Partial Identification in Monotone Binary Models: Discrete Regressors and Interval Data

Binary Choice Models with Discrete Regressors: Identification and Misspecification

In semiparametric binary response models, support conditions on the regressors are required to guarantee point identification of the parameter of interest. For example, one regressor is usually assumed to have continuous support conditional on the other regressors. In some instances, such conditions have precluded the use of these models; in others, practitioners have failed to consider whether...

Semiparametric Binary Choice Panel Data Models without Strictly Exogeneous Regressors

Most previous studies of binary choice panel data models with Þxed effects require strictly exogeneous regressors, and except for the logit model without lagged dependent variables, cannot provide rate root n parameter estimates. We assume that one of the explanatory variables is independent of the individual speciÞc effect and of the errors of the model, conditional on the other explanatory va...

Target setting in additive models with preferences and interval data

Partial Identification and Inference in Binary Choice and Duration Panel Data Models

Many semiparametric fixed effects panel data models, such as binary choice models and duration models, are known to be point identified when at least one regressor has full support on the real line. It is common in practice, however, to have only discrete or continuous, but possibly bounded, regressors. This paper addresses identification and inference for the identified set in such cases, when...

Informational Content of Special Regressors in Heteroskedastic Binary Response Models

We quantify the identifying power of special regressors in heteroskedastic binary regressions with median-independent or conditionally symmetric errors. We measure the identifying power using two criteria: the set of regressor values that help point identify coe¢ cients in latent payo¤s as in (Manski 1988); and the Fisher information of coe¢-cients as in (Chamberlain 1986). We …nd for median-in...