Scale of reference bias and the evolution of health.

The analysis of subjective measures of well-being-such as self-reports by individuals about their health status is frequently hampered by the problem of scale of reference bias. A particular form of scale of reference bias is age norming. In this study we corrected for scale of reference bias by allowing for individual specific effects in an equation on subjective health. A random effects ordered response model was used to analyze scale of reference bias in self-reported health measures. The results indicate that if we do not control for unobservable individual specific effects, the response to a subjective health state measure suffers from age norming. Age norming can be controlled for by a random effects estimation technique using longitudinal data. Further, estimates are presented on the rate of depreciation of health. Finally, simulations of life expectancy indicate that the estimated model provides a reasonably good fit of the true life expectancy.