The Status of Health in Demand Estimation
Beyond Excellent, Good, Fair, and Poor
ResearchPublished 1981
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.
Document Details
- Copyright: RAND Corporation
- Availability: Web Only
- Year: 1981
- Pages: 77
- DOI: https://doi.org/10.7249/pubs
- Document Number: R-2696-1-HHS
Citation
RAND Style Manual
Manning, Willard G., Joseph P. Newhouse, and John E. Ware, The Status of Health in Demand Estimation: Beyond Excellent, Good, Fair, and Poor, RAND Corporation, R-2696-1-HHS, 1981. As of July 31, 2026: https://www.rand.org/pubs/reports/R2696-1.html
Chicago Manual of Style
Manning, Willard G., Joseph P. Newhouse, and John E. Ware, The Status of Health in Demand Estimation: Beyond Excellent, Good, Fair, and Poor. Santa Monica, CA: RAND Corporation, 1981. https://www.rand.org/pubs/reports/R2696-1.html.
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