We investigate whether local average treatment effects (LATE's) can be extrapolated to new settings. We extend the analysis and framework of Dehejia, Pop-Eleches, and Samii (2015), which examines the external validity of the Angrist-Evans (1998) reduced-form natural experiment of having two...

We present a methodology for estimating the distributional effects of an endogenous treatment that varies at the group level when there are group-level unobservables, a quantile extension of Hausman and Taylor (1981). Because of the presence of group-level unobservables, standard quantile...

One of the primary motivations behind the establishment of noncontributory pension programs is to allow beneficiaries to retire from the labor force. Yet, as with other unconditional cash transfer schemes, their aggregate effects may be more complex. Using panel data and instrumental variable...

We explore a key underlying assumption, the exclusion restriction, commonly used in interpreting IV estimates in the presence of heterogenous treatment effects as a local average treatment effect (LATE). We show through a series of simple examples that in some commonly featured cases that this...

In this paper, we discuss the key conditions for the identification and estimation of the local average treatment effect (LATE, Imbens and Angrist, 1994): the valid instrument assumption (LI) and the monotonicity assumption (LM). We show that the joint assumptions of LI and LM have a testable...

This paper estimates peer effects in a university context where students are randomly assigned to sections. While students benefit from better peers on average, low-achieving students are harmed by high-achieving peers. Analyzing students' course evaluations suggests that peer effects are driven...

This paper considers two-sided tests for the parameter of an endogenous variable in an instrumental variable (IV) model with heteroskedastic and autocorrelated errors. We develop the finite-sample theory of weighted-average power (WAP) tests with normal errors and a known long-run variance. We...