Identification and Inference With Many Invalid Instruments

Identification and Inference With Many Invalid Instruments

We study estimation and inference in settings where the interest is in the effect of a potentially endogenous regressor on some outcome. To address the endogeneity we exploit the presence of additional variables. Like conventional instrumental variables, these variables are correlated with the endogenous regressor. However, unlike conventional instrumental variables, they also have direct effec...

IDENTIFICATION AND INFERENCE WITH MANY INVALID INSTRUMENTS Michal

IV estimation with valid and invalid instruments

While 2SLS is the most widely used estimator for simuhaneous equation models, OLS may do better in finite samples. Here we demonstrate analytically that the for the widely used simultaneous equation model with one jointly endogenous variable and valid instruments, 2SLS has smaller MSE error, up to second order, than OLS unless the R , or the F statistic of the reduced form equation is extremely...

Avoiding Invalid Instruments and Coping with Weak Instruments

A rchimedes said, “Give me the place to stand, and a lever long enough, and I will move the Earth” (Hirsch, Kett, and Trefil, 2002, p. 476). Economists have their own powerful lever: the instrumental variable estimator. The instrumental variable estimator can avoid the bias that ordinary least squares suffers when an explanatory variable in a regression is correlated with the regression’s distu...

Integrated Likelihood Approach to Inference with Many Instruments

I analyze a Gaussian linear instrumental variables model with a single endogenous regressor in which the number of instruments is large. I use an invariance property of the model and a Bernstein-von Mises type argument to construct an integrated likelihood which by design yields inference procedures that are valid under many instrument asymptotics and are asymptotically optimal under rotation i...