This paper is concerned with the estimation of nonlinear SUR models with additive AR(1) disturbances using panel data. We propose a transformation which eliminates auto-correlation for the whole system and yields a classical SUR-EC model. We present a general class of minimum distance estimators...

Empirical analysis often involves using inexact measures of desired predictors. The bias created by the correlation between the problematic regressors and the error term motivates the need for instrumental variables estimation. This paper considers a class of estimators that can be used when...

This paper considers dynamic panel models with a factor error structure that is correlated with the regressors. Both short panels (small T) and long panels (large T) are considered. With a small T, consistent estimation requires either a suitable formulation of the reduced form or an appropriate...

While 2SLS is the most widely used estimator for simultaneous equation models, OLS may do better in finite samples. Here we demonstrate analytically that for the widely used simultaneous equation model with one jointly endogenous variable and valid instruments, 2SLS has smaller MSE error, up to...

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...

Empirical analysis often involves using inexact measures of desired predictors. The bias created by the correlation between the problematic regressors and the error term motivates the need for instrumental variables estimation. This paper considers a class of estimators that can be used when...

The speed of convergence of the truncated realized covariance to the integrated covariation between the Brownian parts of two semimartingales is heavily influenced by the presence of infinite activity jumps with infinite variation. Namely, the two small jumps processes play a crucial role...

This paper outlines recently developed techniques for estimating the primitives needed to empirically analyze equilibrium interactions and their implications in oligopolistic markets. It is divided into an introduction and three sections; a section on estimating demand functions, a section on...

The Maximum Likelihood method estimates the parameter values of a statistical model that maximize the corresponding likelihood function, given the sample information. This is the primal approach that, in this paper, is presented as a mathematical programming specification whose solution requires...