This paper investigates how to test for nonresponse selection bias in wage functions induced by missing income information. We suggest an “easy-to-implement” approach which requires information on interviewer IDs and the interview date rather than hard-to-get interviewer characteristics.

This paper investigates how to test for nonresponse selection bias in wage functions induced by missing income information. We suggest an "easy-to-implement" approach which requires information on interviewer IDs and the interview date rather than hard to get interviewer characteristics.

This paper investigates how to test and correct for nonresponse selection bias induced by missing income information when estimating wage functions. The novelty is to use the variation in interviewer-specific response rates as exclusion restriction within the framework of a sample selection model.

This paper investigates how to test and correct for nonresponse selection bias induced by missing income information when estimating wage functions. The novelty is to use the variation in interviewer-specific response rates as exclusion restriction within the framework of a sample selection model.

The paper addresses two questions. First, is item nonresponse (INR) a precursor of panelattrition (UNR), as predicted by the theory of a latent cooperation continuum, or is theinterrelation of another type? Second, are the results in models of item nonresponse behavioraffected by a selectivity...

We develop and estimate a panel data model explaining the answers to questions about subjective probabilities, using data from the US Health and Retirement Study. We explicitly account for nonresponse, rounding, and focal point “50 percent” answers. Our results indicate that for three of the...