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33 Provinces and Six Regions of Indonesia Session 2a: 2017 Annual Update of ACI Competitiveness Ranking and Simulation Studies: 33 Provinces and Six Regions of Indonesia 2017 Asia Economic Forum on “The One-Belt One-Road Initiative: Impact and Implications” Seminar 1: Competitiveness, Trade, Liveability and Productivity in ASEAN Economies Jointly Organised by The World Bank Group & Asia Competitiveness Institute (ACI) at Lee Kuan Yew School of Public Policy (LKYSPP), National University of Singapore (NUS) 28th August 2017 Presenters: Dr. Mulya AMRI Research Fellow & Deputy Director (Research), ACI-LKYSPP-NUS Nursyahida Binte AHMAD Research Assistant, ACI-LKYSPP-NUS Diamanta Vania LAVI Research Assistant, ACI-LKYSPP-NUS Associate Professor Tan Khee Giap Co-Director, ACI-LKYSPP, NUS In 2016 and 2017, ACI was ranked 13th globally, 2nd in Asia and 1st in Singapore amongst 90 think tanks worldwide under the “Best University Affiliated Think Tank” category 1 by the Think Tanks and Civil Societies Program at the University of Pennsylvania, USA. Presentation Outline 1. Motivation and Objectives 2. Research Framework and Methodology 3. Empirical Findings 4. Conclusion and Policy Implications 2 1. MOTIVATION & OBJECTIVES 3 ACI’s Research on Indonesia 4 Motivation: Indonesia’s Economic Potential (1/3) As the largest economy in Southeast Asia, Indonesia contributes 41% of the region’s population and 36% of its GDP. The global commodity price bust affected Indonesia, leading to a steady decline in GDP growth from 6.2% (2011) to 4.8% (2015). Solid macroeconomic foundation is helping Indonesia bring growth back up to 5.0% (2016), but the country is still behind its neighbours in terms of exporting and attracting investments. GDP (2016) Population (2016) Current US$ Thailand Singapore Vietnam 11% 12% 15% Malaysia Myanmar 11% Philippines 8% Malaysia Cambodia Myanmar 12% Vietnam 5% 2% 3% 8% Philippines Other Other 16% 4% 5% Thailand Lao PDR 16% Cambodia 1% 1% Indonesia Indonesia Singapore Lao PDR 41% 36% 1% 1% Brunei Darussalam… Brunei Darussalam… Source: World Bank, World Development Indicators Source: World Bank, World Development Indicators 5 Motivation: Indonesia’s Economic Potential (2/3) ACI’s Annual Competitiveness Analysis of ASEAN-10 countries found that Indonesia’s Overall Competitiveness vis-à-vis its neighbours increased between 2005 and 2010, but has deteriorated until 2013. However, Indonesia’s competitiveness increased again in 2014, mostly due to stabilising conditions and declining performance of Thailand. 2.50 2.00 Singapore 1.50 1.00 Malaysia (2nd) 0.50 Brunei (3rd) Thailand (4th) 0.00 Indonesia (5th) Philippines (6th) -0.50 Vietnam (7th) Overall Overall Competitiveness Score Cambodia (8th) -1.00 Laos (9th) -1.50 Myanmar (10th) -2.00 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 6 Source: Asia Competitiveness Institute Note: Value in the parenthesis denotes the 2017competitiveness ranking amongst ASEAN-10. Motivation: Indonesia’s Economic Potential (3/3) Other international analyses also highlighted a rise followed by decline in Indonesia’s recent competitiveness level. But again recently, Indonesia showed signs of improving competitiveness. IMD World Competitiveness Ranking WEF Global Competitiveness Index (selected ASEAN countries) (selected ASEAN countries) 2012-13 2013-14 2014-15 2015-16 2016-17 2012 2013 2014 2015 2016 2017 0 0 Singapore, 2 Singapore, 3 10 10 20 Malaysia, 25 20 30 34 Thailand, 34 Malaysia, 24 37 40 38 Thailand, 27 Indonesia, 41 30 50 50 Philippines, 57 37 40 39 Philippines, 41 60 Vietnam, 60 42 42 Indonesia, 42 70 48 50 80 Source: WEF Source: IMD 7 Research Objectives: To track the competitiveness landscape across Indonesia’s provinces and regions. Identify strengths and weaknesses and suggest development strategies based on simulation studies and empirical results. Highlight challenges faced by each province/region that require unique solution. To spur intellectual debates among key stakeholders to lift Indonesia’s competitiveness as a whole. To further attract collaboration with strategic partners and strengthen efforts to raise competitiveness in Indonesia through more outward-oriented policies (trade, FDI for technology transfer, etc). 8 2. RESEARCH FRAMEWORK & METHODOLOGY 9 ACI’s Competitiveness Framework Overall Competitiveness • 4 Environments • 12 Sub-environments • 100 Indicators • Aggregation uses equal weightage ACI adopts a comprehensive approach to competitiveness, taking into account different factors that collectively shape the ability of an economy to achieve substantial and inclusive economic development over a sustained period of time. Calculation of Standardised Score 푶풓풊품풊풏풂풍 푽풂풍풖풆 − 푴풆풂풏 푺풕풂풏풅풂풓풅풊풔풆풅 풗풂풍풖풆 = 푺풕풂풏풅풂풓풅 푫풆풗풊풂풕풊풐풏 . 0 (zero) = same as national average . - (negative) = below national average . + (positive) = above national average The further away from zero, the further from national average 10 Source: Asia Competitiveness Institute Data Sources Secondary Data (76%) in 2014: Central Statistical Bureau (BPS) World Bank Indonesia Database for Policy and Economic Research (INDO-DAPOER) Primary Data Bank Indonesia (24 indicators) Ministry of Health Etc. Secondary Data (76 indicators) Primary Data (24%) in 2016: ACI’s perception survey in 33 provinces (in collaboration with Indonesian Employers’ Association (APINDO), provincial government agencies, and local universities). Sampling methodology: Purposive Respondents Number Sampling. APINDO members 803 Measurement: Likert Scale of 1 – 9, Provincial academics 775 where 9 is the most favourable response and 1 is the least. Provincial government 757 The surveys were conducted using Total 2335 an electronic response system, Average per province 71 where questions were presented on a computer projector and participants entered their answers using keypads Source: Asia Competitiveness Institute or “clickers”. 11 What-if Competitiveness Simulation 1. Sort the indicators for each economy . Identifies the potential for each economy to No Indicator Score improve their competitiveness ranking. 1 Indicator A Highest for . Helps each economy to identify priority economy areas for intervention, as well as hints for 2 Indicator B Higher score further research required. 3 Indicator C . Improvement in competitiveness scores 4 Indicator D matter more than rankings; even if rankings remain unchanged, scores do improve. 5 Indicator E … 96 Indicator V 97 Indicator W 2. 3. 4. 98 Indicator X Identify Raise their Recalculate 99 Indicator Y Lower score top 20% values to ranking with 100 Indicator Z Lowest for weakest average if scores for other economy indicators lower than economies average remaining constant 13 Robustness Check of ACI Competitiveness Scores by Shapley Weightage (1/3) Shapley Value Ranking Algorithm • Shapley value is widely applied in cooperative game theory, which measures the marginal contribution of an agent. In our context, the agent could be indicators, sub-environments and environments. • The formula for Shapley value is: 푺 ! 푵 − 푺 − ퟏ ! Ф 풗 = 풗 푺 ∪ 풊 − 풗 푺 푵! 푺⊆푵\{풊 • With different marginal contribution to the overall competitiveness ranking, different weights should be assigned to indicators, sub-environments and environments. • We would like to propose an objective weighting method based on Shapley value – the “Bottom-Up” Approach. 13 Robustness Check of ACI Competitiveness Scores by Shapley Weightage (2/3) Shapley Value Theoretical Foundation • Formally, let 푣퐼 be the characteristic function of the indicators, where 푣퐼: 2퐼 → ℝ. Then for each indicator 푖 ∈ 퐼, 푣퐼(푖) ∶ ℝ퐸 → ℝ , which reflects that the value of indicator 푖 is derived from 푋푒푖 for all 푒 ∈ 퐸. As we involve large number of indicators in our case studies, for the ease of numerical computation, we simply define that 퐼 퐸 푣 (푖) = 푒=1 |푆푉푒푖| . • We further assume the Additivity of the characteristic function 푣퐼, i.e. 푣퐼(푖 ∪ 푗) = 푣퐼 (푖) + 푣퐼(푗) for any indicator 푖 , 푗 ∈ 퐼. • With all these defined, we are able to proceed with the computation of the Shapley 퐼 value Ф푖 of indicator 푖 ∈ 퐼. 핀 ! 퐼− 핀 −1 ! Ф퐼 = (푣퐼 핀 ∪ 푖 − 푣퐼(핀)) for all 푖 ∈ 퐼 푖 핀⊆퐼\{푖 퐼! 핀 ! 퐼 − 핀 − 1 ! 핀 ! 퐼 − 핀 − 1 ! = (푣퐼 핀 ∪ 푖 − 푣퐼(핀)) = 푣퐼 푖 = 푣퐼 푖 퐼! 퐼! 핀⊆퐼\{푖 핀⊆퐼\{푖 퐼 • Then the indicator weight 푤푖 based on Shapley value is simply Ф퐼 푣퐼(푖) 푤퐼 = 푖 = . 푖 퐼 퐼 퐼 퐼 14 푗=1 Ф푗 푗=1 푣 (푗) Robustness Check of ACI Competitiveness Scores by Shapley Weightage (3/3) Shapley Value Simplified: “Bottom-Up” Approach 1 We start from the lowest level of analysis (indicators) and identify the inequality of the units being measured (economies and sub-national economies). This is called the “Shapley Value”, which is computed from the standardised score of each indicator. 2 Subsequently, the Shapley Value is used to calculate Shapley Weight, where more weights are assigned to those indicators with higher Shapley value. 3 The weights of Sub-environments are computed in “bottom-up” manner according to both standardised scores and Shapley Weights of indicators under that particular sub- environment. 4 Finally, the weights of Environments and Overall Index are computed in a similar way. 15 3. EMPIRICAL FINDINGS 16 Indonesia Provincial Competitiveness Ranking & Score Overall Competitiveness Rank Score Rank Score Province Province 2014 2015 2016 2017 2017 2014 2015 2016 2017 2017 1 1 1 1 DKI Jakarta 3.459 14 27 28 18 Jambi -0.296 2 2 2 2 East Java 1.723 28 27 21 19 Gorontalo -0.298 East Kalimantan (inc. 3 3 5 3 1.303 19 15 24 20 North Sumatra -0.304 North Kalimantan) 18 19 17 21 West Kalimantan -0.308 4 5 3 4 Central Java
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