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A nonparametric analysis of firm size, leverage and labour productivity distribution dynamics

Author

Listed:
  • Kim Huynh

    (Bank of Canada - Bank of Canada)

  • David Jacho-Chávez

    (Emory University [Atlanta, GA])

  • Robert Petrunia

    (Lakehead University)

  • Marcel Voia

    (UO - Université d'Orléans, UniBuc - University of Bucharest)

Abstract

This paper investigates the evolution of firm distributions for entrant manufacturing firms in Canada using nonparametric methods. These nonparametric methods use functional principal components to describe these densities over time. This method is applied to a novel administrative firm-level database from Statistics Canada to investigate the evolution of the 1985 and 1989 cohorts of new entrants. We find that firm leverage (debt-to-asset ratio) distributions have persistent deviations from the initial distributions. Bootstrap test statistics suggest that the distributions are different across all time periods. Firm size and labour productivity have transitory deviations and some of the distributions are the same across all time periods. Univariate finite mixture and stochastic dominance tests are used to conduct pairwise comparisons as robustness measures. We find that these static pairwise comparisons confirm the dynamic evolution of these densities. This method illustrates the efficacy of functional principal components to analyse firm distributions. Copyright Springer-Verlag Berlin Heidelberg 2015
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Kim Huynh & David Jacho-Chávez & Robert Petrunia & Marcel Voia, 2014. "A nonparametric analysis of firm size, leverage and labour productivity distribution dynamics," Post-Print hal-04926608, HAL.
    • Handle: RePEc:hal:journl:hal-04926608
    DOI: 10.1007/s00181-014-0807-9
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    References listed on IDEAS

    as
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    Cited by:

    1. Huynh, Kim P. & Jacho-Chávez, David T. & Kryvtsov, Oleksiy & Shepotylo, Oleksandr & Vakhitov, Volodymyr, 2016. "The evolution of firm-level distributions for Ukrainian manufacturing firms," Journal of Comparative Economics, Elsevier, vol. 44(1), pages 148-162.
    2. Sabetti Leonard & Jacho-Chávez David T. & Petrunia Robert & Voia Marcel C., 2018. "Tail Risk in a Retail Payments System," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 238(3-4), pages 353-369, July.
    3. Sakiru Adebola Solarin & Mufutau Opeyemi Bello, 2024. "Modelling labour productivity and the role of research intensity in 129 years: evidence from a new dynamic instrumental variable estimation approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(3), pages 2619-2646, June.
    4. Dixon Jay & Petrunia Robert & Rollin Anne-Marie, 2018. "Studying Firm Growth Distributions with a Large Administrative Employment Database," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 238(3-4), pages 189-221, July.
    5. Gustavo Canavire-Bacarreza & Luis C. Carvajal-Osorio, 2020. "Two Stories of Wage Dynamics in Latin America: Different Policies, Different Outcomes," Journal of Labor Research, Springer, vol. 41(1), pages 128-168, June.

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    More about this item

    JEL classification:

    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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