Aging Issues in the United States and Japan

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The population base in both the United States and Japan is growing older and, as those populations age, they provoke heretofore unexamined economic consequences. This cutting-edge, comparative volume, the third in the joint series offered by the National Bureau of Economic Research and the Japan Center for Economic Research, explores those consequences, drawing specific attention to four key areas: incentives for early retirement; savings, wealth, and asset allocation over the life cycle; health care and health care reform; and population projections.

Given the undeniable global importance of the Japanese and U.S. economies, these innovative essays shed welcome new light on the complex correlations between aging and economic behavior. This insightful work not only deepens our understanding of the Japanese and American economic landscapes but, through careful examination of the comparative social and economic data, clarifies the complex relation between aging societies, public policies, and economic outcomes.

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Meet the Author

Seiritsu Ogura teaches at Hosei University and is a member of the Japan Center for Economic Research.

Toshiaki Tachibanaki is a professor of economics in the Institute for Economic Research at Kyoto University.

David A. Wise is the director of the NBER's program on aging and the John F. Stambaugh Professor of Political Economy at the John F. Kennedy School of Government at Harvard University. He is the editor or coeditor of thirteen volumes in the NBER series, all published by the University of Chicago Pres

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Aging Issues in the United States and Japan

The University of Chicago Press
Copyright © 2001 National Bureau of Economic Research
All right reserved.

ISBN: 978-0-226-62081-7

Chapter One
Choice, Chance, and Wealth Dispersion at Retirement

Steven F. Venti and David A. Wise

Why do some households have substantial wealth at retirement while others have very little? Indeed, why do some households with given lifetime earnings have substantial wealth at retirement, while other households with the same lifetime earnings accumulate very little wealth? In an earlier paper (Venti and Wise 1999), we evaluated the extent to which the different wealth accumulation of households with similar lifetime earnings could be accounted for by random shocks, such as health status and inheritances, that could reduce or increase the available resources out of which saving could be drawn. We concluded that only a small fraction of the dispersion in wealth accumulation within lifetime earnings deciles could be accounted for by random shocks and thus that most of the dispersion could be attributed to choice; some people save while young, others do not. We continue that analysis in this paper but with two additions: First, we attempt to evaluate the effect of investment choice on the accumulation of assets-in particular, how much of the dispersion in wealth can be accounted for by the choice between investment in the stock market and investment in presumably less risky assets such as bonds or bank saving accounts. Second, we attempt to understand the relationship between asset accumulation and individuals' assessment, just prior to retirement, of the adequacy of their saving and their saving behavior. This very exploratory analysis is an attempt to evaluate the usefulness of an experimental saving module administered to a subsample of Health and Retirement Study (HRS) respondents.

People, of course, accumulate different amounts of wealth in part because they have different earnings. We essentially set that dispersion aside by considering persons with similar lifetime earnings. Thus the discussion here is about the dispersion of asset accumulation among persons with the same lifetime earnings. Given lifetime earnings, we consider the importance of "chance" events versus the choice to save in determining asset accumulation. Over the course of a lifetime many events not directly under the control of the household may affect the accumulation of wealth. We refer to these as chance events. They may include both unfavorable shocks, such as health care costs, and positive shocks, such as inheritances.

We distinguish between such chance events, which affect the resources from which saving could be drawn, and the choice of how much to save of the resources that are available. In fact, we consider two components of saving choice: One is the choice to save or not to save; the other is saving mode or investment choice. Households with similar lifetime resources may invest in different assets that earn different rates of return. We might think of three groups: nonsavers, savers who invest conservatively and have low rates of return, and savers who invest in more risky assets and have higher rates of return. Persons who invest in bonds or bank savings accounts will have lower rates of return on average than those who invest in stocks.

Whether accumulated wealth is attributable to the choice to save rather than to chance can have significant implications for government policy. Many policies impose ex post taxes on accumulated assets. For example, elderly Americans who saved when young and thus have higher capital incomes when old pay higher taxes on Social Security benefits. Shoven and Wise (1997, 1998) show that those who save too much in pension plans in particular face very large "success" tax penalties when pension benefits are withdrawn. In addition, pension assets left as a bequest can be virtually confiscated through the tax system. The spend-down Medicaid provision is another example. The belief-perhaps unstated-that chance events determine the dispersion in wealth may weigh in favor of such taxes in the legislative voting that imposes them.

If, on the other hand, the dispersion of wealth among the elderly reflects conscious lifetime spending-versus-saving decisions-rather than differences in lifetime resources-these higher taxes may be harder to justify and appear to penalize savers who spend less when they are young. From an economic perspective, if wealth accumulation is random, taxing saving has no incentive effects. On the other hand, if wealth accumulation results from conscious decisions to save versus spend, penalizing savers may have substantial incentive effects, discouraging individuals from saving for their own retirement and limiting aggregate economic growth. It is important to understand that this paper is about the dispersion in the accumulation of assets of persons with similar lifetime earnings. The issue raised here is not about progressive taxation, but rather about differences in taxes imposed on persons who spend tomorrow versus today, given the same after-tax lifetime earnings.

The same issue arises with respect to return on investments. In this case, higher expected returns come at the expense of more risk when young, just as higher saving rates come at the expense of lower consumption when young. And, just as it may be harder to justify imposing higher taxes on older households who choose to consume less and save more while young, it may also be harder to justify imposing higher taxes on older households for assuming greater risk while young. In addition, of course, the higher taxes may discourage saving and limit economic growth. Again, the question raised here is not about progressive taxation; it is about the different taxing of persons who assume risk while young versus those who do not, given the same lifetime earnings.

We begin this paper by controlling for lifetime earnings as reported in individual Social Security records. Given lifetime earnings, we examine the distribution of wealth, finding a very wide dispersion in the distribution of accumulated saving, even among families with the lowest lifetime earnings. We then show that only a small fraction of the dispersion can be explained by individual circumstances that may have limited the ability to save out of earnings. For persons in the same lifetime earnings decile, we do this by comparing the unconditional dispersion in wealth at retirement with the dispersion after controlling for chance events that may have affected lifetime resources out of which saving could have been drawn. Then we attempt to determine how much of the dispersion might be attributed to investment choices. Here we are limited by available data, having to rely on the allocation of assets at the time of the HRS.

We conclude that the bulk of the dispersion in wealth at retirement results from the choice of some families to save while other similarly situated families choose to spend. For the most part, controlling for lifetime earnings, persons with little saving on the eve of retirement have simply chosen to save less and spend more over their lifetimes. It is particularly striking that some households with very low lifetime resources accumulate a great deal of wealth, and some households with very high lifetime resources accumulate little wealth. We find these saving disparities cannot be accounted for by adverse financial events, such as poor health, or by inheritances. While better control for individual circumstances that may limit resources could change somewhat the magnitudes that we obtain, we believe that the general thrust of the conclusions would not change.

We then consider the wealth that would have been accumulated if families in our sample had followed specific saving plans throughout their working lives. This exercise shows that even families with modest lifetime earnings would have accumulated substantial wealth had they saved consistently and invested prudently over the course of their working lives.

Finally, we consider how asset accumulation, again controlling for lifetime earnings, is related to individual attitudes about saving and saving adequacy.

1.1 The Data

The analysis is based on household data collected in the baseline interview of the Health and Retirement Study (HRS). The household heads were aged fifty-one to sixty-one in 1992 when the baseline survey was conducted. The analysis relies on the wealth of households at the time of the survey and on lifetime earnings, which is measured by historical earnings reported to the Social Security Administration. The Social Security earnings data are available for 8,257 of the 12,652 HRS respondents. Comparison of respondents for whom we do and do not have Social Security records suggests that they are very similar. Selected characteristics of the two groups are shown in table 1.1. The groups have almost the same household income, the same average age, and the same years of education; the same proportion are married; and almost the same proportion are female. A slightly larger proportion of those for whom we have Social Security records are HRS primary respondents (64 percent versus 60 percent).

Our analysis is based on household rather than individual respondent data, however. Historical earnings for a single-person household required only that Social Security earnings records be available for that person. But for a two-person household, it was necessary to have historical earnings for both persons in the household if both had been in the labor force for a significant length of time. The HRS obtained such data for 1,625 single-person households and for 2,751 two-person households, together comprising 4,376 of the 7,607 HRS households. Two additional sample adjustments were made. First, we retained households in which one or both members reported never having worked, even if the household member was missing a Social Security earnings record. We assumed zero earnings for such persons. Second, we excluded from the sample all households that included any member who had zero social security earnings and who reported working for any level of government for five (not necessarily consecutive) years. This latter restriction is intended to exclude households that have zero Social Security earnings due to gaps in coverage. The final sample includes 3,992 households.

The other important data component is wealth at the time of the survey. We need a complete accounting of assets, including personal retirement assets such as IRAs and 401(k) balances, other personal financial assets, employer-provided pension assets, home equity, and assets such as real estate and business equity. In most instances the value of each asset is reported directly. For non-pension assets, the HRS survey reduces nonresponse considerably by adopting bracketing techniques for important wealth questions.

In other cases asset values are not easily determined. The most important asset that is not directly reported is the value of benefits promised under employer-provided defined benefit pension plans. For persons who are retired and receiving benefits, this value can be approximated by using life tables to determine the expected value of the future stream of benefits. But for nonretired persons covered by a defined benefit plan-and for whom the benefit is not known-the value of future benefits can be only imprecisely imputed. The imputation process relies on the respondent description of pension provisions and is described in detail in the appendix. The HRS also surveyed employers about the features of respondent pensions, but those data are not used in this analysis.

1.2 Lifetime Earnings and the Wealth of Households

Social Security earnings form a good measure of lifetime labor earnings for persons whose earnings are consistently below the Social Security earnings maximum and who have been in jobs covered by the Social Security system. Historically, the Social Security earnings maximum has been adjusted on an ad hoc basis. The percentage of HRS respondents exceeding the maximum was at its highest in the early 1970s, peaking at 26.9 percent in 1971. The percentage has been below 10 percent since 1981 and was 4.8 percent in 1991.

For persons with incomes above the limit, reported Social Security earnings can significantly underestimate actual earnings. (In addition, as explained above, some persons may report zero Social Security covered earnings because they were employed in sectors not covered by the Social Security system, and we have excluded certain government employees from the sample.) Thus we do not rely directly on Social Security earnings to establish the level of lifetime earnings, but use reported Social Security earnings to rank families by lifetime earnings. Then we group families into Social Security earnings deciles, to which we refer hereafter as lifetime earnings deciles. We believe that the ranking by Social Security earnings represents a good approximation to a ranking based on actual total earnings, and that thus the deciles are a good approximation to actual lifetime earnings deciles. However, the problems caused by the earnings maximum and by zeros may make results based on the lowest and highest deciles less reliable than results based on the other deciles.

The mean present value of lifetime Social Security earnings within each decile is shown in table 1.2. To obtain lifetime Social Security income, the Consumer Price Index (CPI) was used to convert past earnings to 1992 dollars. The means range from about $36,000 in the lowest decile to just over $1,600,000 in the highest decile. Within the deciles the medians are essentially the same as the means.

The medians of assets, including Social Security wealth, are shown in table 1.3. For single persons Social Security wealth is the mortality-adjusted present value of benefits. For two-person families it is the sum of the mortality-adjusted present value of benefits calculated separately for each person. We have made no additional adjustments for joint mortality or survivorship benefits. Excluding Social Security, the median of total wealth ranges from $5,000 for families in the lowest lifetime earnings decile to almost $388,000 for families in the top lifetime earnings decile. Including Social Security wealth, the median ranges from $33,006 in the lowest decile to $577,107 in the top decile. Many assets are held by fewer than half of the households-indicated by zero medians. The 5th and 6th income deciles span the median of lifetime earnings, and the medians of total wealth in these earnings deciles are $105,166 and $144,188, respectively, excluding Social Security. Fewer than half of the families in these deciles have IRA or 401(k) accounts. Fewer than half have business equity or real estate. And the value of other assets is low. The median of employer-provided pension assets (excluding 401[k] accounts) is $4,000 for the 5th and $14,035 for the 6th lifetime income decile, not much higher than the median values of vehicles-$6,000 and $8,000 respectively. The median levels of financial assets are only $3,000 and $7,000 respectively. The largest component of the wealth of these families is home equity; the medians are $29,000 and $39,000, respectively.

The means of assets by lifetime earnings decile are shown in table 1.4. Comparison of the means and medians foretells the wide dispersion in assets, even among families with similar lifetime earnings. The means are typically much higher than the medians, and in some lifetime earnings deciles the mean of financial assets is more than ten times as large as the median.

1.3 The Distribution of Wealth for Given Lifetime Earnings

We discuss first the distribution of wealth within lifetime earnings deciles. We then consider how much of the dispersion can be accounted for investment choice and by chance shocks to resources. Personal chance events-like health status or children-that might be expected to limit the resources out of which saving might be drawn. Investment choice-e.g., between stocks and bonds-that may be expected to affect the accumulation of assets given saving out of available resources. To the extent that chance events and investment choices are correlated, however, there is of course no way to parcel out a separate effect for each of these factors. Thus we proceed in a way that indicates the maximum portion of dispersion that could be attributed to each.


Excerpted from Aging Issues in the United States and Japan Copyright © 2001 by National Bureau of Economic Research. Excerpted by permission.
All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.
Excerpts are provided by Dial-A-Book Inc. solely for the personal use of visitors to this web site.

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Table of Contents



1. Choice, Chance, and Wealth Dispersion
at Retirement

2. Household Portfolio Allocation over the Life Cycle

3. The Social Security System and the Demand
of Personal Annuity and Life Insurance:
An Analysis of Japanese Microdata, 1990 and 1995

4. An Empirical Invesitigation of Intergenerational
Consumption Distribution: A Comparison
among Japan, the United States, and
the United Kingdom

5. The Third Wave in Health Care Reform

6. Concentration and Persistence of Health
Care Costs for the Aged

7. The Effects of Demographic Change on Health and Medical Expenditures:
A Simulation Analysis

8. Choice among Employer-Provided Insurance Plans

9. Employees' Pension Benefits and the Labor Supply
of Older Japanese Workers, 1980s-1990s

10. The Motivations for Business Retirment Policies

11. Promotion, Incentives, and Wages

12. What Went Wrong with the 1991-92 Official
Population Projection of Japan?

Authors Index
Subject Index

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