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A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies

Author

Listed:
  • Osiewalski, J.
  • Koop, G.
  • Steel, M.F.J.

    (Tilburg University, Center For Economic Research)

Abstract

This paper uses Bayesian stochastic frontier methods to measure the productivity gap between Poland and Western countries that existed before the beginning of the main Polish economic reform. Using data for 20 Western economies, Poland and Yugoslavia (1980-1990) we estimate a translog stochastic frontier and make inference about individual efficiencies. Following the methodology proposed in our earlier work, we also decompose output growth into technical, efficiency and input changes and examine patterns of growth in the period under consideration.

Suggested Citation

  • Osiewalski, J. & Koop, G. & Steel, M.F.J., 1997. "A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies," Discussion Paper 1997-85, Tilburg University, Center for Economic Research.
    • Handle: RePEc:tiu:tiucen:70bc4936-7304-4e87-910c-be186b88a885
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    References listed on IDEAS

    as
    1. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian efficiency analysis through individual effects: Hospital cost frontiers," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 77-105.
    2. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    3. van den Broeck, Julien & Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1994. "Stochastic frontier models : A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 61(2), pages 273-303, April.
    4. Coricelli, Fabrizio & Rocha, Roberto de Rezende, 1991. "Stabilization programs in Eastern Europe : a comparative analysis of the Polish and Yugoslav programs of 1990," Policy Research Working Paper Series 732, The World Bank.
    5. Fernandez, Carmen & Osiewalski, Jacek & Steel, Mark F. J., 1997. "On the use of panel data in stochastic frontier models with improper priors," Journal of Econometrics, Elsevier, vol. 79(1), pages 169-193, July.
    6. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    Citations

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    Cited by:

    1. Heru Margono & Subhash Sharma & Kevin Sylwester & Usama Al-Qalawi, 2009. "Technical efficiency and productivity analysis in Indonesian provincial economies," Applied Economics, Taylor & Francis Journals, vol. 43(6), pages 663-672.
    2. Marco FIORAMANTI, 2010. "Estimation And Decomposition Of Total Factor Productivity Growth In The Eu Manufacturing Sector: A Long Run Perspective," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 5(3(13)/Fal), pages 217-230.
    3. Maria Baquero Forero & Takanori Ida & Toshifumi Kuroda, 2015. "Institutions and Cultural Heterogeneity as Determinants of National Income: A Random-coefficients Stochastic Frontier Model," Review of Development Economics, Wiley Blackwell, vol. 19(3), pages 710-724, August.
    4. Francisco J. Ruge-Murcia, 2000. "Uncovering financial markets' beliefs about inflation targets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 483-512.
    5. Malinka Koparanova, 2007. "Structural Changes in the Manufacturing Industry of Transition Economies," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 3, pages 3-42.
    6. Andrew J Tiffin, 2006. "Ukraine; The Cost of Weak Institutions," IMF Working Papers 06/167, International Monetary Fund.
    7. António Afonso & Miguel St. Aubyn, 2013. "Public and private inputs in aggregate production and growth: a cross-country efficiency approach," Applied Economics, Taylor & Francis Journals, vol. 45(32), pages 4487-4502, November.
    8. Astrid Cullmann & Christian von Hirschhausen, 2007. "From Transition to Competition: Dynamic Efficiency Analysis of Polish Electricity Distribution Companies," Discussion Papers of DIW Berlin 716, DIW Berlin, German Institute for Economic Research.
    9. Weill, Laurent, 2006. "On the consistency of aggregate production frontiers," European Journal of Operational Research, Elsevier, vol. 172(1), pages 326-333, July.
    10. Mastromarco, Camilla & Ghosh, Sucharita, 2009. "Foreign Capital, Human Capital, and Efficiency: A Stochastic Frontier Analysis for Developing Countries," World Development, Elsevier, vol. 37(2), pages 489-502, February.
    11. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676.
    12. Kamil Makieła, 2009. "Economic Growth Decomposition. An Empirical Analysis Using Bayesian Frontier Approach," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 1(4), pages 333-369, December.
    13. Laurent Weill, 2008. "On the inefficiency of European socialist economies," Journal of Productivity Analysis, Springer, vol. 29(2), pages 79-89, April.
    14. Marco Fioramanti, 2009. "Estimation and Decomposition of Total Factor Productivity Growth in the EU Manufacturing Sector: a Stochastic Frontier Approach," ISAE Working Papers 114, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    15. Jaume Puig, 2000. "Technical inefficiency and public capital in US States: A stochastic frontier approach," Economics Working Papers 451, Department of Economics and Business, Universitat Pompeu Fabra.
    16. Kamil Makieła, 2017. "Bayesian Inference and Gibbs Sampling in Generalized True Random-Effects Models," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 9(1), pages 69-95, March.
    17. repec:psc:journl:v:9:y:2017:i:3:p:243-273 is not listed on IDEAS

    More about this item

    Keywords

    Bayesian inference; efficiency; Gibbs sampling; productivity analysis; technical change;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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