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Growth Accounting for Some Selected Developing, Newly Industrialized and Developed Nations from 1966-2000: A Data Envelopment Analysis

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  • Somesh Kumar Mathur

    (Jamia Millia Islamia)

Abstract

We work out technical efficiency levels of 29 countries consisting of some selected South Asian, East Asian and EU countries using data envelopment analysis. Luxembourg has an efficiency score of one(most efficient) in all the years .Netherlands also has an efficiency score of one in 1966,1971,1976 and 1981.Japan,UK,Belgium,Ireland,Indonesia,Spain and Germany has an efficiency score of one in at least one of the years from 1966 to 2000.In the year 2000 though mean efficiency levels(without including life expectancy as input) of South Asian countries is higher than the European Union Countries and East Asian countries. Japan has the highest average efficiency followed by Hong Kong in the East Asian region in the period 1966-2000. We also decompose labor productivity growth into components attributable to technological changes (shifts in the overall production frontier), technological catch up or efficiency changes(movement towards or away from the frontier),capital accumulation(movement along the frontier) and human capital accumulation( proxied by life expectancy).The overall production frontier is constructed using deterministic methods requiring no specification of functional form for the technology nor any assumption about market structure or the absence of market imperfections. Growth accounting results tend to convey that for the East Asian and the South Asian countries efficiency changes(technological catch up) have contributed the most, while for the European countries it is the technical changes which has contributed more to labour productivity changes between 1966-2000. We also analyze the evolution of cross country distribution for the 29 countries included in our sample using Kernel densities. It seems that there are other factors like trade openness,quality of governments,population rate of growth, savings rate, corruption perception indices, rule of law index, social capital and trust variables, formal and informal rules governing the society, among others, rather than the ones that are included below for the growth accounting exercise which may be responsible for productivity accounting on point to point basis. For all the seven periods(point to point basis) we see a major role played by technological changes and efficiency changes together to account for the current period counterfactual distributions and for the bimodal distribution in year 2000, and for the period 1966-2000(not point to point basis –an excercise done similar to Kumar and Russell(2002)) we find technical changes and its combination with other tripartite and quadripartite changes jointly account for the bimodal distribution in year 2000.However, from this growth accounting exercise, we do find that there is convergence in statistical terms of efficiency changes and human capital accumulation across countries of the EU, South Asian and East Asian regions.

Suggested Citation

  • Somesh Kumar Mathur, 2005. "Growth Accounting for Some Selected Developing, Newly Industrialized and Developed Nations from 1966-2000: A Data Envelopment Analysis," GE, Growth, Math methods 0510009, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpge:0510009
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    References listed on IDEAS

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    1. GIJBELS, Irène & MAMMEN, Enno & PARK, Byeong U. & SIMAR, Léopold, 1997. "On estimation of monotone and concave frontier functions," LIDAM Discussion Papers CORE 1997031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Afriat, Sidney N, 1972. "Efficiency Estimation of Production Function," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 13(3), pages 568-598, October.
    3. Oded Galor, 1996. "Convergence?: Inferences from Theoretical Models," Working Papers 96-3, Brown University, Department of Economics.
    4. Kneip, Alois & Park, Byeong U. & Simar, Léopold, 1998. "A Note On The Convergence Of Nonparametric Dea Estimators For Production Efficiency Scores," Econometric Theory, Cambridge University Press, vol. 14(6), pages 783-793, December.
    5. Fare, Rolf & Shawna Grosskopf & Mary Norris & Zhongyang Zhang, 1994. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries," American Economic Review, American Economic Association, vol. 84(1), pages 66-83, March.
    6. Galor, Oded, 1996. "Convergence? Inferences from Theoretical Models," Economic Journal, Royal Economic Society, vol. 106(437), pages 1056-1069, July.
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    More about this item

    Keywords

    : Data envelopment analysis; growth accounting; technical efficiency; efficiency change; technological change; capital accumulation; human capital accumulation; kernel smoothing; cross country labor productivity distribution and counterfactual distributions;
    All these keywords.

    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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