While measurement error in the dependent variable does not lead to bias in some well-known cases, with a binary … dependent variable the bias can be pronounced. In binary choice, Hausman, Abrevaya and Scott-Morton (1998) show that the … asymptotic bias in parametric models allowing for correlation of the errors with both observables and unobservables. Second, we …

We derive the asymptotic bias from misclassification of the dependent variable in binary choice models. Measurement … error is necessarily non-classical in this case, which leads to bias in linear and non-linear models even if only the … dependent variable is mismeasured. A Monte Carlo study and an application to food stamp receipt show that the bias formulas are …

While measurement error in the dependent variable does not lead to bias in some well-known cases, with a binary … dependent variable the bias can be pronounced. In binary choice, Hausman, Abrevaya and Scott-Morton (1998) show that the … asymptotic bias in parametric models allowing for correlation of the errors with both observables and unobservables. Second, we …

testing and correcting for unit and item nonresponse bias in contingent valuation survey data. When sample nonresponse and … selection bias go uncorrected, welfare measures may be overestimated or underestimated contributing to potential errors in …

applicability of the “person-positivity bias” to immigration and investigate the effects of economic and cultural “deservingness” on …