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...

We study how the closeness of electoral race affect the number of invalid ballots under the traditional paper-ballot voting technology. Using a large dataset from the Italian parliamentary elections in 1994-2001, we find a strong positive correlation between the closeness of electoral race and...

Is the decline in voter turnout an indicator of a worse health of a representative democracy? We build a simple probabilistic-voting model with endogenous turnout to address this question. We ?nd that a lower turnout caused by a higher cost of voting implies higher political rents. Contrarily, a...

Mission-driven nonprofi?t organizations compete for donations through fundrais- ing activities. Such competition can lead to inefficient outcomes, if nonpro?fits impose ex- ternalities on each others? output. This paper studies the design of sustainable voluntary cooperation agreements, using a...

Randomized controlled trials (RCT) have become a dominant empirical tool in applied economics. The internal validity of RCTs crucially depends on the (implicit) assumption that the procedure assigning subjects to treatment and control groups has no effect on behavior. We show theoretically 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...