We discuss the relative advantages and disadvantages of four types of convenient estimators of binary choice models when regressors may be endogenous or mismeasured, or when errors are likely to be heteroskedastic. For example, such models arise when treatment is not randomly assigned and...

We study quantile regression estimation for dynamic models with partially varying coefficients so that the values of some coefficients may be functions of informative covariates. Estimation of both parametric and nonparametric functional coefficients are proposed. In particular, we propose a...

This paper provides estimators of discrete choice models, including binary, ordered, and multinomial response (choice) models. The estimators closely resemble ordinary and two stage least squares. The distribution of the model's latent variable error is unknown and may be related to the...

I develop a tractable, two-country, real model of macroeconomic interdependence with a role for net foreign asset dynamics. Absence of Ricardian equivalence in an overlapping generations structure ensures existence of a well-defined, endogenously determined, steady-state, international...

In this paper we consider endogenous regressors in the binary choice model under a weak median exclusion restriction, but without further specification of the distribution of the unobserved random components. Our reduced form specification with heteroscedastic residuals covers various...

We compare the performance of a currency board arrangement, inflation targeting, and dollarization in a small open, developing economy with liberalized capital account. We focus explicitly on the transmission of shocks to currency and country risk premia in international financial markets and on...

Misclassification in binary choice (binomial response) models occurs when the dependent variable is measured with error, that is, when an actual "one" response is sometimes recorded as a zero, and vice versa. This paper shows that binary choice models with misclassification are...

Previous estimators of binary choice panel data models with fixed effects require strong parametric error asumptions, strictly exogeneous regressors, or both. This is because nonlinearity of the model precludes the use of the "moment conditions on differences" based estimators that are generally...

This paper provides a few variants of a simple estimator for binary choice models with endogenous or mismeasured regressors, or with heteroskedastic errors. Unlike control function methods, which are generally only valid when endogenous regressors are continuous, the estimators proposed here can...

This paper provides numerically trivial estimators for short panels of either binary choices or of linear models that suffer from confounded, nonignorable sample selection. The estimators allow for fixed effects, endogenous regressors, lagged dependent variables, and heterokedastic errors with...