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More Is Better! What Can Firm-Specific Estimates of the Impact of Institutional Quality on Performance Tell Us?

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  • Bhaumik, Sumon K.

    () (University of Sheffield)

  • Dimova, Ralitza

    () (University of Manchester)

  • Kumbhakar, Subal C.

    () (Binghamton University, New York)

  • Sun, Kai

    () (Aston University)

Abstract

We introduce a novel approach to modeling the impact of institutional quality on firm performance. Our methodology enables us to estimate the marginal effect of institutional quality on TFP, factor inputs and output of each firm, which gives us within-country distributions of these effects and hence a better picture of the winners and losers associated with a particular level of institutional quality. We are also able to model marginal impact of institutional quality on both TFP and the efficiency of use of factor inputs, and hence on output. This is a departure from stylized approaches that focus on the impact on TFP alone, and our approach therefore informs policy discussions about the impact of institutional quality (and their change) on shares of factor inputs in the output. We use cross-country firm-level data for the textiles and garments sector to demonstrate the advantages of this modeling approach in analyzing the impact of institutional quality.

Suggested Citation

  • Bhaumik, Sumon K. & Dimova, Ralitza & Kumbhakar, Subal C. & Sun, Kai, 2014. "More Is Better! What Can Firm-Specific Estimates of the Impact of Institutional Quality on Performance Tell Us?," IZA Discussion Papers 7886, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp7886
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    References listed on IDEAS

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    1. Rachel Griffith & Stephen Redding & John Van Reenen, 2004. "Mapping the Two Faces of R&D: Productivity Growth in a Panel of OECD Industries," The Review of Economics and Statistics, MIT Press, vol. 86(4), pages 883-895, November.
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    3. Li, Qi, et al, 2002. "Semiparametric Smooth Coefficient Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 412-422, July.
    4. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
    5. Henderson, Daniel J. & Kumbhakar, Subal C. & Parmeter, Christopher F., 2012. "A simple method to visualize results in nonlinear regression models," Economics Letters, Elsevier, vol. 117(3), pages 578-581.
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    8. Sumon Kumar Bhaumik & Ralitza Dimova, 2014. "Good and bad institutions: is the debate over? Cross-country firm-level evidence from the textile industry," Cambridge Journal of Economics, Oxford University Press, vol. 38(1), pages 109-126.
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    10. Daron Acemoglu & Simon Johnson, 2005. "Unbundling Institutions," Journal of Political Economy, University of Chicago Press, vol. 113(5), pages 949-995, October.
    11. Margaret M. Jacobson & Filippo Occhino, 2012. "Labor's declining share of income and rising inequality," Economic Commentary, Federal Reserve Bank of Cleveland, issue Sept.
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    More about this item

    Keywords

    institutional quality; firm performance; marginal effect; textiles industry;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • K31 - Law and Economics - - Other Substantive Areas of Law - - - Labor Law
    • O43 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Institutions and Growth

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