Firm size and concentration inequality: A flexible extension of Gibrat’s law
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The study assesses the performance of the lognormal distribution (Gibrat, 1931) compared with its generalization in terms of a semi-nonparametric (SNP) expansion, the log-SNP distribution, for determining economic concentration and providing adequate values of inequality based on the Gini index adjusted to flexible functional forms. Data from a sample of 1,772 companies from Colombia were collected from 1995 to 2015 and analyzed, and the results indicated that, compared with the lognormal distribution, the log-SNP distribution provided a better fit to firm size distribution, especially in the higher quantiles, which represent larger and smaller companies. Therefore, the traditional assumption of lognormality overestimates the level of economic concentration, rejecting Gibrat’s law. In addition, the estimates of a dynamic panel model indicate that firm characteristics, including size, age, and leverage, are determining factors in explaining firm growth.