On the Accuracy of Different Measures ofq

Tobin's q is widely accepted as a proxy for an underlying “true” q, which is assumed to characterize a firm's incentive to invest. Researchers have developed numerous methods for computing q. This article assesses the measurement quality of different proxies for q. We adapt the measurement-error consistent estimators in Erickson and Whited (2002) to estimate the extent to which variation in true unobservable q explains variation in different proxies for q. We find most proxies for q are poor: careful algorithms for calculating q do little to improve measurement quality. Using elaborate algorithms, however, depletes the number of usable observations and possibly introduces sample selection bias.