In this paper we examine the importance of heterogeneity and self-selection into schooling for the study of inequality. Changes in inequality over time are a combination of price changes, selection bias and composition effects. To distinguish them, we estimate a semiparametric selection model...

We develop a simulated ML method for short-panel estimation of one or more dynamic linear equations, where the dependent variables are only partially observed through ordinal scales. We argue that this latent autoregression (LAR) model is often more appropriate than the usual state-dependence...

This paper develops and implements semiparametric methods for estimating binary response (binary choice) models withcontinuous endogenous regressors. It extends the existing literature on semiparametric estimation in single index binary response models to the case of endogenous regressors. It...

An overview is presented of some parametric and semi-parametric models, estimators, and specification tests that can be used to analyze ordered response variables. In particular, limited dependent variable models that generalize ordered probit are compared to regression models that generalize...

We study econometric models of complete information games with ordered action spaces, such as the number of store fronts operated in a market by a firm, or the daily number of flights on a city-pair offered by an airline. The model generalises single agent models such as ordered probit and logit...

This paper gives an account of the recent literature on estimating models for panel count data. Specifically, the treatment of unobserved individual heterogeneity that is correlated with the explanatory variables and the presence of explanatory variables that are not strictly exogenous are...

In an effort to improve the small sample properties of generalized method of moments (GMM) estimators, a number of alternative estimators have been suggested. These include empirical likelihood (EL), continuous updating, and exponential tilting estimators. We show that these estimators share a...

<p><p>We provide nonparametric estimators of derivative ratio-based average marginal effects of an endogenous cause, X, on a response of interest, Y , for a system of recursive structural equations. The system need not exhibit linearity, separability, or monotonicity. Our estimators are local indirect...</p></p>

This paper studies the estimation of conditional quantiles of counts. Given the discreteness of the data, some smoothness has to be artificially imposed on the problem. The methods currently available to estimate quantiles of count data either assume that the counts result from the...

<p><p>This paper considers parametric estimation problems with independent, identically,non-regularly distributed data. It focuses on rate-effciency, in the sense of maximal possible convergence rates of stochastically bounded estimators, as an optimality criterion,largely unexplored in parametric...</p></p>