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Industry Dynamics and the Distribution of Firm Sizes: A Nonparametric Approach
Author(s) -
Lotti Francesca,
Santarelli Enrico
Publication year - 2004
Publication title -
southern economic journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.762
H-Index - 58
eISSN - 2325-8012
pISSN - 0038-4038
DOI - 10.1002/j.2325-8012.2004.tb00583.x
Subject(s) - distribution (mathematics) , estimator , kernel density estimation , nonparametric statistics , econometrics , convergence (economics) , parametric statistics , industrial organization , economics , kernel (algebra) , statistics , mathematics , macroeconomics , mathematical analysis , combinatorics
The aim of this paper is to analyze the evolution of the size distribution of young firms within some selected industries, using as a background three theories of the distribution of firm sizes that identify a process of passive learning (Jovanovic 1982), one of active learning (Ericson and Pakes 1995), and an evolutionary one (Audretsch 1995) in the postentry dynamics of business firms. 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 of 12 cohorts of new manufacturing firms that were followed on a quarterly base for six years. We find that firm size distribution is in general skewed to the right, although different industries display different paths and speeds of convergence toward the limit distribution. This finding is fairly consistent with theories allowing for industry heterogeneity in terms of structural and technological features, which, in turn, result in industry‐specific evolution of the size distribution of new entrants.