Semiparametric Binary Choice Panel Data Models without Strictly Exogeneous Regressors
نویسندگان
چکیده
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 variables. Based on Lewbel (2000a), we show how this alternative assumption can be used to identify and root-n consistently estimate the parameters of discrete choice panel data models with Þxed effects, only requiring predetermined (as opposed to strictly exogeneous) regressors. The estimator is semiparametric in that the error distribution is not speciÞed, and allows for general forms of heteroscedasticity.
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