NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH
NBER Reporter: Summer 2001


The Economics of Aging

The NBER's Program on Aging, directed by David A. Wise of NBER and Harvard University, held its most recent in a series of conferences on May 17-20. The following papers, which will be published by the University of Chicago Press in an NBER Conference Volume, were presented:


James M. Poterba, NBER and MIT, Steven F. Venti, Dartmouth College and NBER, and David A. Wise, Harvard University, "The Transition to Personal Accounts and Increasing Retirement Wealth: Macro and Micro Evidence"

Discussant: Sylvester Scheiber, Watson Wyatt Worldwide

James J. Choi and David Laibson, NBER and Harvard University; Brigitte Madrian, NBER and University of Chicago; and Andrew Metrick, University of Pennsylvania, "For Better or Worse: Default Effects and 401(k) Savings Behavior"

Discussant: James M. Poterba

Jeffrey R. Brown, NBER and Harvard University, and Scott J. Weisbenner, University of Illinois, "Is a Bird in the Hand Worth More Than a Bird in the Bush? Intergenerational Transfers and Savings Behavior"

Discussant: Alan J. Auerbach, NBER and University of California at Berkeley

James Banks and Richard Blundell, University College London, and James P. Smith, RAND Corporation, "Wealth Portfolios in the UK and the US"

Discussant: John B. Shoven, NBER and Stanford University

Steven F. Venti and David A. Wise, "Aging and Housing Equity: Another Look"

Discussant: Jonathan S. Skinner, NBER and Dartmouth College

Michael D. Hurd, NBER and RAND Corporation, Daniel L. McFadden, NBER and University of California at Berkeley; Angela Merrill, Mathematica, and Tiago Ribiero, University of California at Berkeley, "Healthy, Wealthy, and Wise: The Evidence from AHEAD Wave 3"

Discussant: John P. Rust, NBER and Yale University

David M. Cutler, NBER and Harvard University, and Ellen Meara, Harvard University, "Changes in the Age Distribution of Mortality Over the 20th Century"

Discussant: David Meltzer, NBER and University of Chicago

Victor R. Fuchs and Mark B. McClellan, NBER and Stanford University, "Area Differences in Utilization of Medical Care and Mortality Among U.S. Elderly"

Discussant: Joseph P. Newhouse, NBER and Harvard University

Anne Case, NBER and Princeton University, "Does Money Protect Health Status? Evidence from South African Pensions"

Discussant: Robert T. Jensen, NBER and Harvard University

Robert T. Jensen, "Socioeconomic Status, Nutrition, and Health Among the Elderly"

Discussant: David M. Cutler

Angus S. Deaton and Christina Paxson, NBER and Princeton University, "Mortality, Income, and Income Inequality among British and American Cohorts"

Discussant: James Banks

Poterba, Venti, and Wise use both macro and micro data to describe the change in retirement assets and in retirement savings that is attributable to the shift over the last two decades from employer-managed defined benefit (DB) pensions to retirement plans that are largely managed and controlled by employees. They pay particular attention to the possible substitution of pensions assets in one plan for assets in another plan, especially the substitution of 401(k) assets for DB assets. The macro data show that between 1975 and 1999 assets to support retirement increased about five-fold relative to wage and salary income, suggesting large increases in the wealth of future retirees. Retirement plan contributions, as well as favorable rates of return in the 1990s, explain the large increase in retirement plan assets. The micro data show no evidence that the accumulation of 401(k) assets has been offset by a reduction in DB assets. Because annual saving is much greater under 401(k) than under DB plans, and because of the market return advantage of 401(k) plans, assets at retirement typically would be much higher under a 401(k) plan than under a DB plan. In addition, a large fraction of 401(k) enrollees retained DB coverage, further increasing their retirement saving.

In the last several years, dozens of employers have automatically enrolled new employees in the company 401(k) plan. Choi, Laibson, Madrian, and Metrick analyze three years of 401(k) data from two firms that have experimented with automatic enrollment. They find that automatic enrollment has a dramatic effect on retirement savings behavior. Under automatic enrollment, 401(k) participation rates exceed 85 per cent. In addition, 80 percent of all participants initially accept both the default savings rate (2 or 3 percent for these two companies) and the default investment fund (stable value or money market). Even after three years, over half of participants continue to contribute at the default rate and invest their contributions in the default fund. Automatic enrollment thus encourages participation, but appears to anchor participants to a low default savings rate and in a conservative default investment vehicle. Higher participation raises average wealth accumulation, but low savings rates and conservative investments undercut accumulation. In this sample, the two effects are roughly offsetting. However, automatic enrollment has a large impact on the distribution of 401(k) balances. Under automatic enrollment, few employees have low (that is, zero) balances, because most employees are anchored at the default choices.

Brown and Weisbenner provide new evidence on the decomposition of aggregate household wealth into life-cycle and transfer wealth. Using the 1998 Survey of Consumer Finances, they find that transfer wealth accounts for approximately one-fifth to one-quarter of aggregate wealth, suggesting a larger role for life-cycle savings than some previous estimates. Despite the smaller aggregate level of transfer wealth, its concentration among a small number of households suggests that it can still have an important effect on the savings decisions of recipients. One estimate suggests that past receipts of transfer wealth reduce life-cycle savings by as much as dollar-for-dollar, while expected future transfers do not produce such a crowd-out effect.

Banks, Blundell, and Smith document and attempt to explain differences between the United States and United Kingdom household wealth distributions, emphasizing the quite different portfolios held in stock and housing equities in the two countries. They show that, as a proportion of total wealth, British households hold relatively small amounts of financial assets - including equities in stock - compared to their American counterparts. In contrast, British households appear to move into home ownership at relatively young ages; consequently, a large fraction of their household wealth is concentrated in housing. Moreover, important changes have been taking place in both countries in their housing and equity markets. Especially in Britain, there have been some fundamental changes in national policies that have been aimed at encouraging wider rates of home ownership and greater participation in the equity market. Institutional differences between the countries imply much younger homebuyers in the United Kingdom than in the United States. The authors argue that the higher housing price volatility in the U.K. combined with much younger entry into home ownership there helps to explain the relatively small participation of young British householders in the stock market. It is important to acknowledge the dual role in housing - providing both wealth and consumption services - in understanding differences in wealth accumulation between the United States and the United Kingdom. As a result, institutional differences , particularly in housing markets, that affect the demand and supply of housing services, turn out to be important in generating portfolio differences between the two countries.

Aside from Social Security and, for some, employer-provided pensions, housing equity is the principle asset of a large fraction of older Americans. Many retired persons have essentially no financial assets to support retirement consumption. Nonetheless, Venti and Wise find that housing equity is typically not withdrawn to support non-housing consumption during retirement. In fact, in the absence of the death of a spouse or entry of a family member into a nursing home, families are unlikely to discontinue home ownership. Even in the event of these precipitating shocks, giving up a home is the exception and not the rule. Families that move and purchase a new home tend to increase home equity. However, income-poor and house-rich families are more likely to reduce equity when they move, while house-poor and income-rich households are more likely to increase housing equity. On balance, households that move and buy a new home substantially increase housing equity. Venti and Wise conclude that home equity is typically not liquidated to support general non-housing consumption needs as households age.

Hurd, McFadden, Merrill, and Ribiero use the Asset and Health Dynamics of the Oldest Old (AHEAD) Panel to test for the absence of causal links from socio-economic status (SES) to innovations in health or mortality, and from health conditions to innovations in wealth. They conclude that there is no causal link from SES to mortality or to the incidence of sudden onset health conditions (accidents and, probably, acute conditions), but there is an association of SES with the incidence of gradual onset health conditions (mental conditions and, probably, degenerative and chronic conditions), either because of causal links or persistent unobserved behavioral or genetic factors that have a common influence on both SES and innovations in health. The authors conclude that there is no causal link from health status to innovations in wealth.

Since 1960, reductions in mortality have been associated with two new factors: the conquest of cardiovascular disease in the elderly, and the prevention of death attributable to low birth weight infants. While it is not entirely clear what factors account for the reduction in cardiovascular disease mortality, the traditional roles of nutrition, public health, and antibiotics are certainly less important than factors related to individual behavior, such as smoking and diet and high tech medical equipment. Cutler and Meara term this change the "medicalization" of death: increasingly, reductions in mortality are attributed to medical care and not to social or environmental improvements. The medicalization of death does not imply that medicine is the only factor influencing mortality. For several important causes of death, improvements in income and social programs have had and continue to have a large impact on mortality. For example, Medicare probably has a direct impact on mortality by increasing elderly access to medical care, but it also may have important effects on income since it reduces out-of-pocket spending by the elderly for medical care. Social Security and civil rights programs also may be important in better health. The authors quantify the role of medicine, income, social programs, and other factors in improved mortality in the last half century, but they show examples of where each is important, as a first step in this research process.

Fuchs and McClellan examine 314 United States areas for differences in medical care utilization and mortality among whites ages 65-84 in 1990. The seven regions and five groups are based on population size. The authors find that cross-area variation in utilization is strongly related to variation in mortality. For total utilization, the elasticity ranges between 0.51 and 0.82 (standard errors are about 0.10) after controlling for region, population size of area, education, income, and income inequality. These are lower-bound estimates; the true coefficients would be larger to the extent that there is a negative relationship running from utilization of care to mortality. The elasticities are especially large for medical admissions, and especially small for physicians' diagnostic services and treatments. Also noteworthy is the extent to which the well-known propensity for higher utilization in Florida appears even larger after controlling for socioeconomic variables and mortality. The coefficient for Florida is, on average, over 50 percent (9 percentage points) higher when the other variables are considered. A third result worthy of comment is the much higher utilization in areas of over 500,000 population relative to all other areas. The average differential is about 8 percent. Among the other areas there is no strong pattern related to population size. The authors find no support for the hypothesis that mortality and income inequality are positively related. The coefficient for inequality is actually negative and significantly different from zero. Nor do they find a relationship between mortality and population size. They do find a very large negative coefficient for Florida: this region has by far the lowest mortality of any region regardless of whether or not other variables are controlled for.

Case quantifies the impact on health status of a large, exogenous increase in income - that associated with the South African state old age pension. Elderly Black and Coloured men and women who did not anticipate receiving large pensions in their lifetimes, and who did not pay into a pension system, are currently receiving more than twice the median Black income per capita. These elderly men and women generally live in large (three or four or five generation) households, and this paper documents the effects of the pension on the pensioners, on other adult members of their households, and on the children who live with them. Case finds, in households that pool income, that the pension protects the health of all household members, working in part to protect the nutritional status of household members, in part to improve living conditions, and in part to reduce the stress under which the adult household members negotiate day-to-day life. The health effects of delivering cash provide a benchmark against which other health-related interventions can be evaluated.

Jensen applies data from a nationally representative household-level survey to explore the relationship between health and socioeconomic status (SES) for the elderly in Russia. His objectives are to explore the basic relationship and to present evidence from a variety of measures of health status, including measurements of blood pressure, weight and height conducted by trained enumerators, as well as nutrient intake, derived from 24- and 48-hour food intake diaries. Therefore, he need not rely exclusively on self-reports of health status, where response choices may have different interpretations for different people (as in self-reported overall health status), or where there may be problems of differential reporting by SES (for example, because of differential knowledge or awareness of health conditions). He uses the data to show that the relationship between health and SES in Russia can't be adequately described by simple statements such as: the poor are less healthy than the rich. On net, the rich are healthier than the poor in some overall sense, but there are important ways in which the rich face greater health risks. Jensen also focuses on one particular mechanism, nutrition, through which SES may affect health. In particular, there are important micronutrients beyond calories that are important for good health, especially for the elderly. And the intake of these nutrients may be sensitive to income, as the lowest cost staple foods in most countries (for example, bread and rice) may yield sufficient "bulk" or calories, but (unless fortified) may have low levels of vitamins, minerals and proteins. On the other hand, these foods tend to be low in fat, cholesterol, and sodium, compared to foods which may be more expensive and eaten in larger quantities by the rich, such as meat. Therefore, it is quite possible that nutrition plays a role in the relationship between health and SES, even in countries where calorie malnutrition is scarce and obesity is widespread.

In earlier work, Deaton and Paxson investigated the relationship between mortality, income, and income inequality in the United States. This paper extends their analysis to Britain. They first compare British and U.S. mortality experience over time in relation to the evolution of incomes and income inequality. They find that there is no simple relationship between income, income inequality, and the decline in mortality. Instead, the most plausible account of the data is that mortality declines are driven by technological advances. They then replicate their earlier work on U.S. birth cohorts using British data and find that, once they account for time trends, neither income nor income inequality are related to mortality.

 
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