Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
In this paper, we propose an easy-to-implement procedure to test the key conditions for the identification and estimation of the local average treatment effect (LATE; Imbens & Angrist, 1994). We reformulate the testable implications of LATE assumptions as two conditional inequalities, which can be tested in the intersection bounds framework of Chernozhukov, Lee, and Rosen (2013) and easily implemented using the Stata package of Chernozhukov et al. (2015). We apply the proposed tests to the draft eligibility instrument in Angrist (1991), the college proximity instrument in Card (1993), and the same-sex instrument in Angrist and Evans (1998).