PROBLEMS WITH INSTRUMENTAL VARIABLES ESTIMATION WHEN THE CORRELATION BETWEEN THE INSTRUMENTS AND THE ENDOGENOUS EXPLANATORY VARIABLE IS WEAK

We draw attention to two problems associated with the use of instrumen tal variables (IV), the importance of which for empirical work has not been fully appreciated. First, the use of instruments that explain li ttle of the variation in the endogenous explanatory variables can lead to large inconsistencies in the IV estimates even if only a weak rela tionship exists between the instruments and the error in the structura l equation. Second, in finite samples, IV estimates are biased in the same direction as ordinary least squares (OLS) estimates. The magnitud e of the bias of IV estimates approaches that of OLS estimates as the R(2) between the instruments and the endogenous explanatory variable a pproaches 0. To illustrate these problems, we reexamine the results of a recent paper by Angrist and Krueger, who used large samples from th e U.S. Census to estimate wage equations in which quarter of birth is used as an instrument for educational attainment. We find evidence tha t, despite huge sample sizes, their IV estimates may suffer from finit e-sample bias and may be inconsistent as well. These findings suggest that valid instruments may be more difficult to find than previously i magined. They also indicate that the use of large data sets does not n ecessarily insulate researchers from quantitatively important finite-s ample biases. We suggest that the partial R(2) and the F statistic of the identifying instruments in the first-stage estimation are useful i ndicators of the quality of the IV estimates and should be routinely r eported.d