Consider an observed binary regressor D and an unobserved binary variable D*, both of which affect some other variable Y. This paper considers nonparametric identification and estimation of the effect of D on Y , conditioning on D* = 0. For example, suppose Y is a person's wage, the unobserved D...

This paper is concerned with the problems of posterior simulation and model choice for Poisson panel data models with multiple random effects. Efficient algorithms based on Markov Chain Monte Carlo methods for sampling the posterior distribution are developed. A new parameterization of the...

The Greek Shipping Estimation Model aims to provide a coherent statistical framework for the estimation of Balance of Payments (BoP) items related to shipping activity, based on administrative sources and commercial databases. Given the multi-territorial nature of the shipping sector and its...

Particle filtering is a useful statistical tool which can be used to make inference on the latent variables and the structural parameters of state space models by employing it inside MCMC algorithms (Flury and Shephard, 2011). It only relies on two assumptions (Gordon et al, 1993): a: The...

Matched employer-employee data contain information collected from households and individuals as well as information collected from businesses or establishments. Both administrative and sample survey sources are considered. Both longitudinal and cross-sectional applications are discussed. We...

Two regressions can be interpreted as based on Gini's Mean Difference (GMD): a semiparametric approach, which relies on weighted average of slopes defined between adjacent observations and a minimization approach, which is based on minimization of the GMD of the residuals. The estimators...