A Appendix: Standard Errors

There are several issues concerning computing standard errors for the pooled specification in equation (2). First, insofar as there is heterogeneity in the displaced worker earnings losses, then we expect there to be serial correlation in the standard errors at the individual level. This concern arises even in specification (1). We address this concern by clustering at the person level. Second, a given person-quarter observation might appear several times. For example, if a person continues in a job for several quarters and then loses their job in a mass displacement, then a particular calendar quarter of earnings would show up in two different calendar times. This specification with a given observation potentially appearing multiple times is formally identical to the preferred specification in Dube, Lester, and Reich (2010), and we adopt their solution of clustering at the level of aggregation at which a given observation might appear multiple times.19 To summarize, our standard errors have the following structure: E[uyiku y′ i′k′ ] 6= 0 if i = i ′ or k + y = k′ + y′. As a result, we use the Cameron, Gelbach, and Miller (2011) two-way clustered standard errors where we cluster at the person level and calendar time level. They show that the variance matrix is then V IT = V I + V T − V I∩T where the right hand side are variance matrices from one-way clustering and I is the set of individuals and T is the set of calendar-time periods.20