#1Industry Clusters, Economy of Agglomeration, and Competitiveness in Indonesia Yudo Anggoro, Ph.D Scientific Oration February 23, 2016#2Positive 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)#3Mimorsummit MID CLASS 2014 IMEDIA ONLINE RETAIL SUMMIT In Indonesia, middle class is defined using Asian Development Bank criteria which is population with daily per capita expenditure between $ 2-20 per day) 2014 74 Million 2020 141 Million This rapid increase of middle class leads to the growth of consuming class Indonesians are consistently found to be some of the most confident consumers in the world Source: Lowyinterpreter.org, 2014#4Challenges 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 $2 a day#51.20 Regional GDP 1.00 0.80 0.60 0.40 0.20 -National -Java & Bali -Sumatera -Kalimantan -Sulawesi Nusa Tenggara, Maluku & 0.00 Papua 2004 2005 2006 2007 2008 2009 2010 2011 2012#621.31% 5.80 % 2.60% 7.31% 57.49% 5.50 %#7Masterplan for Acceleration and Expansion of Indonesia Economic Development 2011-2025 • Development of six economic corridors, each corridor focuses on its potentials. • Each economic corridor will be supported by several industry clusters#8Ace Pusat Ekonomi Mega Pusat Ekonomi The Economic Corridors Pangkal P 2 5 6#9Goals of the Masterplan Parameter Population (Million) Before MP3EI (2011) After MP3EI (2025) GDP (US$ Billion) GDP/capita (US$) Economic growth (percent) Inflation (percent) 244.2 273.1 845.7 4,500 3,509 15,500 6.3 6.4 to 7.5 5.9 3#10The 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?#11The Economy of Agglomeration Marshall's Industrial Perroux's Growth Agglomeration (1920) 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.#12Why 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#13The Diamond Model Context for Firm Strategy and Rivalry Factor (Input) Conditions • A local context that encourages appropriate forms of investment and sustained upgrading ⚫ Vigorous competition among locally based rivals Demand Conditions - Factor (input) quantity and cost natural resources - human resources - capital resources - physical infrastructure administrative infrastructure information infrastructure scientific and technological infrastructure • Factor quality • Factor specialization Related and Supporting Industries Presence of capable, locally based suppliers • Presence of competitive related industries ⚫ Sophisticated and demanding local customer(s) • Customers' needs that anticipate those elsewhere • Unusual local demand in specialized segments that can be served globally#14Industrialization in Indonesia#15Industrialization in Indonesia Agriculture Industry Non-Oil Manufacturing Services Year (%) (%) (%) (%) 1965 52.4 14.1 n.a. 33.5 1970 45.5 21.7 n.a. 32.8 1980 30.7 30.9 9.9 38.4 1990 20.1 37.9 17.3 42 1997 14.9 43.2 22.4 42 1998 16.9 42.8 22.4 40.3 2002 15.4 45.5 24.6 39.1 2003 15.2 45.1 24.8 39.7#16Characteristics 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#17Indonesia's Export vs Import Year Export (Billion US $) Import (Billion US $) 2014 176.29 178.18 2013 182.55 186.63 2012 190.03 191.69 2011 203.49 177.44 2010 157.77 135.66 2009 116.51 96.83 2008 137.02 129.19 2007 114.10 74.47 2006 100.79 61.06 2005 85.66 57.70 2004 71.58 46.52 2003 61.06 32.55#18• Four Phases of Industrialization in Indonesia Rapid industrialization period, following the major political and economic changes of 1966-1967. Import Substitution (IS), pro market, open economic policy The 1970s: a shift towards a more diversified industrial structure. ➤ Shift to Export Orientation (EO), labor intensive industries, oil boom, government intervention through pro national policies. The 1980s: a significant industrial exporter. Decline of oil boom era, more open policies 1998-present: post-Asian crisis era ➤ Liberalization, reduced role of government#19Composition of Industries in Clusters Manufacturing 2.6% Chemicals Electronics 1.0% Packaging 0.1% Pharmaceutical. 0.7% 0.1% Oil & Gas Logistics/ -0.3% Metal Machinery 0.6% Textiles 3.5% Plastics Steel-Related 9.5% Warehouse 4.8% 0.9% Consumer Goods Food & 2.3% Beverage 4.2% 1.4% Building Material 4.9% Developer Others 4.4% 3.9% • • Automotive clusters Logistics clusters : 54.8% : 4.8% Automotive 54.8%#20$/20' container 3,000 Cost to ship 1 x 20' container from Jakarta to... Km 2,000 1,000 0 10,000 8,000 6,000 4,000 2,000 Distance Shipping cost 0 Singapore Hong Bangkok Shanghai Tokyo Hamburg Padang Medan BanjarmasinMakassar Ambon Kong#21Research Methodology#22Qualitative Analysis • In-depth Interview ➤ 11 government officials (Minister, Vice Minister, Director General) ➤ 11 business practitioners (Owner, CEO, General Manager) ➤ 8 Academics#23Quantitative Analysis • Location Quotients LQ = Eir Ein / Er' En • Shift-share Analysis National Share ➤ Industry Mix Competitive Shift#24Regional Shift (from Shift-Share) Positive High Location Quotient Low Strong export orientation; Good performer; Suggest strategies to maintain competitiveness, retain industry Possible emerging industry; Study factors that nurture sector and promote expansion; possible import substitution sector Negative Lagging, declining or constrained industry, worthy of retention because of size, suggest opportunities for modernization, improved competitiveness or productivity Limited prospects; poor performer; opportunities for future growth are low.#25Quantitative Analysis (2) • 4 OLS regression model 1. Cluster GDP in 2000 as DV 2. Cluster GDP in 2010 as DV 3. Change in cluster size (2000-2010) as DV 4. Competitive Shift from Shift-share as DV#26• . . • Firm Strategy, Structure, and Rivalry Herfindahl Index Competitiveness Demand Condition Income per capita Human Development Index Poverty Rate Unemployment Economic Change Related and Supporting Industries Employment in industry clusters Factor supply in industry clusters Factor Condition . Ports • University Enrollment • Productivity • Population Density • Regional GDP#27• • Data Source Regional GDP, 2000-2010 Automotive and Logistics Clusters in the Java economic region. • Unit of Analysis: City#28Industry Scope Automotive Clusters: 1. Textile, leather, and footware 2. Paper and printing 3. Fertilizer, chemical, and rubber 4. Basic, metal, iron, and steel 5. Transportation, machinery, and tools 6. Other products Classification is based on the International Standard Industrial Classification by the United Nations#29• Industry Scope (2) Logistics Clusters 1. Railroad 2. Road and highway 3. Water transportation 4. River and lake transportation 5. Air transportation 6. Transportation services Classification is based on the International Standard Industrial Classification by the United Nations#30Results of Qualitative Analysis#31Findings: The Masterplan • Good in theory, but poor in implementation. "There are no extra efforts done by government to implement the masterplan. | mean, the top rank government officials who formulated the plan might understand the urgency of it. However, those who are in the lower rank did not have clear idea on how to translate the plan into action programs" (Chairman of the Indonesian Businessman Association) • Another government's lip service • Misinterpretation in viewing the master plan, should focus on improving human capital.#32Findings: Problems in clusters No coordination among: ➤ National government officials National and local governments Government and industries . Bad quality of infrastructures. "The main problem that hinders the development of clusters in this country is the lack of infrastructure. Clusters need sufficient roads, highways, easy access to ports and airports, railroads, and many more" (Minister of Finance) Problems with the society: land clearance, workers' strike, industries & workers relation.#33Finding: Strategies to Develop Competitive Clusters Building communication among governments "Other essence of this masterplan is what we call as debottlenecking. It means that government should streamline the regulation and bureaucracy that may adapt to change. The quality of bureaucracy in this country is very poor. Many public projects are stopped because nobody has the sense of responsibility" (Minister of Economics) • Workforce development Developing infrastructure Involving the private sector to finance. infrastructure projects#34Results of Quantitative Analysis: LQ and Shift-share Analysis#35Screening Matrix for Logistics Clusters in Java Location Quotient Regional Shift High WT Jakarta RH Jakarta Positive TS Jakarta AT Yogyakarta RH Banten RL Banten RR West Java RR Central Java RH Central Java RR Yogyakarta Negative RH Yogyakarta AT East Java TS East Java AT Banten TS Banten AT West Java WT Central Java RL Central Java WT East Java RL Jakarta AT Jakarta RH West Java WT West Java RL West Java TS West Java AT Central Java TS Central Java TS Yogyakarta Low#36LQ and Shift-share for Logistics Clusters LQ LQ Industry Sectors 2000 2010 % of change National Share (Million IDR) Competitive Industry Mix Shift (Million IDR) (Million IDR) Railroad 1.45 1.25 -0.14 0.74 -0.62 -0.0005 Road and 0.97 0.86 -0.11 15.14 -3.51 -1.44 Highway Water 0.86 0.79 -0.08 3.33 -1.76 -0.14 Transportation River and Lake 0.13 0.11 -0.15 0.14 -0.10 -0.0003 Transportation Air 0.66 0.62 -0.05 1.5 11.34 -0.26 Transportation Transportation 1.08 1.01 -0.07 5.32 -0.07 -0.29 Service#37Matrix for Automotive Clusters in Java Regional Shift Location Quotient High Low Positive TLF West Java TMT West Java OP West Java TLF Central Java PP East Java FCR Banten PP Jakarta OP Jakarta FCR Central Java BIS Central Java TMT Central Java OP Central Java TLF Jakarta Negative TMT Jakarta FCR West Java FCR Jakarta OP Yogyakarta BIS Jakarta OP East Java TLF Banten PP Banten BIS Banten PP West Java BIS West Java PP Central Java TLF Yogyakarta#38LQ and Shift-share for Automotive Clusters Industry Sectors LQ LQ 2000 2010 Change % of National Share (Million IDR) Competitive Industry Mix Shift (Million IDR) (Million IDR) Textile, Leather, 1.60 1.51 -0.06 26.12 -20.39 -0.23 and Footware Paper and Printing 1.40 1.30 -0.08 9.37 2.62 -0.69 Fertilizer, Chemical, 1.33 1.23 -0.07 19.50 -4.78 -0.74 and Rubber Basic Metal, Iron, 1.40 0.99 -0.29 8.29 -5.11 0.41 and Steel Transportation, 1.68 1.48 -0.12 40.65 54.80 -10.42 Machinery & Tools Other Products 1.61 1.37 -0.15 3.16 -1.50 -0.20#39Results for Quantitative Analysis: . • Model 1 • Model 2 • Model 3 • Model 4 OLS Regression Analysis : Cluster GDP in 2000 as DV : Cluster GDP in 2010 as DV : Change in cluster GDP as DV : Competitive shift as DV#40Model 1: Cluster GDP in 2000 (Logistics) Log of Cluster GDP 2000 Coefficient Std. Error t P>Itl VIF Beta HDI 0.047*** Logistics Factor Supply 1.770*** Poverty Economic Change Competitiveness Log of Unemployment -0.004** 0.01*** 0.6*** -0.072 Herfindahl Index -0.036** Ports 0.895** Population Density -0.0004*** 0.013 3.05 0.002 1.92 0.186 0.556 -3.18 0.002 1.02 -0.141 0.006 2.29 0.022 1.86 0.137 0.001 1.64 0.001 1.18 0.078 0.0003 -2.78 0.006 1.11 -0.129 0.052 -1.38 0.168 1.03 -0.061 0.244 0.80 0.023 1.23 0.039 0.113 1.73 0.045 1.21 0.083 0.0005 -0.83 0.007 1.03 -0.036 Log of RGDP -0.050 0.051 -0.98 0.329 1.01 -0.043 Log of University Enrollment -0.036 0.056 -0.64 0.523 1.03 -0.028 Productivity -0.0004 Employment in Logistics -0.0001 Income per Capita 0.0026 0.0003 -1.07 0.285 1.03 0.0004 -0.04 0.965 1.04 0.005 -0.47 0.640 -0.047 -0.001 1.18 -0.022 Constant 3.133 1.121 2.79 0.005 Number of Observation 497 R-squared 0.0718 Adjusted R-squared 0.0449#41Model 2: Cluster GDP in 2010 (Logistics) Log of Cluster GDP 2010 Coefficient Std. Error t P>Itl VIF Beta HDI 0.086*** 0.013 3.13 0.002 2 0.193 Logistics Factor Supply 1.596** **** 2.542 -3.63 0.000 1.03 -0.161 Poverty -0.011** 0.006 2.10 0.036 1.86 0.125 Economic Change 0.098** 0.001 1.73 0.044 1.13 0.080 Competitiveness 0.047*** Log of Unemployment -0.047 Herfindahl Index -0.023** Ports 2.98** Population Density -0.00001*** 0.00001 Log of RGDP -0.079 0.2531 0.0523 -0.91 0.246 0.75 0.113 1.40 -0.90 -0.31 0.0003 -2.87 0.004 1.11 0.363 1.04 0.036 1.25 0.036 0.033 1.23 0.067 0.019 1.25 -0.044 -0.132 -0.040 Log of University Enrollment -0.033 0.055 0.753 1.02 -0.60 0.548 1.03 -0.013 -0.026 Productivity -0.0003 0.003 -0.79 0.428 1.05 -0.035 Income per Capita -0.002 0.006 -0.05 0.958 1.24 -0.019 Employment in Logistics -0.00002 0.003 -0.39 0.697 1.04 -0.002 Constant 3.13 1.99 1.57 0.018 Number of Observation 497 R-squared 0.0792 Adjusted R-squared 0.0525#42Coefficient -0.2*** 0.04** Model 3: Change in Cluster Size (Logistics) Change in Log Cluster Size Log of RGDP 2000 HDI Std. Error t P>Itl VIF B Beta 0.0420 -16.22 0.000 1.08 -0.60 0.0120 2.20 0.028 1.96 0.11 Logistics Factor Supply 1.6030* *** 0.5270 -3.04 0.003 1.02 -0.11 Poverty -0.012** Economic Change 0.001* ** Competitiveness 0.0006** Log of Unemployment -0.0776** Herfindahl Index -0.0417** Ports 0.1020 Population Density -0.0003 Log of RGDP -0.0406 Log of University Enrollment -0.0272 Productivity -0.0003 0.0061 0.0010 1.42 0.035 1.18 0.05 0.0004 -1.85 0.033 1.13 -0.07 0.0490 -1.46 0.045 1.05 -0.05 0.2301 0.18 0.026 1.24 0.00 0.1077 0.95 0.344 1.23 0.03 0.0006 0.0491 -0.83 0.409 1.02 -0.03 0.0529 -0.51 0.608 1.03 -0.01 0.0004 0.98 0.327 1.03 -0.03 2.24 0.026 1.86 0.10 0.53 0.593 1.03 -0.01 Employment in Logistics 0.0002 0.0004 0.60 0.548 1.05 -0.03 Constant 2.2740 1.0692 2.13 0.034 Number of Observation 497 R-squared 0.3707 Adjusted R-squared 0.3524#43Model 4: Competitive Shift (Logistics) Competitive Shift Share of Population University Enrollment Employment Rate Economic Change Logistics Share Workforce Coefficient 7.6060** 0.3764 13.48** 3.8449*** 4.7535** 5.1179*** Std. Error T 1.0240 2.54 0.011 1.18 0.4696 0.80 0.423 1.29 58.6010 -2.33 0.020 1.1 P>Itl VIF Beta 0.1163 0.0385 -0.1095 **** 0.1343 6.29 0.000 1.16 1.5823 -3.00 0.003 1.17 0.2863 -0.1391 Ports Employment in Logistics 10.0532 -0.0726 Log of Income per Capita 18.8920** Log of Population -8.9659 Herfindahl Index -7.4180*** Log of Regional GDP -7.7706 Constant 830.1237 0.0492 2.81 13.8998 0.72 0.470 1.27 0.0474 -1.53 9.1228 2.07 6.3071 -1.42 30.1738 -0.25 0.006 6.4035 -1.21 264.9060 3.13 0.002 0.005 1.02 0.1204 0.0349 0.127 1.04 -0.0655 0.039 1.26 0.0999 0.156 1.08 0.0999 1.3 -0.0120 0.226 1.04 -0.0522 Number of Observation 489 R-squared 0.1535 Adjusted R-squared 0.1321#44Synthesizing Model for Logistics Clusters • Demand Condition Human Development Index • Poverty Rate • . . Economic Change Income per Capita Unemployment Firm Strategy, Structure, and Rivalry Herfindahl Index Competitiveness Related and Supporting Industries Industry Factor Supply Cluster Share • Factor Condition Regional GDP Ports Population Density Workforce#45Synthesizing Model for Automotive Clusters Firm Strategy, Structure, and Rivalry • Demand Condition Income per Capita Poverty Rate Herfindahl Index Factor Condition Related and Supporting Industries • Ports Productivity University Enrollment Cluster Employment#46Measuring Competitiveness in Java#47Competitiveness in Logistics Clusters Actual Model Dependent Variable Competitiveness Predicted Competitiveness Absolute Difference (Million IDR) (Million IDR) (%) Model 1 Cluster GDP 2000 16,622,600.40 13,662,016.20 17.81 Model 2 Cluster GDP 2010 30,150,425.84 27,154,523.45 9.94 Model 3 Change in Cluster Size 1.81 2.12 17.13 Model 4 Competitive Shift 950,219.84 972,932.57 2.39#48Ingredients of Competitive Logistic Clusters Clusters Cluster Ingredients Indonesia Excess/Lack of Ingredients in Java Population Share 0.74 1.27 Excess Employment Rate 1.00 0.98 Lack Economic Change 1.30 1.15 Lack Logistics Share 0.98 1.00 Excess Workforce 0.59 0.27 Lack Income per Capita 0.96 1.37 Excess Herfindahl Index 1.15 0.97 Excess University Enrollment 0.97 1.15 Excess HDI 1.03 1.05 Excess Factor Supply 1.22 0.55 Lack Poverty Rate 0.87 0.75 Excess Competitive Shift 0.33 0.27 Lack Population Density 10.14 1.47 Excess Productivity 1.08 1.55 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#49Competitiveness in Automotive Clusters Absolute Actual Prediction Model Dependent Variable Difference (Million IDR) (Million IDR) (%) Model 1 GDP 2000 4,146,124.57 3,451,294.72 16.76 Model 2 GDP 2010 5,988,908.76 5,318,383.70 11.20 Model 3 Change in Cluster Size 1.48 1.96 32.60 Model 4 Competitive Shift -788,596.27 -469,878.69 40.42#50Ingredients of Successful Automotive Clusters Clusters Excess/Lack of Cluster Ingredients Indonesia in Java Ingredients HDI 1.00 1.05 Excess Poverty Rate 1.05 0.60 Excess Herfindahl Index 0.92 0.93 Lack Productivity 1.16 2.80 Excess Cluster Employment 2.11 0.85 Lack Income per Capita 1.04 7.07 Excess Population Share 0.77 1.48 Excess Employment Rate 1.02 0.96 Lack Economic Change 1.23 1.03 Lack Automotive Share 1.58 2.08 Excess Workforce 1.74 0.83 Lack University Enrollment 1.08 0.82 Lack Population Share 0.74 1.27 Excess Employment Rate 1.00 0.98 Lack Economic Change 1.30 1.15 Lack Logistics Share 0.98 1.00 Excess Workforce 0.59 0.27 Lack Income per Capita 0.96 1.37 Excess Herfindahl Index 1.15 0.97 Excess University Enrollment 0.97 1.15 Excess#51SWOT Analysis#52SWOT 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#53SWOT for Automotive Clusters Strengths Weaknesses Opportunities Threats 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 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 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#54Conclusions and Policy Recommendations#55● 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.#56Research 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#57Research 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.#58● 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.#59• 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#60• • • Policy Recommendations Policy on infrastructure development Entrepreneurship policy Intergovernmental relation policy Local content policy#61What Next The need of studies of policy and competitiveness at SBM ITB • Center of Policy and Competitiveness • Goals: • Providing#62• Declining Competitiveness Dutch Subsidy#63Thank You#64List of Respondents Government Officials Minister of Economics Business Practitioners CEO of General Electric Indonesia Minister of State-Owned Enterprise CEO of Indonesia Port Corporation Minister of Trade Minister of Industry Vice Minister of Economics Vice Minister of Finance 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 CEO of Jababeka Group Chairman of Matsushita Global Commissioner of Indonesia Infrastructure Guarantee Fund (IIGF) Technical Director of Toyota Motor Indonesia Chairman of the Indonesia Businessmen Association Chairman of the Indonesian Industrial Area Association Director of Karawang International Industrial City General Manager of Karawang International Industrial City Owner of a large textile industry in Bandung, West Java Academics Professor of Economics at University of Indonesia Professor of Economic Development at University of Indonesia Professor of Logistic and Supply Chain at Bandung Institute of Technology Professor of Production Systems at Bandung Institute of Technology Professor of Industrial Policy at Bandung Institute of Technology Professor of Entrepreneurship at Bandung Institute of Technology Professor of Transportation at Bandung Institute of Technology Professor of Sustainable Development at Bandung Institute of Technology#65Model 1: Cluster GDP in 2000 (Automotive) Log of Cluster GDP 2000 HDI Automotive Factor Supply Poverty Economic Change Coefficient Std. Error t P>Itl VIF Beta 0.025 0.022 1.16 0.248 1.65 0.093 2.621 2.114 1.24 0.216 1.20 0.085 -0.022** 0.012 1.82 0.040 1.71 0.150 0.002 0.001 1.14 0.255 1.35 0.083 Competitiveness Unemployment 0.0004 0.0009 0.46 0.650 1.21 0.031 -0.000008 0.000057 1.43 0.155 1.17 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 Log of RGDP -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 Income per capita 0.19** 0.015 1.84 0.028 5.12 0.261 Constant 3.165 1.70 1.86 0.004 Number of Observation 232 R-squared 0.1393 Adjusted R-squared 0.0837#66Model 2: Cluster GDP in 2010 (Automotive) Log of Cluster GDP 2010 Coefficient Std. Error t P>Itl VIF Beta HDI 0.096** *** 0.018 0.52 0.003 1.27 0.036 Automotive Factor Supply 4.28 2.66 1.61 0.109 1.22 0.112 Poverty -0.012** 0.011 1.70 0.031 1.50 0.131 Economic Change 0.001 0.001 0.98 0.330 1.28 0.069 Competitiveness 0.00013 0.0009 0.14 0.890 1.18 0.009 Unemployment 0.000006 0.000005 1.06 0.292 1.23 0.073 Herfindahl Index -0.01** 0.285 -2.16 0.032 1.22 -0.149 Ports 0.436*** 0.132 1.02 0.009 1.07 0.066 Population Density 0.00003 0.00001 1.54 0.125 1.59 0.122 Log of RGDP 0.079 0.322 0.25 0.807 1.09 0.016 Log of University Enrollment -0.052 0.071 -0.73 0.464 1.36 -0.053 Productivity 0.0018** 0.0017 -2.16 0.032 1.90 -0.450 Employment in Automotive -0.0012** 0.0009 -1.93 0.046 1.03 -0.123 Income per capita 0.037** 0.016 1.49 0.037 1.33 0.287 Constant 3.619 2.557 1.42 0.008 Number of Observation 232 R-squared 0.1373#67Model 3: Change in Cluster Size (Automotive) Change in Log Cluster Size Coefficient Std. Error T P>Itl VIF Beta Log of RGDP 2000 -0.292*** 0.0646 -13.29 0.000 1.08 -0.6794 HDI 0.0197 0.0224 0.88 0.378 1.67 0.0563 Automotive Factor Supply 2.5308 2.0969 1.21 0.229 1.20 0.0651 Poverty -0.097*** 0.0120 1.65 0.001 1.72 0.1064 Economic Change 0.0016 0.0018 0.93 0.353 1.36 0.0535 Competitiveness 0.0003 0.0009 0.41 0.685 1.21 0.0220 Number of Unemployed -0.0009*** 0.0005 1.26 0.008 1.18 0.0675 Herfindahl Index -0.59** 0.2881 -2.16 0.032 1.26 -0.1193 Ports 0.1337 0.0009 1.00 0.317 1.11 0.0520 Population Density -0.0005 0.0011 -0.43 0.665 1.12 -0.0227 Log of RGDP -0.0159 0.0653 -0.24 0.808 1.12 -0.0127 Log of University Enrollment -0.0525 0.0740 0.71 0.479 1.47 -0.0424 Productivity 0.05** 0.0019 -2.51 0.013 5.45 -0.2883 Employment in Automotive -0.009** 0.0009 -2.16 0.032 1.04 -0.1082 Income 0.001** 0.0150 1.67 0.042 5.15 0.1871 Constant 2.8866 1.6908 1.71 0.039 Number of Observation 232 R-squared 0.4754 Adjusted R-squared 04390#68Model 4: Competitive Shift (Automotive) Competitive Shift Share of Population University Enrollment Employment Rate Coefficient Std. Error t P>Itl VIF Beta 0.039** 0.8448 -1.65 0.036 1.18 -0.1118 0.064** 0.2837 1.21 0.028 1.29 0.0938 46.6890 57.9440 0.81 0.421 1.1 0.0565 Economic Change 0.5938** *** 0.1347 4.41 0.000 1.16 0.3226 Automotive Share -0.1575 0.4144 -0.38 0.704 1.17 -0.0264 Workforce -0.0056 0.0688 -0.08 0.935 1.02 -0.0055 Ports 0.3860** 10.0207 0.14 0.030 1.27 0.0092 Employment in Automotive -28.656** 0.0672 0.98 0.030 1.04 0.0625 Log of Income per Capita 0.3837** 7.3811 -0.73 0.047 1.26 -0.0543 Log of Population 2.9306** 4.8356 0.61 0.045 1.08 0.0398 Herfindahl Index -16.5937** 21.2379 -0.31 0.016 1.3 -0.0209 Log of Regional GDP -6.4255 4.8153 -1.33 0.183 1.04 -0.0881 Constant -790.0497 255.4169 -0.31 0.027 Number of Observation 227 R-squared 0.1476 Adjusted R-squared 0.0998#69Policy 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.#70Policy 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.