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Total Factor Productivity of Korean Manufacturing Industries: Comparison of Competing Models with Firm-Level Data


  • Dong-hyun Oh
  • Almas Heshmati
  • Hans Loof

    () (Technology Management, Economics and Policy Program(TEMEP), Seoul National University)


This paper presents the parametric estimation of the rates of technical change and total factor productivity (TFP) growth of 7,462 Korean manufacturing firms for the period 1987 to 2007. Two alternative formulations of technical change measured by the time trend and the general index approaches are estimated with panel data models assuming flexible functional forms. Several extensions of each approach are also onsidered and their benefits and limitations are discussed. In addition to making estimates of the TFP growth and its decomposition, the paper compares the parametric TFP growth measure with the non-parametric Solow residual serving as a benchmark. Several hypotheses related to technology level, firm sizes, industrial sectors, skill biased technological change and macroeconomic and industrial policies are tested to explain the growth patterns and heterogeneity in technical change, input biases and TFP growth rates. Using second regression analysis, the paper explores the determinants of TFP growth and their policy implications.

Suggested Citation

  • Dong-hyun Oh & Almas Heshmati & Hans Loof, 2009. "Total Factor Productivity of Korean Manufacturing Industries: Comparison of Competing Models with Firm-Level Data," TEMEP Discussion Papers 200922, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Nov 2009.
  • Handle: RePEc:snv:dp2009:200922

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    References listed on IDEAS

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    Cited by:

    1. Edquist, Harald & Henrekson, Magnus, 2016. "Do R&D and ICT Affect Total Factor Productivity Growth Differently?," Working Paper Series 1108, Research Institute of Industrial Economics, revised 28 Nov 2016.
    2. Khayyat, Nabaz T. & Lee, Jongsu & Lee, Jeong-Dong, 2014. "How ICT Investment Influences Energy Demand in South Korea and Japan?," MPRA Paper 55454, University Library of Munich, Germany.
    3. Subal Kumbhakar & Kai Sun, 2012. "Estimation of TFP growth: a semiparametric smooth coefficient approach," Empirical Economics, Springer, vol. 43(1), pages 1-24, August.

    More about this item


    Total factor productivity; technical change; manufacturing industry; determinants of growth;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General

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