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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 non-normality in the micro-economic distribution of firm growth rates and for the presence of a negative scaling relation between their volatility and the size of the firm. Using Compustat data on US publicly traded company, we show that the new index tracks aggregate fluctuations better than the 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 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, 2017. "Aggregate fluctuations and the distribution of firm growth rates," LEM Papers Series 2017/24, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    • Handle: RePEc:ssa:lemwps:2017/24
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    Cited by:

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    2. Scharfenaker, Ellis, 2020. "Implications of quantal response statistical equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    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

    Keywords

    Firm growth rates asymmetry and volatility; Aggregate economic fluctuations and business cycles; Aggregation of non-normal variables;
    All these keywords.

    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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