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Driving Factors of Growth in Hungary - a Decomposition Exercise

Author

Listed:
  • Gábor Kátay

    (Magyar Nemzeti Bank)

  • Zoltán Wolf

    (Tinbergen Institute)

Abstract

Applications tend to ignore that measured TFP reflects the variation of output that cannot be explained by changes in inputs. Such a change is not necessarily technological, so measured TFP differences across firms are an amalgam of technological, efficiency and other differences in attributes, which calls for further refinement in the treatment of TFP. To control for cyclical effects, we modify a standard technique in firmlevel production function estimation using a capacity utilization proxy. Based on a large panel of Hungarian manufacturing firms, we decompose value added growth to input factor, capacity utilization and estimated TFP growth contributions. We find that using an hours worked proxy, the variance of the residual drops considerably. We also find that TFP’s role has not been stable over the period: it contributed to value added growth mostly in periods when/after institutional reforms, privatization or FDI inflow took place and lost its importance several years after the shocks.

Suggested Citation

  • Gábor Kátay & Zoltán Wolf, 2008. "Driving Factors of Growth in Hungary - a Decomposition Exercise," MNB Working Papers 2008/6, Magyar Nemzeti Bank (Central Bank of Hungary).
    • Handle: RePEc:mnb:wpaper:2008/6
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    References listed on IDEAS

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    Cited by:

    1. Konstantins Benkovskis & Ludmila Fadejeva & Julia Wörz, 2013. "How Important Is Total Factor Productivity for Growth in Central, Eastern and Southeastern European Countries?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 1, pages 8-27.
    2. Endrész, Marianna & Harasztosi, Péter, 2014. "Corporate foreign currency borrowing and investment: The case of Hungary," Emerging Markets Review, Elsevier, vol. 21(C), pages 265-287.
    3. Kátay, Gábor, 2008. "Do firms provide wage insurance against shocks? Evidence from Hungary," Working Paper Series 964, European Central Bank.
    4. Alexandra Ferreira Lopes & Tiago Neves Sequeira, 2014. "The dynamics of the trade balance and the terms of trade in Central and Eastern European countries," Acta Oeconomica, Akadémiai Kiadó, Hungary, vol. 64(1), pages 51-71, March.
    5. Báger, Gusztáv & Galbács, Péter & Pulay, Gyula, 2012. "Az állami költségvetés makrogazdasági kockázatainak elemzése [Analysing macroeconomic risks in the state budget]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(9), pages 1014-1036.
    6. Havas, Attila & Nyiri, Lajos, 2007. "National system of innovation in Hungary," MPRA Paper 67161, University Library of Munich, Germany.
    7. Békés, Gábor & Harasztosi, Péter, 2013. "Agglomeration premium and trading activity of firms," Regional Science and Urban Economics, Elsevier, vol. 43(1), pages 51-64.
    8. Péter Harasztosi, 2011. "Growth in Hungary 1994-2008: The role of capital, labour, productivity and reallocation," MNB Working Papers 2011/12, Magyar Nemzeti Bank (Central Bank of Hungary).
    9. Kamil Galuscak & Lubomir Lizal, 2011. "The Impact of Capital Measurement Error Correction on Firm-Level Production Function Estimation," Working Papers 2011/09, Czech National Bank.
    10. Békés, Gábor & Halpern, László & Muraközy, Balázs, 2011. "A teremtő rombolás szerepe a vállalati termelékenység alakulásában Magyarországon [The role of creative destruction in the development of corporate productivity in Hungary]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(2), pages 111-132.
    11. Havas, Attila & Nyiri, Lajos, 2007. "A magyar nemzeti innovációs rendszer: Háttértanulmány az OECD 2007/2008. évi innovációs országjelentése számára [National system of innovation in Hungary: Background report for the OECD Country Rev," MPRA Paper 69379, University Library of Munich, Germany.
    12. Eric J. Bartelsman & Zoltan Wolf, 2014. "Forecasting Aggregate Productivity Using Information from Firm-Level Data," The Review of Economics and Statistics, MIT Press, vol. 96(4), pages 745-755, October.

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    More about this item

    Keywords

    economic growth; production function; input factor contributions; total factor productivity; capacity utilization; aggregation; panel data.;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • 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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