We generalize the standard search, matching, and bargaining framework to allow individuals to acquire productivity-enhancing schooling prior to labor market entry. As is well-known, search frictions and weakness in bargaining position contribute to under-investment from an efficiency...

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 generalize the standard search, matching, and bargaining framework to allow individuals to acquire productivity-enhancing schooling prior to labor market entry. As is wellknown, search frictions and weakness in bargaining position contribute to under-investment from an efficiency perspective....

In this paper we utilize a model of household investments in the cognitive development of children to explore the impact of various transfer policies on the distribution of child cognitive outcomes in target populations. We develop a cost criterion that can be used to compare the cost...

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...

While widely accepted models of labor market search imply a constant reservation wage policy, the empirical evidence strongly suggests that reservation wages decline over the duration of a search spell. This paper reports the results of the first real-time search laboratory experiment. The...

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...