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 approximate agents' wealth and price invariant densities of the prediction market model presented in Kets et al.(2014) is derived using the Fokker-Planck equation of the associated continuous-time jump process. We show that the approximation obtained from the evolution of log-wealth...

Recent empirical analyses on different datasets have revealed a common exponential behaviour in the shape of the probability density of the corporate growth rates. We briefly review these analyses and present new evidence on this topic based on corporate data from Italian Manufacturing Industry....

Analyzing a comprehensive database of limited liability manufacturing firms this paper investigates the relation between a firm’s financial situation and its conditional expected growth rate. Specifically, using quantile regressions, we obtain a quantitative characterization of this relation...

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...

This paper performs an empirical analysis of the international cross sectional distribution of gross domestic product (GDP) growth rates and business cycles. We consider a balanced panel of 91 countries in the period 1960-2010 and two different measures of GDP fluctuations: the logarithmic...

We introduce a new 5-parameter family of distributions, the Asymmetric Exponential Power (AEP), able to cope with asymmetries and leptokurtosis and at the same time allowing for a continuous variation from non-normality to normality. We prove that the Maximum Likelihood (ML) estimates of the AEP...