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.
This report is part of the RAND Corporation report series. The report was a product of the RAND Corporation from 1948 to 1993 that represented the principal publication documenting and transmitting RAND's major research findings and final research.
Permission is given to duplicate this electronic document for personal use only, as long as it is unaltered and complete. Copies may not be duplicated for commercial purposes. Unauthorized posting of RAND PDFs to a non-RAND Web site is prohibited. RAND PDFs are protected under copyright law. For information on reprint and linking permissions, please visit the RAND Permissions page.
The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.