Aggregate fluctuations and the distribution of firm growth rates
Résumé
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.
Domaines
Economies et financesFormat du dépôt | Notice |
---|---|
Type de dépôt | Article dans une revue |
Titre |
en
Aggregate fluctuations and the distribution of firm growth rates
|
Résumé |
en
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.
|
Auteur(s) |
Giulio Bottazzi
1
, Le Li
2
, Angelo Secchi
3, 4
1
SSSUP -
Scuola Universitaria Superiore Sant'Anna [Pisa]
( 58000 )
- Piazza Martiri della Libertà 33 - 56127 Pisa
- Italie
2
Chuo University -
Chuo University
( 61142 )
- Chuo University 742-1 HIgashinakano Hachioji-shi, Tokyo 192-0393 Japan Tel:+81-42-674-2211,2212 Fax:+81-42-674-2214
- Japon
3
PSE -
Paris School of Economics
( 301309 )
- 48 boulevard Jourdan 75014 Paris
- France
4
PJSE -
Paris Jourdan Sciences Economiques
( 1171428 )
- 48 boulevard Jourdan 75014 Paris
- France
|
Langue du document |
Anglais
|
Nom de la revue |
|
Vulgarisation |
Non
|
Comité de lecture |
Oui
|
Audience |
Internationale
|
Date de publication |
2019-06
|
Volume |
28
|
Numéro |
3
|
Page/Identifiant |
635-656
|
Domaine(s) |
|
DOI | 10.1093/icc/dtz016 |
Loading...