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Industry Clusters, Economy of Agglomeration and Competitiveness In Indonesia

Omar Rashid
By Omar Rashid
9 years ago
Presentation by Yudo Anggoro on: Industry Clusters, Economy of Agglomeration and Competitiveness In Indonesia

Mal, Commenda

Sustainability

International Trade

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  1. Industry Clusters , Economy of Agglomeration, and Competitiveness in Indonesia Yudo Anggoro, Ph.D Scientific Oration February 23, 2016
  2. Positive Sides of Indonesian Economy  Growth 6.3 % (2011), 6.1 % (2012), 5.8% (2013), 5.2% (2014), 4.7% (2015), and 5.1% (2016)  Debt to GDP ratio : 23 %  GDP $ 850 Billion (15th in the world)  Youth population  Middle class is increasing (74 Million in 2014)
  4. Challenges of Indonesian Economy Disparity of development Lack of Infrastructure Overly concentrated development and population in Java Lacking of human capital 43% of the population earns less than $2 a day
  5. Regional GDP 1 .20 National 1.00 Java & Bali 0.80 Sumatera 0.60 Kalimantan 0.40 Sulawesi 0.20 Nusa Tenggara, Maluku & Papua 0.00 2004 2005 2006 2007 2008 2009 2010 2011 2012
  6. 21 .31% 5.80 % 7.31% 57.49% 5.50 % 2.60%
  7. Masterplan for Acceleration and Expansion of Indonesia Economic Development 2011-2025 • Development of six economic corridors, each corridor focuses on its potentials. • Each economic corridor will be supported by several industry clusters
  8. The Economic Corridors
  9. Goals of the Masterplan Parameter Before MP3EI (2011) After MP3EI (2025) Population (Million) 244.2 273.1 GDP (US$ Billion) 845.7 4,500 GDP/capita (US$) 3,509 15,500 Economic growth (percent) 6.3 6.4 to 7.5 Inflation (percent) 5.9 3
  10. The Questions • Does Indonesia have the right ingredients for its industry clusters to develop economic competitiveness? • What strategies are needed to create a competitive environment among domestic firms in Indonesia’s industry clusters?
  11. The Economy of Agglomeration Marshall ’s Industrial Agglomeration (1920) Perroux’s Growth Pole theory (1955) Porter’s Industry Clusters (1990) • Industrial agglomeration reduces transportation costs-the cost of moving goods, people, and ideas (Marshall 1920). • Growth pole theory (Perroux 1955): growth is not uniform over an entire region, but instead takes place around a specific pole.
  12. Why Cluster ? • Clusters (Porter 1990):  Concentration of interconnected firms  In a specific geographic location  Not only compete but also cooperate • Benefits:      Lowering transportation cost. Increasing productivity Building dialogue and collaboration Fostering innovation Providing labor market pool
  13. The Diamond Model
  14. Industrialization in Indonesia
  15. Industrialization in Indonesia Year Agriculture (%) Industry (%) Non-Oil Manufacturing (%) Services (%) 1965 1970 1980 1990 1997 1998 2002 2003 52.4 45.5 30.7 20.1 14.9 16.9 15.4 15.2 14.1 21.7 30.9 37.9 43.2 42.8 45.5 45.1 n.a. n.a. 9.9 17.3 22.4 22.4 24.6 24.8 33.5 32.8 38.4 42 42 40.3 39.1 39.7
  16. Characteristics of Indonesia ’s Export • Resource-based export • The scale of Indonesia’s manufactured export products is less than it is in neighboring countries. Malaysia has 2.5 times larger Thailand has 1.5 percent higher • Less value-added products, i.e: electronics
  17. Indonesia ’s Export vs Import Year 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 Export (Billion US $) 176.29 182.55 190.03 203.49 157.77 116.51 137.02 114.10 100.79 85.66 71.58 61.06 Import (Billion US $) 178.18 186.63 191.69 177.44 135.66 96.83 129.19 74.47 61.06 57.70 46.52 32.55
  18. Four Phases of Industrialization in Indonesia • Rapid industrialization period, following the major political and economic changes of 1966-1967.  Import Substitution (IS), pro market, open economic policy • The 1970s: a shift towards a more diversified industrial structure.  Shift to Export Orientation (EO), labor intensive industries, oil boom, government intervention through pro national policies. • The 1980s: a significant industrial exporter.  Decline of oil boom era, more open policies • 1998-present: post-Asian crisis era  Liberalization, reduced role of government
  19. Composition of Industries in Clusters • Automotive clusters • Logistics clusters : 54.8 % : 4.8 %
  21. Research Methodology
  22. Qualitative Analysis • In-depth Interview  11 government officials (Minister, Vice Minister, Director General)  11 business practitioners (Owner, CEO, General Manager)  8 Academics
  23. Quantitative Analysis • Location Quotients
  24. Model 2: Cluster GDP in 2010 (Logistics) Log of Cluster GDP 2010 HDI Logistics Factor Supply Poverty Economic Change Competitiveness Log of Unemployment Herfindahl Index Ports Population Density Log of RGDP Log of University Enrollment Productivity Income per Capita Employment in Logistics Constant Number of Observation R-squared Adjusted R-squared Coefficient 0.086*** 1.596*** -0.011** 0.098** 0.047*** -0.047 -0.023** 2.98** -0.00001*** -0.079 -0.033 -0.0003 -0.002 -0.00002 3.13 497 0.0792 0.0525 Std. Error 0.013 2.542 0.006 0.001 0.0003 0.0523 0.246 0.113 0.00001 0.2531 0.055 0.003 0.006 0.003 1.99 t 3.13 -3.63 2.10 1.73 -2.87 -0.91 0.75 1.40 -0.90 -0.31 -0.60 -0.79 -0.05 -0.39 1.57 P>ItI 0.002 0.000 0.036 0.044 0.004 0.363 0.036 0.033 0.019 0.753 0.548 0.428 0.958 0.697 0.018 VIF 2 1.03 1.86 1.13 1.11 1.04 1.25 1.23 1.25 1.02 1.03 1.05 1.24 1.04 Beta 0.193 -0.161 0.125 0.080 -0.132 -0.040 0.036 0.067 -0.044 -0.013 -0.026 -0.035 -0.019 -0.002
  25. Model 3 : Change in Cluster Size (Logistics) Change in Log Cluster Size Log of RGDP 2000 Coefficient Std. Error -0.2*** 0.0420 HDI 0.04** 1.6030*** -0.012** 0.001** 0.0006** -0.0776** -0.0417** 0.1020 -0.0003 -0.0406 -0.0272 -0.0003 0.0002 2.2740 497 0.3707 0.3524 Logistics Factor Supply Poverty Economic Change Competitiveness Log of Unemployment Herfindahl Index Ports Population Density Log of RGDP Log of University Enrollment Productivity Employment in Logistics Constant Number of Observation R-squared Adjusted R-squared t -16.22 P>ItI 0.000 VIF 1.08 Beta -0.60 0.0120 0.5270 0.0061 0.0010 0.0004 0.0490 0.2301 0.1077 0.0006 0.0491 0.0529 0.0004 2.20 -3.04 2.24 1.42 -1.85 -1.46 0.18 0.95 0.53 -0.83 -0.51 0.98 0.028 0.003 0.026 0.035 0.033 0.045 0.026 0.344 0.593 0.409 0.608 0.327 1.96 1.02 1.86 1.18 1.13 1.05 1.24 1.23 1.03 1.02 1.03 1.03 0.11 -0.11 0.10 0.05 -0.07 -0.05 0.00 0.03 -0.01 -0.03 -0.01 -0.03 0.0004 1.0692 0.60 2.13 0.548 1.05 0.034 -0.03
  26. Model 4 : Competitive Shift (Logistics) Competitive Shift Share of Population University Enrollment Employment Rate Economic Change Logistics Share Workforce Ports Employment in Logistics Log of Income per Capita Log of Population Herfindahl Index Log of Regional GDP Constant Number of Observation R-squared Adjusted R-squared Coefficient 7.6060** 0.3764 13.48** 3.8449*** 4.7535*** 5.1179*** 10.0532 -0.0726 18.8920** -8.9659 -7.4180*** -7.7706 830.1237 489 0.1535 0.1321 Std. Error 1.0240 0.4696 58.6010 0.1343 1.5823 0.0492 13.8998 0.0474 9.1228 6.3071 30.1738 6.4035 264.9060 T 2.54 0.80 -2.33 6.29 -3.00 2.81 0.72 -1.53 2.07 -1.42 -0.25 -1.21 3.13 P>ItI 0.011 0.423 0.020 0.000 0.003 0.005 0.470 0.127 0.039 0.156 0.006 0.226 0.002 VIF 1.18 1.29 1.1 1.16 1.17 1.02 1.27 1.04 1.26 1.08 1.3 1.04 Beta 0.1163 0.0385 -0.1095 0.2863 -0.1391 0.1204 0.0349 -0.0655 0.0999 0.0999 -0.0120 -0.0522
  27. Synthesizing Model for Logistics Clusters Firm Strategy , Structure, and Rivalry  Herfindahl Index  Competitiveness Demand Condition • • • • • Factor Condition Human Development Index Poverty Rate Economic Change Income per Capita Unemployment • • • • Related and Supporting Industries  Industry Factor Supply  Cluster Share Regional GDP Ports Population Density Workforce
  28. Synthesizing Model for Automotive Clusters Firm Strategy , Structure, and Rivalry  Herfindahl Index Demand Condition • • Factor Condition Income per Capita Poverty Rate Related and Supporting Industries  Cluster Employment • Ports • Productivity • University Enrollment
  29. Measuring Competitiveness in Java
  30. Competitiveness in Logistics Clusters Model Model 1 Model 2 Model 3 Model 4 Actual Predicted Absolute Competitiveness Competitiveness Difference Dependent Variable (Million IDR) (Million IDR) (%) Cluster GDP 2000 16,622,600.40 13,662,016.20 17.81 Cluster GDP 2010 30,150,425.84 27,154,523.45 9.94 Change in Cluster Size 1.81 2.12 17.13 Competitive Shift 950,219.84 972,932.57 2.39
  31. Ingredients of Competitive Logistic Clusters Population Share Employment Rate Economic Change Logistics Share Workforce Income per Capita Herfindahl Index 0 .74 1.00 1.30 0.98 0.59 0.96 1.15 Clusters in Java 1.27 0.98 1.15 1.00 0.27 1.37 0.97 University Enrollment 0.97 1.15 Excess HDI Factor Supply Poverty Rate Competitive Shift Population Density Productivity 1.03 1.22 0.87 0.33 10.14 1.08 1.05 0.55 0.75 0.27 1.47 1.55 Excess Lack Excess Lack Excess Excess Unemployment Rate 1.18 1.25 Lack Cluster Employment 0.61 0.36 Lack Labor Supply 1.07 1.29 Excess Number of University 0.52 0.54 Excess Cluster Ingredients Indonesia Excess/Lack of Ingredients Excess Lack Lack Excess Lack Excess Excess
  32. Competitiveness in Automotive Clusters Model Dependent Variable Actual (Million IDR) Model 1 Model 2 Model 3 Model 4 GDP 2000 GDP 2010 Change in Cluster Size Competitive Shift 4,146,124.57 5,988,908.76 1.48 -788,596.27 Prediction (Million IDR) 3,451,294.72 5,318,383.70 1.96 -469,878.69 Absolute Difference (%) 16.76 11.20 32.60 40.42
  33. Ingredients of Successful Automotive Clusters Cluster Ingredients HDI Poverty Rate Herfindahl Index Productivity Cluster Employment Income per Capita Population Share Employment Rate Economic Change Automotive Share Workforce University Enrollment Population Share Employment Rate Economic Change Logistics Share Workforce Income per Capita Herfindahl Index University Enrollment Indonesia 1 .00 1.05 0.92 1.16 2.11 1.04 0.77 1.02 1.23 1.58 1.74 1.08 0.74 1.00 1.30 0.98 0.59 0.96 1.15 0.97 Clusters in Java 1.05 0.60 0.93 2.80 0.85 7.07 1.48 0.96 1.03 2.08 0.83 0.82 1.27 0.98 1.15 1.00 0.27 1.37 0.97 1.15 Excess/Lack of Ingredients Excess Excess Lack Excess Lack Excess Excess Lack Lack Excess Lack Lack Excess Lack Lack Excess Lack Excess Excess Excess
  34. SWOT Analysis
  35. SWOT for Logistics Clusters Strengths Weaknesses Opportunities Threats Strong commitment from government to build infrastructure Supply of human capital and labor resources Stable political , economic, and social condition Poor infrastructure Government's bureaucratic structure Remote location Lack of connectivity Centralized development in Java Corruption and bribery practice Inefficiency in logistics practice Rise of the middle class Youth Population Economic growth provides room for business expansion New port development in some cities ASEAN Economic Community 2015 provides new opportunity to play in the region An emerging digital and technology-driven nation Intense competition with other countries in the region (Singapore, Malaysia, Thailand) Technological advancement is faster than the ability to adopt it
  36. SWOT for Automotive Clusters Strengths Weaknesses High economic growth Stable car prices Strong local demand The biggest car market in the region Increasing automotive exports Low labor cost Poor infrastructure High transportation cost Automotive industries are dominated by foreign-based companies (Japanese cars comprise 95.2 percent of the market) No proactive industrial development policy Not much progress on localization Opportunities New middle class creates demand for local low cost cars Environment concern drives demand for eco cars Small car segment is the opportunity for local automotive industries Threats Production base for small and midsize MPVs for regional market Intense rivalry with other car producer nations in the region (mostly with Thailand) The slowdown of global economy might weaken market Increase in dependence of imported parts from Thailand
  37. Conclusions and Policy Recommendations
  38. Research Question 1 : What are the ingredients of successful Clusters? • Porter (1990) postulates four factors of successful clusters: (1) demand conditions, (2) factor conditions, (3) firm strategy, structure and rivalry, and (4) related and supporting industries. • Sheffi (2012) addresses two important factors for logistics clusters: location and human capital.
  39. Research Question 2 : Does Indonesia have the ingredients? • Some important factors are missing: infrastructure, human capital quality, and government support. • Industries need to be retained: textile, leather and footware in West Java, paper and printing in East Java. • Important factors for logistics clusters: Herfindahl index, competitive shift, human development index, poverty rate, economic change, income per capita, unemployment, factor supply, cluster share, regional GDP, ports, population density, and workforce
  40. Research Question 2 (Continued) • Important factors for automotive clusters: Herfindahl index, income per capita, poverty rate, cluster employment, ports, productivity, and university enrollment • For logistics clusters, Java has some ingredients that are better than overall Indonesia: Population share, logistics share, income per capita, herfindahl index, university enrollment, human development index, poverty rate, population density, productivity, labor supply, and the number of university.
  41. Research Question 2 (Continued) • For automotive clusters, Java has some ingredients that are better than overall Indonesia: Human development index, poverty rate, productivity, income per capita, population share, automotive share, factor supply, competitive shift, labor supply, and number of university.
  42. Research Question 3 : What are the strategies to create competitive clusters in Indonesia? • Develop more infrastructures • Focus on human capital development and workforce development • Create more entrepreneurs • Spread developments outside Java
  43. Policy Recommendations • • • • Policy on infrastructure development Entrepreneurship policy Intergovernmental relation policy Local content policy
  44. What Next • The need of studies of policy and competitiveness at SBM ITB • Center of Policy and Competitiveness • Goals: • Providing
  45. • Declining Competitiveness • Dutch Subsidy
  46. Thank You
  47. List of Respondents Government Officials Business Practitioners Academics Minister of Economics CEO of General Electric Indonesia Professor of Economics at University of Indonesia Minister of State-Owned Enterprise CEO of Indonesia Port Corporation Professor of Economic Development at University of Indonesia Minister of Trade CEO of Jababeka Group Professor of Logistic and Supply Chain at Bandung Institute of Technology Minister of Industry Chairman of Matsushita Global Professor of Production Systems at Bandung Institute of Technology Vice Minister of Economics Commissioner of Indonesia Infrastructure Guarantee Fund (IIGF) Professor of Industrial Policy at Bandung Institute of Technology Vice Minister of Finance Technical Director of Toyota Motor Indonesia Professor of Entrepreneurship at Bandung Institute of Technology Chairman of the Indonesia Businessmen Association Chairman of the Indonesian Industrial Area Association Professor of Transportation at Bandung Institute of Technology Professor of Sustainable Development at Bandung Institute of Technology Vice Minister of National Planning Head of Statistics Division at Ministry of Industry Head of Industrial Area Department at Ministry of Industry Assistant to the Head of President's Delivery Unit Economic Assistant to the Head of President's Delivery Unit Director of Karawang International Industrial City General Manager of Karawang International Industrial City Owner of a large textile industry in Bandung, West Java
  48. Model 1 : Cluster GDP in 2000 (Automotive) Log of Cluster GDP 2000 HDI Automotive Factor Supply Poverty Economic Change Competitiveness Unemployment Coefficient Std. Error t P>ItI VIF Beta 0.025 2.621 -0.022** 0.002 0.0004 -0.000008 0.022 2.114 0.012 0.001 0.0009 0.000057 1.16 1.24 1.82 1.14 0.46 1.43 0.248 0.216 0.040 0.255 0.650 0.155 1.65 1.20 1.71 1.35 1.21 1.17 0.093 0.085 0.150 0.083 0.031 0.097 Herfindahl Index -0.41** 0.287 -2.45 0.015 1.24 -0.171 Ports 0.731** 0.134 0.98 0.050 1.11 0.064 Population Density -0.0004 0.001 -0.43 0.669 1.12 -0.028 -0.022 0.065 -0.34 0.727 1.11 -0.022 Log of University Enrollment 0.0679** 0.074 -0.91 0.032 1.46 -0.069 Productivity 0.096*** 0.001 -2.64 0.009 5.42 -0.386 Employment in Automotive -0.002** 0.0009 -2.22 0.027 1.03 -0.142 0.19** 3.165 232 0.1393 0.0837 0.015 1.70 1.84 1.86 0.028 0.004 5.12 0.261 Log of RGDP Income per capita Constant Number of Observation R-squared Adjusted R-squared
  49. Model 2 : Cluster GDP in 2010 (Automotive) Log of Cluster GDP 2010 HDI Automotive Factor Supply Poverty Economic Change Competitiveness Unemployment Herfindahl Index Ports Population Density Log of RGDP Log of University Enrollment Productivity Employment in Automotive Income per capita Constant Number of Observation R-squared Coefficient Std. Error t P>ItI VIF Beta 0.096*** 4.28 -0.012** 0.001 0.00013 0.000006 0.018 2.66 0.011 0.001 0.0009 0.000005 0.52 1.61 1.70 0.98 0.14 1.06 0.003 0.109 0.031 0.330 0.890 0.292 1.27 1.22 1.50 1.28 1.18 1.23 0.036 0.112 0.131 0.069 0.009 0.073 -0.01** 0.285 -2.16 0.032 1.22 -0.149 0.436*** 0.00003 0.079 0.132 0.00001 0.322 1.02 1.54 0.25 0.009 0.125 0.807 1.07 1.59 1.09 0.066 0.122 0.016 -0.052 0.071 -0.73 0.464 1.36 -0.053 0.0018** 0.0017 -2.16 0.032 1.90 -0.450 -0.0012** 0.0009 -1.93 0.046 1.03 -0.123 0.037** 3.619 232 0.1373 0.016 2.557 1.49 1.42 0.037 0.008 1.33 0.287
  50. Model 3 : Change in Cluster Size (Automotive) Change in Log Cluster Size Log of RGDP 2000 HDI Automotive Factor Supply Poverty Economic Change Competitiveness Number of Unemployed Herfindahl Index Ports Population Density Log of RGDP Log of University Enrollment Productivity Employment in Automotive Income Constant Number of Observation R-squared Coefficient Std. Error T P>ItI VIF Beta -0.292*** 0.0197 2.5308 -0.097*** 0.0016 0.0003 -0.0009*** -0.59** 0.1337 -0.0005 -0.0159 0.0646 0.0224 2.0969 0.0120 0.0018 0.0009 0.0005 0.2881 0.0009 0.0011 0.0653 -13.29 0.88 1.21 1.65 0.93 0.41 1.26 -2.16 1.00 -0.43 -0.24 0.000 0.378 0.229 0.001 0.353 0.685 0.008 0.032 0.317 0.665 0.808 1.08 1.67 1.20 1.72 1.36 1.21 1.18 1.26 1.11 1.12 1.12 -0.6794 0.0563 0.0651 0.1064 0.0535 0.0220 0.0675 -0.1193 0.0520 -0.0227 -0.0127 -0.0525 0.0740 0.71 0.479 1.47 -0.0424 0.05** 0.0019 -2.51 0.013 5.45 -0.2883 -0.009** 0.0009 -2.16 0.032 1.04 -0.1082 0.001** 2.8866 232 0.4754 0.0150 1.6908 1.67 1.71 0.042 0.039 5.15 0.1871
  51. Model 4 : Competitive Shift (Automotive) Competitive Shift Share of Population University Enrollment Employment Rate Economic Change Automotive Share Workforce Ports Employment in Automotive Log of Income per Capita Log of Population Herfindahl Index Log of Regional GDP Constant Number of Observation R-squared Adjusted R-squared Coefficient Std. Error 0.039** 0.8448 0.064** 0.2837 46.6890 57.9440 0.5938*** 0.1347 -0.1575 0.4144 -0.0056 0.0688 0.3860** 10.0207 -28.656** 0.0672 0.3837** 7.3811 2.9306** 4.8356 -16.5937** 21.2379 -6.4255 4.8153 -790.0497 255.4169 227 0.1476 0.0998 t -1.65 1.21 0.81 4.41 -0.38 -0.08 0.14 0.98 -0.73 0.61 -0.31 -1.33 -0.31 P>ItI 0.036 0.028 0.421 0.000 0.704 0.935 0.030 0.030 0.047 0.045 0.016 0.183 0.027 VIF 1.18 1.29 1.1 1.16 1.17 1.02 1.27 1.04 1.26 1.08 1.3 1.04 Beta -0.1118 0.0938 0.0565 0.3226 -0.0264 -0.0055 0.0092 0.0625 -0.0543 0.0398 -0.0209 -0.0881
  52. Policy Recommendations : For Government • Streamline the bureaucracy. • Focus on improving human capital. • Incentives for industries. • Joint collaboration with private sectors to finance the development of infrastructures.
  53. Policy Recommendations : For Industries • Building constructive dialogue with government and universities. • Making collaboration with universities for joint research and labor supply. • For local industries, focus to serve on the 3rd layer of industry.