35.13 24.97 42.68 41.89 11.7 8.48 30.4 25.73 -66.70 -66.04 -28.77 -38.58 Poverty Gap Index 5.78 4.21 9.15 9.66 1.25 1.03 5.68 5.05 -78.37 -75.53 -37.92 -47.72 FGT Index 1.4 1.11 2.77 3.17 0.20 0.18 1.61 1.5 -85.71 -83.78 -41.88 -52.68 Note: The estimates of deprivation corresponding to the normative poverty lines by the Tendulkar methodology. Source: Authors’ estimates based on the NSS 61st and 68th round central sample unit record data (Mixed Reference Period).

Table 3.8b: Estimates of Deprivation in the Urban Sector: Incidence, Depth and Severity (2004/05 vs. 2011/12) 2004-05 2011-12 % reduction Uttara All Uttara All Uttara All Poverty Measures khand HP UP India khand HP UP India khand HP UP India Head-count ratio 13.07 4.55 34.05 25.77 10.48 4.33 26.17 13.69 -19.82 -4.84 -23.14 -46.88 Poverty Gap Index 1.66 1.07 7.8 6.09 1.56 0.76 5.29 2.7 -6.02 -28.97 -32.18 -55.67 FGT Index 0.38 0.41 2.53 2.05 0.38 0.21 1.51 0.8 0.00 -48.78 -40.32 -60.98 Note:The estimates of deprivation corresponding to the normative poverty lines by the Tendulkar methodology. Source: Authors’ estimates based on the NSS 61st and 68th round central sample unit record data (Mixed Reference Period).

VI. MAINSTREAMING/MARGINALISATION

1. Conceptual Outline6

This Section examines the inclusive/exclusive profiles across social groups in the rural and urban sectors of Uttarakhand. The moot question would pertain to conceptualization and measurement: How do we define progress and inclusion in a plural society characterized by social stratification? When there are different social groups, and welfare schemes exclusively meant for some select social groups are pursued, it would be worthwhile to examine (i) the extent of progress of each group as a whole in an absolute sense as well as relative to the mainstream; and (ii) verify how far such programmes have enabled the deprived in these groups to catch up with better-off in their own strata as well as with those in the mainstream.

6 The conceptual framework and methodological details outlined in this section are based largely on Suryanarayana (2008, 2016).

55 To address these dual objectives, we examined the following (a) average progress, absolute as well as relative, made by each social group/region, and (b) mainstreaming/marginalization of the deprived in each of the social groups independently and also in a collective sense.

This would call for defining measures of strata (sub-stream)-specific as well as overall (mainstream) progress; this may be done in terms of estimates of group (sub-stream)  specific as well as overall (mainstream)  specific median. In a similar way, one may measure inclusion/exclusion of the poorest in each social group in its own progress as well as that of the mainstream by estimating the inclusion coefficients proposed in equation (1) with reference to mainstream and sub-stream medians respectively. The measures corresponding to these two concepts and their implications are as follows.

2. Measure of Inter-group Disparity (Inclusion/Exclusion) Methodologically, verification of absolute progress would involve review of status/improvement in median income/ consumption of the specific social group only. Assessment of inclusion or improvement relative to the mainstream would involve estimates of inter-group median disparities. For the latter, one may define the following measures.

Let μm denote mainstream (overall) median and μs sub-stream median. Disparity between the sub-group and the mainstream could be examined by comparing the median estimates. The following results would follow:

1) μs< αμm implies exclusion of the sub-group

2) μs> αμm would imply inclusion

Let us define a measure of inclusion (ηinter) as follows:

ηinter = [(μs/ αμm)-1] … (2) where 0 <α< 1; (0.6 in this study)

ηinter> 0 => Inter-group inclusion and ηinter < 0 => Inter-group exclusion

56 3. Measure of Mainstreaming/Marginalization

One may examine income/consumption of the bottom rungs of a given social group relative to its own median (one aspect of the intra-group dimension, that is, inclusion in the sub-group progress, namely, IC-subgroup) as well as the mainstream median (another aspect of the intra-group dimension, that is, inclusion in the mainstream progress, namely, IC-mainstream).

These estimates may be worked out by defining the estimator (1) with respect to sub- stream and mainstream median respectively. The former would give us a measure of participation of the bottom rungs of the social group concerned in its own (group-specific) progress while the latter with respect to mainstream progress.

It could so happen that there is some progress in terms of inclusion of the deprived section of a given social sub-group in its own progress (median) but the progress is quite unsatisfactory when measured with reference to the community as a whole. Such differences in progress could be measured by taking the ratio (ω) of IC – mainstream to IC-Subgroup, which may be called Inclusive Coefficient in a Plural society (ICP). ICP would take the value ‘one’ when the extent of inclusion is the same with respect to both sub-group and mainstream median; a value less than one would imply that the extent of inclusion in the mainstream is less than the extent of inclusion in the sub-group’s own progress; it would be an indication of marginalization . If one could consider IC-sub-group as a measure of inherent potential of the social group under review, the extent of its marginalization in the economy could be defined with reference to ICP (ω). A given social group is marginalized if its ω < 1 and the extent of marginalization is given by (ω-1). If ω> 1, (ω -1) would be > 0, which would indicate mainstreaming of the social group in the economy.

The estimators would be as follows:

Define inclusion coefficient (1) with respect to both mainstream median (ψm) and sub-stream median (ψs); their ratio ω would provide a measure of sub-group inclusion from its distributional perspective.

Define ηintra = (ω – 1) … (3)

We have ηintra> 0 => mainstreaming and ηintra< 0 => marginalization

57 Marginalization: First, Second & Third Degree

Marginalization: First Degree

When the distribution for a certain social group, say SG1, lies entirely to the left of the distribution corresponding to the rest of the population (RoP) such that the following conditions hold: th (i) P99(SGr) < P1(SGrop) where P99(SGr) = 99 income/consumption percentile of the st social group under review (SGr) and P1(SGrop) = 1 income/consumption

percentile of the rest of the population (SGrop)

(ii) ηintra = (-) 1

Marginalization: Second Degree

– ηinter< 0

– ηintra< 0

Marginalization: Third Degree

– ηinter> 0

– ηintra< 0

Given this framework, estimates of median across different social groups could be worked out using the latest available NSS data sets on consumption distribution for the years as those in Table 3.3. For this purpose, the following social groups (for which data are available) are considered: Scheduled Tribes (STs), Scheduled Castes (SCs), Other Backward Castes (OBCs) and others, of whom the first three are generally considered to be marginalized.

4. Results

Social Groups: Absolute Standards of Living and Deprivation Going by measures of absolute standard of living in terms of MPCE across percentiles for different social groups in rural Uttarakhand, both mean and order based estimates indicate that the OSGs are the most well-off, followed by OBCs and SCs, in 2004/05 as well as in 2011/12 (Table 3.9a). The profile of the STs changes abruptly between 2004/05 and 2011/12;

58 this could be due to statistical reasons.7The profile holds the same for the urban sector too (Table 3.9b).

Table 3.9a: Summary Statistics on Per Capita Monthly Consumer Expenditure Distribution by Social Groups: Rural Uttarakhand

Rural 2004-05 2011-12 Percentiles ST SC OBC Others Total ST SC OBC Others Total 1 311.70 271.72 300.26 298.46 296.40 678.77 700.12 680.4 688.91 681.39 5 367.60 327.76 333.69 369.57 344.24 808.47 753.18 742.28 821.81 791.37 10 387.46 345.25 345.96 393.81 372.23 844.47 817.96 841.85 925.95 848.39 25 460.49 404.92 420.84 472.93 449.13 1034.71 938.67 1110.88 1143.15 1024.42 50 521.81 498.39 539.20 604.38 555.72 1288.66 1061.4 1414.27 1365.81 1282.70 75 640.18 647.84 769.73 778.60 751.25 1678.34 1494.91 1739.92 1828.74 1739.92 90 827.39 946.67 941.22 1064.93 996.54 3093.51 1918.66 2171.87 2638.38 2373.71 95 1147.33 1113.83 1173.02 1318.07 1191.26 3093.51 4650.09 2423.97 3717.12 3256.17 99 1996.85 1749.98 1721.17 1942.55 1860.27 4091.54 5499.2 3624.68 5002.82 5499.20 Smallest 311.70 165.75 269.12 115.75 115.75 678.77 557.2 569.89 517.69 517.69 Largest 2158.01 2619.62 2616.00 9254.31 9254.31 6897.43 19662.56 6039.95 11677.86 19662.56 Range 1846.31 2453.87 2346.88 9138.56 9138.56 6218.66 19105.36 5470.06 11160.17 19144.87 IQR 179.70 242.92 348.89 305.67 302.12 643.63 556.24 629.04 685.59 715.50 Mean 599.69 576.74 615.77 696.43 648.94 1562.16 1417.37 1443.86 1641.76 1551.41 Std. Deviation 268.01 277.12 282.43 423.46 366.77 843.11 1101.90 584.90 902.26 917.57 Skewness 3.00 2.74 1.94 7.03 6.43 2.31 4.99 1.82 3.07 3.85 Kurtosis 14.80 14.86 8.64 101.66 101.17 11.54 52.05 9.85 19.02 36.29

7 For statistical reasons, the discussion on the results would not touch upon the estimates for STs in Uttarakhand, Himachal Pradesh and Uttar Pradesh.

59 Table 3.9b: Summary Statistics on Per Capita Monthly Consumer Expenditure Distribution by Social Groups: Urban Uttarakhand

Urban 2004-05 2011-12 Percentiles ST SC OBC Others Total ST SC OBC Others Total 1 440.72 293.45 364.89 340.65 338.72 645.36 909.85 700.83 769.60 700.83 5 525.82 376.39 379.25 462.43 418.61 645.36 1000.37 876.39 1038.82 957.92 10 525.82 418.61 421.16 525.12 467.64 645.36 1084.61 1000.45 1157.69 1075.22 25 582.23 486.77 539.02 691.93 598.26 1027.90 1165.21 1178.89 1549.62 1302.67 50 640.19 628.43 641.66 935.19 828.40 1302.74 1405.51 1485.65 2240.08 1829.39 75 749.95 793.26 974.09 1385.32 1246.72 1806.13 2133.53 2230.81 3267.29 2863.38 90 749.95 1241.65 1264.18 2029.50 1843.59 2980.70 2829.53 3139.11 4937.44 4012.96 95 2871.84 1468.51 1459.08 2701.48 2412.22 2980.70 3503.99 3593.53 6657.74 5625.18 99 2871.84 2648.67 1548.48 3617.06 3539.76 5167.47 5406.70 10996.54 16339.63 13730.12 Smallest 440.72 256.57 302.73 188.78 188.78 645.36 553.23 625.44 677.46 553.23 Largest 2871.84 5955.75 2806.72 8195.85 8195.85 5167.47 10773.79 10996.54 20563.76 20563.76 Range 2431.11 5699.18 2503.99 8007.07 8007.07 4522.11 10220.56 10371.10 19886.30 20010.53 IQR 167.72 306.49 435.07 693.39 648.47 778.23 968.32 1051.92 1717.67 1560.71 Mean 841.69 761.90 775.07 1173.44 1027.58 1643.18 1812.01 1915.51 2860.79 2451.97 Std. Deviation 647.36 620.22 337.28 775.73 714.27 932.11 1023.04 1485.07 2433.32 2109.38 Skewness 2.67 5.61 1.14 3.02 3.37 1.72 3.62 3.81 3.62 3.99 Kurtosis 8.41 44.21 4.16 19.60 22.99 7.13 24.14 21.03 19.77 24.45

Source: Authors’ estimates at current prices based on the NSS 61st and 68th round central sample unit record data (Schedule Type I).

To measure the different dimensions (incidence, depth and severity) of deprivation, we use the poverty lines estimated following the methodology proposed by the Tendulkar Committee. Consistent with the estimates of absolute levels of living, we find the incidence of absolute poverty to be the least among the OSGs, followed by OBCs and highest for SCs in 2004/05. The percentage point reduction in poverty in Uttarakhand between 2004/05 and 2011/12 is the maximum among the SCs (30.34) followed by OBCs (29.06), STs (20.52) and OSGs (18.88) (Fig. 3.1). Consistent with the increase in real consumption noted in Table 3.4a, we find a more or less uniform reduction (around 65 percent) in incidence of poverty among all the social groups in rural Uttarakhand (Table 3.10a). The relative profile of deprivation across social groups is similar in Himachal Pradesh and Uttarakhand but with a difference. The difference is that, unlike Uttarakhand, the extent of reduction in deprivation is highly uneven across social groups in Himachal Pradesh and Uttar Pradesh: Incidence of poverty declined by 88 per cent among the OBCs and by 62 per cent among the OSGs in Himachal

60 Pradesh and by 27 percent (OBCs) and 52 per cent (OSGs) in Uttar Pradesh. At the all India level, percentage poverty reduction fell in the range between 38 and 42 per cent among SCs, OBCs and OSGs.

Table 3.10a: Estimates of Deprivation: Incidence, Depth and Severity by Social Group: Rural Sector (2004/05 & 2011/12)

2004-05 2011-12 Reduction in poverty (%)

ST SC OBC OSGs Total ST SC OBC OSGs Total ST SC OBC Others Total Poverty Measures Uttarakhand Head-count 32.4 46.2 43.4 14.4 - - - - ratio 4 4 6 27.89 35.13 11.92 15.90 0 9.01 11.7 63.26 65.61 66.87 -67.69 66.70 Poverty Gap - - - - Index 4.81 8.53 7.34 4.2 5.78 0.89 1.75 1.71 0.92 1.25 81.50 79.48 76.70 -78.10 78.37 - - - - FGT Index 0.97 2.24 1.82 0.96 1.4 0.10 0.27 0.31 0.15 0.20 89.69 87.95 82.97 -84.38 85.71 Himachal Pradesh Head-count 35.3 39.4 - - - - ratio 7 5 19 18.28 24.97 9.48 16.45 2.28 7.00 8.48 73.20 58.30 88.00 -61.71 66.04 Poverty Gap - - - - Index 7.87 7.35 3.08 2.57 4.21 1.19 2.02 0.31 0.83 1.03 84.88 72.52 89.94 -67.70 75.53 - - - - FGT Index 2.86 2.05 0.74 0.57 1.11 0.25 0.37 0.06 0.14 0.18 91.26 81.95 91.89 -75.44 83.78 Uttar Pradesh Head-count 41.9 56.4 42.1 30.7 - - - - ratio 9 8 7 26.01 42.68 27.01 41.11 2 12.47 30.4 35.68 27.21 27.15 -52.06 28.77 Poverty Gap 12.7 - - - Index 5.92 8 8.84 5.31 9.15 6.29 8.06 5.58 2.16 5.68 6.25 36.93 36.88 -59.32 37.92 - - - FGT Index 1.25 4.02 2.61 1.57 2.77 1.99 2.21 1.62 0.58 1.61 59.20 45.02 37.93 -63.06 41.88 All India Head-count 61.9 52.7 41.0 24.0 - - - - ratio 7 8 2 26.21 41.89 42.74 32.28 1 14.99 25.73 31.03 38.84 41.47 -42.81 38.58 Poverty Gap 18.1 12.6 - - - - Index 2 4 8.79 5.18 9.66 10.41 6.54 4.4 2.38 5.05 42.55 48.26 49.94 -54.05 47.72 - - - - FGT Index 7.04 4.2 2.71 1.5 3.17 3.6 1.93 1.24 0.59 1.5 48.86 54.05 54.24 -60.67 52.68 Note: The estimates of deprivation corresponding to the normative poverty lines by the Tendulkar methodology

Source: Authors’ estimates based on the NSS 68th round central sample unit record data (Schedule Type I).

61 Fig. 3.1: Incidence of Poverty (%) across Social Groups: Rural Uttarakhand

The relative profiles of absolute deprivation in urban Uttarakhand are slightly different from those observed for the rural sector (Table 3.10b). Even though the relative standing of the three social groups–SCs, OBCs and OSGs – is the same as for the rural one for the year 2004/05, it changes for the year 2011/12:The SCs and OBCs interchange their rank in terms of the extent of deprivation. This is because of a massive reduction in deprivation (80 percent) among the SCs as compared to only 45 per cent among the OBCs. Thus, unlike the rural sector, the extent of reduction in poverty across social groups in urban Uttarakhand is highly uneven: the percentage point reduction in urban poverty was the maximum among SCs (38.17) followed by OBCs (15.86), STs (13.32) and OSGs (11.51) (Fig.3.2). The same profile could be found in Himachal Pradesh and Uttar Pradesh. As regards Himachal Pradesh, poverty actually increased among the STs and SCs in urban areas. Urban all India too has experienced uneven extent of reduction in poverty among the four social groups under review.

62 Table 3.10b: Estimates of Deprivation: Incidence, Depth and Severity by Social Group: Urban Sector (2004/05 & 2011/12)

2004-05 2011-12 Reduction in Poverty (%) Othe Othe Othe ST SC OBC rs Total ST SC OBC rs Total ST SC OBC rs Total Poverty Measures Uttarakhand Head-count 17.9 25.7 19.1 - - - - ratio 39.05 47.46 34.97 3 26.20 3 9.29 1 6.42 10.48 -34.11 80.43 45.35 64.19 60.00 Poverty Gap - - - Index 4.04 10.13 7.04 3.22 1.66 8.80 0.95 2.72 0.95 1.56 117.82 90.62 61.36 70.50 -6.02 - - - FGT Index 0.59 2.94 1.93 0.87 0.38 3.36 0.13 0.63 0.23 0.38 469.49 95.58 67.36 73.56 0.00

Himachal Pradesh Head-count - ratio 2.42 9.24 10.84 2.53 4.55 4.01 9.93 9.86 1.74 4.33 65.70 7.47 -9.04 31.23 -4.84 Poverty Gap - - - Index 0.69 1.67 2.62 0.71 1.07 0.31 2.21 1.61 0.22 0.76 -55.07 32.34 38.55 69.01 28.97 - - - FGT Index 0.20 0.50 0.77 0.34 0.41 0.04 0.73 0.28 0.06 0.21 -80.00 46.00 63.64 82.35 48.78

Uttar Pradesh Head-count 20.8 16.3 39.1 32.3 - - - - ratio 40.31 44.24 42.71 6 34.05 1 4 1 12.77 26.17 -59.54 11.53 24.35 38.78 23.14 Poverty Gap - - - - Index 10.55 11.58 9.77 4.28 7.8 5.16 8.31 6.5 2.44 5.29 -51.09 28.24 33.47 42.99 32.18 - - - - FGT Index 3.83 3.92 3.19 1.31 2.53 1.72 2.48 1.81 0.71 1.51 -55.09 36.73 43.26 45.80 40.32

All India Head-count 15.8 23.2 21.5 16.2 - - - - ratio 35.05 40.03 31.46 9 25.77 7 7 3 7.38 13.69 -33.61 46.12 48.41 53.56 46.88 Poverty Gap - - - - Index 10.44 10.13 7.44 3.37 6.09 5.04 4.29 3.28 1.34 2.7 -51.72 57.65 55.91 60.24 55.67 - - - - FGT Index 4.2 3.58 2.49 1.05 2.05 1.59 1.29 0.98 0.36 0.8 -62.14 63.97 60.64 65.71 60.98 Note: The estimates of deprivation corresponding to the normative poverty lines by the Tendulkar methodology

Source: Authors’ estimates based on the NSS 68th round central sample unit record data (Schedule Type I).

Fig. 3.2: Incidence of Poverty (%) across Social Groups: Urban Uttarakhand

63 Social Group Inclusion/Exclusion One would seldom come across evidence for marginalization of the first degree anywhere in

India. The estimates of disparity ratios (ηinter ) clearly provide unambiguous evidence of inter- group inclusion of all the social groups in the state mainstream in both rural and urban sectors of Uttarakhand as well as the remaining states under review. The extent of inclusion varies across social groups, however measured. The main findings are as follows:

Rural Uttarakhand:

(i) The extent of median inclusion in rural Uttarakhand was the highest for the OSGs (81 per cent) in 2004/05 which declined to 77 per cent by 2011/12 (Table 3.11a). It has been lowest for SCs, which declined from 49 per cent to 38 per cent in rural Uttarakhand. The mean based estimates confirm this profile only for OSGs but not for SCs. Given the robust property of the order-based estimates for skewed distributions, one may confirm the findings based on the order-based estimates. (ii) The OBCs improved their extent of mainstream median inclusion from 62 per cent in 2004/05 to 84 per cent in 2011/12. The STs too improved their inter-group median inclusion from 57 per cent to 67 per cent between the two years under review. The mean based inclusion measures confirm this finding for STs only. However, the estimates for STs may not be robust. (iii) These results show that inclusion process for SCs was far behind as compared to other social groups in rural Uttarakhand; and the reach of high economic growth to SCs was less than satisfactory.

Urban Uttarakhand:

(iv) Both OBCs and OSGs improved their lot as measured by both mean- and order- based measures inter-group inclusion (Table 3.11b). (v) These two measures unambiguously reveal a reduction in inter-group inclusion of the STs. The order based measure showed marginal improvement in the inter- group inclusion of the SCs in urban areas of Uttarakhand.

64 Table 3.11a: Measures of Inter-Group Inclusion/Exclusion: Rural Uttarakhand

2004-05 2011-12 ST SC OBC Others Total ST SC OBC Others Total Mean 599.69 576.74 615.77 696.43 648.94 1562.16 1417.37 1443.86 1641.76 1551.41 Disparity wrtUtatrak hand Total mean MPCE (ηinter%) 54.02 48.12 58.15 78.86 67.82 52.27 55.11 76.37 - Median 521.81 498.39 539.20 604.38 555.72 1288.66 1061.4 1414.27 1365.81 1282.70 Disparity wrt Uttarakhan d Total median MPCE (ηinter%) 56.50 49.47 61.71 81.26 67.44 37.91 83.76 77.47 Source: Authors’ estimates at current prices based on the NSS 61st and 68th round central sample unit record data sets (Schedule Type I).

Table 3.11b: Measures of Inter-Group Inclusion/Exclusion: Urban Uttarakhand

2004-05 2011-12 ST SC OBC Others Total ST SC OBC Others Total Mean 841.69 761.90 775.07 1173.44 1027.58 1643.18 1812.01 1915.51 2860.79 2451.97 Disparity wrtUtatrak hand Total mean MPCE (ηinter%) 36.52 23.58 25.71 90.32 11.69 23.17 30.20 94.46 Median 640.19 628.43 641.66 935.19 828.40 1302.74 1405.51 1485.65 2240.08 1829.39 Disparity wrt Uttarakhan d Total median MPCE (ηinter%) 28.80 26.43 29.10 88.15 18.69 28.05 35.35 104.08 Source: Authors’ estimates at current prices based on the NSS 61st and 68th round central sample unit record data sets (Schedule Type I).

Social Group Mainstreaming/Marginalization

The extent of mainstreaming/marginalization of different social groups could be examined in terms of estimates of ηintra coefficient (Table 3.12). The results are as follows:

65 Rural Sector:

(i) Uttarakhand: In 2004/05, mainstream inclusion was the maximum for STs in rural Uttarakhand. The extent of mainstream inclusion for the bottom half of STs and OSGs exceeded that for SCs and OBCs. This profile remained the same in 2011/12 but for some marginal decline in mainstream inclusion for STs, OBCs and OSGs. As regards the SCs, main stream inclusion increased marginally between the two years. The SCs and OBCs were the marginalized social groups in 2004/05; only SCs continued to be so in 2011/12.

(ii) Himachal Pradesh: The extent of mainstream inclusion was the highest for OSGS in 2004/05; the OBCs replaced OSGs in this position in 2011/12. Mainstream inclusion for STs and SCs is less than the average for the population as a whole. However, the extent of mainstream inclusion improved for STs, SCs and OBCs in 2011/12. Both SCs (13%) and STs (18%) are the marginalized sections of the Himachal population; the extent of marginalization of the SCs, however, declined from 27 per cent in 2004/05 to 18 per cent in 2011/12.

(iii) Uttar Pradesh: Among the SCs, OBCs and OSGs, the extent of mainstreaming was highest for OSGs in 2004/05 followed by OBCs and SCs. The profile remained the same in 2011/12 even though the extent of mainstreaming of OBCs and SCs declined. The SCs are the most marginalized group whose extent of marginalization increased between the two years under consideration. The OBCs appear to be slightly marginalized in 2011/12 only.

(iv) All India: The extent of mainstreaming is the highest for OSGs, followed by OBCs, SCs and STs. Barring the OSGs, mainstreaming has declined for all the social groups. Both STs and SCs are the marginalized ones whose extent of marginalization declined in 2011/12.

Urban Sector

Uttarakhand: In 2004/05, mainstream inclusion was the maximum for the STs in urban Uttarakhand. The extent of mainstream inclusion for the bottom half of the STs and OSGs exceeded that for the SCs and OBCs. This profile changed altogether in 2011/12 which saw a drastic reduction for the STs and improvement for the SCs in mainstream inclusion The STs, SCs and OBCs are the marginalized social groups in 2004/05 as well as 2011/12; however,

66 the extent of marginalization of the SCs and OBCs has declined between the years under review (Table 3.12b).

Table 3.12a: Extent of Mainstreaming/Marginalization by Social Groups: Rural Sector Rural 2004-05 2011-12 ST SC OBC Others Total ST SC OBC Others Total Uttarakhand Mainstream Inclusion 0.977 0.865 0.902 0.969 0.934 0.975 0.874 0.863 0.944 0.915 Substream Inclusion 0.977 0.955 0.938 0.908 0.934 0.975 0.992 0.768 0.903 0.915 Mainstreaming vs. Marginalization (ηintra %) 0.00 (-)9.39 (-)3.80 6.78 0.00 0.00 (-)11.97 12.39 4.59 0.00 Himachal Pradesh Mainstream Inclusion 0.721 0.647 0.866 0.900 0.818 0.817 0.730 0.967 0.871 0.853 Substream Inclusion 0.756 0.886 0.866 0.82666 0.818 0.942 0.887 0.868 0.806 0.853 Mainstreaming vs. Marginalization (ηintra %) (-)4.60 (-)26.92 0.00 8.89 0.00 (-)13.26 (-)17.64 11.39 8.07 0.00 Uttar Pradesh Mainstream Inclusion 0.958 0.804 0.874 0.934 0.868 0.772 0.752 0.862 0.948 0.846 Substream Inclusion 0.981 0.911 0.869 0.825 0.868 0.742 0.901 0.877 0.840 0.846 Mainstreaming vs. Marginalization (ηintra %) (-)2.36 (-)11.68 0.55 13.18 0.00 3.98 (-)16.51 (-)1.70 12.89 0.00 All-India Mainstream 0.546 0.743 0.844 0.923 0.812 0.559 0.716 0.820 0.923 0.793 Inclusion Substream 0.814 0.861 0.840 0.786 0.812 0.790 0.796 0.807 0.779 0.793 Inclusion Mainstreaming vs. Marginalization -32.87 -13.64 0.38 17.36 0.00 -29.33 -10.14 1.54 18.41 0.00 (ηintra %)

Himachal Pradesh: The extent of mainstream inclusion was the highest for the STs in 2004/05 and 2011/12. Mainstream inclusion for the SCs and OSGs was less than the average for the population as a whole. The extent of mainstream inclusion has declined for all the social groups between the two years under review. Both the SCs and OBCs are the marginalized sections of the Himachal population; the extent of marginalization of SCs, however, increased from 20 per cent to 82 per cent and that for OBCs from one per cent to 25 per cent.

67 Uttar Pradesh: Among the SCs, OBCs and OSGs, the extent of mainstreaming was the highest for OSGs followed by OBCs and SCs in 2004/05 and 2011/12.The extent of mainstreaming of these three social groups and the profile for the population as a whole improved during this period. The SCs and the OBCs are the marginalized social groups.

All India: The extent of mainstreaming is the highest for OSGs, followed by OBCs, SCs and STs. Mainstreaming improved for the STs and OSGs but declined for SCs and OBCs. The STs, SCs and OBCs are the marginalized ones; the extent of marginalization of STs increased while that of SCs and OBCs declined marginally in 2011/12.

Table 3.12b: Extent of Mainstreaming/Marginalization by social groups: Urban Sector

Urban 2004-05 2011-12 ST SC OBC Others Total ST SC OBC Others Total Uttarakhand Mainstream Inclusion 0.934 0.473 0.660 0.812 0.729 0.485 0.786 0.602 0.850 0.770 Substream Inclusion 1 0.889 0.898 0.727 0.729 0.599 0.991 0.864 0.687 0.770 Mainstreaming vs. Marginalization (ηintra %) -6.62 -46.84 -26.49 11.67 0.00 -19.03 -20.64 -30.34 23.73 0.00 Himachal Pradesh Mainstream Inclusion 0.952 0.731 0.773 0.738 0.746 0.920 0.142 0.542 0.675 0.568 Substream Inclusion 0.952 0.911 0.783 0.574 0.746 0.814 0.784 0.724 0.675 0.568 Mainstreaming vs. Marginalization (ηintra %) 0.00 -19.73 -1.31 28.58 0.00 13.04 -81.91 -25.19 0.00 0.00 Uttar Pradesh Mainstream Inclusion 0.748 0.563 0.623 0.863 0.713 0.691 0.581 0.688 0.888 0.745 Substream Inclusion 0.748 0.798 0.790 0.672 0.713 0.114 0.850 0.851 0.592 0.745 Mainstreaming vs. Marginalization (ηintra %) 0.00 -29.47 -21.19 28.52 0.00 505.26 -31.63 -19.13 49.85 0.00 All-India 0.445 0.416 0.559 0.789 0.639 0.417 0.425 0.553 0.784 0.623 Mainstream Inclusion 0.569 0.727 0.711 0.600 0.639 0.605 0.687 0.675 0.606 0.623 Substream Inclusion Mainstreaming vs. Marginalization -21.72 -42.75 -21.32 31.62 0.00 -31.13 -38.15 -18.01 29.40 0.00 (ηintra %) Source: Authors’ estimates based on the NSS 68th round central sample unit record data (Mixed Reference Period).

Thus, the estimates of inclusion/exclusion and mainstreaming/marginalization presented in Tables 3.12 and 3.13 provide unambiguous evidence of Third-degree marginalization in the three states under review and India as a whole.

68 VII. SUMMARY

Defining a concept of deprivation and deriving a corresponding measure of it consistently across heterogeneous regional contexts is an empirical challenge for studies on a state like Uttarakhand. Therefore, this study has made an attempt to examine issues related to deprivation and inequality in Uttarakahand from a statistical perspective as well as in terms of conventional concepts and measures. In order to assess the challenges and achievements of Uttarakhand, we carry out the analysis in a comparative setting involving its parent state, Uttar Pradesh, the neighbouring hill state of Himachal Pradesh and the national context of India. The major findings are as follows:

Uttarakhand stands second among the three states under review in terms of estimates of measures of average consumer expenditures for both rural and urban sectors. It has improved while both Himachal Pradesh and Uttar Pradesh have declined in terms of their average consumption levels relative to that of the nation as a whole. This would suggest that Uttarakhand’s pace of progress is better than that of the rest of India; not so for Himachal Pradesh and Uttar Pradesh.

Inequality in rural nominal consumption distribution, however, measured, was the least in Uttarakhand in 2004/05. The extent of relative nominal consumption inequality increased in Uttarakhand by 2011/12; the percentage points increase was the highest in Uttarakhand among the four states (all-India inclusive) under review. As regards urban nominal consumption inequality, it increased in all the states under review; the percentage increase was the highest in Himachal Pradesh followed by Uttar Pradesh, Uttarakhand and All-India respectively.

The extent of inclusion of the bottom half of the rural population in the mainstream was 93.40 per cent in Uttarakhand in 2004/05, which was the highest of the cases under review. Mainstream inclusion increased in urban Uttarakhand and Uttar Pradesh but declined in Himachal Pradesh and all-India. The reasons for such inclusion could be improved reach of government’s redistributive programmes in rural areas of these states.

Estimates of absolute deprivation vary depending upon the concept and measure used. This study has explored conventional as well as contemporary approaches in this respect. As per the Lakdawala approach, the incidence of rural poverty was the highest in Uttarakhand, followed by Uttar Pradesh and Himachal Pradesh in the rural, urban and total economy as a

69 whole in 2004/05. This profile is different from the one revealed by the Tendulkar Committee method for the same year, which show the incidence of deprivation to be the highest in Uttar Pradesh followed by Uttarakhand and Himachal Pradesh in the same year. In general, both Tendulkar and Rangarajan Committee approaches reveal a reduction in poverty in all the states at successive points of time under review. As regards urban poverty, the reduction was much higher at the national level than in Uttar Pradesh followed by Uttarakhand and Himachal Pradesh respectively.

Consistent with the estimates of absolute levels of living, we find the incidence of absolute poverty to be the least among the OSGs, followed by OBCs and highest for SCs in 2004/05. The percentage point reduction in poverty in Uttarakhand between 2004/05 and 2011/12 was the maximum among the SCs (30.34) followed by the OBCs (29.06), the STs (20.52) and the OSGs (18.88). There was a more or less uniform reduction (around 65 percent) in incidence of poverty among all the social groups in rural Uttarakhand. The relative profile of deprivation across social groups is similar in Himachal Pradesh and Uttarakhand but with a difference. The difference is that, unlike Uttarakhand, the extent of reduction in deprivation is highly uneven across social groups in Himachal Pradesh and Uttar Pradesh: Incidence of poverty declined by 88 per cent among OBCs and by 62 per cent among OSGs in Himachal Pradesh, and by 27 per cent (OBCs) and 52 per cent (OSGs) in Uttar Pradesh. At the all India level, percentage poverty reduction fell in the range between 38 and 42 per cent among SCs, OBCs and OSGs.

The relative profiles of absolute deprivation in urban Uttarakhand is slightly different from the one observed for the rural one. Even though the relative standing of the three social groups– the SCs, OBCs and OSGs – is the same as the rural one for the year 2004/05, it changes for the year 2011/12 – the SCs and the OBCs interchange their rank in terms of the extent of deprivation. This is because of a massive reduction in deprivation (80 percent) among the SCs as compared to only 45 per cent among the OBCs. Thus, unlike the rural sector, the extent of reduction in poverty across social groups in urban Uttarakhand is highly uneven: the percentage point reduction in urban poverty was the maximum among SCs (38.17) followed by OBCs (15.86), STs (13.32) and OSGs (11.51). The same profile could be found in Himachal Pradesh and Uttar Pradesh. As regards Himachal Pradesh, poverty actually increased among STs and SCs in urban areas. Urban all India too has experienced uneven extent of reduction in poverty among the four social groups under review.

70 The extent of mainstream inclusion in rural Uttarakhand was the highest for OSGs (81%) in 2004/05 which declined to 77 per cent by 2011/12. It has been the lowest for SCs, which declined from 49 per cent to 38 per cent in rural Uttarakhand. The rural OBCs improved their extent of mainstream inclusion from 62 per cent in 2004/05 to 84 per cent in 2011/12. The STs too improved their inter-group inclusion from 57 per cent to 67 per cent between these two years under review. These results show that inclusion process for SCs was far behind compared to other social groups in rural Uttarakhand; and the reach of high economic growth to SCs was less than satisfactory. Both the OBCs and OSGs improved their lot as measured by both mean- and order-based measures of inter-group inclusion in urban Uttarakhand.

Mainstream inclusion was the maximum for STs in rural Uttarakhand in 2004/05. The extent of mainstream inclusion for the bottom half of the STs and OSGs exceeded that for the SCs and OBCs. This profile remained the same in 2011/12 but for some marginal decline in mainstream inclusion for the STs, OBCs and OSGs. As regards the SCs, mainstream inclusion increased marginally between the two years. The SCs and OBCs were the marginalized social groups in 2004/05; only the SCs continued to be so in 2011/12.

Mainstream inclusion was maximum for the STs in urban Uttarakhand. The extent of mainstream inclusion for the bottom half of the STs and OSGs exceeded that for the SCs and OBCs. This profile changed altogether in 2011/12 which saw a drastic reduction for the STs and improvement for the SCs in mainstream inclusion. The STs, SCs and OBCs were the marginalized social groups in 2004/05 as well as 2011/12; however, the extent of marginalization of the SCs and the OBCs declined between the years under review.

71 Chapter - IV

DEPRIVATION IN UTTARAKHAND A District-wise Profile

Having presented the macro profiles of levels of living, extent of mainstream and sub stream inclusion, extent of inequality, deprivation and marginalization across rural/urban sectors and by social groups for Uttarakhand in juxtaposition with those for Himachal Pradesh, Uttar Pradesh and All India, this Chapter presents empirical evidence on select distributional issues at the district level in Uttarakhand. The reference year is 2011/12. To be specific, it seeks to examine the following issues:

(i) What is the extent of inter-district disparities and observed profile in terms of monthly per capita household consumer expenditure?

(ii) What is the extent of nominal relative inequality in per capita household consumer expenditure in the rural and urban sectors across districts and in the state as a whole?

(iii) How lopsided is the welfare outcome as reflected in estimate of incidence of poverty between hill and plain regions?

(iv) What is the profile of incidence of absolute poverty across social groups in hill and plain districts/regions?

(v) What are the major covariates of poverty across districts in rural and urban Uttarakhand?

In pursuit of empirical evidence for the questions raided above, the chapter is structured as follows: Section Ideals with the data, its limitations and methodology of estimation of poverty at district-level for Uttarakhand. Section II analyses rural-urban disparities in monthly per capita consumer expenditure (MPCE) across districts and their rural and urban areas, in a comparative framework. Section IIIpresents estimate of extent of relative inequality across districts by rural and urban sectors. Section IVprovides district-wise estimates of poverty separately for rural and urban areas. Section Vexamines the rural urban profiles in different consumption related parameters. Section VI provides profiles of poverty across social groups by hill and plain regions in rural and urban Uttarakhand. Section VII analyses the determinants of poverty. The final section concludes the chapter.

72 I. DATA BASE AND METHODOLOGY

The NSS is based on stratified multi-stage sample design. The stratification involves division of the state into different regions with respect to population and agro-economic parameters. Conventional NSS design is such as to generate samples representative at the regional level. The NSS samples at the district level are suspect to suffer from inadequate number of sample observations. As a result, samples at the district level would not show enough variability to permit robust statistical analysis. Hence, it has become customary for studies on state and district level human development reports to pool state and central samples of NSS household consumption distribution to generate representative samples at the district level ( a la Minas and Sardana, 1990). For the current study on Uttarakhand, the Directorate of Economics and Statistics (DES), Government of Uttarakhand has pooled the central and state samples of NSS 68th round data for Uttarakhand (Government of Uttarakhand (GoUK), 2016).8

NSS estimates are generally made available at current local prices. Hence there is a need to revise the estimates at some comparable prices for different district wise information. The price adjustments are carried out using district-wise cost of living indices estimated a la the Fisher ideal index number. For this purpose, we have made use of unit values derived from district-wise NSS estimates of values and quantities of 102major items of consumption reported in the pooled state-central samples for rural and urban sectors separately. We have used the same spatial cost of living indices to work out district-specific poverty lines corresponding to the state level poverty lines of Rs 880 for therural sector and Rs 1082 for the urban sector (vide methodology recommended by the Tendulkar Committee methodology (see Section 4 & Table 7)).

II. INTER-DISTRICT DISPARITIES IN CONSUMPTION

The district-wise estimates of mean MPCE (with and without adjustments for inter-district variations in prices) by rural and urban sectors in Uttarakhand are presented in Tables 4.1 and 4.2 respectively. They show variability in the distribution for each district. Some salient features are as follows:

8Please refer to GoUK (2016) for statistical details on pooling and estimates of relative standard errors. Weights for the pooling the state and central samples are worked out using the matching ratio method. This method involves obtaining an aggregate estimate of pooled sample in proportion matching ratio m: n of central and state sample aggregate estimate; where, m and n are the allotted sample for central and state sample respectively for rural and urban sector. When the State’s participation is equal matching of central samples, the simple average of two estimates may be a way of combining the estimates considering central and state samples as independent samples. The sample sizes of households and person and persons across districts are provided in Annexure 1 of the chapter.

73 1. Rural Sector

(i) The average MPCE (at average state level prices) in rural Uttarakhand was Rs 1460.10 in 2012/13. The district-wise average MPCE ranged from the minimum of Rs 1292.03 (Pithoragarh) to Rs 1927.07 (Nainital) (Table 4.1b). Thus, Nainital and Pithoragarh turn out to be the best-off and worst-off districts in the rural Uttarakhand.

(ii) The marginal distribution of rural mean MPCE across districts is positively skewed (Figure 1), which indicates high density of the poor half of the districts in a narrow range at low levels of living and limited scattered prosperity across districts at the over a wide upper range. Nainital is even an outlier prosperous district in the rural sector (Figure 4.1).

(iii)Pithoragarh, Pauri Garhwal, Haridwar and Dehradun hills constitute the poorest quartile group of districts in terms of average per capita consumer expenditure at state level prices; Rudraprayag, Chamoli, Nainital Hills and Tehri Garhwal form the lower middle quartile group; Bageshwar, Uttarkashi, Almora and Champawat belong to the upper middle quartile group;Dehradun, Udham Singh Nagar and Nainital form the richest quartile group in the rural sector of Uttarakhand (Table 4.7)

(iv) As per estimate at local prices, the poorest of the district-wise poorest sample observation across districts is located in Pithoragarh (Rs 424.4) while the richest among the district-wise poorest is found in Nainital Hills (Rs 704.61). Conversely, the poorest of among the district-wise richest is located in Nainital Hills (Rs 4271.23) while the richest among the district-wise richest rich is found in Dehradun (Rs 19662.56) (Table 4.1a)

(v) MPCE (at local prices) distribution varied across districts with respect to its different dimensions. While the range between the richest and the poorest was the minimum in Nainital Hills (Rs 3566.62), inter-quartile range was the minimum in Tehri Garhwal (Rs 410.96) and standard deviation in Nainital Hills (Rs 563.72). The range between the poorest and the richest was the maximum in Dehradun (Rs19092.67), inter- quartile range was the maximum in Nainital (Rs 986) and standard deviation in Champawat (Rs 1218.99).This clearly brings out how heterogeneous are the districts with respect to even the factors governing the distribution of per capita household consumer expenditure (Table 4.1a).

74 Table 4.1a: Summary Profiles of District-wise Consumer Expenditure Distribution: Rural Uttarakhand 2011/12 (At current local prices)

Percentiles Uttarkashi Chamoli Rudraprayag Tehri Garhwal Dehradun Pauri Garhwal Pithoragarh Bageshwar Almora Champawat Nainital Udham Singh Nagar Haridwar Nainital Hills Dehradun Hills State as a whole

1 551.17 714.35 487.38 667.67 602.71 502.68 424.4 476.32 543.12 633.72 597.82 681.39 445.47 704.61 678.77 502.68

5 578.19 807.1 726.41 847.48 602.71 565 538.48 557.2 634.22 765.06 841.85 820.19 601.32 766.11 781.81 622.9

10 578.19 843.49 781.14 874.22 838.38 686.27 755.63 677.95 709.44 790.85 877.46 923.28 601.32 837.33 921.29 753.18

25 914.49 1002.39 953.41 1056.09 1125.63 851.52 959.89 855.02 924.18 976.68 1213.53 1155.38 905.57 965.44 1083.23 950.91

50 1262.34 1230.83 1318.12 1206.12 1340.42 1067.89 1112.48 1165.04 1129.92 1310.86 1537.84 1453.66 1091.00 1300.27 1288.66 1232.14

75 1686.54 1627.46 1591.41 1467.05 2033.34 1706.26 1460.08 1535.25 1670.64 1708.88 2196.39 1869.57 1522.27 1739.16 1515.19 1697.84

90 2198.35 2267.28 2063.55 1893.02 3076.03 2195.74 1866.41 2173.59 2257.75 2724.97 3253.66 2328.64 2036.89 1801.42 1693.25 2249.08

95 2556.76 2576.44 2489.79 2230.07 3256.17 2694.59 2250.98 2680.91 2795.46 3676.5 3737.58 3673.26 3093.51 2681.39 2463.99 3093.51

99 5842.37 4086.18 3695.68 3801.4 4457.78 3951.95 3599.67 4091.54 4607.64 10066.66 4893.34 4469.88 5499.2 4238.81 7206.75 5002.82

Smallest 442 681.03 487.38 566.32 569.89 441.61 424.4 476.32 475.53 633.72 546.79 681.39 445.47 704.61 678.77 424.4

Largest 11677.34 4766.29 4810.81 5434.57 19662.56 6970.68 6626.62 6405.86 4715.19 10066.66 12749.86 11677.86 7571.72 4271.23 9207.68 19662.56

Range 11235.34 4085.26 4323.43 4868.25 19092.67 6529.07 6202.22 5929.54 4239.66 9432.94 12203.07 10996.47 7126.25 3566.62 8528.91 19238.16

IQR 772.05 625.07 638.00 410.96 907.71 854.74 500.19 680.23 746.46 732.20 982.86 714.19 616.70 773.72 431.96 746.93

Mean 1429.54 1426.53 1382.37 1354.70 1698.95 1353.30 1274.28 1331.35 1377.84 1581.95 1904.54 1638.13 1346.29 1375.29 1408.50 1460.10

Std. Deviation 1165.80 669.73 601.17 604.45 1005.71 749.73 596.18 759.33 737.19 1218.99 1054.97 862.67 936.28 563.72 797.92 873.55 Skewness 6.20 2.25 1.76 3.27 5.37 2.12 2.49 2.57 2.01 4.44 2.52 2.78 3.18 1.95 5.99 3.83 Kurtosis 53.21 9.32 7.84 18.39 82.66 10.28 14.40 13.02 7.97 28.21 18.17 14.98 15.43 9.19 47.80 35.82 Note: NSSO collects sample separately from hill and plain areas of Nainital and Dehradun districts for capturing geographic-specific diversities in consumption expenditure and employment. These two sub-samples from hill and plain areas are then aggregated to arrive at district level estimates. Source:Authors’ estimates based on the NSS 68th round central and state sample pooled unit record data

75 Table 4.1b: Summary Profiles of District-wise Consumer Expenditure Distribution: Rural Uttarakhand 2011/12 (Atcurrent average state level rural prices) Udham Singh Percentiles Uttarkashi Chamoli Rudraprayag Tehri Garhwal Dehradun Pauri Garhwal Pithoragarh Bageshwar Almora Champawat Nainital Nagar Haridwar Nainital Hills Dehradun Hills State 1 536.78 670.73 466.85 666.35 553.46 480.98 430.31 490.97 595.12 608.80 604.89 692.63 428.98 689.20 633.71 502.68 5 563.10 757.82 695.81 845.80 553.46 540.61 545.98 574.34 694.94 734.97 851.81 833.72 579.06 749.35 729.91 622.9 10 563.10 791.99 748.24 872.49 769.88 656.64 766.15 698.80 777.36 759.75 887.84 938.51 579.06 819.01 860.13 753.18 25 890.62 941.19 913.25 1054.00 1033.66 814.75 973.26 881.32 1012.66 938.27 1227.88 1174.44 872.05 944.32 1011.32 950.91 50 1229.39 1155.68 1262.60 1203.73 1230.90 1021.78 1127.98 1200.87 1238.10 1259.31 1556.03 1477.64 1050.61 1271.82 1203.11 1232.14 75 1642.52 1528.09 1524.37 1464.14 1867.20 1632.59 1480.42 1582.47 1830.58 1641.67 2222.37 1900.42 1465.92 1701.11 1414.60 1697.84 90 2140.97 2128.84 1976.63 1889.27 2824.69 2100.93 1892.41 2240.44 2473.90 2617.80 3292.14 2367.06 1961.49 1762.01 1580.84 2249.08 95 2490.03 2419.13 2384.91 2225.65 2990.11 2578.25 2282.33 2763.37 3063.09 3531.91 3781.79 3733.87 2978.99 2622.73 2300.41 3093.51 99 5689.88 3836.68 3540.00 3793.87 4093.54 3781.32 3649.81 4217.38 5048.77 9670.76 4951.22 4543.63 5295.62 4146.08 6728.31 5002.82 Mean MPCE 1392.23 1339.43 1324.14 1352.02 1560.13 1294.87 1292.03 1372.30 1509.75 1519.73 1927.07 1665.15 1296.45 1345.21 1314.99 1460.10 Note and Source: Same as in Table 4.1a.

76 Figure 4.1: Mean Levels of Living across Rural and Urban Districts: Uttarakhand

Levels of Living: Uttarakhand Rural & Urban Sectors 3 , 0 0 0 2 , 5 0 0

2 Nainital , 0 0 0 D 1 i , s 5 t r 0 i c 0 t w i s e 1

m , 0 e 0 a

0 Rural Urban n

M P C

Note: TE he estimates of MPCEs are at current local prices. 2. Urban Sector

(i) The average MPCE in urban Uttarakhand was Rs 2403.53 in 2012/13. The price-adjusted district wise average MPCE ranged from the minimum of Rs 1951.26 (Champawat) to Rs 2791.77 (Nainital Hills) (Table 4.2b).

(ii) The marginal distribution of rural mean MPCE across districts is negatively skewed (Figure 1); thus, the urban distributional profile is the reverse of the one observed for the rural sector across districts.

(iii) Champawat, Udham Singh Nagar, Dehradun Hills, Nainital and Pauri Garhwalbelong to the poorest quartile group; Chamoli, Pithoragarh, and Uttarkashi form the lower middle quartile group; Rudraprayag, Dehradun, Bageshwar, and Almora belong to the upper middle quartile group; Tehri Garhwal, Haridwar, and Nainital Hills form the richest quartile group in the urban sector (Table 4.7)

77 (iv) The poorest of the district-wise poorest sample observation across districts is located in Nainital Hills (Rs 489.39) while the richest among the district-wise poorest is found in Tehri Garhwal (Rs 1183.971). Conversely, the poorest of among the district-wise richest is located in Rudraprayag (Rs 5327.95) while the richest among the rich is found in Haridwar (Rs 20563.76) (Table 4.2a)

(v) MPCE (at current local prices) distribution varied across districts with respect to its different dimensions. While the range between the richest and the poorest was the minimum in Rudraprayag (Rs4709.97), inter-quartile range was the minimum in Udham Singh Nagar (Rs 803.07) and standard deviation in Rudraprayag (Rs 934.02). The range between the poorest and the richest was the maximum in Haridwar (Rs19886.30), inter-quartile range was the maximum in Nainital Hills (Rs 1884.98) and standard deviation in Haridwar (Rs 2386.51) (Table 4.2a).

78 Table 4.2a: Summary Profiles of District wise Consumer Expenditure Distribution: Urban Uttarakhand 2011/12 (At current local prices)

Udham Singh Nainital Dehradun Percentiles Uttarkashi Chamoli Rudraprayag Tehri Garhwal Dehradun Pauri Garhwal Pithoragarh Bageshwar Almora Champawat Nainital Nagar Haridwar Hills Hills State

1 897.43 753.41 617.98 1460.79 876.32 706.68 689.13 865.59 898.9 635.33 558.34 700.83 901.14 817.64 859.73 700.83

5 1149.49 946.34 936.68 1533.37 1019.56 766.93 788.33 938.53 1001.79 645.36 848.38 835.26 1027.26 948.17 918.87 942.94

10 1397.63 1210.01 1086.65 1617.16 1165.21 942.94 914.89 1161.25 1134.39 645.36 1072.08 1028.63 1191.53 1213.21 1091.95 1063.83

25 1760.87 1496.02 1941.67 1788.44 1367.19 1330.62 1396.33 1544.37 1434.6 765.61 1258.52 1141.46 1452.79 1488.02 1437.61 1286.47

50 2104.89 1977.17 2407.24 2163.41 1888.95 1885.85 2138.51 1973.13 2383.02 1128.6 1714.93 1437.14 2017.5 2452.72 1782.9 1800.36

75 2875.13 3034.5 3023.51 3423.86 3033.34 2622.73 2768.3 3070.37 2829.53 2601.4 2863.38 1944.53 3249.19 3373 2319.52 2813.36

90 3406.86 4486.22 3458.38 4518.53 4784.54 3426.74 4194.45 4111.64 3744.84 4956.75 3139.11 2858.79 5744.27 6228.15 2929.79 4105.4

95 4496.38 4784.09 4003.65 5396.36 6210.64 4370.16 5295.67 5874.13 4803.21 6955.9 4029.51 4049.1 7483.3 7687.34 3160.64 5855.14

99 7077.06 6370.11 5327.95 6137.6 12778 7826.27 7228.65 7282.03 10773.79 9368.43 7307.04 16339.63 11404.82 9322.93 7250.12 11774.45

Smallest 507.22 753.41 617.98 1183.97 695.68 535.34 650.65 724.89 687.04 608.51 512.87 519.92 677.46 489.39 553.23 489.39

Largest 11473.04 7293.52 5327.95 8106.3 13730.12 8970.35 7228.65 7286.14 10773.79 9763.92 9215.23 19318.37 20563.76 13263.66 9666.03 20563.76

Range 10965.82 6540.11 4709.97 6922.33 13034.44 8435.01 6578.00 6561.25 10086.75 9155.41 8702.36 18798.45 19886.30 12774.27 9112.80 20074.37

IQR 1114.26 1538.48 1081.84 1635.42 1666.15 1292.11 1371.97 1526.00 1394.93 1835.79 1604.86 803.07 1796.40 1884.98 881.91 1526.89

Mean 2420.49 2440.32 2431.74 2699.01 2591.22 2144.58 2328.19 2490.56 2422.42 2037.36 2124.77 1970.87 2869.94 2953.91 1987.12 2403.53 Std. Deviation 1104.34 1317.31 934.02 1248.92 1982.96 1244.41 1417.07 1357.98 1313.73 1944.98 1197.09 2158.10 2386.51 2041.22 954.37 2002.77 Skewness 3.05 1.26 0.33 1.42 2.90 1.95 1.52 1.39 2.88 2.24 2.05 4.83 3.11 1.85 2.77 3.58 Kurtosis 19.82 4.12 3.40 4.58 13.68 8.78 5.44 4.73 17.93 7.91 9.45 28.70 17.23 6.77 17.30 20.81 Source: Same as in Table 4.1

79 Table 4.2b: Summary Profiles of District wise Consumer Expenditure Distribution: Urban Uttarakhand 2011/12 (At current average state level urban prices)

Udham Nainital Dehradun Percentiles Uttarkashi Chamoli Rudraprayag Tehri Garhwal Dehradun Pauri Garhwal Pithoragarh Bageshwar Almora Champawat Nainital Singh Nagar Haridwar Hills Hills State 1 888.38 733.03 620.63 1472.50 830.92 707.03 704.40 877.37 938.36 608.48 549.17 710.89 863.92 772.76 892.89 700.83 5 1137.90 920.74 940.70 1545.67 966.74 767.31 805.80 951.30 1045.76 618.09 834.44 847.25 984.83 896.12 954.31 942.94 10 1383.53 1177.27 1091.31 1630.13 1104.84 943.40 935.16 1177.06 1184.18 618.09 1054.46 1043.40 1142.32 1146.62 1134.07 1063.83 25 1743.11 1455.54 1950.00 1802.78 1296.36 1331.27 1427.27 1565.39 1497.57 733.25 1237.84 1157.85 1392.78 1406.34 1493.06 1286.47 50 2083.66 1923.68 2417.57 2180.76 1791.09 1886.77 2185.90 1999.99 2487.62 1080.90 1686.75 1457.77 1934.17 2318.09 1851.67 1800.36 75 2846.13 2952.40 3036.48 3451.32 2876.19 2624.01 2829.64 3112.16 2953.73 2491.46 2816.33 1972.44 3114.99 3187.85 2408.99 2813.36 90 3372.50 4364.84 3473.22 4554.77 4536.66 3428.42 4287.39 4167.60 3909.22 4747.27 3087.53 2899.83 5507.01 5886.28 3042.80 4105.4 95 4451.03 4654.65 4020.83 5439.64 5888.88 4372.30 5413.02 5954.08 5014.05 6661.93 3963.30 4107.22 7174.21 7265.37 3282.55 5855.14 99 7005.67 6197.76 5350.81 6186.82 12116.00 7830.10 7388.83 7381.14 11246.70 8972.50 7186.98 16574.18 10933.75 8811.18 7529.77 11774.45 Mean 2396.08 2374.30 2442.17 2720.65 2456.98 2145.62 2379.78 2524.46 2528.75 1951.26 2089.85 1999.16 2751.40 2791.77 2063.77 2403.53 Source: Same as in Table 4.1

80 III. RELATIVE INEQUALITY: DISTRICT-WISE NOMINAL CONSUMPTION DISTRIBUTION

The district-wise estimates of the extent of inequality as measured by different estimators by rural and urban sectors are presented in Tables 4.3 (Fig. 4.2).

Rural Sector

There is no consistent relation between levels of mean MPCE and extent of inequality in the rural sector. The pairwise correlation between estimates of Lorenz ration and rural MPCE is statistically insignificant (0.32). For instance, the extent of inequality in consumption distribution is the highest in Haridwar even though it is the third poorest district in terms of mean MPCE, belying the Kuznets inverted-U hypothesis (Table 4.6). The distribution of estimates of Lorenz ratios across districts is negatively skewed (Fig. 4.2); the upper middle quartile groups of districts (in terms of Lorenz ratios) constitute a dense group in a narrow interval. In other words, the extent of inequality in nominal consumption distribution is quite high in the top half of the districts.

Urban Sector

Estimates of average MPCE and Lorenz ratio do not show any pair wise association. The pairwise correlation is statistically insignificant (-0.17). Though Champawat is the poorest district in terms of average MPCE, the extent of relative inequality is the highest in this district.

81 82 Table 4.3a: Extent of Inequality in MPCE Distribution: Districts-wise - Rural Uttarakhand (2011/12) (At current local prices)

Udham Tehri Cham Singh Nainital Dehradun Inequality Measures Uttarkashi Chamoli Rudraprayag Garhwal Dehradun Pauri Garhwal Pithoragarh Bageshwar Almora pawat Nainital Nagar Haridwar Hills Hills STATE

Relative mean deviation 0.209 0.161 0.156 0.140 0.202 0.203 0.159 0.195 0.192 0.205 0.201 0.173 0.214 0.148 0.133 0.191

Coefficient of variation 0.816 0.469 0.435 0.446 0.592 0.554 0.468 0.570 0.535 0.771 0.554 0.527 0.695 0.410 0.567 0.598

Standard deviation of logs 0.499 0.381 0.393 0.338 0.474 0.474 0.409 0.468 0.449 0.476 0.486 0.417 0.499 0.359 0.341 0.460

Gini coefficient 0.297 0.226 0.222 0.198 0.273 0.275 0.225 0.272 0.264 0.293 0.276 0.245 0.299 0.207 0.198 0.270

Mehran measure 0.392 0.301 0.307 0.261 0.366 0.370 0.306 0.365 0.352 0.372 0.374 0.326 0.389 0.286 0.262 0.359

Piesch measure 0.250 0.189 0.179 0.166 0.227 0.228 0.184 0.225 0.220 0.253 0.226 0.204 0.254 0.167 0.166 0.226

Kakwani measure 0.084 0.048 0.046 0.039 0.068 0.068 0.049 0.068 0.063 0.084 0.069 0.057 0.084 0.040 0.044 0.068

Theil index (GE(a), a = 1) 0.189 0.090 0.083 0.077 0.131 0.128 0.091 0.129 0.119 0.184 0.128 0.109 0.172 0.073 0.098 0.133 Mean Log Deviation (GE(a), a = 0) 0.150 0.081 0.080 0.066 0.121 0.120 0.087 0.119 0.110 0.145 0.123 0.097 0.147 0.068 0.075 0.118 Entropy index (GE(a), a = - 1) 0.150 0.079 0.084 0.062 0.127 0.126 0.093 0.123 0.112 0.135 0.133 0.096 0.146 0.069 0.066 0.120 Half (Coeff.Var. squared) (GE(a), a = 2) 0.332 0.110 0.094 0.099 0.175 0.153 0.109 0.162 0.143 0.296 0.153 0.139 0.242 0.084 0.160 0.179 Source: Same as in Table 4.1

83 Table 4.3b: Extent of Inequality in MPCE Distribution: District-wise - Urban Uttarakhand (2011/12) (At current local prices) Udham Rudra Tehri Pauri Cham- Singh Nainital Dehradun Inequality Measures Uttarkashi Chamoli prayag Garhwal Dehradun Garhwal Pithoragarh Bageshwar Almora pawat Nainital Nagar Haridwar Hills Hills STATE Relative mean deviation 0.150 0.213 0.151 0.183 0.254 0.208 0.222 0.211 0.174 0.328 0.209 0.262 0.272 0.242 0.165 0.257 Coefficient of variation 0.456 0.540 0.384 0.463 0.765 0.580 0.609 0.545 0.542 0.955 0.563 1.095 0.832 0.691 0.480 0.833 Standard deviation of logs 0.389 0.496 0.449 0.402 0.559 0.526 0.565 0.499 0.470 0.735 0.501 0.542 0.609 0.605 0.413 0.576 Gini coefficient 0.213 0.283 0.213 0.238 0.340 0.293 0.314 0.284 0.258 0.436 0.281 0.354 0.369 0.341 0.232 0.351 Mehran measure 0.293 0.383 0.317 0.316 0.436 0.402 0.428 0.385 0.358 0.553 0.384 0.426 0.472 0.453 0.321 0.448 Piesch measure 0.173 0.233 0.161 0.199 0.292 0.239 0.257 0.234 0.207 0.377 0.230 0.318 0.317 0.284 0.188 0.303 Kakwani measure 0.045 0.072 0.045 0.052 0.104 0.077 0.088 0.072 0.063 0.166 0.072 0.124 0.120 0.103 0.051 0.111 Theil index (GE(a), a = 1) 0.084 0.130 0.076 0.094 0.211 0.143 0.161 0.131 0.119 0.335 0.134 0.308 0.245 0.196 0.095 0.233 Mean Log Deviation (GE(a), a = 0) 0.079 0.127 0.087 0.088 0.183 0.141 0.161 0.128 0.113 0.309 0.129 0.218 0.216 0.191 0.089 0.198 Entropy index (GE(a), a = -1) 0.083 0.137 0.112 0.087 0.186 0.158 0.184 0.139 0.124 0.349 0.142 0.194 0.226 0.219 0.094 0.202 Half (Coeff.Var. squared) (GE(a), a = 2) 0.104 0.145 0.073 0.107 0.292 0.168 0.184 0.148 0.146 0.454 0.158 0.599 0.345 0.238 0.115 0.347 Source: Same as in Table 4.1

84 Fig. 4.2: Extent of Inequality across Districts: Uttarakhand (2011/12)

Lorenz ratio across Districts: Uttarakhand Rural and Urban Profiles . 4 5 . 4 . 3 5 . 3 L o r e n z

r . a 2 t 5 i o . 2

Rural Urban

IV. DISTRICT-WISE ESTIMATES OF POVERTY The district-wise estimates of poverty correspondto the average state level poverty line of Rs. 880 per capita per month for the rural sector and Rs. 1082 for the urban sector (vide methodology recommended by the Tendulkar Committee (GoI, 2014)) (Table 4.4). The salient findings are as follows:

Less-than one-fifth (17.52 per cent) of the rural population in Uttarakhand lives in sub- subsistence. This incidence is the minimum in the district of Udham Singh Nagar (9.40 per cent) and maximum in Pauri Garhwal (29.89 per cent). As regards urban deprivation, the state level average incidence is 11.51 per cent. It ranged from the minimum of nil in Tehri Garhwal to the maximum of nearly half of the urban population (48.70 per cent) in Champawat. The average incidence of poverty for the state as a whole (rural and urban combined) is 16 per cent. It ranged from 9.22 per cent in Dehradun to 28.50 per cent in Pauri Garhwal.

85 Table 4.4: District-wise Estimates of Poverty based on uniform state-level poverty lines: Uttarakhand (2011/12) (%)

NSS Code District Rural Urban Combined 1 Uttarkashi 19.97 2.02 18.98 2 Chamoli 13.09 8.15 12.47 3 Rudraprayag 19.26 7.06 18.75 4 Tehri Garhwal 10.85 0.00 10.15 5 Dehradun 11.87 7.05 9.42 15 Dehradun Hills 6.73 9.45 6.77 Dehradun Combined 11.16 7.06 9.22 6 Pauri Garhwal 29.89 20.66 28.50 7 Pithoragarh 16.74 15.97 16.64 8 Bageshwar 28.04 6.99 27.37 9 Almora 21.89 6.35 20.73 10 Champawat 18.31 48.70 23.03 12 Udham Singh Nagar 9.40 18.93 13.13 13 Haridwar 23.50 5.89 19.49 11 Nainital 10.03 10.04 10.03 14 Nainital Hills 13.75 6.19 12.57 Nainital Combined 11.53 9.42 1086 Uttarakhand 17.52 11.51 16.03 Note: The districtwise estimates of poverty are based on uniform application of state level poverty line Rs 880 for the rural sector and Rs 1082 for the urban sector (vide Tendulkar methodology (GoI 2014))

These estimates do not account for inter-district variations in prices and hence, cost of living. In order to obtain a realistic profile of district-wise poverty, there is a need to adjust state- level poverty lines for rural and urban sectors for district-wise price variation. We have made a limited attempt to address this need by estimating spatial cost of living indices based on household budget data at the district level and corresponding adjustments in poverty lines across districts (Tables (iii) and (iv) in the Annexure). The distribution of spatial cost living indices across districts is negatively skewed with respect to both the lowest and lower middle quartile groups in the rural sector. A regards the urban sector, the distribution is positively skewed for the middle half of the quartile groups (Fig. 4.3).The district-wise poverty lines corresponding to that at the state level are presented in Table 4.5 and the corresponding poverty estimates in Table 4.6. Summary profiles of deprivation across districts are presented in Table 4.7

86 Fig. 4.3: Spatial Cost of Living Indices (Fisher Index) across Districts: Uttarakhand (2011/12)

Spatial Cost of Living Indices across Districts: Uttarakhand Rural and Urban Profiles 1 . 1 1 . 0 5 1 C o . 9 s 5 t

o f

L i v i n . g 9

I n d

e Rural Urban x

Table 4.5: District wise Estimates of Price-adjusted Poverty Lines: Uttarakhand 2011/12 (Rs.) NSS Code District Rural Urban 1 Uttarkashi 903.58 1093.03 2 Chamoli 937.23 1112.09 3 Rudraprayag 918.70 1077.38 4 Tehri Garhwal 881.75 1073.39 5 Dehradun 958.30 1141.12 6 Pauri Garhwal 919.71 1081.47 7 Pithoragarh 867.91 1058.54 8 Bageshwar 853.74 1067.47 9 Almora 803.11 1036.50 10 Champawat 916.03 1129.75 11 Nainital 869.71 1100.08 12 Udham Singh Nagar 865.72 1066.69 13 Haridwar 913.83 1128.62 14 Nainital Hills 899.68 1144.84 15 Dehradun Hills 942.58 1041.82 State 880.00 1082.00 Note: The district specific poverty lines are obtained with price adjustments for the state-level poverty lines recommended by the Tendulkar Committee (GoI 2014). Price adjustments are made using Fisher spatial cost of living indices for the food basket across districts.

87 Table 4.6: District-wise Estimates of Poverty: Uttarakhand (2011/12) (%)

NSS Code District Rural Urban Combined 1 Uttarkashi 21.50 2.30 20.44 2 Chamoli 22.10 8.60 20.37 3 Rudraprayag 21.30 7.10 20.71 4 Tehri Garhwal 10.80 0.00 10.15 5 Dehradun 13.24 7.05 10.09 15 Dehradun Hills 17.41 7.81 17.26 Dehradun Combined 13.81 7.06 10.62 6 Pauri Garhwal 30.90 20.7 29.36 7 Pithoragarh 15.80 16.0 15.85 8 Bageshwar 24.60 7.0 24.01 9 Almora 14.30 5.2 13.62 10 Champawat 22.10 50.60 26.55 12 Udham Singh Nagar 8.90 18.40 12.60 13 Haridwar 27.60 5.90 22.63 11 Nainital 7.91 10.04 8.75 14 Nainital Hills 18.18 7.28 16.48 Nainital Combined 12.05 9.60 11.27 Uttarakhand 17.5 11.5 16.88 Note: The estimates of poverty correspond to the district-specific poverty lines in Table 4.5.

Deprivation: Salient Features

The salient features of the deprivation profiles presented in Table 4.6 and Figures 1 to 4 are as follows:

Rural Sector:

(i) Incidence of rural poverty is generally the lowest in the richest quartile group of districts. Other indicators of deprivation like food share in household budget and cost of living also report a favourable profile of these districts. In sum, the best-off threedistricts, namely Dehradun, Udham Singh Nagar and Nainital seem to be doing reasonably well in terms of all the indicators under review.

(ii) The marginal distribution of incidence of rural poverty across districts is nearly symmetric while those pertaining to extent of inequality and cost of living are highly negatively skewed ones. This would mean that at least half of the districts are densely located with respect to high extent of relative inequality and cost of living.

88 Urban Sector:

1. In general, there is an inverse association between district-wise mean MPCE and incidence of poverty.

2. Unlike the rural profiles, the marginal distributions the incidence of poverty, extent of inequality and cost of living are positively skewed ones. This would mean that half of the districts are densely located in a narrow range at the lower end of the distributions of incidence of poverty, extent of relative inequality and cost of living.

Figure 4.4: Incidence of Poverty across Districts: Uttarakhand (2011/12)

Incidence of Poverty across Districts: Uttarakhand Rural and Urban Profiles

Champawat 5 0 4 0 3 0 2 0 H e a 1 d 0 c o u n t

0 r a t i o

( % Rural Urban )

89 90 Table 4.7: Poverty Profiles across Districts: Rural and Urban Uttarakhand (2011/12)

Rural Uttarakhand Urban Uttarakhand Quartile Rural Lorenz Incidence of Spatial Food Quartile Urban Lorenz Incidence of Spatial CLI Food Group District MPCE ratio poverty CLI share Group District MPCE ratio poverty Urban share Pithoragarh 1292.03 0.22 15.83 0.99 54.02 Champawat 1951.26 0.44 50.64 1.04 41.85 Udham Singh Pauri Garhwal 1294.87 0.28 30.90 1.05 49.06 Nagar 1999.16 0.35 18.36 0.99 50.20 Dehradun Haridwar 1296.45 0.30 27.57 1.04 49.17 Hills 2063.77 0.23 7.81 0.96 43.38 Dehradun Poorest Hills 1314.99 0.20 17.41 1.07 49.74 Poorest Nainital 2089.85 0.28 10.04 1.02 46.27 Rudraprayag 1324.14 0.22 21.31 1.04 49.95 Pauri Garhwal 2145.62 0.29 20.66 1.00 39.77 Chamoli 1339.43 0.23 22.06 1.07 50.29 Chamoli 2374.30 0.28 8.59 1.03 42.91 Lower Lower middle Nainital Hills 1345.21 0.21 18.18 1.02 51.39 middle Pithoragarh 2379.78 0.31 15.97 0.98 41.44 Tehri Garhwal 1352.02 0.20 10.85 1.00 52.15 Uttarkashi 2396.08 0.21 2.30 1.01 39.80 Bageshwar 1372.30 0.27 24.56 0.97 55.62 Rudraprayag 2442.17 0.21 7.06 1.00 45.34 Uttarkashi 1392.23 0.30 21.50 1.03 48.52 Dehradun 2456.98 0.34 7.05 1.05 37.56 Upper Upper middle Almora 1509.75 0.26 14.30 0.91 49.82 middle Bageshwar 2524.46 0.28 6.99 0.99 45.92 Champawat 1519.73 0.29 22.12 1.04 48.26 Almora 2528.75 0.26 5.18 0.96 45.92 Dehradun 1560.13 0.27 13.24 1.09 43.06 Tehri Garhwal 2720.65 0.24 0.00 0.99 40.53 Udham Singh Nagar 1665.15 0.24 8.89 0.98 49.74 Haridwar 2751.40 0.37 5.89 1.04 36.04 Richest Nainital 1927.07 0.28 7.91 0.99 40.33 Richest Nainital Hills 2791.77 0.34 7.28 1.06 35.29 State 1460.10 0.270 17.50 1.00 48.85 State 2403.53 0.351 11.50 1.00 41.21 Notes: Lowest welfare quartile group:

Lower middle welfare quartile group:

Upper middle welfare quartile group:

Top welfare quartile group: Note: 1. Estimates based on pooled central and state samples 2. Districts arranged in ascending order of mean MPCE by sector.

91 V. RURAL-URBAN PROFILE 1. Urban mean MPCE exceeds that of rural in all the districts. Rural-urban disparity in mean MPCE is the lowest in Nainital (108.45), which is the richest in terms of rural mean MPCE but poorest fourth in terms urban mean MPCE. MPCE disparity is the highest is Haridwar (212.13), which is the third poorest rural district but second richest district urban one. Finally, the median disparity in Uttarakashi (172.10) falls in the upper middle quartile group in both rural and urban sectors (Table 4.8). In other words, failure of urban development to catch up with the rural prosperity seems to have led to a development process far removed from theKuzents’ inverted-U postulate. 2. Extent of income/consumption inequality is generally higher in the urban than in the rural sector. However, the profile is the reverse in the districts of Uttarakashi, Rudraprayag and Almora. Among these three, Almora is the only district which falls in the same upper middle quartile group in both the rural and urban sectors. Uttarakashi falls in the rural lowest middle quartile group but urban topmost quartile group while Rudraprayag falls in the rural lower middle quartile group but urban upper middle quartile group. In other words, it appears that factors other than level income/consumption could be influencing the relative inequality profiles in the rural and urban districts of Uttarakhand. Rural-urban disparity is the maximum in Nainital Hills and is one of the highest even the district of Pithoragarh with the poorest rural district. 3. Incidence of urban poverty is generally less than that of rural one. However, the profile is the reverse one in the majority of the districts, viz., Dehradun, Dehradun Hills, Pauri Garhwal, Almora, Uttarkashi, Chamoli, Bageshwar, Rudraprayag, Nainital Hills and Haridwar. As a result, we find rural poverty to be less than urban one in the state as a whole. 4. Relative rural-urban spatial cost of living too throws up a picture different from the conventional perception. In a majority of the districts, the rural spatial cost of living exceeds the urban one. 5. Nainital is the only district where the household budget share of food exceeds the corresponding parameter for the rural one.

92 Table 4.8: Rural-Urban Disparities in Economic Profiles

Rural sector Urban sector Rural-urban disparity Mean Lorenz Incidence of Spatial Food Mean Lorenz Incidence of Spatial CLI Food Mean Lorenz Incidence of Spatial CLI Food District MPCE ratio poverty CLI share MPCE ratio poverty Urban share MPCE ratio poverty Urban share

Almora 1509.75 0.26 14.30 0.91 49.82 2528.75 0.26 5.18 0.96 45.92 167.49 97.74 36.23 104.97 92.16

Bageshwar 1372.30 0.27 24.56 0.97 55.62 2524.46 0.28 6.99 0.99 45.92 183.96 104.53 28.46 101.69 82.55

Chamoli 1339.43 0.23 22.06 1.07 50.29 2374.30 0.28 8.59 1.03 42.91 177.26 125.18 38.94 96.51 85.33

Champawat 1519.73 0.29 22.12 1.04 48.26 1951.26 0.44 50.64 1.04 41.85 128.39 148.90 228.92 100.31 86.70

Dehradun 1560.13 0.27 13.24 1.09 43.06 2456.98 0.34 7.05 1.05 37.56 157.49 124.49 53.29 96.85 87.23 Dehradun Hills 1314.99 0.20 17.41 1.07 49.74 2063.77 0.23 7.81 0.96 43.38 156.94 117.12 44.84 89.89 87.21

Haridwar 1296.45 0.30 27.57 1.04 49.17 2751.40 0.37 5.89 1.04 36.04 212.23 123.21 21.37 100.45 73.29

Nainital 1927.07 0.28 7.91 0.99 40.33 2089.85 0.28 10.04 1.02 46.27 108.45 102.00 126.92 102.87 114.72

Nainital Hills 1345.21 0.21 18.18 1.02 51.39 2791.77 0.34 7.28 1.06 35.29 207.53 164.84 40.02 103.49 68.66 Pauri Garhwal 1294.87 0.28 30.90 1.05 49.06 2145.62 0.29 20.66 1.00 39.77 165.70 106.53 66.86 95.64 81.08

Pithoragarh 1292.03 0.22 15.83 0.99 54.02 2379.78 0.31 15.97 0.98 41.44 184.19 139.67 100.91 99.19 76.72

Rudraprayag 1324.14 0.22 21.31 1.04 49.95 2442.17 0.21 7.06 1.00 45.34 184.43 95.99 33.11 95.38 90.78 Tehri Garhwal 1352.02 0.20 10.85 1.00 52.15 2720.65 0.24 0.00 0.99 40.53 201.23 120.26 0.00 99.01 77.72 Udham Singh Nagar 1665.15 0.24 8.89 0.98 49.74 1999.16 0.35 18.36 0.99 50.20 120.06 144.64 206.52 100.21 100.92

Uttarkashi 1392.23 0.30 21.50 1.03 48.52 2396.08 0.21 2.30 1.01 39.80 172.10 71.60 10.68 98.38 82.02

State 1460.10 0.270 17.50 1.00 48.85 2403.53 0.351 11.50 1.00 41.21 164.61 130.00 65.71 100.00 84.36

Minimum 1292.03 0.198 7.91 0.91 40.33 1951.26 0.213 0.00 0.96 35.29 108.45 71.60 0.00 89.89 68.66

Quarile1 1319.57 0.223 13.77 0.99 48.79 2117.74 0.248 6.44 0.99 39.79 157.21 103.27 30.78 96.68 79.40

Quartile 2 1352.02 0.264 18.18 1.03 49.74 2396.08 0.284 7.28 1.00 41.85 172.10 120.26 40.02 99.19 85.33

Quartile3 1514.74 0.275 22.09 1.04 50.84 2526.60 0.340 13.01 1.04 45.63 184.31 132.42 83.89 101.07 89.00

Maximum 1927.07 0.299 30.90 1.09 55.62 2791.77 0.436 50.64 1.06 50.20 212.23 164.84 228.92 104.97 114.72 Note:1.Districts arranged in alphabetical order.2. Rural-urban disparity is measured as the ratio urban to rural parameter/variable values Key:Lowest welfare quartile group: Lower middle welfare quartile group: Upper middle welfare quartile group: Top welfare quartile group:

93 VI. INCIDENCE OF POVERTY ACROSS HILLS AND PLAINS

There is a general perception that the hilly regions of Uttarakhand are economically backward and poor. This is one reason which has motivated migration, both intra- and inter- state migration, from these regions. The price-adjusted district-wise estimates of poverty by this hill/plain classification corroborate this perception (Table 4.9).However, the differences appear marginal; this could be because of inward remittances, which could have insulated the poor against the burden of deprivation to some extent (Mamgain and Reddy, 2016).

Table 4.9: Estimates of Poverty by Hills and Plains: Uttarakhand: 2011/12 Region Rural Urban Combined Hills Total 19.59 14.91 19.12 Plain total 17.70 10.67 15.15 State Total 18.68 11.41 16.88

Note: These estimate are based on district-wise price-adjusted poverty lines. Hence the rural and urban estimates would not tally with those in Table 4.10 which are based on uniform application of state level poverty line across districts in rural and urban sectors. The social group profile of deprivation across hills and plains in rural and urban Uttarakhand reveal the following features (Table 4.10). For reasons like statistical robustness, we avoid discussing the findings for the STs. As regards the remaining three social groups, the salient findings are as follows: (i) Headcount ratio estimates: The SCs are the most deprived across both the hills and the plains in the rural sector; the SCs are followed by the OBCs and the other social groups. As regards the urban profile, the OBCs are the most deprived followed by the SCs and the ‘Others’ across hills and plains. (ii) Poverty gap estimates: The profile remains broadly the same as that revealed by headcount ratio estimates for both the hills and the plains in both rural and urban Uttarakhand. (iii) Severity of poverty: Severity is the highest among the SCs followed by other and the OBCS in the hills and the highest among the OBCs followed by the SCs and the other in the plains in rural Uttarakhand. As regards the urban sector, severity is the highest among the OBCs, followed by the SCs and the ‘Others’ in the hills and the highest among the OBCS, followed by the ‘Others’ and the SCs in the plains.

94 Table 4.10: Estimates of Poverty (Incidence, depth and severity) across social groups by Hills and Plains: Uttarakhand: 2011/12

Rural Urban Region STs SCs OBCs Others Total ST SC OBC Others Total

Hills Total Head-count ratio (%) 15.32 27.85 16.52 15.49 18.9 38.1 17.6 27.36 10.22 14.67 Poverty gap index (%) 0.98 6.07 2.48 2.16 3.18 11.5 2.86 4.31 2.1 2.93 Squared poverty gap index (%) 0.14 1.96 0.49 0.52 0.89 4.16 0.71 0.97 0.57 0.81 Plains Total Head-count ratio (%) 18.58 25.5 21.52 3.74 16.03 1.08 7.44 21.09 6.95 10.85 Poverty gap index (%) 4.38 5.18 5.21 0.50 3.48 0 0.98 2.69 0.88 1.38 Squared poverty gap index (%) 1.91 1.22 1.54 0.10 1.00 0 0.16 0.72 0.21 0.34 Note: These estimates correspond to price unadjusted state level poverty lines for rural and urban Uttarakhand (Rs 880 and Rs 1082 respectively). VII. DEPRIVATION AND ITS DETERMINANTS

This section seeks to explain the district wise estimates of poverty in rural and urban Uttarakhand in terms of conventional explanatory variables like mean MPCE, extent of inequality, and cost of living. However, only mean MPCE and extent of inequality turn out to be statistically significant explanatory variables (Table 4.11).

95 Table 4.11:Poverty and its Determinants

. regress incidenceofpoverty mpceatstatelevelprices lorenzratio rcli

Source SS df MS Number of obs = 15 F( 3, 11) = 15.06 Model 508.369513 3 169.456504 Prob > F = 0.0003 Residual 123.752296 11 11.2502088 R-squared = 0.8042 Adj R-squared = 0.7508 Total 632.12181 14 45.1515578 Root MSE = 3.3541

incidenceofpoverty Coef. Std. Err. t P>|t| [95% Conf. Interval] mpceatstatelevelprices -.0310628 .0055818 -5.57 0.000 -.0433482 -.0187774 lorenzratio 113.8089 26.30278 4.33 0.001 55.91687 171.7009 rcli 21.63677 20.06838 1.08 0.304 -22.53343 65.80697 _cons 12.31766 23.93328 0.51 0.617 -40.35913 64.99444

. *(4 variables, 15 observations pasted into data editor)

. regress povertyurban mpceurban lrurban cli

Source SS df MS Number of obs = 15 F( 3, 11) = 12.64 Model 1606.87437 3 535.624791 Prob > F = 0.0007 Residual 466.08003 11 42.3709118 R-squared = 0.7752 Adj R-squared = 0.7138 Total 2072.9544 14 148.068172 Root MSE = 6.5093

povertyurban Coef. Std. Err. t P>|t| [95% Conf. Interval]

mpceurban -.0234585 .0070432 -3.33 0.007 -.0389605 -.0079566 lrurban 122.4251 36.07067 3.39 0.006 43.03406 201.8161 cli -17.66612 73.76276 -0.24 0.815 -180.0169 144.6846 _cons 48.78412 63.77771 0.76 0.460 -91.58968 189.1579

. VIII. FINDINGS AND RECOMMENDATIONS

The first chapter on an overview of the is unambiguous in its presentation of its macroeconomic transition from a slow growth economy into a high-growth one, cross-sectional profile of disparities in resource endowments, economic opportunities and hence, economic welfare levels like per capita consumer expenditure and incidence of poverty. Empirical evidence on levels of living and deprivation provide enough evidence of the State’s achievements in this respect. Growth in real consumption (price adjusted average per capita MPCE of 58%) in both the rural and urban sectors is higher than those in the states of Himachal Pradesh and Uttar Pradesh and in the nation as a whole (Table 3.4). Percentage reduction in rural poverty is also the highest while the urban one has almost reached the

96 single-digit level. How far these changes are reflected in real outcome indicators like measures of health status, say, of children? Available estimates for 2005/06 (Table 4.9) show that Uttarakhand was doing much better than the nation as a whole on these indicators. As regards wasting and under-weight its performance in 2005/06 was comparable to that of Himachal Pradesh. Recent evidence for the year 2015/16 speaks of a sustained improvement in health indicators.9 Stunting declined from 44.4 per cent in 2005/06 to 33.5 per cent in 2015/16 while the decline at the national level was from 48 per cent to 38.4 per cent between the same two points of time. Wasting increased in both Uttarakhand and India as a whole: it increased from 18.8 per cent to 19.5 per cent in Uttarakhand and from 19.8 per cent to 21.0 per cent in India as a whole. However, there was good improvement in terms of proportion children underweight. It declined from 38 per cent to 26.6 per cent in Uttarakhand as against from 42.5 per cent to 35.7 per cent in the nation as a whole.

However, the cross sectional results across districts presented in this chapter do not really tally with the descriptions provided in the overview profile. For instance, Haridwar falls in the poorest quartile group in terms of rural MPCE, extent of inequality in consumer expenditure distribution and incidence of poverty even though one would expect it in the richest quartile group because of its rich resource endowments and opportunities as a district in the plains. Similarly, Almora falls in the upper middle quartile group in terms of MPCE, extent of inequality, incidence of poverty, food share in total consumer expenditure andlowest quartile group in terms of cost of living. The urban profile too corroborates this kind of mismatch. How do we explain this mismatch? One critical explanation could be in terms of migration between the hilly districts and the plain ones, state intervention in stabilizing prices through the public distribution system, state role in assured employment (about 25 per cent of the employment is regular and government oriented ones). In other words, the evaluation of the land and labour markets coupled with state intervention in providing assured income seems to have played a critical role in pursuit of inclusive growth of Uttarakhand.

9Source: Summary reports available at http://rchiips.org/nfhs/pdf/NFHS4/UT_FactSheet.pdf

97 Annexure I Table (i): District-wise Sample Household Size Cod Rural Urban All District e Stat Centra Poole Stat Centra Poole Stat Centra Poole e l d e l d e l d 1 Uttarkashi 64 64 128 32 32 64 96 96 192 2 Chamoli 57 64 121 32 32 64 89 96 185 3 Rudraprayag 56 64 120 32 32 64 88 96 184 4 Tehri Garhwal 96 96 192 32 32 64 128 128 256 5 Dehradun 88 88 176 96 95 191 184 183 367 6 Pauri Garhwal 96 96 192 64 64 128 160 160 320 7 Pithoragarh 64 64 128 32 32 64 96 96 192 8 Bageshwar 64 64 128 32 32 64 96 96 192 9 Almora 96 96 192 32 32 64 128 128 256 10 Champawat 32 32 64 32 32 64 64 64 128 11 Nainital 64 64 128 64 64 128 128 128 256 Udham Singh 12 Nagar 96 96 192 96 96 192 192 192 384 13 Haridwar 96 96 192 96 96 192 192 192 384 14 Nainital Hills 32 32 64 32 32 64 64 64 128 15 Dehradun Hills 32 32 64 32 32 64 64 64 128 103 176 Uttarakhand 3 1048 2081 736 735 1471 9 1783 3552

Table (ii) : District-wise Sample Person Size Rural Urban All Code District Stat Centra Poole Stat Centra Poole Stat Centra Poole e l d e l d e l d 1 Uttarkashi 282 273 555 122 114 236 404 387 791 2 Chamoli 299 283 582 128 124 252 427 407 834 3 Rudraprayag 216 267 483 113 108 221 329 375 704 4 Tehri Garhwal 402 424 826 94 120 214 496 544 1040 5 Dehradun 414 433 847 421 414 835 835 847 1682 6 Pauri Garhwal 357 416 773 290 275 565 647 691 1338 7 Pithoragarh 241 271 512 123 123 246 364 394 758 8 Bageshwar 260 277 537 133 130 263 393 407 800 9 Almora 421 427 848 114 122 236 535 549 1084 10 Champawat 168 165 333 148 122 270 316 287 603 11 Nainital 317 308 625 308 295 603 625 603 1228 Udham Singh 12 Nagar 492 469 961 445 459 904 937 928 1865 101 13 Haridwar 590 507 1097 426 411 837 6 918 1934 14 Nainital Hills 159 196 355 135 121 256 294 317 611 15 Dehradun Hills 236 172 408 145 97 242 381 269 650 485 314 799 Uttarakhand 4 4888 9742 5 3035 6180 9 7923 15922

98 Table (iii) : Spatial Cost of Living Indices, Poverty lines and Ratios across Districts : Rural Uttarakhand Paasche Fisher NSS Name of Laspeyres Poverty Index Index HCR Code District Index (L) Line (P) (F) 1 Uttarkashi 1.023 1.031 1.027 903.6 21.5 2 Chamoli 1.071 1.059 1.065 937.2 22.1 3 Rudraprayag 1.044 1.044 1.044 918.7 21.3 4 Tehri Garhwal 1.006 0.998 1.002 881.7 10.8 5 Dehradun 1.084 1.094 1.089 958.3 13.2 6 Pauri Garhwal 1.048 1.042 1.045 919.7 30.9 7 Pithoragarh 0.986 0.987 0.986 867.9 15.8 8 Bageshwar 0.963 0.978 0.970 853.7 24.6 9 Almora 0.909 0.916 0.913 803.1 14.3 10 Champawat 1.056 1.026 1.041 916.0 22.1 11 Nainital 0.987 0.990 0.988 869.7 7.9 Udham Singh 12 Nagar 0.986 0.981 0.984 865.7 8.9 13 Haridwar 1.042 1.035 1.038 913.8 27.6 14 Nainital Hills 1.022 1.023 1.022 899.7 18.2 15 Dehradun Hills 1.088 1.054 1.071 942.6 17.4

Table (iv): Spatial Cost of Living Indices, Poverty lines and Ratios across Districts : Urban Uttarakhand Paasche Laspeyres Fisher Poverty NSS Code Name of District HCR Index (P) Index (L) Index (F) Line

1 Uttarkashi 1.010 1.011 1.010 1093.0 2.3 2 Chamoli 1.026 1.029 1.028 1112.1 8.6 3 Rudraprayag 0.995 0.997 0.996 1077.4 7.1 4 Tehri Garhwal 1.002 0.982 0.992 1073.4 0.0 5 Dehradun 1.055 1.054 1.055 1141.1 7.1 6 Pauri Garhwal 1.003 0.996 1.000 1081.5 20.7 7 Pithoragarh 0.974 0.982 0.978 1058.5 16.0 8 Bageshwar 0.985 0.988 0.987 1067.5 7.0 9 Almora 0.963 0.953 0.958 1036.5 5.2 10 Champawat 1.054 1.034 1.044 1129.7 50.6 11 Nainital 1.006 1.028 1.017 1100.1 10.0 12 Udham Singh Nagar 0.997 0.975 0.986 1066.7 18.4 13 Haridwar 1.047 1.039 1.043 1128.6 5.9 14 Nainital Hills 1.060 1.056 1.058 1144.8 7.3 15 Dehradun Hills 0.966 0.96 0.963 1041.8 7.8

99 Chapter - V EXPLAINING POVERTY IN THE FRAMEWORK OF EMPLOYMENT AND ITS QUALITY

I. INTRODUCTION

One of the main reasons of poverty and inequality is the lack of gainful employment opportunities particularly in developing countries like India. In India the growth of employment over the years has been less than satisfactory, particularly after the onset of economic reforms in the early 1990s. Most of the employment opportunities are characterized with low earnings without any social security (IHD-ISLE, 2014). An overwhelming majority of workers are labouringin the informal sector at low levels of productivity, low earnings and in poor working conditions (Kannan, et al. 2017). Such a scenarioof low quality of employment could hardly induce effective demand for goods and services for the majority of population across different regions inthe country. Due to lack of employment opportunities in backward regions, employmentrelated migration of workers has accelerated over the years (GoI, 2017).Unlike developed countries, the unemployment rates in India are generally low. The major issue here, however, is underemployment and poor quality of employment, resulting in poor income levels and higher incidence of poverty (Kannan, et al. 2017; Papola, 2013). Uttarakhand is no exception to such macro features of employment growth. However, the sharp rise in regional inequalities in Uttarakhand are also evidenced in the slow growth in employment opportunities in the hill region of the state, resulting in widespread outmigration of population from this region in search of employment (Mamgain and Reddy, 2015). Such migration is largely of longer duration wherein the entire household tends to migrate out to avoid the drudgeries of life in the inhospitable mountain terrain. There is hardly any significant diversification in the structure of employment in hill areas of the state, whereas the plains areas have witnessed reasonable diversification in favour of non-farm activities.

It is against this backdropthatthischapter attempts to examine in detail the growth and structural changes in employment in Uttarakhand at a more disaggregated level in Section II. It points outthat despite a very high economic growth, the structure of employment has not changed at a desired pace, particularly in the hilly areas. Section III examines the quality of employment from the perspective of earnings and poverty reduction. It showsthat

100 overdependence of a large majority of workers on low productive agriculture, particularly in the Hill Region have created a subsistence economy with little to invest in productive activities. Section IV looks into the demand-side dynamics of employment generation. The concluding Section V finds very slow pace of structural diversification in employment particularly in hill districts as a major concern for policy intervention. Though the levels of absolute deprivation of population in the state are comparatively at a much lower side than rest of the country, it is the nature and quality of livelihoods that only support a subsistence economy but certainly not as a modern diversified economy for a large majority of population living in the state. This Section also cautions that interpretation of results of poverty and inequality emerging from the previous chapter need to be carefully interpreted from the perspective of policy interventions. More so, consumption expenditure may not be a holistic indicator of measuring deprivation of population. Thus, the study calls for measuring poverty in its multidimensional forms.

II. EMPLOYMENTIN UTTARAKHAND

In Uttarakhand, there were 3.87 million workers10 in 2011, constituting about 38 per cent of its population. The proportion of working population in the state is far less than Himachal Pradesh but nearly the same as national average (Figure 5.1). Gender-wise, nearly half of the male population wasworkingin the state. The corresponding proportion for femaleswas about 27 per cent in 2011. However, the work participation rate (WPR) among male population was lower in Uttarakhand as compared to the national average (53.3 per cent). In Himachal Pradesh, the WPR for males as well as females is very high (58.7 per cent for men and 44.8 for women). A fairly high proportion of women in Uttarakhand and other regions of the country are working as marginal workers. This shows the limited access to employment opportunities on a fairly longer duration, particularly for women in many states including Uttarakhand.

10The figure includes main as well as marginal workers. Population Census 2011 defines main workers as those working for more than 180 days in a year. Marginal workers are those working less than six months.

101 Table 5.1: Gender-wise Work Participation Rates in Uttarakhand, 2011 (in %)

Total workers (Main+Marginal) Main workers Men Women Men Women Total 49.67 26.68 40.30 16.16 Rural 49.07 32.94 37.58 19.18 Urban 50.98 11.29 46.22 8.74

Source:Primary Census Abstract, Population Census, 2011.

Source:Primary Census Abstract, Population Census, 2011.

There is wide difference in work participation rate of hill and plain regions of the state.It is 43.7 per cent for hills region and 33.5 per cent for plains region in 2011. This difference is primarily due to a very high work participation rate of women in hill region (50.8 per cent) compared to a mere 14.2 per cent in plains region of the state (Table 2.2 in chapter 2).

Such difference in work participation rate is observed even at district level disaggregation WPRs that are found to be higher among hill districts, primarily due to higher participation of women therein. The WPR tended to increase marginally (less than two percentage points) in most of the districts of the state between 2001 and 2011 except where it declined by two percentage points during the period. However,

102 itconsiderably improved in Udham Singh Nagar (4.2 percentage points), Dehradun (3.1 percentage points) and Nainital (2.8 percentages points)districts (Figure 5.2).

Source:Primary Census Abstract, Population Census, 2011.

Similar to Population Census data, NSSO data on employment and unemployment also show lower workforce participation rates (WFPRs) of population in Uttarakhand in comparison to Himachal Pradesh and national average, particularly in case of male population (Figure 5.3). This is seen both in rural and urban areas of Uttarakhand. The low WFPRs of men may be due to (i) lack of employment opportunities; (ii) higher participation in education, and (iii) higher incomes of households requiring lesser participation in work.

103 Source:NSSO, 68th Round on Employment and Unemployment, 2011-12.

The higher WPRs of women is not necessarily an indicator of economic well-being as has been observed in case of Himachal Pradesh or Uttarakhand in Figure 5.3. Rather it may be due to the nature of livelihood resources available with the households that necessitate higher participation in work coupled with social recognition of women’s work. For example, the higher participation of women in hilly districts of Uttarakhand is largely associated with the backbreaking agriculture and animal husbandry related activities that demand more of physical work compared to plain areas of the state.

Prevalence of Marginal Workers

Duration of employment along with the earnings and condition of work is one of the important aspects to understand the employment scenario. According to the estimate based on census 2011 data, one-fourth of the total workers in Uttarakhand were marginal workers, i.e. they workedin gainful economic activities for less than 180 days in a year. The proportion of marginal workers in total workers is found to be more than double among women (39.4 per cent) than men (18.9 per cent) in the state(Table 5.2). In Tehri Garhwal, Pauri Garhwal and Champawat districts more than half of women workers were working as marginal workers despite their low workforce participation rates. In fact, the pace of such marginalization of women workers in Bageshwar, Tehri Garhwal and Garhwal districts increased substantially

104 whereas it substantially declined in the three plains districts between 2001 and 2011. Across the hilly and plains districts of Uttarakhand, the ratio of marginal workers among men workforce was double in the hill districts than that in the plains districts. Simply put, the proportion of marginal workers increased mostly in the Hill Regionof the state during the period 2001-2011, indicating marked deterioration in the availability of work for a relatively longer period during a year.

Table 5.2: District-wise Percentage Share of Marginal Workers in Uttarakhand Person Male Female District 2001 2011 2001 2011 2001 2011 Almora 30.0 32.6 24.8 28.2 34.1 36.5 Bageshwar 28.0 36.8 24.7 33.9 30.6 39.5 Chamoli 41.2 36.4 33.7 30.1 48.7 43.1 Champawat 37.7 37.0 24.9 28.4 52.5 50.3 Rudraprayag 25.4 30.2 20.8 28.0 29.2 32.0 Tehri Garhwal 31.5 40.8 20.5 30.0 42.8 51.8 Uttarkashi 15.5 18.4 12.3 15.0 19.2 22.2 Pauri Garhwal 36.4 40.0 27.9 30.8 44.9 50.8 Pithoragarh 37.6 32.8 28.4 29.2 46.6 36.8 Nainital 20.8 21.2 14.5 15.4 34.6 33.7 Hardwar 16.9 14.4 11.8 11.5 48.0 31.9 U. S. Nagar 23.5 23.8 15.4 16.1 54.8 47.1 Dehradun 16.0 16.2 12.5 12.9 31.1 28.6 Uttarakhand 25.9 25.9 17.9 18.9 40.0 39.4

Source: Calculated from Population Census, 2001 and 2011.

III. STRUCTURE AND QUALITY OF EMPLOYMENT

1. Sectoral Composition of Employment

Sectoral composition of employment and changes therein is one of the important aspects of understanding the quality of employment. The dominance of agriculture and allied activities in employment generation shows the slow pace of employment opportunities outside the farm sector and persistence of low income for majority of workers. According to 2011 Census,

105 about half of the workers in Uttarakhand are working in agriculture sector as cultivators or agricultural labourers (Table 5.3). This excludes a substantive share of workers who are engaged in allied activities such as animal husbandry, fisheries, forestry, etc. Even using this broader categorization of workers, there appears huge difference between the hilly and plain regions of the state. A large proportion of workers in hilly districts is working as cultivators on their tiny parcels of land. In contrast, cultivators account for less than one-fifth of total workers in plains districts of the state. The proportion of agriculture wage workers is found to be highest (28 per cent of total workers) in Udham Singh Nagar district in 2011. Overall sectoral pattern of employment in Uttarakhand reveals dominance of cultivators in hilly districts while same is not true for plains districts. Higher engagement of workers as cultivators in hilly districts (agriculturally) is an indication of poor quality of employment.

Table 5.3: Occupational Distribution of Workers (Main+Marginal), 2011

District Cultivator Agricultural Labour Household industries Other Almora 69.6 3.4 1.4 25.5 Bageshwar 68.9 7.3 2.4 21.5 Chamoli 67.0 2.1 3.0 27.9 Champawat 60.3 4.0 1.6 34.1 Garhwal 54.9 5.0 2.1 38.0 Nainital 36.6 9.2 2.6 51.6 Pithoragarh 63.4 2.5 2.8 31.3 Rudraprayag 73.6 2.8 1.9 21.7 Tehri Garhwal 66.7 2.9 1.4 28.9 Uttarkashi 74.6 2.8 2.0 20.7 Dehradun 13.2 6.6 3.9 76.3 Udham Singh Nagar 20.7 27.9 4.5 46.9 Hardwar 16.2 17.8 3.5 62.5 Uttarakhand 40.8 10.4 3.0 45.8

Source: Primary Census Abstract, Population Census, 2011.

Analysis of NSSO’s employment-unemployment survey data also reveals the dominance of primary sector (agriculture and allied activities) in providing employment to the people of Uttarakhand. It accommodateshalf of the state’s workforce in 2011-12.

106 Interestingly, the dominance of primary sector in providing employment in Uttarakhand is lower in comparison to Himachal Pradesh and Uttar Pradesh. The secondary sector largely consists of construction and manufacturing, employing about 9.3 per cent and 12.2 per cent of total workers, respectively in Uttarakhand. Overall sectoral composition of employment in Uttarakhand is found to be quite similar to the national pattern. However, as mentioned earlier, there exist wide disparities in sectoral composition of employment between hills and plains areas of the state, which generally get concealed at aggregate state level of analysis.

2. District-wise Sectoral Composition of Employment

Based on a primary survey of 100 villages across ten hilly districts in Uttarakhand during 2005, significant variations were observed in the sectoral composition of workforce (Mamgain et al., 2005). For example, more than three-fourths of workers in Pauri were engaged in agriculture and allied activities while it was lowest at about 57 per cent in Uttarkashi district. For other districts the share of agriculture and allied activities remains quite high between 68 to 72 per cent. This large proportion of employment in agriculture indicates lack of employment opportunities outside agriculture.

After agriculture,construction is another important sector of employment in Uttarakhand. It engages more than one-fifth of workforce in Champawat, Nainital and Pithoragarh districts. In all the other hill districts except Rudraprayag, it provided employment to a sizeable percentage of the workforce (Table 5.4). In fact, there was a significant increase

107 in developmental projects in all the hill districts in the state soon after its formation which led to intensive construction related work.This boosted the demand for labour in the construction sector. It, however, needs to be mentioned here that in major hydro power construction sites there was a negligible number of local labourers involved. The reasons for such a situation can broadly be traced to lack of required skills among local labour, tendency of local youth to out-migrate and preferences for outside labour by the employers.

The share of the service sector in employment was the highest at about 16 per cent in Rudraprayag and the lowest at about 6 per cent in . The other districts with comparatively higher share of service sector employment were Tehri Garhwal, Bageshwar and Uttarkashi. These districts also have a better flow of tourists, which promotes demand for the service sector, mainly hotels and amenity services. It needs to be mentioned here that nearly half of the total service sector employment was inpublic services, which largely include teachers and health workers in the rural areas of the hill districts. This was found true in all the hill districts considered for the analysis.

The manufacturing sector employed a very small percentage (1 to 2 per cent) of the workforce in most of the hill districts except Uttarkashi and Chamoli. In these two districts, 17 per cent and 6.3 per cent of the workforce respectively was employed in the manufacturing sector. In both these districts particularly at the high altitudes, most of the households were engaged in weaving, knitting and manufacturing woollen garments based on locally available wool and skills. This has been a traditional occupation of these communities but in the recent past they have been facing problems such as availability of raw material, higher cost of production and stiff competition from cheaper and better finished products from urban areas. As a result this traditional occupation is gradually vanishing.These features of employment underscore a need to initiate a suitable growth process which will help in shifting a larger proportion of the workforce to rural non-farm employment with adequate incomes.

108 Table 5.4: Sector-wise Composition of Employment in Rural Areas of Hilly Districts of Uttarakhand, 2005 District Agric- Manuf Constr- Trade, Trans- Financ Public All Total a- e, admn, number ulture uction hotel & port educatio of cturing Busine etc. restaurant n, sample ss, etc.. commer employe cial d services persons

Almora 71.88 1.92 15.63 2.40 1.20 0.48 6.49 100 416

Bageshwar 70.55 0.91 16.44 3.65 0.91 0.91 6.62 100 438

Chamoli 68.50 5.73 15.42 3.74 1.98 0.00 4.63 100 454

Champawat 68.53 1.74 21.24 3.67 1.54 0.19 3.09 100 518

Nainital 68.77 1.62 22.02 2.53 0.72 0.36 3.97 100 554

Pauri 100 Garhwal 75.10 0.99 18.18 2.17 0.59 0.20 2.77 506

Pithoragarh 69.37 0.90 20.50 3.15 0.90 0.00 5.18 100 444

Rudraprayag 73.52 1.43 8.96 3.05 2.24 0.20 10.59 100 491

Tehri 100 Garhwal 70.88 1.20 14.46 3.82 3.82 0.20 5.62 498

Uttarkashi 57.03 17.27 10.84 5.02 1.81 0.00 6.22 100 498

Total 69.36 3.40 16.44 3.32 1.58 0.25 5.46 100 4817

Source: Mamgain et al. (2005).

3. Nature of Employment

Self-employment is the predominant mode of employment in Uttarakhand. Nearly three- fourths of rural workers and over half of urban workers are self-employed in 2011-12 which is higherthan the national average at56 per cent and 42 per cent respectively (Figure 5.5a and 5.5b). Nearly 11 per cent of workers in rural areas of the state are in regular salaried jobs. Thus, the percentage of casual wage workers is comparatively much less in Uttarakhand as compared to Uttar Pradesh and India (Figure 5.5a and 5.5b).

109 Fig. 5.5a: Nature of Employment, 2011-12--Rural

Source:NSSO 68th Round, 2011-12.

Source:NSSO 68th Round, 2011-12

4. Nature of Employment across Social Group of Workers

The nature of employment differs significantly among workers belonging to various social groups in Uttarakhand. While self-employment is a dominant mode of employment among all

110 social groups, the highest 83 per cent of ST workforce was self-employment in Uttarakhand during 2011-12. The share of self-employed workers was lowest among SCs (59.3 per cent). Interestingly, STs constituted the highest self-employed group (34 per cent) in the non-farm activities which comprises mainly artisanworks and petty trade (Figure 5.6). Workers belonging to other castesor social groups (OSGs)are relatively better positioned in terms of employment.While a good one-fourth of them were in regular salaried employment, another 26 per cent were in non-farm self-employment. The other castes or OSGs were also the biggest workforce group in regular employment. Thus, we observe that SCs are at the most disadvantageous position as they were largely working as casual labour,or in self-employed agriculture activities, fetching low income to them. This pattern in the availability of employment opportunities to various social groups in the state broadly follows the national pattern; however, SCs in Uttarakhand are relatively better placed in terms of quality of their employment as compared to their counterparts at national level.

Fig. 5.6: Nature of Employment across Social Group of Workers in Uttarakhand, 2011-12

Source:NSSO 68th Round, 2011-12.

111 A higher dependence of population for employment on agriculture and allied activities as self-employed also speaks about the relatively poor situation of such workers particularly in hill regions where agriculture productivity is much less than half that inplain areas. More so the labour input required for cultivating a similar parcel of land is more than double in hill agriculture. This speaks their miseries. Mamgain (2004) estimated per person perday farm earnings in hill region of Uttarakhand. It is found to be almost half of the prevailing minimum daily wages in the region. In other words, the conventional time-based approach of employment measurement serves little purpose when devoid of income measure, particularly in agriculture and other self-employed ventures.

5. Regional Variation in Salaried Employment

In contrast to NSSO data, the Socio-Economic Caste Census (SECC) 2011, shows that nearly one-fourth of rural households in Uttarakhand haveatleast one salaried worker (Figure 5.7). The corresponding figure of India is much less at 9.7 per cent. The Labour Bureau data also show about 31.6 per cent rural households in Uttarakhand having at least one person working in wage/salaried employment in 2015-16. The share isalmost half at national level (16.4 per cent) but higher in case of Himachal Pradesh (40 per cent). Similarly, about 51.7 per cent of urban households in Uttarakhand haveatleast one person with wage/salaried jobs as compared to just 37.9 per cent in India (Labour Bureau, 2016). Both the SECC and Labour Bureau data clearly show the relatively less vulnerability of rural households in Uttarakhand to income fluctuations associated with other forms of employment such as casual and self-employment.

112 Source: SECC, 2011

According to SECC data, the proportion of rural households with at least one person in salaried employment widely varied from a highest (39.4 per cent) in Dehradun to lowest (14.6 per cent) in Uttarkashi. There were four districts namely, Champawat, Hardwar, Udham Singh Nagar and Uttarkashi reporting less than one-fifth of their rural households with salaried workers. Among the rural households with salaried workers, government salaried jobs predominate in almost all districts, indicating the relatively better quality of regular jobs. Surprisingly, rural households in industrially developed districts of Udham Singh Nagar and Hardwar reported much lower prevalence of salaried workers (18.3 per cent and 15.8 per cent) including around 9 per cent in private sector jobs. This means that the rural households in these two districts could benefit little with the industrial progress achieved in the districts during the last one and half decade. In brief, the SECC 2011 data show rural areas of Uttarakhand having relatively better quality of employment as compared to many other states in India. Most of the available salaried employment in rural areas of the state is in government sector. Perhaps due to this regional spread of salaried workers in Uttarakhand there is relatively low incidence of poverty among rural households in the state as compared to national average.

6. Levels of Earnings

The rapid growth in per capita income in the state is also marked with the increasing inter- sectoral income inequalities. About 49 per cent of workers in Uttarakhand contributed only

113 14.4 per cent of GSDP of the state in 2014-15, thereby implying abysmally low levels of earnings for a large segment of workers in the state. For example, in 2004-05 per worker GSDP in agriculture was lowest at Rs. 17897 (at 1999-2000 prices), which is almost three times lower than the average of the state. Construction, which employed nearly 7 per cent of the workforce, was yet another sector with marginally higher pay per worker GSDP (Rs. 24715) than agriculture. Per worker GSDP was highest in electricity, gas and water supply followed by finance & business (Table 5.5).

Table 5.5: Per Capita GSDP in Uttarakhand by sector, 2004-05 (at 1999-2000 constant prices)

Sector Per worker GSDP (Rs.) Agriculture, Forestry & Fishing 17897 Manufacturing 115577 Electricity, Gas and Water Supply 1379395 Construction 24715 Trade, Hotels & Restaurants 43126 Transport, Storage & Communication 257629 Finance., Real Est. & Business 454152 Other services 76409 Uttarakhand (GSDP) 51824

Source: Mamgain, 2006.

The situation in the hill areas of the state is more serious where productivity of agriculture is very low (even less than half in case of major crops such wheat and rice) as compared to plain areas (Mamgain, 2004).The situation almost remainedthe same till as recentlyas 2015 (Figure 5.8). Furthermore, agriculture in the hills largely depends on climatic conditions; therefore it is subject to large fluctuations and uncertainties in production. Agriculture in a large part of the state suffers from several inherent maladies such as scarcity of cultivable land, high degree of marginalisation and fragmented land holdings. A study by Mamgain et al. (2005) shows that nearly half of the labour input in agricultural sector (employing nearly 70 per cent of the rural workforce) in the hilly districts of Uttarakhand could not fetch even a minimum wage level (Rs. 60 per day) during the year 2004. The available technical

114 know-how in the field of agricultural development has also failed to make any significant contribution towards the development of agriculture in the mountain region. In fact, it has been observed that agriculture in mountain region requires more human and animal labour in comparison to plains region It also faces the inherent difficulty of implementing modern technologies. Due to poor agriculture and lack of alternative employment opportunities and other basic infrastructure, a majority of rural households in the hill region are forced to migrate out as a part of their survival strategy.

Source: Calculated from Uttarakhand Statistical Diary, 2015.

IV. DEMAND SIDE DYNAMICS OF EMPLOYMENT

Much of employment generation in any economy to a large extent depends on the growth of enterprises. Viewed from this perspective, let us look at the growth of private enterprise in Uttarakhand based on the data of Sixth Economic Census (SEC) 2013 that reveals some interesting patterns. It is observed that the number of private enterprises excluding crop production and plantation increased by 26.1 per cent during the period 2005- 2013. This growth was unevenly distributed across the districts of the state. It was as low as 5 per cent in Almora, Chamoli, Pithoragarh, Rudraprayag and Champawat districts to and as high as 53 per cent in Hardwar and other plains districts (Table 5.6). A high correlation coefficient value of 0.77 between per capita income and growth in number of enterprises across districts reveals the importance of development of enterprises to improve income levels of the population. Thus, despite the long history of self-employment programme, namely, Swarn Jayanti Gram Swarojgar Yojana (SGSY) and its recent format, National Rural Livelihood

115 Mission (also called Aajivika Mission), no visible impacts have beenseen in enterprise development, particularly in a large part of hill region of the state.

The government wage employment programmes such as MNREGA (Mahatma Gandhi National Rural Employment Guarantee Act) managed to ameliorate to some extent the demand for wage employment foraugmenting the income levels of poor rural households, particularly in hill areas. The average days of employment per household ranged between 26 in Tehri Garhwal and44 in Nainital and Dehradun districts each in 2016-17. However, such demand of wage employment tended to overburden women in the state, particularly those living in theHill Region (Mamgain and Reddy, 2015).

Table 5.6: Growth in Number of Enterprises* and Employment between 2005 and 2013 (% change) Average employment per District Establishments Employment enterprise (No.) 52.8 95.2 Hardwar 3.1 38.6 71.3 Dehradun 3.0 33.3 94.1 U. S. Nagar 3.3 26.1 57.1 Uttarakhand 2.6 23.9 43.0 Bageshwar 1.8 23.5 43.7 Pauri Garhwal 2.3 16.6 40.6 Tehri Garhwal 2.2 12.5 13.8 Nainital 2.4 10.4 27.1 Uttarkashi 2.0 5.8 28.7 Rudraprayag 2.1 5.4 16.2 Pithoragarh 1.4 5.0 4.5 Champawat 1.7 4.6 6.5 Almora 1.8 3.6 14.3 Chamoli 1.9

Note:* Enterprises excluding crop production, plantation, public administration, defence and compulsory social security services activities.

Source: Sixth Economic Census, 2013, Uttarakhand.

116 V. CORRELATES OF POVERTY AND EMPLOYMENT

We have attempted to compute a correlation matrix based on select variables pertaining to employment, its regularity, structure, resultant income and poverty across the 13 districts of Uttarakhand (Table 5.7). The results are on expected lines. As obvious, there is an inverse correlation between poverty ratio and per capita income as well with other variables like the share of non-farm workers, farm productivity and urbanization, educational levels of population and nutritional status of children. There is a positive correlation of poverty with proportion of SC population, marginal workers and Gini coefficient of income inequality. But such correlation is insignificant, thereby implying that more needs to be done to improve the income and its distribution in thestate. For this, diversification of employment within the farm sector and towards non-farm sector might be an important strategy. A significant correlation between the share of non-farm workers and per capita income shows the importance of diversification towards non-farm sector in improving the income levelsand reducing the incidence of poverty. A significant positive correlation between the share of non-farm employment and rate of urbanization, size of enterprises and percentage share of educated people in the population indicates the direction of interventions needed to accelerate the growth of non-farm employment in those areas which are lagging behindin these aspects of development.The regularity of employment too has significant impact on income levels. A large share of marginal workers among the workforce significantly reduces the per capita income. Similarly, a significant negative correlation coefficient value between the share of SC population and per capita income, agriculture productivity, hired workers in enterprises and size of employment is an indication of low income levels of SC population. That might be due to engagement of SC population in low quality of employment.A significant inversecorrelation of SC population with the shares of hired workers and employment size of non-farm enterprisesreaffirms the lack of employment opportunities in the districts with higher share of SC population. It also explains the higher incidence of poverty among SC population of the state.

Educational level of population turns out to be a significant variable in improving income levels and employment prospectsin the non-farm sector. For explaining this we have considered here the share of high school and above educated people in the age-group of 15 years and above. An insignificant correlation of child malnutrition with poverty only reaffirms earlier findings that the issue of child malnutrition is not just a poverty driven

117 phenomenonbut has much to do with a mother’s educational levels and awareness (Mamgain and Diwakar, 2012).

VI. SUMMING UP

The overall growth path of Uttarakhand has been impressive since its separation from Uttar Pradesh. However, this growth has created huge regional inequalities within the state. The growth process failed to generate gainful employment opportunities in the Hill Region of Uttarakhand.A comparatively higher educational level of the population in Uttarakhand in general, and in its hill region in particular, has not been able to reap the desired benefits from the growth process which is largely concentrated in plains districts of the state.

Overall, the work force participation rates of population in Uttarakhand are lower in comparison to Himachal Pradesh and the national average, particularly in case of male population. This is largely due to higher participation in education and higher outmigration of males in Uttarakhand. Work opportunities are marred with seasonality as one-fourth of total workers in Uttarakhand were marginal workers, i.e. they worked in gainful economic activities for less than 180 days (six months) in a year. The proportion of such marginal workers is more than double among women than among men, particularly in the hill districts. A high dependence on agriculture and allied activities forself-employment speaks volumes about the relatively poor situation of marginalworkers particularly in the hill areas where agriculture productivity is much less than half of productivity in plain areas. There is hardly any evidence of progress in agriculture sector in the Hill Region. Further, due to low productivity, uncertainty and crop destruction by wild animals, agriculture becomes unattractive for the youth. Other than theagriculture sector, construction sector has shown significant growth in terms of employment opportunities, but local people are mostly unwilling to undertake manual work therein. Moreover, the youth were not able to utilize the skilled job opportunities generated in the construction sector due to lack of required skills. Although employment opportunities in trade, transport and government services have expanded in both the hill and plain regions of the state, yet theyremain very limited in the Hill Region. The pace of enterprise development has been reasonably good in most of the plains districts of the state, whereas it has been far less than the desired pace in the Hill Region. Thus, the lack of remunerative employment opportunities coupled with obsession for salaried jobs has perpetuated large scale long term outmigration of youths from the hill areas towards urban centers. In other words, the conventional time-based approach of employment

118 measurement serves little purpose when devoid of income measure, particularly in agriculture and other self-employed ventures.

Despite a fast growth in enterprise development in Hardwar, the incidence of poverty remainshigh in its rural areas, indicating the need for strengthening redistributive measures of state government. This again reaffirms our argument that government redistributive measures in hill districts coupled with transfer income from migrant workers have been enabling factors for faster reduction in absolute deprivations of population in most of the hill districts in Uttarakhand. However, neglecting productive employment opportunities at the cost of redistributive measures would not last long as it has serious economic and political consequences particularly emanating from large scale job related long-term out-migration from the hill districts of the state.

A positive yet insignificant correlation of poverty with proportion of SC population, marginal workers and Gini coefficient of income inequality implies that more needs to be done to improve the income opportunities and its distribution in Uttarakhand. For this, diversification of employment within the farm sector and towards non-farm sector might be an important strategy. A significant correlation between the share of non-farm workers and per capita income shows the importance of diversification towards non-farm sector in improving income level and reducing incidence of poverty. A significant positive correlation between the share of non-farm employment and rate of urbanization, size of enterprises and percentage share of the educated in population shows the direction of interventions needed to accelerate the growth of non-farm employment in those areas which are lagging behind in these aspects of development. The regularity of employment has significant impact on income levels. A large share of marginal workers among the workforce significantly reduces the per capita income. Similarly, a significant negative correlation coefficient value between the share of SC population and per capita income, agriculture productivity, hired workers in enterprises and size of employment is an indication of low income levels of SC population. That might be due to engagement of SC population in low quality of employment. A significant inverse correlation of SC population with the shares of hired workers and employment size of non-farm enterprises reaffirmsthe lack of employment opportunities in the districts with higher share of SC population. It also explains the higher incidence of poverty among SC population of the state.

119 Table 5.7: Correlation Matrix Wei ght_ Povert Gini_ Gini_ Percapit Productivi Enterprisespe hired_w Empl_pere marginal_ nonfarm_ urban SC_ Educ for_ Variable y Rural Urban a_DDP typerha r_lakhpop orkers nterprise workers workers _pop pop ated age Poverty 1 Gini_Rural .426 1 Gini_Urban .077 .403 1 Percapita_DDP -.441 .143 .440 1

Productivityperha -.521 .081 .259 .761** 1

Enterprisesper_lakhp .059 .301 .511 .165 .077 1 op hired_workers -.300 .027 .065 .680* .551 -.417 1 Empl_perenterprise -.370 .199 .274 .891** .841** -.042 .858** 1 marginal_workers .376 -.494 -.125 -.568* -.686** -.316 -.301 -.644* 1 nonfarm_workers -.403 .253 .396 .779** .465 -.085 .537 .624* -.427 1 urban_pop -.533 .289 .507 .919** .699** .203 .574* .802** -.686** .879** 1 SC_pop .511 .127 -.413 -.683* -.553 .118 -.744** -.732** .260 -.570* -.660* 1 Educated -.093 .247 .192 .642* .136 -.003 .569* .565* -.355 .728** .674* - 1 .474 Weight_for_age -.389 -.104 -.398 -.042 .179 -.431 .421 .242 -.252 -.137 .001 - -.103 1 .221 13 13 13 13 13 13 13 13 13 13 13 13 13 13

Note:* Correlation is significant at the 0.05 level (2-tailed); ** Correlation is significant at the 0.01 level (2-tailed).

120 Educational level of population turns out to be a significant variable in improving income levels and employment prospects in non-farm sector. An insignificant correlation of child malnutrition with poverty only reconfirms the earlier findings that the issue of child malnutrition is not just a poverty driven phenomenon but has much to do with a mother’s educational levels and awareness. In the plains districts, especially Hardwar, the existing programmes of development and redistribution have beenless than satisfactory in ameliorating poverty and inequality.Thus, they need to be strengthened with respect to their design, outreach and effective implementation. The district lags much behind in most of the development indicators particularly due to poor redistribution mechanisms in its rural areas. This warrants a serious attention and multipronged strategy to eradicate poverty and improve income distribution by creating employment opportunities and upscaling quality skill development programmes.

Annexure Table 5.1: District-wise Work Participation Rates (%), 2001 and 2011 2001 2011 District Person Male Female Person Male Female Almora 46.3 44.5 47.9 47.9 48.9 47.0 Bageshwar 47.6 45.1 49.9 47.6 47.2 47.9 Chamoli 44.5 44.9 44.1 46.2 48.4 44.1 Champawat 40.2 43.5 36.9 38.3 46.1 30.5 Uttarkashi 46.1 48.3 43.7 47.6 50.0 45.2 Pauri Garhwal 38.7 40.8 36.8 39.9 45.1 35.2 Rudraprayag 44.9 42.3 47.1 46.7 45.7 47.5 Tehri Garhwal 43.8 45.1 42.5 45.3 47.3 43.5 Pithoragarh 43.0 43.4 42.6 44.8 47.4 42.2 Hardwar 29.4 47.2 8.8 30.6 49.5 9.1 Nainital 36.6 48.1 23.9 39.4 52.0 25.9 U. S. Nagar 31.7 48.0 13.7 35.9 51.8 18.6 Dehradun 31.2 47.8 12.6 34.3 51.4 15.4 Uttarakhand 36.9 46.1 27.3 38.4 49.7 26.7

Note: Work participation is calculated by including main and marginal workers. Source : Calculated from Primary Census Abstract data of Population Census for the year 2001& 2011

Annexure Table 5.2: Gender-wise WPRs, 2011-12 (Usual status) (%)

121 State Male Female Person Rural Uttarakhand 45.2 30.8 38.1 Himachal Pradesh 54.1 52.4 53.3 Uttar Pradesh 49.1 17.7 33.8 India 54.3 54.8 39.9 Urban Uttarakhand 50.6 8.6 30.5 Himachal Pradesh 60 21.2 41.6 Uttar Pradesh 51.1 10.2 31.7 India 54.6 14.7 35.5 Total Uttarakhand 46.6 25.2 36.1 Himachal Pradesh 54.8 49.2 52 Uttar Pradesh 49.5 16.1 33.3 India 54.4 21.9 38.6 Source: NSSO 68th Round on Employment and Unemployment, 2011-12. Annexure Table 5.3: Rural Households (%) with at least one Person in Salaried Jobs District Salaried jobs Government sector Public sector Private sector Dehradun 39.38 20.72 2.60 16.06 Bageshwar 29.95 15.65 2.10 12.20 Pithoragarh 28.50 20.45 1.13 6.92 Chamoli 26.91 20.80 1.57 4.54 Tehri Garhwal 26.35 8.92 2.36 15.06 Garhwal 25.00 16.43 2.01 6.56 Nainital 24.03 11.51 3.25 9.26 Rudraprayag 22.60 12.88 2.28 7.44 Almora 21.53 11.79 1.54 8.20 US Nagar 18.29 7.48 1.95 8.86 Champawat 16.56 11.26 0.73 4.56 Hardwar 15.82 5.05 2.07 8.71 Uttarkashi 14.60 11.71 0.63 2.26 State Total 23.67 12.44 2.00 9.23 All India 9.65 5.00 1.12 3.57 Source:Socio-Economic Caste Census, Uttarakhand, 2011 Annexure Table 5.4: Reasons for Migration, 2011

122 Uttarakhand India Reason Persons Males Females Persons Males Females Work/Employment/Business 15.41 39.46 2.68 11.18 29.95 2.72 Education 3.11 5.49 1.85 1.77 3.39 1.03 Marriage 42.64 1.38 64.49 49.35 4.27 69.68 Moved after birth 3.62 6.25 2.22 10.57 20.23 6.22 Moved with household 26.30 32.88 22.81 15.39 22.33 12.26 Others 8.92 14.54 5.94 11.74 19.82 8.10 Total 100 100 100 100 100 100

Source: Calculated from Population Census, 2011, D-5 series (provisional)

123 Chapter - VI SUMMARY AND CONCLUSIONS

Measurement of poverty and its elimination has been a core strategy of the development planning process in India since its First Five Year Plan. There has been significant progress in the methodology of the measurement of poverty in India. However, poverty measurement still suffers due to paucity of data at a more disaggregated level for effective policy interventions. The NSSO quinquennial surveys pooled data for centre and state samples on consumption expenditure makes it possible to estimate poverty at district level for rural and urban areas but does not allow estimation at further disaggregation.

Keeping in view the Terms of Reference (ToR) of Department of Economics and Statistics (DES), Government of Uttarakhand, the present study attempted to generate district-wise poverty estimates, separately for rural and urban areas of Uttarakhand by using NSSO’s 68th Round pooled data on consumption expenditure for the year 2011-12. Given the constraint of access to other data sources, such as SECC, 2011 and NFHS-4, the present exercise mainly concentrated on NSSO data for district-wise poverty estimation in Uttarakhand. The report spans through six chapters including this one. The major findings emanating from the study are briefly presented in the following sections.

A remarkable progress in attaining high economic growth in Uttarakhand has also been accompanied with widening regional disparities. Most of the hilly districts of the state lagged behind the three plains districts including Dehradun in economic development. Though the situation of hilly districts on educational development indicators is far better than the two plains districts of Hardwar and Udham Singh Nagar, there are hardly any employment opportunities for such educated labour force in the Hill Region. As a result, most of the hilly districts are witnessing a huge out-migration of its able-bodied population, mostly males,in search of livelihoods. There has been a rapid increase in permanent out-migration from hilly areas of the state in recent decades, which is likely to havefar-reaching socio- political implications in coming years. Out-migration could hardly make any multiplier impact on the economy of source areas of migration. The growing regional disparities in

124 development outcomes in Uttarakhand only reinforces the need to understand poverty in the statein its multidimensional forms as the general indicators of development used to assess progress in mountain economies may sometime lead to confusing interpretations. It must be remembered that the available data used for calculation of poverty in the contexts of Hill Region rather fall inadequate, and therefore need to be interpreted with utmost care.

Deprivation and Inequality-A Comparative Picture of Uttarakhand with Select States

Based on consumption expenditure data of NSSO for the years2004-05 and 2011-12, the report estimates deprivation and inequality in Uttarakhand. However, defining a concept of deprivation and deriving a corresponding measure of it consistently across heterogeneous regional contexts is an empirical challenge for studies on a state like Uttarakhand. Our analysis was made in a comparative setting involving its parent-state of Uttar Pradesh, the adjacent hill state of Himachal Pradesh and the national context of India. The major findings are as follows:

Uttarakhand stands second among the three states under review in terms of estimates of measures of average consumer expenditures for both rural and urban sectors. It has improved while both Himachal Pradesh and Uttar Pradesh have declined in terms of their average consumption levels relative to that of the nation as a whole. This indicatesbetter pace of progress in Uttarakhandthan that of the rest of India.

Inequality in rural nominal consumption distributionwas the least in Uttarakhand in 2004/05, but tended to increase at a faster rate between the period 2004-05/2011-12, thereby outpacing Himachal Pradesh, Uttar Pradesh and the national average. As regards urban nominal consumption inequality, it increased in all the states under review; the percentage increase was the highest in Himachal Pradesh followed by Uttar Pradesh, Uttarakhand and All-India respectively.

The extent of inclusion of the bottom half of the rural population in the mainstream was 93.40 per cent in Uttarakhand in 2004/05, which was the highest amongthe cases under review. Mainstream inclusion increased in urban Uttarakhand and Uttar Pradesh butdeclined

125 in Himachal Pradesh and all-India. The reasons for such inclusion could be improved reach of government’s redistributive programmes in rural areas of these states.

Estimates of absolute deprivation (poverty) vary depending upon the concept and measure used. This study has explored conventional as well as contemporary approaches in this respect. As per the Lakdawala approach, the incidence of poverty was the highest in Uttarakhand, followed by Uttar Pradesh and Himachal Pradesh in 2004/05. This profile is different from the one revealed by the Tendulkar Committee method for the same year, which shows the incidence of poverty to be the highest in Uttar Pradesh followed by Uttarakhand and Himachal Pradesh in the same year. In general, both Tendulkar and Rangarajan Committee approaches reveal a reduction in poverty in all the states at successive points of time under review. As regards urban poverty, the reduction was much higher at the national level than in Uttar Pradesh followed by Uttarakhand and Himachal Pradesh respectively.

Social group-wise, the incidence of absolute poverty was the least among the OSGs, followed by OBCs and was highest for SCs in 2004-05. The percentage point reduction in poverty in Uttarakhand was maximum among the SCs (30.34) followed by OBCs (29.06), STs (20.52) and OSGs (18.88) between 2004-05 and 2011-12. There was a more or less uniform reduction (around 65 percent) in the incidence of poverty among all the social groups in rural Uttarakhand. The relative profile of deprivation across social groups is similar in Himachal Pradesh and Uttarakhand but with a difference. The difference being, unlike Uttarakhand, the extent of reduction in poverty is highly uneven across social groups in Himachal Pradesh and Uttar Pradesh: Incidence of poverty declined by 88 per cent among OBCs and by 62 per cent among OSGs in Himachal Pradesh and by 27 per cent (OBCs) and 52 per cent (OSGs) in Uttar Pradesh. At the all India level, percentage poverty reduction fell in the range between 38 and 42 per cent among the SCs, OBCs and OSGs.

The relative profiles of absolute deprivation in urban Uttarakhand is slightly different from the one observed for rural Uttarakhand. Even though the relative standing of the three social groups– the SCs, OBCs and OSGs– is the same as the rural one for the year 2004-05, it changes for the year 2011/12 – the SCs and the OBCs interchange their rank in terms of the extent of deprivation. This is because of a massive reduction in deprivation (80 percent)

126 among the SCs as compared to only 45 per cent among the OBCs. Thus, unlike the rural sector, the extent of reduction in poverty across social groups in urban Uttarakhand is highly uneven: the percentage point reduction in urban poverty was the maximum among the SCs (38.17) followed by OBCs (15.86), STs (13.32) and OSGs (11.51). The same profile could be found in Himachal Pradesh and Uttar Pradesh. As regards Himachal Pradesh, poverty actually increased among the STs and SCs in urban areas. Urban all India too has experienced uneven extent of reduction in poverty among the four social groups under review.

As regards the extent of mainstream inclusion in rural Uttarakhand, it was the highest for the OSGs (81 per cent) in 2004/05 which declined to 77 per cent by 2011-12. It has been the lowest for SCs, which declined from 49 per cent to 38 per cent in rural Uttarakhand. The rural OBCs improved their extent of mainstream inclusion from 62 per cent in 2004-05 to 84 per cent in 2011-12. The STs too improved their inter-group inclusion from 57 per cent to 67 per cent between these two years. These results show that inclusion process for the SCs was far behind other social groups in rural Uttarakhand; and the reach of high economic growth to SCs was less than satisfactory. Both the OBCs and OSGs improved their lot as reflectedby both mean- and order-based measures of inter-group inclusion in urban Uttarakhand.

Mainstream inclusion was the maximum for the STs in rural Uttarakhand in 2004/05. The extent of mainstream inclusion for the bottom half of STs and OSGs exceeded that for SCs and OBCs. This profile remained the same in 2011-12 but for some marginal decline in mainstream inclusion for the STs, OBCs and OSGs. As regards SCs, mainstream inclusion increased marginally between these two years. The SCs and OBCs were the marginalized social groups in 2004/05; only the SCs remained so in 2011-12.

Mainstream inclusion was maximum for the STs in urban Uttarakhand. The extent of mainstream inclusion for the bottom half of the STs and OSGs exceeded that for SCs and OBCs. This profile changed altogether in 2011-12 which saw a drastic reduction for the STs and improvement for the SCs in mainstream inclusion The STs, SCs and OBCs are the marginalized social groups in 2004-05 as well as 2011-12; however, the extent of marginalization of SCs and OBCs has declined between the years under review.

127 District-wise Poverty and Inequality in Uttarakhand

The calculation of district-level poverty and inequality was based on pooled state and central sample of NSSO consumption expenditure data for Uttarakhand for the year 2011-12. The average MPCE (at average state level prices) in rural Uttarakhand was Rs 1460.10 in 2011-12. The marginal distribution of rural mean MPCE across districts reveals high density of the bottom half of the districts in a narrow range and limited scattered prosperity across districts over a wide upper range. Nainital is even an outlier prosperous district in the rural sector. Pithoragarh, Pauri Garhwal, Hardwar and Dehradun Hills constitute the poorest quartile group of districts; Rudraprayag, Chamoli, Nainital Hills and Tehri Garhwal form the lower middle quartile group; Bageshwar, Uttarkashi, Almora and Champawat belong to the upper middle quartile group; Dehradun, Udham Singh Nagar and Nainital form the richest quartile group in the rural sector of Uttarakhand. MPCE distribution varied across districts with respect to its different dimensions. This clearly brings out how heterogeneous the districts are with respect to even the factors governing the distribution of per capita household consumer expenditure.

The marginal distribution of urban mean MPCE across districts is negatively skewed; the urban distributional profile is the reverse of the one observed for the rural sector across districts. Champawat, Udham Singh Nagar, Dehradun Hills, Nainital and Pauri Garhwal belong to the poorest quartile group; Chamoli, Pithoragarh, and Uttarkashi form the lower middle quartile group; Rudraprayag, Dehradun, Bageshwar, and Almora belong to the upper middle quartile group; Tehri Garhwal, Hardwar, and Nainital Hills form the richest quartile group in the urban sector.

There is no consistent relation between levels of mean MPCE and extent of inequality in both the rural and the urban sectors.

Almost every fifth rural resident of Uttarakhand lives in poverty. This incidence is minimum in the Dehradun Hills region of Dehradun district (6.7 per cent) and maximum in Pauri Garhwal (29.9 per cent). As regards urban deprivation, the state level average incidence is 11.5 per cent. It ranged from the minimum of nil in Tehri Garhwal to the maximum of nearly half of the urban population (48.7 per cent) in Champawat. The average incidence of

128 poverty for the state as a whole (rural and urban combined) is 16 per cent. It ranged from 6.8 per cent in Dehradun Hills to 28.5 per cent in Pauri Garhwal.

Incidence of rural poverty is generally the lowest in the richest quartile group of districts. Other indicators of deprivation like food share in household budget and cost of living also report a favourable profile of these districts. In sum, the best-off three districts, namely Dehradun, Udham Singh Nagar and Nainital seem to be doing reasonably well in terms of all the indicators under review.

The marginal distribution of incidence of rural poverty across districts is nearly uniform while those pertaining to extent of inequality and cost of living are highly negatively skewed ones. This would mean that at least half of the districts are densely located with respect to high extent of relative inequality and cost of living.

Unlike the rural profiles, the marginal distributions of the incidence of poverty, extent of inequality and cost of living are positively skewed ones in the urban sector. This would mean that half of the districts are densely located in a narrow range at the lower end of the distributions of incidence of poverty, extent of relative inequality and cost of living.

Urban mean MPCE exceeds that of rural mean MPCE in all the districts. Rural-urban disparity in mean MPCE is the lowest in Nainital (108.45), which is the richest in terms of rural mean MPCE but poorest fourth in terms of urban mean MPCE. MPCE disparity is the highest is Hardwar (212.13), which is the third poorest rural district but second richest urban district. Finally, the median disparity is in Uttarakashi (172.10), which falls in the rural upper middle and urban lower middle quartile group. In other words, failure of urban development to catch up with rural prosperity seems to have led to a development process far removed from the Kuzents’s inverted-U postulate.

Thecross-sectional estimates of poverty and inequality across districts do not really tally with the descriptions provided in the overview profile of Uttarakhand. For instance, Hardwar falls in the poorest quartile group in terms of rural MPCE, extent of inequality in consumer expenditure distribution and incidence of poverty even though one would expect it in the richest quartile group because of its rich resource endowments and opportunities as a

129 district in the plains. Similarly, Almora falls in the upper quartile group in terms of MPCE, extent of inequality, incidence of poverty, topmost quartile group in terms of food share in total consumer expenditure and lower quartile group in terms of cost of living. The urban profile too corroborates this kind of mismatch. How do we explain this mismatch? One critical explanation could be migration between the hilly and plains districts, state intervention in stabilizing prices through the public distribution system, state’s role in public employment (about 25 per cent of the households with atleast one member in regular job,andgovernment oriented employment), etc.

The pattern of poverty and inequality clearly shows how a large number of population is concentrated in lower income quintiles, marginally above the poverty line in most of the districts in Uttarakhand. They are vulnerable to marginal fluctuations in their income levels with a likelihood of falling back into the poverty trap. We attempted to understand this scenarioof poverty and vulnerability in the context of nature and quality of employment in Uttarakhand. We observed a predominance of agriculture as a source of employment and income, particularly in most of the hill districts in Uttarakhand, with very slow pace of diversification. Moreover, the productivity of agriculture in hill districts is almost half of the plain regions of the state, mainly associated with undulated geographical terrains, dependence on rains and scattered farmlands demanding highlabour inputs. The available employment opportunities outside farm sector are mostly manual andextremely limited. Most of the youth are educated and in search of regular salaried employment, even in menial jobs at low levels of income. The lack of remunerative employment opportunities coupled with obsession for salaried jobs has led to large scale long term out-migration among youths towards urban centres.

Eradicating Poverty and Reducing Vulnerability through Creating Quality Employment

The second chapter on the overview of economy of Uttarakhand is unambiguous in its presentation of the state’smacroeconomic transition from a slow growth economy into a high- growth one. It presentscross-sectional profile of disparities in resource endowments, economic opportunities and hence, economic welfare levels like per capita consumer

130 expenditure and incidence of poverty. Empirical evidence on the levels of living and deprivation provide enough evidence of the state’s achievements in this respect. Growth in real consumption (price adjusted average per capita MPCE of 58 per cent) in both the rural and urban sectors is higher than those in the states of Himachal Pradesh and Uttar Pradesh and in the nation as a whole. Percentage reduction in rural poverty is also the highest while the urban poverty has almost reached the single-digit level. How far these changes are reflected in real outcome indicators like measures of health status, say, of children? Available estimates for 2005-06 show that Uttarakhand was doing much better than the nation as a whole on these indicators. As regards wasting and under-weight its performance in 2005-06 was comparable to that of Himachal Pradesh. Recent evidence for the year 2015-16 speaks of a sustained improvement in health indicators. Stunting declined from 44.4 per cent in 2005- 06 to 33.5 per cent in 2015-16 while the decline at the national level was from 48 per cent to 38.4 per cent between the same two points of time. Wasting increased in both Uttarakhand and India as a whole: it increased from 18.8 per cent to 19.5 per cent in Uttarakhand and from 19.8 per cent to 21.0 per cent in India as a whole. However, there was good improvement in terms of proportion children underweight. It declined from 38 per cent to 26.6 per cent in Uttarakhand as against a drop from 42.5 per cent to 35.7 per cent in the nation as a whole during the stated period 2005-06 /2015-16.

However, there is hardly any evidence of progress in agriculture sector in the Hill Region,thus keeping intact the related vulnerability of a large section of population dependent on it. In addition, due to low productivity, uncertainty and crop destruction by wild animals, agriculturebecomes unattractive for the youth, who are by and large well-educated. Although construction sector has shown significant growth in employment opportunities, local people are mostly unwilling to undertake manual work. Moreover, they are not able to utilize the skilled job opportunities generated in the construction sector due to lack of required skills. Though employment opportunities in trade, transport and government services have expanded in the hill region of the state, theyremain very limited. The lack of remunerative employment opportunities coupled with obsession for salaried jobs led to the large scale long term out migration among youths towards urban centres. The gravity of the situation can be understood fromthe fact that there are a number of villages left with single digitpopulations.

131 Such destitution needs to be reversed. This precarious situation needs to be reversed through appropriate policies and programmes aimed at employment creation with special focus on the development needs of such regions.

Overall, the work force participation rates of population in Uttarakhand are lower in comparison to Himachal Pradesh and national average, particularly in case of male population. This is largely due to higher participation in education and higher migration of males in Uttarakhand. Work opportunities are marred with seasonality as one-fourth of total workers in Uttarakhand were marginal workers, i.e. they work forlesser part of the year (less than 180 days or six months) in gainful economic activities.The proportion of such marginal workers is more than double among women than in men, particularly in the HillRegion. A higher engagement of workers as cultivators in hilly districts is an indication of poor quality of employment. A higher dependence of population on agriculture and allied activities forself-employment also reflects the relatively poor situation of such workers, particularly in hillyareaswhere agriculture productivity is less than half than in plains areas.In other words, the conventional time-based approach of employment measurement serves little purpose when devoid of income measure, particularly in agriculture and other self-employed ventures.

The pace of enterprise development has been reasonably good in most of the plains districts of the state, yet far less than the desired pace. Despite a fast growth in enterprise development in Hardwar, the incidence of poverty remained high in its rural areas, indicating the need for strengthening redistributive measures of state government. This again reaffirms our argument that government redistributive measures in hillydistricts coupled with transfer income from migrant workers have been enabling factors for faster reduction in absolute deprivations of population in most of the hill districts in Uttarakhand. However, neglecting productive employment opportunities at the cost of redistributive measures would not last long as it has serious economic and political consequences particularly emanating from large scale job related out-migration from hilly districts of the state.

A positive yet insignificant correlation of poverty with proportion of SC population, marginal workers and Gini coefficient of income inequality implythat more needs to be done to improve income opportunities and theirdistribution in Uttarakhand. For this diversification

132 of employment within the farm sector and towards non-farm sector might be an important strategy. A significant correlation between the share of non-farm workers and per capita income shows the importance of diversification towards non-farm sector in improving income level and reducingtheincidenceof poverty. A significant positive correlation between the share of non-farm employment and rate of urbanization, size of enterprises and percentage share of educated people in population indicatesthe direction of interventions needed to accelerate the growth of non-farm employment in those areas which are lagging behind on these aspects of development. The regularity of employment has significant impact on income levels. A large share of marginal workers among the workforce significantly reduces the per capita income. Similarly, a significant negative correlation coefficient value between the share of SC population and per capita income, agriculture productivity, hired workers in enterprises and size of employment is an indication of low income levels of SC population. That might be due to engagement of SC population in low quality of employment. A significant inverse correlation of SC population with the shares of hired workers and employment size of non-farm enterprises reaffirmsthe lack of employment opportunities in the districts with higher share of SC population. It also explains the higher incidence of poverty among SC population of the state. Educational level of population turns out to be a significant variable in improving income levels and employment prospects in the non-farm sector. An insignificant correlation of child malnutrition with poverty only reaffirms the earlier findings that the question of child malnutrition is not just a poverty driven phenomenon but has much to do with a mother’s educational levels and awareness.

In brief, the creationof gainful employment opportunities with reasonable social safety measures iscritical in eradication of poverty and reduction in vulnerabilities of population belonging to various regions and disadvantaged sub-groups of population in Uttarakhand. Thus, along with the creation of employment opportunities, skill development of both men and women is crucial for various trades and occupations to improve their employability and productivity. Most of the people including migrants of the Hill Region though better educated, lack skill training. This severely affects their employability and earnings. They require training on a larger scale in different vocations in response to market demand. The skill training measures need to be generic as well as area specific depending on

133 the choices and opportunities for such skills. The existing skill development programmes in the state need to be assessed in terms of their coverage and utility in order to undertake suitable midway corrections.

With the growing emphasis on protection of environment in the context of climate change, role of hill and mountain regions is being seen as critical towards this endeavour. In this direction, an EcoTaskForce could be created on the lines of Territorial Army by recruiting local people, whose services can be used in afforestation drives and their maintenance. This will not only help in improving environment but also provide salaried employment to local youth.

The state government can learn from the encouraginggrass root examples of promoting sustainable livelihoods in farm as well as non-farm sector by various NGOs, which linked these to value chains and resulted in improving quality of life inrural areas in the hill districts. Such measures need upscaling with support of government and active engagement of local communities. Improved access to information, skills, technology, markets, policy and institutional support leading to better terms of engagement for small producers are equally important for enterprise development in the state. The rate of success would depend on efficient implementation of policiesand programmes which need to be developed with a pro-poor and mountain bias. Institutions responsible for the implementation of such policies must be pro-active and develop a synergy and coordination to avoid conflicts and produce better results. Mobilising and empowering communities with information, skills and support services are of paramount importance (ICIMOD, 2013).

In sum, the programmatic interventions must support the higher growth initiatives in Hill Region of Uttarakhand which hasyet to witness a remarkable improvement in employment and income opportunities for itspopulation. These efforts should also percolate to poor and marginalized sections of the society such as SCs and religious minorities. The development dreams of the people of Uttarakhand, which they visualized at the time of demand for a new state, particularly of those residing in hilly districts must be addressed on a priority basis. In fact, there is need for a strong political will to initiate a process of niche baseddevelopment strategy for the hilly areas of the state with a strong support of

134 bureaucracy. The myopic vision of developing already developed regions will not prove to be an inclusive strategy. This will also be a fitting tribute to those who sacrificed their lives for making Uttarakhand a state of their dreams where everybody gets decent work opportunities with least out-migration.

In the plains districts, especially Hardwar, the existing programmes of development and redistribution have beenless than satisfactory in ameliorating poverty and inequality, and thus need to be strengthened in terms of their design, outreach and effective implementation. The district lags much behind in most development indicators particularly due to poor redistribution mechanisms in its rural areas. This warrants a serious attention and multipronged strategy to eradicate poverty and improve income distribution through creating employment opportunities and upscaling quality skill development programmes.

135 References

Alkire, S., and G. Robles (2015),“Multidimensional Poverty Index 2015: Brief Methodological Note and Results”, . Oxford, UK: Oxford University. Available from www.ophi.org.uk/wp-content/uploads/MPI-2015-BriefMethodological- Note_June.pdf?cb41ae Alkire, S., and J.E. Foster. 2011. “Counting and Multidimensional Poverty Measurement.” Journal of Public Economics. 95(7-8): 476-487. Atkinson, E.T. (1882), North Western Provinces Gazetteers, Vol. XII. (Reprinted in 1976), The Himalayan Gazetteer, Vols, I, II and III, Cosmo Publications, Delhi. Awasthi, I.C. (2012), Livelihood Diversities in Mountain Economy: Constraints and Opportunities, Concept Publishing Company Pvt.Ltd., . Bora, R.S. (1996), Himalayan Out-migration, Sage Publication, New Delhi. CBED (2012), Annual Report 2011-12, Centre for Business and Entrepreneurial Development, Dehradun CSO (2013), Annual Survey of Industries, New Delhi. Deshangikar, P. and Farrington, J. (2009), Circular Migration and Multidimensional Livelihood Strategies in Rural India, Oxford University Press, New Delhi. Dhyani, R.P. (1994), An Approach to Economic Planning for the Rural Poor of Central , Classical, New Delhi. Dobhal, G.L. (1987), Development of the Hill Areas: A Case Study of Pauri Garhwal District, Concept, New Delhi. Fei, J.C.H. and Ranis, G. (1964), Development of the Labour Surplus Economy: Theory and Practice, Irwin Press, Homewood. GoI-MoA (2013), Agricultural Census 2010-11, Ministry of Agriculture, Government of India, New Delhi. GoI-NSSO (2014), All India Debt and Investment Survey, 70th NSSO Round, National Sample Survey Organisation, Government of India, New Delhi. GoUK (2012), Project Implementation Manual of Integrated Livelihood Support Project, . Central Project Coordinating Unit, Uttarakhand GramyaVikasSamiti, Watershed Management Directorate & Uttarakhand ParvatiyaAajeevikaSanvardhan Company, Dehradun. GoUK (2012), Uttarakhand PIP 2011-12, Uttarakhand Health & Family Welfare Society, Dehradun. GoUK (2012), Uttarakhand Twelfth Five Year Plan and Annual Plan 2012-13, Presentation of Finalisation Meeting between Deputy Chairman, Planning Commission and Chief Minsiter of Uttarakhand, Government of Utarakhand, New Delhi.

136 GoUK (2013), EC_Minutes_20.11.13 , Uttarakhand State Rural Livelihood Mission, Dehradun,. Retrieved from http://usrlm.uk.gov.in/files/EC_Minutes_20.11.13.pdf GoUK (2014), Annual Plan 2013-14, State Planning Commssion, Government of Utarakhand, New Delhi. Government of India (1993): Report of the Expert Group on Estimation of Proportion and Number of Poor, Perspective Planning Division, Planning Commission, New Delhi. Government of India (2009): Report of the Expert Group to Review the Methodology for Estimation of Poverty, Planning Commission, New Delhi Government of India (2014): Report of the Expert Group to Review the Methodology for Measurement of Poverty, Planning Commission, New Delhi. GoI- RGI (2017), Migration Data, Population Census, 2011, D-5 Series (provisional), Registrar General of India, New Delhi. GoI-MoF (2017), Economic Survey 2016-17, Ministry of Finance, Government of India, New Delhi. Government of Uttarakhand (2016): Household Consumer Expenditure (Type 1 & Type 2), Employment and Unemployment Survey, NSS 68th Round (July 2011 – June2012), Directorate of Economics & Statistics Department of Planning, Government of Uttarakhand, Road, Dehradun. ICIMOD (2010), "Labour Migration and Remittances in Uttarakhand--Case StudyReport", International Centre for Integrated Mountain Development, Kathmandu. ICIMOD (2010), "Labour Migration and Remittances in Uttarakhand--Case Study Report", International Centre for Integrated Mountain Development, Kathmandu. ICIMOD (2013), “The Value Chain Approach for Mountain Development: Case Studies from Uttarakhand, India”, ICIMOD Working Paper 2013/6, Authors: Choudhary, Dyutiman; Ghosh, Idraneel; Chauhan, Sushrut; Bahti, Sanjay and Juyal, Manish, International Centre for Integrated Mountain Development, Kathmandu. ICIMOD (2016), Towards an Integrated Approach to Nutrition Security in the Hindu Kush Himalayan Region, ICIMOD Working Paper 2016/7, Kathmandu. IFAD.no date. India: Integrated Livelihood Support Project. Retrieved from http://www.ifad.org/operations/pipeline/pi/india.htmhttp://www.ugvs.org/Doc_ULIP H.html http://www.ugvs.org/Doc_ILSP.html# IHD-ISLE (2014), India Labour and Employment Report 2014: Workers in a Globalising World, Institute for Human Development and Indian Society of Labour Economics, Academic Foundation, New Delhi. India Brand Equity Foundation (2014), Uttarakhand August 2014. New Delhi. Institute for Human Development (IHD) (2011), Poverty and Gender Analysis of Uttarakhand, A study for the International Fund for Agricultural Development, June.

137 Jayraj, D. (2013), “Family Migration in India: “Push” or “Pull” or Both or What?”,Economic and Political Weekly, Vol. XLVIII, No. 42., pp. 44-52. Joshi, B.K. (2010), “Reflections on Reform of Higher ”, Occasional Paper 1, Doon Library & Research Centre, Dehradun. Kannan, K.P., Rajendra P. Mamgain and PreetRustagi (eds.) (2017), Labour and Development: Essays in Honour of Prof. T.S. Papola, Academic Foundation, New Delhi. Kannan, K.P., Rajendra P. Mamgain and PreetRustagi (2017), “Labour and Development: Introduction and Overview”, in Kannan et al. (eds.), Labour and Development: Essays in Honour of Prof. T.S. Papola, Academic Foundation, New Delhi. Krishna Anirudh (2010), One Illness Away: Why People Become Poor and How They Escape Poverty, Oxford University Press. Labour Bureau-GoI (2016), Report on Fifth Annual Employment-Unemployment Survey (2015-16), Vol. I, Ministry of Labour, Government of India, Shimla. Lee, E.S. (1966), “A Theory of Migration”, Demography, Vol. 3, No.1. Lewis, Arthur (1954), “Economic Development with Unlimited Supplies of Labour”, Manchester School of Economic and Social Studies, May. Mamgain, Rajendra P. (2004), Employment, Migration and Livelihoods in the Hill Economy of Uttaranchal, Ph.D. Thesis, Centre for the Study of Regional Development, Jawaharlal Nehru University, New Delhi. Mamgain, Rajendra P. (2017), “Occupational Diversification in India: Trends and Determinants”, in Kannan et. al. (eds). Mamgain, Rajendra P. and G. DilipDiwakar (2012), ‘Elimination of Identity-based Discrimination in Food and Nutrition Programmes in India’, IDS Bulletin, Vol. 43, No. S1, Special Issue, July, Sussex: Institute of Development Studies. Mamgain, Rajendra P. and D.N. Reddy (2016), “Outmigration from Hill Region of Uttarakhand: Magnitude, Challenges and Policy Options”, GIDS Working Paper No. 216, Giri Institute of Development Studies, Lucknow. Mamgain, Rajendra P., I.C. Awasthi and B.S. Mehta (2005), Employment Opportunities in Uttaranchal: Constraints and Opportunities, Institute for Human Development, New Delhi (mimeo). Mathur, Ashok & Rajendra P Mamgain (2004), "Human Capital Stocks, Their Level of Utilization and Economic Development in India", Indian Journal of Labour Economics, 47(4): 655-75. Mehta, G.S. (2016), Migration in Uttarakhand, Giri Institute of Development Studies, Lucknow (mimeo). Minhas, B S and M G Sardana (1990): “A Note on Pooling of Central and State Samples Data of National Sample Survey’, Sarvekshana, Vol XIV, No 1, Issue No 44, pp 1-4.

138 MoF-GoI, (2017), Economic Survey 2016-17, Ministry of Finance, Government of India, New Delhi. Papola, T.S. (2000), “Enterprise Development for Poverty Alleviation with Sustainable Resource Management: Trends, Experiences and Policies in the HKH Region”, in Banskota, Papola and Richter (eds.) (2000). Papola, T.S. (2002), Poverty in Mountain Areas of the Hindu Kush Himalayas: Some Basic Issues in Measurement, Diagnosis and Alleviation, Talking Points 2/02, ICIMOD, Kathmandu. Papola, T.S. (2013), “Economic Growth and Employment Linkages: The Indian Experience”, ISID Working Paper 2013/01, Institute for Studies in Industrial Development, New Delhi. Planning Commission (2007), Press Note on Poverty Estimates, 2004-05, New Delhi. Planning Commission (2007), Eleventh Five Year Plan, Vol 2, New Delhi Planning Commission (2009), Report of the Expert Group to Review the Methodology for Estimation of Poverty (Chairman: S D Tendulkar), Government of India, New Delhi. Planning Commission (2013), Press Note on Poverty Estimates, 2011-12, July, New Delhi. Planning Commission (2013), Twelfth Five Year Plan (2012-2017): Faster, More Inclusive and Sustaibale Growth, Vol. I, New Delhi. Planning Commission (2014), Report of the Expert Group to Review the Methodology for Measurement of Poverty, New Delhi. Radhakrishna, R.; Ravi, C. and Reddy, B. Sambi (2010), “Can We Really Measure Poverty and Identify the Poor when Poverty Encompasses Multiple Deprivations?” IHD Working Paper Series, Institute for Human Development, New Delhi. Sabharwal, Nidhi S. (2011), ‘Caste, Religion and Malnutrition Linkages’, Economic and Political Weekly, 46(50): 16–18 Sen, A.K. and Jean Dreze (2013), An Uncertain Glory: India and its contradictions, Princeton University Press, New Jersey. Shultz, T.W. (1961), “Investment in Human Capital”, The American Economic Review, Vol. 51, No.1, pp. 1-17 Srivastava, Ravi (2011), “Internal Migration in India: An Overview of Its Features, Trends and Policy Challenges”, Paper presneted at UNESCO-UNICEF National Workshop on Internal Migration and Human Development in India, 6-7 December 2011, New Delhi. Stark, Odded (1991), The Migration of Labour, Basil Blackwell, Cambridge, MA. Suryanarayana, M.H (2008): “What Is Exclusive about ‘Inclusive Growth’?” Economic and Political Weekly, Vol. 43, No. 43, pp. 91-101. Suryanarayana, M.H (2011): “Expert Group on Poverty: Confusion worse Confounded”, Economic and Political Weekly, Vol. XLVI, No. 46, pp. 36-39.

139 Suryanarayana, M.H. (2010), “Nutritional Norms for Poverty: Issues and Implications”, Concept paper prepared for the Expert Group to Review the Methodology for Estimation of Poverty, Planning Commission, New Delhi. Suryanarayana, M.H. (2016): “Marginalization &Food Insecurity in Uttar Pradesh: A Positive Perspective”, Paper presented at the seminar on Growth, Disparities and Inclusive Development in Uttar Pradesh: Experiences, Challenges and Policy Options, organized by the Giri Institute of Development Studies, Lucknow, 23-25 September 2016. Thorat, Sukhadeo and Dubey, Amaresh (2012), “Has Growth been Socially Inclusive during 1993-94/2009-10”, Economic and Political Weekly, Vol. 47, No. 10, pp. Trivedi, Anupam (2012), “Ghost Villages”, Hindustan Times, 21 January, Rudrapryag. Umar (2012), “The Ghost Villages of Uttarakhand”, Tehelka Magazine, Vol. 9, Issue 27, 7 June. UNESCO (2013), Social Inclusion of Internal Migrants in India, United Nations Educational, Scientific and Cultural Organization, June, New Delhi. Walton, H.G. (1910), British Garhwal: A Gazetteer, Reprint 1994, Indus Publishing Company, New Delhi. World Bank (2012), India: Uttarakhand Economic Assessment, Report No. 62494-IN, Poverty Reduction and Economic Management Unit, South Asia Region, New Delhi. World Bank (2011), “Employability and Skill Set of Newly Graduated Engineers in India”, Andreas Blom Hiroshi Saeki, Policy Research Working Paper 5640, The World bank, South Asia Region Education Team, New Delhi, April.

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