Significant departures from log normality are observed in income data, in violation of Gibrat's law. We identify a new empirical regularity, which is that the distribution of consumption expenditures across households is, within cohorts, closer to log normal than the distribution of income. We...

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...

This paper considers identification and estimation of the marginal effect of a mismeasured binary regressor in a nonparametric regression, or the conditional average effect of a binary treatment or policy on some outcome where treatment may be misclassified. Misclassification probabilities and...

We consider estimation of means of functions that are scaled by an unknown density, or equivalently, integrals of conditional expectations. The "ordered data" estimator we provide is root n consistent, asymptotically normal, and is numerically extremely simple, involving little more than...

Relative prices are nonstationary and standard root-T inference is invalid for demand systems. But demand systems are nonlinear functions of relative prices, and standard methods for dealing with nonstationarity in linear models cannot be used. Demand system residuals are also frequently found...

For vectors z and w and scalar v, let r(v,z,w) be a function that can be nonparametrically estimated consistently and asymptotically normally, such as a distribution, density, or conditional mean regression function. We provide consistent, asymptotically normal nonparametric estimators for the...

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...

The existing literature on binary games with incomplete information assumes that either payoff functions or the distribution of private information are finitely parameterized to obtain point identification. In contrast, we show that, given excluded regressors, payoff functions and the...

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

This chapter provides background for understanding and applying special regressor methods. This chapter is intended for inclusion in the "Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics," Co-edited by Aman Ullah, Jeffrey Racine, and Liangjun Su, to be published...