The Decline of Defined Benefit Retirement Plans and Asset Flows

Transcription

1 Preliminary and Partial Draft Please Do Not Quote The Decline of Defined Benefit Retirement Plans and Asset Flows James Poterba MIT and NBER Steven Venti Dartmouth College and NBER David A. Wise Harvard University and NBER Prepared for the 8th Annual Joint Conference of the Retirement Research Consortium Pathways to a Secure Retirement August 1-11, 26 Washington, D.C. This research was supported by the U.S. Social Security Administration through grant #1-P to the National Bureau of Economic Research as part of the SSA Retirement Research Consortium. The findings and conclusions expressed are solely those of the author(s) and do not represent the views of SSA, any agency of the Federal Government, or the NBER.

2 Just two or three decades ago, employer-provided defined benefit (DB) pension plans were the primary means of saving for retirement in the United States. But since that time, 41(k) and other personal retirement accounts have become the principal form of retirement saving in the private sector. Defined benefit plans have remained an important form of retirement saving for federal employees and for state and local employees, although even for these employees personal retirement accounts are becoming increasingly important. In 2, about 87 percent of private retirement plan contributions were to 41(k) and other personal accounts, although the contributions to personal accounts dropped to 82 percent of the total in 21 when there was a large increase in contributions to DB plans. Contributions to personal retirement plans accounted for only 12 percent of total contributions to Federal pension plans in 2, but had increased to 17 percent by 24. In this paper we describe the decline in defined benefit plans and assess the implications of the decline for the flow of assets into and out of DB plans over the next four decades. The paper is intended to be a companion to our paper on New Estimates of the Future Path of 41(k) Assets -- Poterba, Venti, and Wise (25). Both papers will provide input to an analysis of Demographic Change, Retirement Saving, and Financial Market Returns described in Poterba, Venti, and Wise (25). In section 1, we present a cohort description of the decline in the participation rate of employed persons in DB plans over the past two decades. Then we describe a series of analyses that provide the basis for projections of future assets in DB plans. We begin in section 2, with a cohort description of the dollar amount of pension benefits received by persons over age 55, and we explain our projections of DB benefits in the future. In section 3, we present a parallel cohort description of the probability of receipt of DB benefits. To project the probability of receipt of DB benefits after retirement by younger cohorts, we rely in part on the DB plan participation rate prior to retirement for these same cohorts. Because the benefit receipt data (data on benefits received) pertain to the population of older persons, we need to develop DB plan participation data for the population as a whole rather than employed persons, discussed in section 1. Thus in section 4 we consider the likelihood that a person in the population participates in a DB plan. In section 5, we combine the information described in sections 2, 3, and 4 to ` 1

3 develop projections of the total value of DB benefits in future years. In section 6, we show projections of the DB pension wealth of cohorts retiring between 1982 and 24 and, for each cohort we compare DB wealth to projected 41(k) assets (based on our earlier paper). In section 7, we consider projections of the total value of assets in DB trust funds. It is the change in the assets in DB trust funds combined with the change in the assets in personal retirement accounts that may affect the rate of return on the investments of future generations of retirees. 1. Participation of Employees in DB Plans DB participation data were obtained from the Survey of Income and Program Participation (SIPP) for the years 1984, 1987, 1991, 1993, 1995, 1998, and 23. Our analysis here and in subsequent sections of the paper is based on organization of the data by cohort. We sometimes define cohorts by the age of the cohort in 1984 and sometimes by the year in which the cohort attains age 65. When referring to the cohort age in 1984, the age is proceeded by C. When referring to the year the cohort attains age 65, the year is proceeded by A. Thus, for example, C65 and A1984 both identify the same cohort. Figure 1-1 shows the data for selected cohorts. It is clear that the DB participation rate of employed persons declined consistently with successively younger cohorts. For example, at age 45, the participation rate of the C45 cohort that attained age 45 in 1984 was about 43 percent. But the participation rate of the C27 cohort that attained age 45 in 22 was about 29 percent. Comparisons at ages 31, 37, and 55 show similar differences. Not only are there differences between cohorts, with younger cohorts having successively lower participation rate at all ages, but there is also a within-cohort decline in the participation rate with age. The within-cohort decline with age for older cohorts is likely explained in part by retirement. DB plans typically provide incentives to retire early and DB participants on average retire earlier than persons without these plans; some participants may retire as early as age 55. But even for younger cohorts there is typically a within-cohort decline in DB participation rates with age. For, comparison, similar cohort data for 41(k) plans (including other personal retirement plans as well, are shown in Figure 1-2 At age 45, the 41(k) participation rate ` 2

4 of the C45 cohort that attained age 45 in 1984 was only 8 percent. But the participation rate of the C25 cohort that attained age 45 in 22 was about 47 percent Figure 1-1. DB participation rate of employed persons, selected cohorts C C Participation Rate % C13 C Age Participation Rate % Figure (k) participation rate of employed persons, selected cohorts C C C45 C Age ` 3

5 The cohort data illustrated in Figures 1-1 allow comparison of the participation rate of some cohorts at a given age say 45 but these data alone do not allow comparison of very young and very old cohorts. To do this we need to project forward the future participation rates of younger cohorts at older ages and project backwards the participation rates of older cohorts at younger ages. As explained in the Working Paper version of this paper, we make these projections by fitting the participation data with a probit model and then using the estimated parameters to predict outside range of the observed data. The projected data for younger cohorts suggest, for example, that for the cohort that is born in 1984 (the C cohort), the DB participation rate will never exceed 19 percent, with the maximum at about age 35. As discussed below, to project future assets in DB plans, we need to consider the proportion of all persons that participates in a DB plan. In section 4 we return to this issue. 2. DB Pension Benefits of Recipients and Projections We now describe a series of analyses that provide the basis for projections of future assets in DB plans. A more detailed description is presented in the Working Paper version of the paper. We begin in this section with a cohort description of the dollar amount of DB benefits received by all persons over 55 and then describe how we project benefit amounts in the future. In section 3, we present a parallel description of the percent of older persons that receives DB benefits. Data on DB benefits received, like the participation data shown above, are obtained from SIPP waves for the years 1984, 1987, 1991, 1993, 1995, 1998, and 23. And, as with the participation data, we first present a cohort description of the observed data. We then fit the observed data and use the fitted model to project benefits outside the range of the observed data. Figure 2-1 shows the actual data for the level of benefits for selected cohorts. The data are for all persons age 55 to 85 and thus include persons who are receiving benefits from federal or state and local retirement programs, as well as from private sector pensions plans. Two features of the data stand out. One is that benefits of younger cohorts are much greater than benefits of older cohorts. For example, the benefit at age ` 4

6 6 for the cohort that attained that age in 1984 was about $6 per month; the benefit for the cohort that attained age 6 in 23 (this comparison is circled in the figure) was about $1,6 per month. The other feature of the data is that within-cohort benefits increase with age. In part this results from the indexing of benefits from some DB plans, especially federal and state and local plans. In addition, private employer plans, which are typically not indexed, sometimes grant cost-of-living increases on an ad hoc basis after retirement. Figure 2-1. DB benefit reciept for selected cohorts Dollars per Month Age We fit the data using a piecewise linear specification for age and allowing for separate intercepts for each cohort (cohort effects). We then use the estimated parameters to project benefits forward for the younger cohorts and to project benefits backward for the older cohorts. There are not enough SIPP observations to reliably estimate cohort effects for cohorts younger than A212 or older than A197. The most important projections are for cohorts younger that the A212 cohort. We make these projections by using the estimated age effects, together with extrapolation of the estimated year-to-year change in cohort effects. Over the 1982 to 23 period there is a close association between the four-year moving average of the change in the estimated cohort effects and the Social Security Administration average wage index. After 23, the SSA assumes a ` 5

7 wage increase of 3.9 percent annually. On average the change in the cohort effects was only about 2.9 percent over these years. Based on these and other data we have assumed that for younger cohorts benefits will increase at 3.9 percent for each successively younger cohort, the same as the SSA intermediate assumption for the average wage index. 3. The Receipt of DB Pension Benefits In section 2 above, we considered the dollar amount of the DB benefits of persons who received DB benefits at each age. To obtain an estimate of the total dollar amount of DB benefits for all persons, we need also to determine the proportion of persons who receive benefits at each age. We consider the probability of benefit receipt in this section. We again begin with cohort data (not shown) on the percentage of persons receiving DB benefits at each age. Two features of the data are evident. First, the cohort effects are rather small, with the exception of the older cohorts. In other words, the profile of benefit receipt by age is about the same for all the cohorts represented in the SIPP data (with the exception of the oldest cohorts). For example, among cohorts observed at age 7, the probability of receipt of benefits ranges from about 45 percent for the youngest cohort to 49 percent for the oldest cohort. Second, the age at which the maximum percent of persons receive benefits is about 7. To project benefit receipt for future (younger) cohorts, that are not observed in the SIPP data, we assume the age-benefit-receipt profile observed in the SIPP data continues to apply. However, we allow this profile to shift (downward) for younger cohorts. To do this we first estimate age and cohort effects for cohorts observed in the SIPP. Then we predict benefits for younger cohorts, assuming that--except for the cohort effects--the age-benefit-receipt profile is the same for younger cohorts as it has been for older cohorts observed in the SIPP. Because we cannot reliably estimate cohort effects for cohorts younger than A23, we assume that the benefit receipt rates of successively younger cohorts follow the same pattern as the DB participation rates of these same cohorts when they were in the labor force. The assumption is that if fewer persons in a particular cohort participated when young, then fewer persons will receive benefits after retirement. We do this by ` 6

8 first calculating the maximum DB participation rate over ages for each cohort. We use this maximum rate to predict benefit receipt when the cohort is retired. We use yearto-year changes in the maximum DB participation rate, and the 23 fitted age-benefit receipt profile, to project benefit receipt for cohorts A24 through A26. Before presenting these projections, we describe the population-based DB participation rates that are required to make the calculations. 4. Population-Based DB Participation Rates The calculations described in the section above require an estimate of the maximum DB participation rate for each cohort. To predict future participation rates for this purpose, however, we must consider not the participation rate of employed persons (estimated in section 1), but rather the likelihood that a person in the population participates in a DB plan. This is necessary to yield participation rates that correspond to the benefit receipt rates that are. That is, the SIPP data we use pertains to the probability that a person in the population receives DB pension benefit. The person-based participation rates and the population-based rated can differ substantially. To see this, note that the percent of population that participates in a DB plan at age a is given by ( ) = ( ) DB / P E / P Pr[ DB E ] The last term, Pr [ ] a a a a a a DB E, declined between 1984 and 23, but the fraction of the population employed( E/ P) increased between 1984 and 1998 but fell in The a percentage of employed persons participating in a DB plan declined from 39.4 percent to 29.7 percent. The overall effect of these trends is that cohort effects are smaller when all persons are used as the base than when employed persons are used as the base. For example, at age 45 the difference in the participation rates of cohorts 27 and 45 is about 13 percentage points based on those employed but only about 1 percentage points based on all persons. 1 The employment to population ratio for persons 16 and over reported by the BLS shows an increase from 59.5% in 1984 to 64.1% in 1998 and then a drop to 62.3% in 23. The SIPP data we use are for ages 25 to 64. ` 7

9 Figure 4-2. Actual versus fitted profiles for selected cohorts (persons) Participation Rate % Age As with the participation based on employed persons, we fit the population-based participation data using a probit model. Selected fitted cohort profiles together with the corresponding cohort data are shown in Figure 4-2. We judge that the fitted profiles represent the data quite well. We then use the model estimates to predict populationbased participation rates at all ages (25 to 64) for each of the cohorts for which we are able to estimate cohort effects. We predict at all ages for each cohort because we want to determine the age at which the participation rate is at a maximum for each of the cohorts. Predicting at older ages for the younger cohorts suggests that by the time these cohorts reach retirement age, their participation in DB plans will be very low. For example, based on these predictions the DB participation rate of persons in the C11 cohort will be only 8.8 percent when that cohort attains age 55 (cohort C11 attains age 65 in 238). 5. Projected Benefits Paid We want to project the total value of benefits in future years. To do this we combine estimates of the level of benefits in section 2 with estimates of the probability of benefit receipt in section 3. For cohorts that attain age 65 after 23 we use populationbased estimates of DB participation to predict pension receipt after retirement. We first use the estimates of benefit receipt for cohorts A1982 to A23 to predict the percent of ` 8

10 each of these cohorts that receives benefits at age 7. As discussed in section 3, for these cohorts there are a sufficient number of SIPP observations to obtain reasonable estimates reliable estimates of benefit receipt. These probabilities are graphed in Figure 5-1 (the blue bars). To project benefits at age 7 for younger cohorts (A24 to A24), we use additional data on population-based DB participation rates, discussed in section 4. From these data, we have calculated the maximum participation rates, over ages 25 to 64, for each cohort. We use the maximum participation rate to predict the probability of benefit receipt at age 7 for cohorts A24 and younger. We assume that the year-to-year percent change in the probability of receipt of benefits at age 7 is the same as the yearto-year percent change in the maximum DB participation rate. For cohorts younger than A24 a two percent decline is assumed, an extrapolation of the decline for cohorts A231 to A24 (shown in red in Figure 5-1). From the percent that receives benefits at age 7, we predict the percent that that receives benefits at each age, as described above. These estimates are shown for selected cohorts in Figure 5-2. Figure 5-1. Percent receiving benefits at age 7, by cohort (blue is fitted SIPP estimate and red is projected) Percent Age attains age 65 ` 9

11 6 Figure 5-2. Projected percent receiving benefits for selected cohorts attaining age 65 in years 1982 through 24 (blue is fitted SIPP estimate and red is projected) A2 5 4 Percent 3 2 A24 1 David: Note that 1982 is not the highest Age 6. Present Value of DB benefits at 65 From the projected data on benefits, we have calculated the average present value at age 65 of future DB benefits of all persons, including those that do not receive DB benefits. Results are presented for each cohort and have been converted to constant year 2 dollars. A real discount rate of 3 percent and average SSA age-specific survival probabilities are assumed. We have also calculated the average present value of DB benefits at age 65 of persons who receive DB benefits. Both series are graphed in Figure 6-1. We assume that the benefits of successive cohorts will increase 3.9 percent annually ` 1

12 Figure 6-1. Present value DB benefits at age 65: all persons and persons with a DB year 2 dollars 2, 18, 16, 14, 12, 1, 8, 6, 4, 2, Year cohort attains age 65 All persons Persons with DB in the future, while the assumed discount rate is only 3 percent. Thus the top profile shows that the average present value of DB benefits for recipients will be greater for future than for current cohorts. However, the lower profile shows that the PV of DB wealth, averaged across all persons, will decline in the future as fewer persons participate. The projections show that DB wealth peaks in 23 at about $73, and falls to about $5, by For comparison, the value of 41(k) assets (reported in Poterba, Venti and Wise 25) are shown for all persons and for persons with 41(k) assets in Figures 6-2 and 6-3 respectively. Average 41(k) assets of all persons reach the average PV of DB benefits of all persons in 21 when both are about $64,. Thereafter assets in 41(k) accounts continue to grow, reaching about $125, in 22, $214, in 23, and $48, in 24. The assets of persons with 41(k) accounts reach the level of the PV of DB benefits for persons who receive benefits in 213. Thereafter the 41(k) assets continue 2 These estimates indicate that in 2 the average of DB benefits over all persons was $67,795. Based on HRS data, Johnson, Burman and Kobes (24), estimate that the mean present value of employer sponsored pension income for persons 65 to 69 in 2 was $5,23. Our estimate should be larger than theirs because we include persons of all ages. In particular, average benefits increase with age because death rates selectively leave in the sample persons with higher benefits, and because of ad hoc cost of living increases and indexed benefits in many government plans. ` 11

13 to grow, reaching about $217, in 22, $349, in 23, and $549, in 24. For persons with DB plans the average present value of benefits also continues to grow, reaching $187, by 24. Figure 6-2. Present value DB benefits at age 65 and 41(k) assets at age 65, all persons 6, 5, year 2 dollars 4, 3, 2, 1, Year cohort attains age 65 PV of DB benefits 41(k)assets ` 12

14 Figure 6-3. Present value of DB benefits at age 65 for persons with a DB and 41(k) assets at age 65 for persons with a 41(k) 6, 5, year 2 dollars 4, 3, 2, 1, Year cohort attains age 65 PV of DB benefits 41(k)assets Assets in DB Trust Funds and Total Benefits Paid This work will feed into an analysis of future changes in the demand for financial assets and, in turn, on the potential effect of changes in asset demand on future rates of return. We made similar calculations with respect to 41(k) and other personal retirement account assets in Poterba, Venti, and Wise (25). This DB component, together with the 41(k) component will, we believe, provide a reasonable estimate of the change in asset demand due to changing demographic trends. One way to predict future assets in DB plans is to predict total benefits paid in future years and then to suppose that assets held by DB plans in each year are sufficient to pay the present value of these future obligations. The results shown here are based on this approach. We believe, however, that this approach should yield fully-funded current assets that are greater than actual assets. A second way is to predict future assets based on an extrapolation of current assets compared to fully-funded liabilities. As described above, we have projected the DB benefits of recipients by cohort and we have projected the probability of benefit receipt by cohort. From these data, together with demographic forecasts of the number of persons at each age in each year in the future, we can calculate the estimated total amount of DB benefits paid each year. ` 13

15 Figure 7-1, shows these totals for the years 1982 to 24, together with a constructed series that sums together private sector DB benefits, DB benefits paid to federal employees, and all benefits paid to state and local employees. 3 Figure 7-1. Projected total benefits paid compared to actual benefits paid, 1982 to 24 4, 35, 3, 25, 2, 15, 1, 5, Projected total 1995 Actual total The projected totals are close to the actual totals in the early years but fall short in the later years. The discrepancy is due in part at least the growing importance of 41(k)- like accounts in the state and local government plans. Thus we believe that the comparison lends credence to our estimates, based on SIPP data, for these years. Our forward projections, of course depend on the assumptions we have made to project benefit levels and benefit receipt for future cohorts not represented in the SIPP data. Our projected estimates of total DB benefits in future years are shown in Figure 7-2 below, in year 2 dollars. Total benefits paid from DB plans continue to increase until 227. The profile turns down eventually because the probability that benefits are received (at age 7) reaches a maximum with the cohort that attains age 65 in 27, 3 The private sector data are from the form 55 data and exclude benefits paid directly by insurance carriers. Federal DB benefits include payments made by the Civil Service Retirement System, the Federal Employees Retirement System, and the Military Service Retirement System. DB and DC benefits are not reported separately for state and local plans. The data used here include DC as well as DB benefits. Thus our projected DB benefits should be somewhat greater than sum of these reported government and private sector benefits. ` 14

16 although this cohort continues to receive benefits after 27. From a peak of $435, in 227, the real value of total benefits paid declines modestly to $392, by 24. As shown in Figures 6-2 and 6-3, the real level of benefits increases through the end of the projection period, so the decline in total benefits in Figure 7-2 is driven by the decline in the probability of benefit receipt. Figure 7-2. Projected benefits paid: by year 5, 45, millions of year 2 dollars 4, 35, 3, 25, 2, 15, 1, 5, Year For comparison, projected benefits paid from DB plans are graphed together with the projected amounts withdrawn from 41(k) plans in Figure Benefits from DB plans exceed withdrawals of 41(k) assets until 229. After 229 the value of DB benefits falls each year and 41(k) withdrawals increase rapidly thereafter. 4 The 41(k) withdrawals shown in this figure are projected amounts disbursed when account owners are alive and do not include balances that remain in accounts when account owners die. We are in the process of refining our withdrawal assumptions. ` 15

17 Figure 7-3. DB benefits paid vs 41(k) withdrawals 1,2, millions of year 2 dollars 1,, 8, 6, 4, 2, Year DB payouts 41(k) payouts (alive) Suppose that in each year assets held by DB plan sponsors were equal to the present value of these future obligations. If future liabilities are discounted at 3 percent and firms have a twenty year planning horizon, the present value of liabilities each year is shown in Figure 7-4. The figure also shows two series representing total assets in DB plans. The first is from the Flow of Funds accounts that include private sector DB plans and the value of assets in DB and DC plans for government sponsors. The second series is composed of private sector DB assets from Form 55 reports, federal DB assets from various federal agency annual reports, and the sum of DB and DC assets for state and local governments from Census reports. Actual assets, for the years they are available, are substantially below this calculation of the present value of liabilities in all years, with the possible exception of It is perhaps not surprising that actual assets are less than our estimates of the assets employers would have to hold to fully fund projected liabilities (based on our assumptions). Private sector plan sponsors have substantial latitude in the assumption of interest rates, investment returns, when benefits will be paid, and other features that ` 16

18 determine funding levels. 5 There are even fewer restrictions on the funding of federal, state, and local plans and many are thought to be substantially under-funded. Figure 7-4. Present value of DB liabilities vs DB assets 7,, millions of year 2 dollars 6,, 5,, 4,, 3,, 2,, 1,, Year Flow of Funds assets F55+EBRI+Census assets PV of future liabilities 8. DB and 41(k) Assets Combined How will assets in DB and 41(k) plans combined change in future years? In our prior work we projected assets held in 41(k) plans. These 41(k) assets, DB plan liabilities ( fully-funded DB assets) and the sum of both series are shown in Figure 8-1. We also consider total contributions to DB and 41(k) plans combined and total withdrawals from DB and 41(k) plans combined. Figure 8-2 below shows contributions to 41(k) plans, the annual change in DB liabilities (a rough measure of contributions to a fully funded DB plan) and the sum of these contributions. Projected total contributions are relatively flat between 2 and 24. Withdrawals from 41(k) plans, DB benefits paid, and the sum of the two are shown in Figure 8-3. The sum of benefits paid grows rapidly through Bergstresser, Desai, and Rauh (26) discuss these issues in the context of earnings manipulation. Bradley Belt (25) estimated that private DB plans were underfunded by $45 billion in 24. ` 17

19 18,, 16,, Figure 8-1. Projected assets: 41(k), DB, and combined millions of year 2 dollars 14,, 12,, 1,, 8,, 6,, 4,, 2,, Year (k) DB Combined , Figure 8-2. Projected contributions: 41(k), DB (change in liabilities), and combined millions of year 2 dollars 5, 4, 3, 2, 1, ` Year Change in DB liabilities 41(k) contributions combined

20 Figure 8-3. Projected withdrawals: 41(k), DB (benefits paid), and combined millions of year 2 dollars 1,6, 1,4, 1,2, 1,, 8, 6, 4, 2, year DB benefits paid 41(k) withdrawals combined Figure 8-4 shows the total projected contributions to and withdrawals from DB and 41(k) plans combined. Figure 8-5 shows withdrawals minus contributions for DB and 41(k) plans combined. Withdrawals exceed contributions after 219 and the excess reaches about $.56 trillion by 24 (in year 2 dollars). 6 Whether demographically induced changes in DB and DC asset levels will have an appreciable effect on financial rates of return will depend upon the size of swings in DB and DC assets relative to the size of the total asset market. The greatest concern of some analysts seems to be the possible effect of demographic trends on equity markets. We will consider the possible effect in subsequent analysis. For now, an example may provide some intuition. 6 Schieber and Shoven ( 1997) consider the implications of population aging for private pension fund saving and project saving as a percent of payrolls. Although their projection method is very different from ours, their conclusions seem rather similar. Their projections suggest that total private pension withdrawals will exceed contributions beginning in 224 and would thus cease being a net source of saving. ` 19

21 The effect depends on the size of the change in net withdrawals of pension equities relative to the value of the total equity market. Between 1965 and 25 the real value of the equity market increased by 4 percent on average. If this rate were to continue (on average) until 24, the value of the equity market would increase from $16.1 trillion in 25 to 63.7 trillion in 24 (in 2 dollars). Based on our projections, equities in pension plans would increase from $4.6 trillion to $9.1 trillion over this same period (in 2 dollars), but the pension plan share of the total equity market would decline from about 28 percent to about 14 percent. 7 In 25, net pension plan withdrawals (withdrawals minus contributions) from the equity market are about -$.9 trillion. By 24, net withdrawals would be about $.5 trillion, or about.8 percent of the total equity market. The magnitudes seem rather small to us. 1,6, Figure 8-4. Projected contributions and withdrawals: DB and 41(k) plans combined 1,4, millions of year 2 dollars 1,2, 1,, 8, 6, 4, 2, Contributions Year Withdrawals Assuming that 6 percent of pension assets are in equities and that DB plans are 75 percent funded. ` 2

22 1,, Figure 8-5. Projected withdrawals minus contributions: DB and 41(k) plans combined millions of year 2 dollars 8, 6, 4, 2, -2, Year Summary The initial motivation for undertaking this analysis was to consider the potential effect of demographic trends on the demand for financial assets and, in turn, on rates of return in financial markets. This paper on DB pension plan assets is a companion paper to our earlier paper on 41(k) assets. We have described the rather dramatic decline in DB participation in the past three decades and we have assessed the implications of this decline for the flow of funds into and out of DB trust funds over the next four decades. We have compared the results for DB assets with our prior results on 41(k) assets. We find that the projected withdrawals minus contributions to DB and 41(k)-type plans combined rises from approximately -$.9 trillion in 25 to about $.5 trillion by 24 (in year 2 dollars). This amount, however, seems to us to be small relative to the likely size of the total equity market by 24. Thus we suspect that the effect on rates of return is unlikely to be large. Subsequent formal analysis will help to clarify the magnitude. We also projected the present value of DB benefits at age 65 for cohorts who reach age 65 in each year from 1982 to 24. These estimates are of considerable interest independently of the effect of the changing level of retirement assets on financial ` 21

23 market rates of return. Our projections suggest that the average, over all persons, of the present value of DB benefits (in year 2 dollars) at age 65 will reach a maximum (at $72,637) in 23. The present value of benefits at 65 for persons with a DB plan also reached a maximum in 23 (at $153,561). Comparable data for 41(k) plans show that the value of 41(k) assets surpasses the present value of DB benefits for all persons in 211 and for persons with DB or 41(k) plans in 212. Thereafter the value of 41(k) assets grows rapidly, reaching levels much greater than the present value of DB benefits. Over all persons, the value of 41(k) assets in 23, for example, will be over three times as great as the maximum value of DB assets attained in 23. Based only on persons with a DB or a 41(k) plan, the average of 41(k) assets at 65 will be over twice as large as the maximum of DB assets attained in 23. Although our findings show that retirement saving through 41(k)-type plans in future years will be much greater than retirement saving in DB plans has been, 41(k) plans as well as DB plans have at least one important limitation. Like DB plans, 41(k) plans are often not provided in small firms with predominantly low-income employees. Perhaps the greatest improvement to the personal retirement plan system would come from policies to hasten the penetration of 41(k) plans to lower-income employees. References Belt, Bradley D, Testimony Before the Committee on Education and the Workforce, United States House of Representatives, March 2, 25. Bergstresser Daniel, Mihir A. Desai and Joshua Rauh Earnings Manipulation and Managerial Investment Decisions: Evidence from Sponsored Pension Plans ; Quarterly Journal of Economics, vol 121, no. 1, 26 Poterba, James, Steven Venti, and David A. Wise, 24, The Transition to Personal Accounts and Increasing Retirement Wealth: Macro and Micro Evidence, In D.A. Wise, (ed.), Perspectives on the Economics of Aging, University of Chicago Press. Poterba, James M., Steven F. Venti, and David A. Wise, "Demographic Change, Retirement Saving, and Financial Market Returns." Working Paper Prepared for the 7th Annual Joint Conference of the Retirement Research Consortium, "Creating a Secure Retirement System," August 11-12, 25, Washington, D.C. Schieber, Sylvester and John Shoven. The Consequences of population Aging for Private pension Fund Saving and Asset Markets, in M. Hurd and N. Yashiro (ed.) The Economic Effects of Aging in the United states and Japan. The University of Chicago Press, William Wiatrowski, Documenting Benefits Coverage for all Workers, USDOL/BLS, December 25. ` 22