In this paper, we consider identification in a correlated random effects model for panel data. We assume that the likelihood for each individual in the panel is known up to a finite dimensional common parameter and an individual specific parameter. We allow the distribution of unobserved individual specific effects to depend on observed explanatory variables and make no assumptions about the pa...

The problem of predicting a vector of ordered parameters or its part arises in contexts such as measurement error models, signal processing, data disclosure, and small area estimation. Often estimators of functions of the ordered random effects are obtained under strong distributional assumptions, e.g., normality. We discuss a simple generalized shrinkage estimator for predicting ordered random...

In this paper, we consider identification and estimation of average marginal effects in a correlated random effects model without imposing strong functional form assumptions on the structural likelihood or the mixing distribution. Identification is achieved through imposing that the mixing distribution depends on observed covariates only through an index function and the assumption that at leas...

This paper examines the relationship between child labor and access to credit at a crosscountry level. Even though this link is theoretically central to child labor, so far there has been little work done to assess its importance empirically. We measure child labor as a country aggregate, and credit constraints are proxied by the extent of financial development. These two variables display a st...

This paper presents a monopolistic competition model of trade and multinational production that incorporates asymmetric trade barriers and international differences in production costs. The model predicts the functional form for the dependence of U.S. exports and multinational production on tariffs, distance, and production costs. To deal with simultaneity, we estimate the nonlinear equations o...

Subjective Well-Being and the Family: Results from an Ordered Probit Model with Multiple Random Effects The previous literature on the determinants of individual well-being has failed to fully account for the interdependencies in well-being at the family level. This paper develops an ordered probit model with multiple random effects that allows to identify the intrafamily correlation in well-be...

Assuming a multivariate linear regression model with one random factor, we consider the parameters defined as exponentials of mixed effects, i.e., linear combinations of fixed and random effects. Such parameters are of particular interest in prediction problems where the dependent variable is the logarithm of the variable that is the object of inference. We derive bias-corrected empirical predi...

Many observational studies have shown an association between income and health. However, much less research has assessed how changes in income influence health over time. This could help illuminate the issue of whether income is causally related to health, if longitudinal survey data were analysed with methods to account for bias from both measured and unmeasured time-invariant confounders. The...