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Mark Duggan Brookings Institution, University of Maryland, and

Discussant Comments for: The Importance of Objective Health Measures in Predicting Early Receipt of Social Security Benefits: The Case of Fatness. Mark Duggan Brookings Institution, University of Maryland, and National Bureau of Economic Research August 10, 2006. Background.

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Mark Duggan Brookings Institution, University of Maryland, and

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  1. Discussant Comments for:The Importance of Objective Health Measures inPredicting Early Receipt of Social Security Benefits:The Case of Fatness Mark Duggan Brookings Institution, University of Maryland, and National Bureau of Economic Research August 10, 2006

  2. Background • Effect of health status on labor supply and/or OASDI claiming • Lumsdaine and Mitchell (1999), Currie and Madrian (1999), and Bound, Steinbricker, and Waidmann (2006) • Persistent obstacles to reliable identification • Self-reported health has many limitations • Health status not exogenous – may be correlated with wage, etc. • Thus a need for: • “Better” health measures • Plausibly exogenous source of variation in health status

  3. Alternative measure of health – “fatness” • Advantages over self-reported health status • More objectively measured • Continuous rather than discrete • Large and growing fraction of U.S. residents is obese • 14.4% of adults in 1976-80 vs. 30.5% by 1999-2000 (AOA, 2006) • Obesity may influence the net utility of work • Direct effect – work more difficult • Indirect effect – health shocks (e.g. heart attack) more likely • Could change optimal time to claim OASI retirement benefits

  4. Measuring “Fatness” • Most commonly used measure is BMI (w / h2) • But large literature suggests other measures are superior • Percent body fat (PBF), total body fat (TBF), etc. • BMI measure understates % obese and has substantial Type I,II error • But these superior measures cannot be calculated in PSID, etc. • Thus cannot relate PBF, TBF, etc. to labor supply • Approach used by the authors: • Use NHANES III data to estimate TBF = f(Age, Weight, Height) • Take this equation to PSID to estimate TBF

  5. Does Fatness Influence OASI Claiming? • Parameter of interest is b in following (simplified) equation SSj = Fjb + Xjd + uj with SSj equal to one if j claims OASI at age of 62 • Problem – Fj not exogenous • Thus b does not necessarily capture a causal effect • Authors’ strategy for dealing with this problem • Instrument for Fj with the fatness of the respondent’s adult child • Correlation likely to be (at least partially) driven by genetic factors • Assumes fatness of child uncorrelated with other causes of claiming

  6. Results • Measure used influences % considered to be obese • 23% (with BMI) vs. 70% (PBF) of women and 19% vs. 43% of men • Also changes black-white obesity gap • Narrows difference for women • White men significantly more obese with PBF, no difference with BMI • Fatness significantly positively correlated with early OASI claiming • Qualitatively similar estimates using BMI and PBF measures • IV estimates imprecisely estimated – “benefit not worth the cost”

  7. Possible Next Steps • What is the mechanism? • Does obesity makes work more difficult and hasten LF exit? • Is there some other driving factor that is correlated with obesity? • Are individuals claiming so as to maximize present value of benefits?

  8. Possible Next Steps (cont.) • Can rise in obesity partially explain growth in SSDI / SSI enrollment? • From 3.2 percent of non-elderly adults in 1985 to 5.9 percent in 2005 • Currently this group is excluded from analysis • Fraction claiming OASI relatively stable over same period • 55 percent of men and 60 percent of women claimed at 62 in 2004 • Similar to corresponding rates of 54 and 59 percent in 1985 • What other factors are offsetting effect of obesity on early claiming (which should be rising given results here)? • Further probing on identification strategy given endogeneity of Fj

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