Lotti, Francesca ;
Santarelli, Enrico
(2001)
Industry Dynamics and the Distiribution of Firm Sizes: A Non-Parametric Apporoach.
Bologna:
Dipartimento di Scienze economiche DSE,
p. 21.
DOI
10.6092/unibo/amsacta/4895.
In: Quaderni - Working Paper DSE
(406).
ISSN 2282-6483.
Full text disponibile come:
Abstract
The aim of this paper is to analyze the evolution of the size distribution of young firms within some
selected industries, trying to assess the empirical implications of different models of industry dynamics:
the model of passive learning (Jovanovic 1982), the model of active learning (Ericson and Pakes, 1995),
and the evolutionary model (Audretsch, 1995). We use a non-parametric technique, the Kernel density
estimator, applied to a data set from the Italian National Institute for Social Security (INPS), consisting in
12 cohorts of new manufacturing firms followed for 6 years. Since the patterns of convergence to the
limit distribution are different between industries, we conclude that the model of passive learning is
consistent with some of them, the active exploration model with others, the evolutionary model with all of
them.
Abstract
The aim of this paper is to analyze the evolution of the size distribution of young firms within some
selected industries, trying to assess the empirical implications of different models of industry dynamics:
the model of passive learning (Jovanovic 1982), the model of active learning (Ericson and Pakes, 1995),
and the evolutionary model (Audretsch, 1995). We use a non-parametric technique, the Kernel density
estimator, applied to a data set from the Italian National Institute for Social Security (INPS), consisting in
12 cohorts of new manufacturing firms followed for 6 years. Since the patterns of convergence to the
limit distribution are different between industries, we conclude that the model of passive learning is
consistent with some of them, the active exploration model with others, the evolutionary model with all of
them.
Tipologia del documento
Monografia
(Working paper)
Autori
Parole chiave
Cohorts; Gibrat’s Law; Kernel; Industry Dynamics; Non-parametric; Shakeouts
Settori scientifico-disciplinari
ISSN
2282-6483
DOI
Data di deposito
17 Mar 2016 11:21
Ultima modifica
17 Mar 2016 11:21
URI
Altri metadati
Tipologia del documento
Monografia
(Working paper)
Autori
Parole chiave
Cohorts; Gibrat’s Law; Kernel; Industry Dynamics; Non-parametric; Shakeouts
Settori scientifico-disciplinari
ISSN
2282-6483
DOI
Data di deposito
17 Mar 2016 11:21
Ultima modifica
17 Mar 2016 11:21
URI
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