This paper shows that many estimators of thresholds in ordered response models exist, because binary choice location estimators can be converted into threshold estimators. A new threshold estimator is proposed that is consistent under more general conditions. An extension to random thresholds is provided. JEL codes: C14, C25, C13.

We consider a bivariate Poisson model that is based on the lognormal heterogeneity model. Two recent applications have used this model. We suggest that the correlation estimated in their model frameworks is an ambiguous measure of the correlation of the variables of interest, and may substantially overstate it. We conclude with a detailed application of the proposed method using the data employ...

The Semiparametric Least Squares (SLS) estimation for single index models is studied. Applying the isometric regression by Ayer et al (1955), the method minimizes the mean squared errors with respect to both finite and infinite dimensional parameters. A proof of consistency and an upper bound of convergence rates is offered. As an application example of the SLS estimation, asymptotic normality ...

This paper proposes minimum distance estimation procedures for the slope coefficients and location parameter in randomly censored regression models that are used in duration and competing risk models. The proposed procedure generalizes existing work in terms of weakening the restrictions imposed on the distribution of the error term and the censoring variable. Examples of such generalizations i...

This paper considers the evaluation of the average treatment effect of a binary endogenous regressor on a binary outcome when one imposes a threshold crossing model on both the endogenous regressor and the outcome variable but without imposing parametric functional form or distributional assumptions. Without parametric restrictions, the average effect of the binary endogenous variable is not ge...

This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of the coefficients in a truncated regression model. The distribution of the errors is unknown and permits general forms of unknown heteroskedasticity. Also provided is an instrumental variables based two stage least squares estimator for this model, which can be used when some regressors are endogen...

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 regressors, e.g., the model could have errors that are heteroscedastic or correlated with regressors. The est...

Recent work on nonparametric identification of average partial effects (APEs) from panel data require restrictions on individual or time heterogeneity. Identifying assumptions under the “generalized first-differencing” category, such as time homogeneity (Chernozhukov, Fernandez-Val, Hahn, and Newey, 2013), have testable equality restrictions on the distribution of the outcome variable. This pap...

Concern over the distributional effects of policies which induce changes in peer group structure, or ‘associational redistributions’ (Durlauf, 1996c), motivates a substantial body of theoretical and empirical research in economics, sociology, psychology, and education. A growing collection of econometric methods for characterizing the effects of such policies are now available. This chapter sur...