This paper develops a method to estimate workers’ outside employment opportunities. We outline a matching model with two-sided heterogeneity, from which we derive a sufficient statistic, the “outside options index” (OOI), for the effect of outside options on earnings, holding worker productivity constant. The OOI uses the cross-sectional concentration of similar workers across job types to quantify workers’ outside options as a function of workers’ commuting costs, preferences, and skills. Using German micro-data, we find that differences in options explain 20% of the gender earnings gap, and that gender gaps in options are mostly due to differences in the implicit costs of commuting and moving.

The validity of instrumental variable (IV) designs is typically tested using two types of falsification tests. We characterize these tests as conditional independence tests between negative control variables—proxies for unobserved variables posing a threat to the identification—and the IV or the outcome. We describe the conditions variables must satisfy in order to serve as negative controls. We show these falsification tests examine not only independence and the exclusion restriction but also functional form assumptions. Our analysis reveals conventional applications of these tests may flag problems even in valid IV designs. We offer implementation guidance to address these issues.