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Productivity and Technical Change: The Case of Taiwan

Author

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  • R. Fare

    (Southern Illinois Univ. at Carbondale)

  • Shawna Grosskopf

    (Southern Illinois Univ. at Carbondale)

  • W-F Lee

Abstract

"Technical change" and "technical efficiency change" are two key factors to productivity growth that are associated with different sources; hence, different policies may be required to address them. Therefore, it is important to decompose productivity growth into these two components. Technical change may be further decomposed into output- and input-biases. These biases have impacts on factor income distribution and hence policy implications associated with them. It is therefore important to identify the output- and input-bias components of technical change and measure them empirically. In this paper, we explore the above issues for the disaggregate cases of 18 Taiwan manufacturing industries at the 2-digit level grouping during the period 1978-92. To pursue our goal we decompose the Malmquist total factor productivity (TFP) index into two components: technical change and technical efficiency change. Here, however, we further decompose the technical change component; in particular we define output bias, input bias and a magnitude term. In addition, we are able to identify the directions of the input biases.

Suggested Citation

  • R. Fare & Shawna Grosskopf & W-F Lee, 1995. "Productivity and Technical Change: The Case of Taiwan," GE, Growth, Math methods 9509001, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpge:9509001
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    1. Binswanger, Hans P, 1974. "The Measurement of Technical Change Biases with Many Factors of Production," American Economic Review, American Economic Association, vol. 64(6), pages 964-976, December.
    2. Diewert, W E, 1980. "Capital and the Theory of Productivity Measurement," American Economic Review, American Economic Association, vol. 70(2), pages 260-267, May.
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    Cited by:

    1. Charles-Henri DI MARIA & Chiara PERONI, 2012. "Unit labor cost and productivity recovery under non neutral technical change," LEO Working Papers / DR LEO 1734, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    2. Yuxin Meng & Lu Liu & Zhenlong Xu & Wenwen Gong & Guanpeng Yan, 2022. "Research on the Heterogeneity of Green Biased Technology Progress in Chinese Industries: Decomposition Index Analysis Based on the Slacks-based measure integrating," Journal of Economic Analysis, Anser Press, vol. 1(2), pages 17-34, December.
    3. Maria Bonilla-Musoles & Leandro Garcia-Menendez & Ma Luisa Marti-Selva, 2007. "Efficiency in the eurobond market: application of nonparametric techniques," Applied Financial Economics, Taylor & Francis Journals, vol. 17(6), pages 431-444.
    4. repec:ind:nipfwp:22 is not listed on IDEAS
    5. Nguepi Tsafack Elvis & Hua Cheng & Buregeya Ingabire Providence, 2022. "The Illustrative Understanding on the Informal Sector and Its Influence in Firm Productivity in Sub-Saharan Africa (SSA): Evidence from Cameroon," Sustainability, MDPI, vol. 14(15), pages 1-22, August.
    6. Galanopoulos, Konstantinos & Lindberg, Emma & Surry, Yves R. & Mattas, Konstadinos, 2006. "Agricultural productivity growth in the Mediterranean and tests of convergence among countries," 98th Seminar, June 29-July 2, 2006, Chania, Crete, Greece 10101, European Association of Agricultural Economists.
    7. Magdalena Kapelko & Alfons Oude Lansink, 2015. "An international comparison of productivity change in the textile and clothing industry: a bootstrapped Malmquist index approach," Empirical Economics, Springer, vol. 48(4), pages 1499-1523, June.
    8. Ky‐hyang Yuhn & Seung R. Park, 2010. "Information Technology, Organizational Transformation and Productivity Growth: An Examination of the Brynjolfsson–Hitt Proposition," Asian Economic Journal, East Asian Economic Association, vol. 24(1), pages 87-108, March.
    9. Xiyue Zhang & Fangcheng Sun & Huaizu Wang & Yi Qu, 2020. "Green Biased Technical Change in Terms of Industrial Water Resources in China’s Yangtze River Economic Belt," IJERPH, MDPI, vol. 17(8), pages 1-20, April.
    10. Oh Sang Kwon & Hyunok Lee, 2004. "Productivity improvement in Korean rice farming: parametric and non‐parametric analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 48(2), pages 323-346, June.
    11. Yan, Siqi & Peng, Jianchao & Wu, Qun, 2020. "Exploring the non-linear effects of city size on urban industrial land use efficiency: A spatial econometric analysis of cities in eastern China," Land Use Policy, Elsevier, vol. 99(C).
    12. repec:npf:wpaper:22 is not listed on IDEAS
    13. Diogo Cunha Ferreira & Rui Cunha Marques, 2016. "Malmquist and Hicks–Moorsteen Productivity Indexes for Clusters Performance Evaluation," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(05), pages 1015-1053, September.
    14. Kumar, Surender, 2004. "Decomposition of total factor productivity growth: A regional analysis of Indian industrial manufacturing growth," Working Papers 04/22, National Institute of Public Finance and Policy.
    15. Po-Chi Chen & Ming-Miin Yu, 2014. "Total factor productivity growth and directions of technical change bias: evidence from 99 OECD and non-OECD countries," Annals of Operations Research, Springer, vol. 214(1), pages 143-165, March.
    16. Ming‐Miin Yu, 2008. "Productivity Change and the Effects of the Enhancement of the Mass Transportation Programme on the Bus Transit System in Taiwan," Transport Reviews, Taylor & Francis Journals, vol. 28(5), pages 573-592, January.
    17. Shuai Zhang & Xiaoman Zhao & Changwei Yuan & Xiu Wang, 2020. "Technological Bias and Its Influencing Factors in Sustainable Development of China’s Transportation," Sustainability, MDPI, vol. 12(14), pages 1-26, July.
    18. Charles-Henri Dimaria, 2012. "Cannon Was Right But Incomplete: Frankel Was A Neglected Early Contribution To Growth Theory," Working Papers halshs-00826519, HAL.
    19. Sun, Chia-Hung, 2004. "Decomposing productivity growth in Taiwan's manufacturing, 1981-1999," Journal of Asian Economics, Elsevier, vol. 15(4), pages 759-776, August.
    20. Kortelainen, Mika, 2008. "Dynamic environmental performance analysis: A Malmquist index approach," Ecological Economics, Elsevier, vol. 64(4), pages 701-715, February.
    21. Wong, Lawrence, 2001. "Measuring technological change in the U.S. motor carrier industry," Research in Transportation Economics, Elsevier, vol. 6(1), pages 25-54, January.
    22. Zhao, Wei & Liu, Ling & Zhao, Ting, 2010. "The contribution of outward direct investment to productivity changes within China, 1991-2007," Journal of International Management, Elsevier, vol. 16(2), pages 121-130, June.
    23. Briec, Walter & Peypoch, Nicolas & Ratsimbanierana, Hermann, 2011. "Productivity growth and biased technological change in hydroelectric dams," Energy Economics, Elsevier, vol. 33(5), pages 853-858, September.
    24. Yang, Chih-Hai, 2006. "Is innovation the story of Taiwan's economic growth?," Journal of Asian Economics, Elsevier, vol. 17(5), pages 867-878, November.

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    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • D5 - Microeconomics - - General Equilibrium and Disequilibrium
    • D9 - Microeconomics - - Micro-Based Behavioral Economics

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