  Many studies use shift-share (or ``Bartik'') instruments, which average a set
of shocks with exposure share weights. We provide a new econometric framework
for shift-share instrumental variable (SSIV) regressions in which
identification follows from the quasi-random assignment of shocks, while
exposure shares are allowed to be endogenous. The framework is motivated by an
equivalence result: the orthogonality between a shift-share instrument and an
unobserved residual can be represented as the orthogonality between the
underlying shocks and a shock-level unobservable. SSIV regression coefficients
can similarly be obtained from an equivalent shock-level regression, motivating
shock-level conditions for their consistency. We discuss and illustrate several
practical insights of this framework in the setting of Autor et al. (2013),
estimating the effect of Chinese import competition on manufacturing employment
across U.S. commuting zones.
