We propose a flexible stochastic framework for modeling the market share dynamics over time in a multiple markets setting, where firms interact within and between markets. Firms undergo stochastic idiosyncratic shocks, which contract their shares, and compete to consolidate their position by...

Tournaments are designed to enhance participants’ effort and productivity. However, ranking near the top may increase psychological pressure and reduce performance. We empirically study the impact of interim rank on performance using data from international diving tournaments. We find...

There is little evidence on the joint evolution of gender differences in wages and other job amenities. We analyze gender differences in wages and workplace safety using 9 years of Italian administrative micro-level data. We document that a decline in the gender wage gap was accompanied by a...

Little is known about the effects of revealing information on relative performance during a dynamic tournament. We empirically study the impact of interim rank on risk taking and performance using data on professionals competing in tournaments for large rewards. As our data allows us to observe...

We study the repeal of a regulation that imposed maximum wholesale and retail markups for all but five fresh fruits and vegetables. We compare the prices of products affected by regulation before and after the policy change and use the unregulated products as a control group. We find that...

The study of properties of mean functionals of random probability measures is an important area of research in the theory of Bayesian nonparametric statistics. Many results are known by now for random Dirichlet means but little is known, especially in terms of posterior distributions, for...

A Bayesian nonparametric methodology has been recently proposed in order to deal with the issue of prediction within species sampling problems. Such problems concern the evaluation, conditional on a sample of size n, of the species variety featured by an additional sample of size m. Genomic...

An important issue in survival analysis is the investigation and the modeling of hazard rates. Within a Bayesian nonparametric framework, a natural and popular approach is to model hazard rates as kernel mixtures with respect to a completely random measure. In this paper we provide a...

Bayesian nonparametric inference is a relatively young area of research and it has recently undergone a strong development. Most of its success can be explained by the considerable degree of flexibility it ensures in statistical modelling, if compared to parametric alternatives, and by the...

The present paper provides a review of the results concerning distributional properties of means of random probability measures. Our interest in this topic has originated from inferential problems in Bayesian Nonparametrics. Nonetheless, it is worth noting that these random quantities play an...