We define and investigate a new class of measure-valued Markov chains by resorting to ideas formulated in Bayesian nonparametrics related to the Dirichlet process and the Gibbs sampler. Dependent random probability measures in this class are shown to be stationary and ergodic with respect to the...

The paper proposes a new nonparametric prior for two-dimensional vectors of survival functions (S1,S2). The definition we introduce is based on the notion of Lévy copula and it will be used to model, in a nonparametric Bayesian framework, two-sample survival data. Such an application will yield...

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...

A random distribution function on the positive real line which belongs to the class of neutral to the right priors is defined. It corresponds to the superposition of independent beta processes at the cumulative hazard level. The definition is constructive and starts with a discrete time process...

This paper studies gender wage differentials in Italy by providing a structural estimation of the frictional parameters of two different theoretical specifications of an equilibrium search model. I alternatively allow for firm heterogeneity and discrimination empirically using maximum likelihood...

In this paper I review the main strengths and weaknesses of agent-based computational models. In particular I rationalise the main theoretical critiques, which point to the following problematic areas: (i) interpretation of the simulation dynamics, (ii) estimation of the simulation model, and...

Earnings differentials between men and women have experienced a stable convergence during the 1980s, following a process started in the late 1970s. However, in the 1990s the convergence has almost stopped. The first objective of the paper is to evaluate if discrimination, defined as explicit...