An Application of Convergence Theory to Japan’s Post-WWII “Economic Miracle”. Proceeding of the 7th Asia Pacific Industrial Engineering and Management Systems Conference (AIPEMS2000), Taipei. Understanding the Concept of Productivity. Measurement of Technical Efficiency: A-brief Survey on Parametric and Non-Parametric Techniques. Microeconomic Theory Basic Principle and Extensions. Cross-country convergence in energy and electricity consumption, 1971–2007. Analisis Efisiensi Teknis, Alokatif dan Ekonomi Produksi Nanas di Kabupaten Subang, Provinsi Jawa Barat. Revisiting World Energy Intensity Convergence for Regional Differences. Energy Demand in Industry: What Factors Are Important? New York: Springer Science & Business Media Dordrecht. Examine the convergence in Per Capita Energy Consumption in China with Breakpoints. A Window-DEA Based Efficiency Evaluation of the Public Hospital Sector in Greece during the 5 Year Economic Crisis. Journal of the Royal Statistical Society, 120(3), 253-290.įlokou, Angeliki, Aletras, V., & Niakas, D. The Measurement of Productive Efficiency. Procedia Social and Behavioral Sciences, 24(1), 206-218.įarrell, M. Measuring the Technical Efficiency of Telecommunication Sector within Global Crisis: Comparison of G8 Countries and Turkey. Queensland: Springer Science & Business Media.ĭiskaya, F., Emir, S., & Orhan, N. An Introduction to Efficiency and Productivity Analysis. The Classical Approach to Convergence Analysis. Journal of Productivity Analysis, 15(1), 159-183.īarro, R. Scale Efficiency and Productivity Change. Surabaya: Badan Pusat Stastistik Provinsi Jawa Timur.īalk, B. Energy Economics, 62, 404-410.īadan Pusat Statistik Provinsi Jawa Timur.
Convergence in energy consumption per capita across the US states, 1970–2013: An exploration through selected parametric and non-parametric methods. Energy Economics, 62, 396-403.īadan Pusat Statistik. Conditional convergence in Australia's energy consumption at the sector level.
Jakarta: Badan Pusat Statistik.īadan Pusat Statistik. Klasifikasi Baku Lapangan Usaha Indonesia 2015. Energy Efficiency, 5(4), 583-597.īadan Pusat Statistik. OECD Energy Intensity: Measures, Trends, and convergence. Klasifikasi Baku Lapangan Usaha indonesia. Journal of Economic History, 46(2), 385-406.īadan Pusat Statistik. Catching Up, Forgoing Ahead, and Falling Behind. The GMM estimation results show that factors that significantly affect the efficiency of manufacturing industries are energy intensity, capital-labor ratio, capital intensity, and industrial share.Ībramovitz, M. On the other hand, the results of testing four convergence models show different results, sigma, gamma, and stochastic convergence indicating the convergence of manufacturing industry efficiency, while conditional beta convergence testing shows an indication of the divergence in manufacturing industry efficiency. Technological progress at 54 percent each year is a major contributor to the increase in manufacturing industry productivity by 55 percent during 2007-2015. The results of the score of technical efficiency analysis show that the manufacturing industry in East Java is still in an inefficient condition with the electrical equipment industry being the highest efficiency score sector, while the furniture industry is the most inefficient sector. Conditional beta convergence analysis (β), sigma convergence (σ), gamma convergence (γ), and stochastic convergence is used to analyze efficiency convergence. While the calculation of productivity changes in this study uses the Malmquist Index. To calculate the value of technical efficiency, this study uses Data Envelopment Analysis (DEA) with a bootstrapping approach with 2000 times the number of iterations. There are 24 manufacturing industry sectors that were observed in this study.
The level of efficiency that approaches the frontier signifies convergence, while divergence indicates that the level of efficiency that has not approached the frontier. On the other hand, this research also aims to determine the direction of the efficiency of the manufacturing industry sub-sector and the factors that influence the level of efficiency of the manufacturing industry. This study aims to analyze technical efficiency and to find out the main contributors to the productivity of the manufacturing industry in East Java, which increased in 2007-2015.
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