In this article, we propose a new methodology based on a (log) semi-nonparametric (log- SNP) distribution that nests the lognormal and enables better fits in the upper tail of the distribution through the introduction of new parameters. We test the performance of the lognormal and log-SNP...

We propose a new three-step model-selection framework for size distributions in empirical data. It generalizes a recent frequentist plausibility-of-fit analysis (Step 1) and combines it with a relative ranking based on the Bayesian Akaike Information Criterion (Step 2). We enhance these...

The upper tail of the firm size distribution is often assumed to follow a Power Law. Several recent papers, using different estimators and different data sets, conclude that the Zipf Law, in particular, provides a good fit, implying that the fraction of firms with size above a given value is...

We propose an aggregate growth index that explicitly accounts for non-normality in the micro-economic distribution of firm growth rates and for the presence of a negative scaling relation between their volatility and the size of the firm. Using Compustat data on US publicly traded company, we...

The cross-sectional distribution of consumption is commonly approximated by the lognormal distribution. This note shows that consumption is better described by the double Pareto-lognormal distribution (dPlN), which has a lognormal body with two Pareto tails and arises as the stationary...

Sutton (1998) has recently proposed a theoretical lower bound to firm size inequality when a market is made of several independent submarkets. His results are valid asymptotically, as the number of submarkets becomes arbitrarily large. We show that, in small samples, his results can be...