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...

Stigma of welfare participation is important for policy and survey design, because it deters program take-up and increases misreporting. Stigma is also relevant to the literature on social image concerns, yet empirical evidence is scant because stigma is difficult to empirically identify. We use...

Large literatures have analyzed racial and ethnic disparities in economic outcomes and access to the safety net. For such analyses that rely on survey data, it is crucial that survey accuracy does not vary by race and ethnicity. Otherwise, the observed disparities may be confounded by...