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Aggregate fluctuations and the distribution of firm growth rates

Author

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  • Giulio Bottazzi
  • Le Li
  • Angelo Secchi

Abstract

We propose an aggregate growth index that explicitly accounts for fat tails in the firm size distribution and for the negative scaling relation between the size of the firm and the volatility of its growth rates. Using Compustat data on US publicly traded company, we show that the new index tracks aggregate fluctuations much better than simpler measures of central tendency of the dynamics of firms, like the growth rates sample average, confirming that the statistical properties characterizing the micro-economic dynamics of firms are relevant for the dynamics of the aggregate. To better characterize the origins of aggregate fluctuations, we decompose the index in two parts, describing, respectively, the modal (typical) value of log growth rates and the tilt (asymmetry) of their distribution. Regression analysis shows that models based on this decomposition, despite their simplicity, possess a remarkable explanatory and predictive power with respect to the aggregate growth.

Suggested Citation

  • Giulio Bottazzi & Le Li & Angelo Secchi, 2019. "Aggregate fluctuations and the distribution of firm growth rates," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 28(3), pages 635-656.
  • Handle: RePEc:oup:indcch:v:28:y:2019:i:3:p:635-656.
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    File URL: http://hdl.handle.net/10.1093/icc/dtz016
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    Cited by:

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    3. Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Tania Treibich, 2019. "Debunking the granular origins of aggregate fluctuations: from real business cycles back to Keynes," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 67-90, March.
    4. Ellis Scharfenaker, 2022. "Statistical Equilibrium Methods In Analytical Political Economy," Journal of Economic Surveys, Wiley Blackwell, vol. 36(2), pages 276-309, April.
    5. Torsten Heinrich & Jangho Yang & Shuanping Dai, 2020. "Levels of structural change: An analysis of China's development push 1998-2014," Papers 2005.01882, arXiv.org, revised Sep 2020.
    6. Torsten Heinrich & Jangho Yang & Shuanping Dai, 2022. "Levels of structural change," Journal of Evolutionary Economics, Springer, vol. 32(1), pages 35-86, January.
    7. David Vidal-Tomás & Alba Ruiz-Buforn & Omar Blanco-Arroyo & Simone Alfarano, 2022. "A Cross-Sectional Analysis of Growth and Profit Rate Distribution: The Spanish Case," Mathematics, MDPI, vol. 10(6), pages 1-20, March.
    8. Matteo Barigozzi & Angelo Cuzzola & Marco Grazzi & Daniele Moschella, 2021. "Factoring in the micro: a transaction-level dynamic factor approach to the decomposition of export volatility," LEM Papers Series 2021/22, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

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    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance

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