%0 Report %D 2013 %T Health, Education, and the Post-Retirement Evolution of Household Assets %A James M. Poterba %A Steven F Venti %A David A Wise %K Demographics %K Health Conditions and Status %K Net Worth and Assets %K Retirement Planning and Satisfaction %X This paper explores the relationship between education and the evolution of wealth after retirement. Asset growth following retirement depends in part on health capital and financial capital accumulated prior to retirement, which in turn are strongly related to educational attainment. These initial conditions for retirement can have a lingering effect on subsequent asset evolution. Our aim is to disentangle the effects of education on post-retirement asset evolution that operate through health and financial capital accumulated prior to retirement from the effects of education that impinge directly on asset evolution after retirement. We consider the indirect effect of education through financial resources in particular Social Security benefits and defined benefit pension benefits and through health capital that was accumulated before retirement. We also consider the direct effect of education on asset growth following retirement, emphasizing the correlation between education and the returns households earn on their post-retirement investments. Households with different levels of education invest, on average, in different assets, and they may consequently earn different rates of return. Finally, we consider the additional effects of education that are not captured through these pathways. Our empirical findings suggest a substantial association between education and the evolution of assets. For example, for two person households the growth of assets between 1998 and 2008 is on average much greater for college graduates than for those with less than a high school degree. This difference ranges from about 82,000 in the lowest asset quintile to over 600,000 in the highest. %I Cambridge, MA, National Bureau of Economic Research %G eng %4 education/wealth/asset accumulation/household finances/retirement planning/health capital/health capital %$ 69270 %0 Book Section %B Analyses in the Economics of Aging %D 2005 %T Healthy, Wealthy, and Knowing Where to Live: Trajectories of Health, Wealth, and Living Arrangements among the Oldest Old %A Florian Heiss %A Michael D Hurd %A Axel Borsch-Supan %E David A Wise %K Consumption and Savings %K Health Conditions and Status %K Net Worth and Assets %X There are many mechanisms that suggest that living arrangements and well-being derived from health and economic status are closely related. This paper investigates the joint evolution of the three conditions, using a microeconometric approach similar to what is known as vector autoregressions (VAR) in the macroeconomics literature. %B Analyses in the Economics of Aging %I University of Chicago Press %C Chicago %P 241-275 %G eng %L wp_2003/Heiss-Hurd-Supan_NBER9897.pdf %4 Health Status/Wealth/Living Standards %$ 11622 %+ NBER Working Paper 9897. Copies available from: National Bureau of Economic Research, 1050 Massachusetts Avenue,Cambridge, MA 02138. %! Healthy, Wealthy, and Knowing Where to Live: Trajectories of Health, Wealth, and Living Arrangements among the Oldest Old %R 10.3386/w9897 %0 Book Section %B Inquiries in the economics of aging %D 1998 %T Household Wealth of the Elderly under Alternative Imputation Procedures %A Hoynes, Hilary %A Michael D Hurd %A Chand, Harish %E David A Wise %K Consumption and Savings %K Demographics %K Income %K Net Worth and Assets %K Retirement Planning and Satisfaction %X Although many reach retirement with few resources except housing equity and a claim to social security and Medicare, financial wealth, nonetheless, makes an important contribution to the economic status of many of the elderly. Most of our up-to-date information about the wealth of the elderly is based on the Survey of Income and Program Participation (SIPP), which sometimes adds an asset module to its core survey. As in many surveys of assets, the rate of missing data on individual asset items is high, about 30 to 40 percent among those with the asset. This raises the issue of the reliability of SIPP wealth measures because respondents who refuse or are unable to give a value to an asset item may not be representative of the population. Indeed, in the Health and Retirement Survey (HRS) it is clear that asset data are not missing at random. Through the use of bracketing methods, which we will discuss below, the HRS was able to reduce the rate of missing asset data substantially, and the data that were added in this way increased mean wealth in the HRS by about 40 percent (Smith 1995). Furthermore, because the additional data increased the mean so much, they undoubtedly increased measures of wealth inequality. %B Inquiries in the economics of aging %I University of Chicago Press %C Chicago and London %P 229 -54 %G eng %U https://www.nber.org/chapters/c7088 %N NBER Project Report series %4 Economics of the Elderly/Retirement/Retirement Policies/Personal Income and Wealth Distribution/Elderly/Wealth %$ 1008 %! Household Wealth of the Elderly under Alternative Imputation Procedures