عدم تجانس در تغییر میزان هزینه ها در دوران بازنشستگی

The simple one-good model of life-cycle consumption requires that consumption be continuous over retirement; yet prior research based on partial measures of consumption or on synthetic panels indicates that spending drops at retirement, a result that has been called the retirement-consumption puzzle. Using panel data on total spending, nondurable spending and food spending, we find that spending declines at small rates at retirement, rates that could be explained by mechanisms such as the cessation of work-related expenses, unexpected retirement due to a health shock or by the substitution of time for spending. We find substantial heterogeneity in spending change at retirement: in the upper half of the wealth distribution spending increased. In the low-wealth population where spending did decline at higher rates, the main explanation for the decline appears to be early retirement due to poor health, possibly augmented by a short planning horizon by a minority of the population.

The simple one-good model of life-cycle consumption requires “consumption smoothing:” the trajectory of consumption by an individual should be continuous in time. If the trajectory is not continuous, a reallocation of consumption so as to reduce the size of the discontinuity will increase lifetime utility without an increase in the use of resources. However, British households apparently reduce consumption at the ages associated with retirement, and the reduction cannot be explained by the life-cycle model (Banks et al., 1998). Households in the Panel Study of Income Dynamics (PSID) sharply reduced several components of consumption at retirement (Bernheim et al., 2001). Because the mechanisms underlying this observed drop in consumption at retirement are not well understood, it has been referred to as the retirement-consumption puzzle. There are a number of interpretations or explanations for this drop. The most obvious has to do with the cessation of work-related expenses, but it appears that such expenses are not large enough to explain the observed drop in consumption at retirement (Banks, Blundell and Tanner). A second explanation is that workers do not adequately foresee the decline in income associated with retirement (Bernheim et al., 2001). On reaching retirement they assess their financial resources, and, finding them less than anticipated, reduce consumption. This interpretation is damaging to the life-cycle model, which assumes that economic agents are forward-looking planners. For most workers, retirement is a predicable event, and workers should be assessing continuously their financial situation so that they will not be surprised. They should have saved enough so that they would not have to reduce consumption at retirement. However, at least on average, this explanation lacks empirical support: prior to retirement workers anticipate a decline in spending at retirement (Hurd and Rohwedder, 2003). A third interpretation is that workers under-saved but they were aware they had under-saved: they were not surprised by the inadequacy of their resources. A lack of self control caused the under-saving and the decline in income forced them to reduce consumption. This interpretation is also damaging to the life-cycle model, which assumes that people are both forward-looking and that they follow through on their (optimal) plans. A fourth interpretation is that the timing of retirement is uncertain. Some workers retire earlier than anticipated because of a health event or unemployment, resulting in an unexpected reduction in lifetime resources, and the reduction leads to a concurrent reduction in consumption. Such a reduction in consumption is well within the spirit of the life-cycle model. A final explanation is that retired households have considerably more leisure than working households. The increased leisure can be used to purchase goods more efficiently or to substitute home-produced goods for purchased goods. In this interpretation, spending declines, but actual consumption does not (Aguir and Hurst, 2007). We note, however, that the increased leisure time could also lead to increases in purchased goods because of complementarities such as spending on travel. If some uses of time are substitutes for market-purchased goods and some are complements, the overall effect is ambiguous, but we would expect consumption to change at retirement, not that it be smooth. Because of the multiplicity of explanations, heterogeneity in spending change at retirement should be expected: some identifiable groups are less forward-looking than others; some are more subject to health shocks; some are more time-constrained in spending prior to retirement; and so forth. Apparently, in the literature cited above, these disaggregated spending changes averaged to a spending decline in the population. In this paper we use panel data on the total spending of individual households. Consequently we are able to make a number of contributions to the literature. We use a measure of total spending based on 36 categories of spending plus 6 big-ticket items in panel data. While the measure is based on fewer items than the US Consumer Expenditure Survey, it is comprehensive and so avoids the difficulties that have been identified in the literature of measures based just on food spending. Our spending measure is embedded in the HRS allowing us to study heterogeneity in spending change at retirement as a function of observable characteristics. We make use of longitudinal data on personal characteristics such as health, on expectations and on qualitative assessments such as recollections to provide evidence about causal mechanisms. We have complete measures of income and wealth in close proximity to the spending measures to assess the levels and changes in economic resources associated with retirement. Based on panel data on spending before and after retirement, we find that, spending declines at retirement at a small rate, 1% to 6% depending on the measure. We cannot reject the hypothesis of no change in spending, and the 95% confidence intervals do not cover large changes. A change of these magnitudes could plausibly be due to the cessation of work-related expenses, a loss of earnings due to early retirement in response to a health shock, by the use of time to economize on spending, or by a combination of these factors. We conclude that these data do not support a retirement-consumption puzzle at the population level. We analyze spending change as a function of pre-retirement wealth, of planning horizon, and of the importance of health as a factor associated with retirement. We found substantial heterogeneity across wealth quartiles showing declines in spending at retirement among low wealth households and increases in spending among those in the highest wealth quartile. In subpopulations where spending does decline at larger rates, the main explanation seems to be early retirement associated with poor health. We found some support for an explanation based on a short planning horizon, but the fraction of the population where this applies is small.

In panel data on total spending, nondurable spending or food spending, we found small declines in spending associated with retirement. The magnitudes of the declines could reasonably be explained by the cessation of work-related expenses or by efficiencies in shopping made possible by the greater availability of time or by the substitution of home production for market purchased goods and services. An additional explanation, which we have not yet discussed, is found in the standard life-cycle model itself. In the simplest version where the only uncertainty is mortality risk, consumption should begin to decline when mortality risk becomes important and the rate of decline should accelerate with increased aging. For example, mortality risk is 0.015 at age 65, so that for a single person where the subjective time rate of discount equals the interest rate, consumption should decline at 1.5% per year or 3% over two years. This is approximately the two-year change we observe. Thus, there are at least three explanations in conventional economic theory for the magnitude of the spending declines observed in Table 1. Our main conclusion is that according to these data there is no retirement-consumption puzzle at the population level. Nonetheless, the population is far from homogeneous. At the household level we observe both substantial increases and substantial decreases in spending. Some of the change is observation error. Our method of addressing observation error is to look at spending changes in subpopulations using statistics that are relatively robust to observation error such as the change in population medians and means, and the median of household-level changes. We focused on the subpopulation with below average economic resources which has been the object of attention in the literature and which is important from the point of view of policy. We found declines in spending in the bottom half of the wealth distribution. Addressing the question about foresight, we found that those in the lowest quartile experienced a decline what was substantially greater than anticipated, whereas in the other quartiles, spending declined by less than anticipated. In the lowest wealth quartile, median nonhousing wealth could not finance even one year of the drop in income at retirement. Thus this group under saved ex post. To address the explanation of a lack of foresight, we use the HRS measure of planning horizon. While just 14% of those in the top quartile had a short planning horizon, 33% of those in the lowest quartile had a short planning horizon and, possibly, a lack of foresight. In the two lowest wealth quartiles, a short planning horizon was associated with median household spending change of −10.4 percent and −23.4 percent respectively. When health was an important reason for retirement, spending declined at a greater rate than when it was not important. However, the largest declines were confined to the lowest wealth quartiles and a substantially greater fraction of retirees in the lowest quartile gave health as a reason for retirement. When the actual retirement age is compared with the expected retirement age as estimated from the subjective probability of working past 65, it is clear that health is associated with an unexpectedly early retirement. The amount of earnings lost was a significant amount compared with nonhousing wealth in the lowest wealth quartile. For this group at least some of the decline in spending can be explained by an unexpected reduction of lifetime wealth. In the regressions wealth quartile per se was not as important, and it was not statistically significant. Rather it was a short planning horizon among those in the lowest half of the wealth distribution and whether health was an important reason for retirement. These results hold approximately whether education is included. Our results are qualitatively similar to Bernheim, Skinner and Weinberg in that they find greater declines in the lower part of the wealth distribution as we do. Of course, theirs are quantitatively different, and that difference is important as it changes the retirement-consumption puzzle from a question about the population to a question about subpopulations. Subpopulations can have characteristics that offer explanations for the puzzle, and those explanations can help us learn about behavior. Similarly our results have an element in common with those of Smith (2006). She found a decline in food spending only among those who experienced involuntary retirement. Our major subpopulation with declining spending was the subpopulation where health was an important factor in retirement: it is likely that many in that subpopulation retired involuntarily. Even though the change in spending at retirement does not indicate widespread suboptimal behavior, the change does not show that the spending level is optimal. To address that issue we would need to compare spending levels with available resources in a life-cycle setting. That is, conditions on the rate of change of spending are necessary conditions, but not necessary and sufficient conditions for optimality. Because of the emphasis in the literature and in public policy on the low wealth population, we explored explanations for the decline in spending in that group. However, from the point of view of economic theory, the behavior of the top wealth quartile is certainly of interest. That group increased spending by 7–18% depending on the measure. The most obvious explanation is that it takes time to spend money. It is beyond the scope of this paper to undertake this analysis, but the variation across wealth quartiles is an example of the substantial heterogeneity in spending change at retirement that would have to be taken into account. This variation indicates that time use is likely to be an important explanation for the heterogeneity in spending change.