We propose a methodology to classify individuals into few but meaningful health groups by estimating a panel Markov switching model that exploits rich information from panel household surveys. Using the HRS, we identify four persistent health groups, depending on individual's physical and mental disabilities. Our classification outperforms existing health measures at explaining entry in nursing homes, home health care, out-of-pocket medical expenses, and mortality for individuals in the HRS, ELSA, and SHARE. Through a workhorse model of savings, we recover an asset cost of bad health that is twice as big as when using self-reported health.
