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In this paper, we develop a measure of household resources that converts total financial and non-financial assets, plus annuity-like assets (mainly, Social Security and defined-benefit pensions) into an expected annual amount of wealth per person in retirement. We use this measure, which we call “annualized comprehensive wealth,” to investigate spend-down behavior among a panel of older households in the Health and Retirement Study (HRS) from 1998 to 2006. Our analysis indicates that for most retired households, comprehensive wealth balances decline much more slowly than their remaining life expectancies, so that the predominate trend is for real annualized wealth to rise significantly with age over the course of retirement. Comparing the estimated age profiles for annualized wealth with profiles simulated from several different life-cycle models, we find that a model that takes into account uncertain longevity, random medical expenses, and intended bequests lines up best with the broad patterns of rising annualized wealth in the HRS.

The ability to finance consumption in old age depends not only on the total amount of resources at the onset of retirement, but also, crucially, on how quickly or slowly those resources are spent after retirement. To provide a new empirical perspective on spend-down patterns, we construct a measure of the total resources available per expected year of life for a panel of retired households in the Health and Retirement Study (HRS) from 1998 to 2006. We call our measure “annualized comprehensive wealth.” Our measure is comprehensive because in addition to net worth as it is usually defined–the sum of financial and non-financial assets net of debt–it also includes the value of Social Security benefits, defined-benefit pensions, and, for eligible recipients, transfer payments such as Food Stamps and Supplemental Security Income. For many retirees, these additional items constitute a sizable fraction of total resources. Our measure is an annualized concept in the sense that it measures the amount of wealth that is available for each expected year of remaining life and for each person in a retired household. In examining this measure of retirement wealth, we were motivated by the following reasoning. Annualized comprehensive wealth measures the constant amount that a retired household could afford to spend, in expectation, every year until they die. If the micro-data showed a strong tendency for annualized comprehensive wealth to either fall or rise substantially in retirement, we would probably want to know why. Our paper adds to a large and growing body of research on the evolution and adequacy of retirement wealth.1 Most directly, our paper is related to two studies that highlight the importance of precautionary saving for explaining the wealth holdings of older Americans (Palumbo, 1999 and De Nardi et al., 2008). These studies each find that wealth balances do not decline as quickly as standard life-cycle models would predict but that a slow decumulation pattern can be explained (at least partly) by the precautionary effects of uncertain out-of-pocket medical costs. The key contribution of our study is to look at a similar set of questions through the lens of annualized wealth, which we argue provides a more direct measure of the evolution of household resources. While an annualized concept of wealth is not itself an entirely new idea, as far as we know, we are the first to examine annualized wealth in the context of the life-cycle model.2 What are the advantages of looking at annualized wealth as opposed to wealth balances alone? First, it helps us identify the direction of change in a household's ability to finance future spending in retirement. Whereas a decline in wealth balances can be consistent with either an increase or a decrease in the amount of resources available per expected remaining year of life, a decline in annualized wealth implies an unambiguous contraction. Second, annualized comprehensive wealth is a measurement concept that could help distinguish between reductions in consumption due to insufficient resources (in which case we would expect both annualized wealth and consumption to be low) and the consequences of other motives, such as precautionary savings or intentional bequests (in which cases we would expect annualized wealth to exceed consumption). Whether annualized wealth rises or falls during retirement therefore can provide important clues that can help in sorting out the underlying causes of spending and saving behavior in retirement. Finally, because we generally lack household-level panel data on wealth and consumption changes over retirement, annualized wealth provides a bridge between wealth balances and what those balances imply for annual consumption possibilities.3 Developing that bridge is one of the principle motivations and contributions of the current study. Our analysis of the HRS panel documents strongly rising patterns of annualized wealth in retirement. We find that the median value of annualized comprehensive wealth for the cohort of households aged 70 to 75 years in 1998 rises significantly in retirement, from about $32,800 per person per year in 1998 to about $42,200 per person per year in 2006—a net increase of nearly 30% in just eight years. That is, comprehensive wealth balances in the HRS tend to decrease much more slowly than life expectancy shortens in old age. Our regression-based estimates of the age profile through the full span of retirement indicate that the median surviving household tends to see its annualized comprehensive wealth climb from $25,600 per person per expected year of life at age 65 to more than $50,000 by age 90.4 As in other studies of household savings, we find considerable heterogeneity in the evolution of household wealth, with annualized wealth falling for some households and rising for others. The distribution, however, is heavily tilted toward increases in annualized wealth. Indeed, we estimate that nearly one-half of older households saw their annualized comprehensive wealth rise by more than 25% from 1998 through 2006, while about one in eight experienced a decrease of 25% or more over the same time period. Further, this distribution of outcomes is surprisingly similar when we look across retired households by marital status and even by household income. We also find (to varying degrees) patterns of increasing median annualized wealth across race, education, and health groups. Looking at wealth components, we find that both financial and non-financial wealth rose in annualized terms over the sample period.5 Although some of the increase in non-financial wealth in the HRS panel seems to have been accounted for by large capital gains accruing to housing between 1998 and 2006, the data indicate that we would have estimated a net increase in annualized wealth in retirement even if those unusual gains were absent. Why might households draw down their wealth balances so slowly relative to life expectancy? To consider some possible explanations, we simulate several specifications of life-cycle models of retirement consumption, including several elements that have been emphasized in previous studies: uncertain longevity (Yaari, 1965, Davies, 1981, Hubbard, 1987 and Hurd, 1989), random (and potentially large) out-of-pocket medical expenses (Palumbo, 1999, French and Jones, 2008 and Anderson et al., 2004), and explicit bequest motives (Kotlikoff and Summers, 1981, Hurd, 1987, Hurd, 1989, Bernheim, 1991, Laitner and Juster, 1996, Dynan et al., 2002, De Nardi, 2004 and Kopczuk and Lupton, 2007). We benchmark our model specifications to the HRS data on a household-by-household basis and compare simulated annualized wealth trajectories with the empirical trends. We find that although models incorporating either random medical expenses or altruistic bequests can generate upward-sloping profiles of annualized wealth, the simulated profiles are generally much flatter than those evident in the HRS panel data. Rather, the strength of the overall increase in annualized comprehensive wealth seen in the HRS lines up best with model simulations that incorporate both of these saving motives, in combination with uncertain longevity. In particular, we find that the prospect of large medical expenses induces retirees to build a precautionary buffer early on, while a desire to leave a bequest leads them to maintain “excess savings” toward the end of life, and the size of these effects is not far from the patterns in the HRS. We also find that while conventional life-cycle specifications may do a good job explaining some general tendencies of annualized wealth changes for the median household, they are less successful at matching the heterogeneity in wealth trajectories across individual households. The key contribution of our modeling approach is to investigate the behavior of annualized wealth (rather than wealth levels) in standard specifications of stochastic life-cycle models. Doing so not only allows us to connect the simulation findings to our empirical measures; it also highlights how the evolution of consumption (what we would ideally like to measure) and annualized wealth (what we are actually able to measure) is likely to differ depending on the relative importance of bequests and precautionary saving at the tail end of the life cycle.

By examining the trajectory of annualized comprehensive wealth–a measure of total resources per person per expected remaining year of retirement–our analysis brings some saving patterns into relief that would otherwise be difficult to discern. Our primary empirical finding from the HRS is that annualized comprehensive wealth tends to rise with age in retirement, reflecting the tendency for wealth balances to decrease more slowly than remaining life expectancies shorten. And the magnitudes of the typical increases in annualized wealth are significant. We find this pattern of increasing annualized wealth over retirement for most types of households and for the major components of comprehensive wealth. In addition, we estimate that a much larger share of retirees experience a considerable increase in annualized comprehensive wealth over the eight years covered by our HRS sample (1998 to 2006) than experience a significant decline (45% to 15%). It is reasonably well known that retirees in the lower range of the income distribution (conditional on their age and marital status) rely almost exclusively on DB pension benefits, Social Security benefits, and other government transfers to finance spending. Although these sources do not constitute a high level of comprehensive wealth, their annuity-like payout scheme means that they can finance a more or less constant path of outlays through retirement. While annuity-like benefits are also an important source of wealth for retirees in the middle- and upper-income groups, these retirees also tend to have significant financial and non-financial wealth. A new finding from our analysis is that, for the median retiree in the middle- and upper-income groups, annualized comprehensive wealth tends to rise over retirement. One might have expected wealth balances to fall more or less in line with their decreasing life expectancy at older ages—after all, this is the trajectory that would be predicted by the simplest life-cycle model of consumption in retirement. To begin to gauge what factors could lie behind the tendency for annualized comprehensive wealth to rise in retirement, we compare the empirical age profiles of annualized wealth from the HRS data with simulated profiles from life-cycle models that are extended to include uncertainty about longevity, precautionary saving in light of uncertain medical expenses, and an explicit motive for retirees with greater resources to leave bequests. Within the class of models we consider, specifications that include all three of these factors seem to line up best with the rate of increase of annualized comprehensive wealth in the HRS data. In this case, saving in retirement (relative to the simplest life-cycle benchmark) provides insurance against the possibility of financing consumption into advanced ages, is available to help finance possibly very large medical expenditures, and it increases the size of intended (as well as unanticipated) bequests. Quantitatively, the simulated age profiles for annualized wealth match up fairly well with the estimated profiles, although the stylized models cannot capture much of the significant heterogeneity of annualized wealth patterns across retirees in the HRS. Overall, we think more work is needed to better understand what combination of experiences and motivations might be most important for accounting for the rising trajectory of annualized wealth in old age.