2013/17 | LEM Working Paper Series | ||||||||||||||||
Zipf Law and the Firm Size Distribution: a critical discussion of popular estimators |
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Giulio Bottazzi, Davide Pirino, Federico Tamagni |
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Keywords | |||||||||||||||||
Firm size distribution; Zipf Law; Power-like distribution;
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JEL Classifications | |||||||||||||||||
L11; C15; C46; D20
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Abstract | |||||||||||||||||
The upper tail of the firm size distribution is often assumed to
follows a Power Law behavior. Recently, using different estimators
and on different data sets, several papers conclude that this
distribution follows the Zipf Law, that is that the fraction of
firms whose size is above a given value is inversely proportional to
the value itself. We compare the different methods through which
this conclusion has been reached. We find that the family of
estimators most widely adopted, based on an OLS regression, is in
fact unreliable and basically useless for appropriate inference.
This finding rises some doubts about previously identified Zipf
Laws. In general, when individual observations are available, we
recommend the adoption of the Hill estimator over any other method.
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