Abstract
Self-rated health status (SRHS) is one of the most frequently used health measures in empirical health economics. This article analyzes the first seven waves of the Health and Retirement Study (HRS) and finds that (1) all available lags have decreasing but significant predictive power for current SRHS and (2) SRHS and future mortality are strongly related which leads to a specific selection problem known as survivorship bias. A parsimonious joint model with an autocorrelated latent health component in both the SRHS and the mortality equation is suggested. It is better able to capture the empirical facts than commonly used models including random effects and/or state dependence and better able to correct the survivorship bias than commonly used strategies such as inverse probability weighting.