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Retrieving initial capital distributions from panel data

Author

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  • Chen, Xi
  • Plotnikova, Tatiana

Abstract

A common problem in the empirical production analysis at the firm-level is that the initial values of capital are often missing in the data. Most empirical studies impute initial capital according to some ad hoc criteria based on a single arbitrary proxy. This paper evaluates the bias of production function estimations that is introduced when these traditional initial value approximations are used. We propose a generalized framework to deal with the missing initial capital problem by using multiple proxies where the choice of proxies is data-driven. We conduct a series of Monte Carlo experiments where the proposed method is tested against traditional approaches and apply the method to the firm-level data.

Suggested Citation

  • Chen, Xi & Plotnikova, Tatiana, 2014. "Retrieving initial capital distributions from panel data," MPRA Paper 61154, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:61154
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    File URL: https://mpra.ub.uni-muenchen.de/61154/1/MPRA_paper_61154.pdf
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    References listed on IDEAS

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    1. Nina Pavcnik, 2002. "Trade Liberalization, Exit, and Productivity Improvements: Evidence from Chilean Plants," Review of Economic Studies, Oxford University Press, vol. 69(1), pages 245-276.
    2. Liu, Lili, 1993. "Entry-exit, learning, and productivity change Evidence from Chile," Journal of Development Economics, Elsevier, vol. 42(2), pages 217-242, December.
    3. Arvid Raknerud & Dag Rønningen & Terje Skjerpen, 2007. "A Method for Improved Capital Measurement by Combining Accounts and Firm Investment Data. A revised version," Discussion Papers 365, Statistics Norway, Research Department.
    4. Ariél Pakes & Zvi Griliches, 1984. "Estimating Distributed Lags in Short Panels with an Application to the Specification of Depreciation Patterns and Capital Stock Constructs," Review of Economic Studies, Oxford University Press, vol. 51(2), pages 243-262.
    5. Bob Gilhooly, 2009. "Firm-level estimates of capital stock and productivity," Economic & Labour Market Review, Palgrave Macmillan;Office for National Statistics, vol. 3(5), pages 36-41, May.
    6. Lucia Foster & Cheryl Grim & John Haltiwanger, 2016. "Reallocation in the Great Recession: Cleansing or Not?," Journal of Labor Economics, University of Chicago Press, vol. 34(S1), pages 293-331.
    7. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-1297, November.
    8. Hall, Bronwyn H. & Mairesse, Jacques, 1995. "Exploring the relationship between R&D and productivity in French manufacturing firms," Journal of Econometrics, Elsevier, vol. 65(1), pages 263-293, January.
    9. Berndt, Ernst R. & Fuss, Melvyn A., 1986. "Productivity measurement with adjustments for variations in capacity utilization and other forms of temporary equilibrium," Journal of Econometrics, Elsevier, vol. 33(1-2), pages 7-29.
    10. Arvid Raknerud & Dag Rønningen & Terje Skjerpen, 2007. "A Method For Improved Capital Measurement By Combining Accounts And Firm Investment Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 53(3), pages 397-421, September.
    11. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," Review of Economic Studies, Oxford University Press, vol. 70(2), pages 317-341.
    12. Hicks, John R, 1974. "Capital Controversies: Ancient and Modern," American Economic Review, American Economic Association, vol. 64(2), pages 307-316, May.
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    Cited by:

    1. Richiardi, Matteo G. & Valenzuela, Luis, 2019. "Firm Heterogeneity and the Aggregate Labour Share," MPRA Paper 94561, University Library of Munich, Germany.

    More about this item

    Keywords

    capital stock measurement; production function estimation; Monte Carlo simulation; non-linear regression;

    JEL classification:

    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D20 - Microeconomics - - Production and Organizations - - - General

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