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Asymmetry Reversals and the Business Cycle

Author

Listed:
  • Roberta Distante

    (Fondazione Eni Enrico Mattei)

  • Ivan Petrella

    (Department of Economics, Mathematics and Statistics, Birkbeck, University of London)

  • Emiliano Santoro

    (Department of Economics and Finance, Catholic University of Milan and Department of Economics, University of Copenhagen)

Abstract

The cross-sectional dynamics of the U.S. business cycle is examined through the lens of quantile regression models. Conditioning the quantiles of firm-level growth to different measures of technological change highlights a deep connection between counter-cyclical skewness and the transmission of aggregate disturbances. Asymmetry reversals emerge as the dominant source of cyclical variation in the probability density, generating a powerful amplification of aggregate shocks to firm technology. Designing and validating heterogeneous firm business cycle models should necessarily account for this empirical finding.

Suggested Citation

  • Roberta Distante & Ivan Petrella & Emiliano Santoro, 2013. "Asymmetry Reversals and the Business Cycle," Working Papers 2013.54, Fondazione Eni Enrico Mattei.
  • Handle: RePEc:fem:femwpa:2013.54
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    References listed on IDEAS

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    1. R?diger Bachmann & Christian Bayer, 2014. "Investment Dispersion and the Business Cycle," American Economic Review, American Economic Association, vol. 104(4), pages 1392-1416, April.
    2. Roberta Distante & Ivan Petrella & Emiliano Santoro, 2014. "Size, Age and the Growth of Firms: New Evidence from Quantile Regressions," Working Papers 2014.69, Fondazione Eni Enrico Mattei.
    3. Steven J. Davis & R. Jason Faberman & John Haltiwanger & Ron Jarmin & Javier Miranda, 2010. "Business Volatility, Job Destruction, and Unemployment," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(2), pages 259-287, April.
    4. Julia K. Thomas, 2002. "Is Lumpy Investment Relevant for the Business Cycle?," Journal of Political Economy, University of Chicago Press, vol. 110(3), pages 508-534, June.
    5. Nicholas Bloom & Max Floetotto & Nir Jaimovich & Itay Saporta-Eksten & Stephen J. Terry, 2012. "Really Uncertain Business Cycles," NBER Working Papers 18245, National Bureau of Economic Research, Inc.
    6. Emmanuel De Veirman & Andrew Levin, 2011. "Cyclical changes in firm volatility," Reserve Bank of New Zealand Discussion Paper Series DP2011/06, Reserve Bank of New Zealand.
    7. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, March.
    8. Jovanovic, Boyan, 1982. "Selection and the Evolution of Industry," Econometrica, Econometric Society, vol. 50(3), pages 649-670, May.
    9. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters,in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1 National Bureau of Economic Research, Inc.
    10. Sean Holly & Ivan Petrella & Emiliano Santoro, 2013. "Aggregate fluctuations and the cross-sectional dynamics of firm growth," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(2), pages 459-479, February.
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    12. Don Harding & Adrian Pagan, 1999. "Knowing the Cycle," Melbourne Institute Working Paper Series wp1999n12, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    13. Hall, Bronwyn H, 1987. "The Relationship between Firm Size and Firm Growth in the U.S. Manufacturing Sector," Journal of Industrial Economics, Wiley Blackwell, vol. 35(4), pages 583-606, June.
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    15. repec:ran:wpaper:710-1 is not listed on IDEAS
    16. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1.
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    Cited by:

    1. Nicholas Bloom & Fatih Guvenen & Sergio Salgado, 2016. "Skewed Business Cycles," 2016 Meeting Papers 1621, Society for Economic Dynamics.
    2. Distante, Roberta & Petrella, Ivan & Santoro, Emiliano, 2017. "Gibrat's Law and Quantile Regressions: an Application to Firm Growth," EMF Research Papers 16, Economic Modelling and Forecasting Group.
    3. Roberta Distante & Ivan Petrella & Emiliano Santoro, 2014. "Size, Age and the Growth of Firms: New Evidence from Quantile Regressions," Working Papers 2014.69, Fondazione Eni Enrico Mattei.

    More about this item

    Keywords

    Corporate Growth; Conditional Quantiles; Business Cycles; Asymmetry Reversals;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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