Empirical labor market studies often do not include controls for family and income structure. Because these variables are significantly correlated with many of the variables commonly included, such as education, estimated coefficients are subject to omitted variable bias. We demonstrate how omission of family and income variables can lead to statistically biased coefficient estimates on nonfamily variables and can lead to false inferences by examining labor force attachment of workers who have lost their previous job. The traditional variables most biased by the omission of family and income characteristics are education, displacement age, and predicted pre-displacement wages. As an indication of the extent of the bias, we calculate expected labor force participation rates for single women, married women, and married men using the average characteristics for each group using both the biased and unbiased coefficients. We find a 50 percent reduction in the extent to which market-oriented opportunities explain the differences in observed labor force attachment between married women and men when family characteristics are included relative to when they are not.
No takes yet. Share an insight, caveat, or question.
Netz et al. (1999) studied this question.
Synapse has enriched 5 related papers. Consider them for comparative context: