The status of health in demand estimation :
Manning, Willard G.
The status of health in demand estimation : beyond excellent, good, fair, and poor / Willard G. Manning, Joseph P. Newhouse, John E. Ware, Jr. - xi, 62 pages ; 28 cm - Health insurance experiment series .
"August 1981."
Includes bibliographical references (p. 59-62).
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.
0833002929
RAND/R-2696-1-HHS
$25.00
81000331
Health status indicators.
Health surveys.
Medical care--Utilization.
RA408.5 / .M3 1981
The status of health in demand estimation : beyond excellent, good, fair, and poor / Willard G. Manning, Joseph P. Newhouse, John E. Ware, Jr. - xi, 62 pages ; 28 cm - Health insurance experiment series .
"August 1981."
Includes bibliographical references (p. 59-62).
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.
0833002929
RAND/R-2696-1-HHS
$25.00
81000331
Health status indicators.
Health surveys.
Medical care--Utilization.
RA408.5 / .M3 1981