The Status of Health in Demand Estimation

This study addresses two issues. (1) What can one gain by using more comprehensive measures of health status in demand estimation than a common single item measure? Would you rate your health as excellent, good, fair, or poor? The authors find that by using multidimensional and less-coarse health status measures they achieve an increase in precision approximately equivalent to a 10 percent increase in sample size. (2) What is the consequence of employing postdiction (i.e., predicting utilization from health status measured after the fact) rather than prediction? Using a simple, but plausible, model, the authors show that such measures cause the estimates to be inconsistent; the direction of the inconsistency generally cannot be signed a priori. Empirically the direction is generally away from zero.