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 marginal effects in the observed data differ from the true ones...

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...

Previous studies tend to find that immigration has a weak negative effect on the employment and earnings of native-born workers. These studies generally overlook the effect of immigration on an important sector of the labor force, the self-employed. Anecdotal evidence suggests that immigrants,...

There is an extensive literature on the extent to which public health insurance coverage through Medicaid induces less private health insurance coverage. However, little is known about the effect of other components of the health care safety net in crowding out private coverage. We examine the...

This paper uses a policy discontinuity to identify the immediate and long-term effects of public health insurance coverage during childhood. Our identification strategy exploits a unique feature of several early Medicaid expansions that extended eligibility only to children born after September...

High rates of understatement are found for many government transfer programs and in many datasets. This understatement has major implications for our understanding of economic well-being and the effects of transfer programs. We provide estimates of the extent of under-reporting for ten transfer...