Are Consumption Patterns of Elderly Households Consistent With a Life-Cycle Model?

ABSTRACT - A life-cycle savings model was tested to analyze consumption patterns of elderly U.S. households, using the 1990 and 1991 BLS Interview Survey of Consumer Expenditures. The model implies substantial, planned decreases in consumption after retirement, regardless of income patterns. The empirical analysis suggests that as the world population ages, total consumption will decrease, as will most categories of consumption.



Citation:

Chiu Fui Joyce Mok, Hui Wang, and Sherman D. Hanna (1994) ,"Are Consumption Patterns of Elderly Households Consistent With a Life-Cycle Model?", in AP - Asia Pacific Advances in Consumer Research Volume 1, eds. Joseph A. Cote and Siew Meng Leong, Provo, UT : Association for Consumer Research, Pages: 237-245.

Asia Pacific Advances in Consumer Research Volume 1, 1994      Pages 237-245

ARE CONSUMPTION PATTERNS OF ELDERLY HOUSEHOLDS CONSISTENT WITH A LIFE-CYCLE MODEL?

Chiu Fui Joyce Mok, Ohio State University

Hui Wang, Ohio State University

Sherman D. Hanna, Ohio State University

ABSTRACT -

A life-cycle savings model was tested to analyze consumption patterns of elderly U.S. households, using the 1990 and 1991 BLS Interview Survey of Consumer Expenditures. The model implies substantial, planned decreases in consumption after retirement, regardless of income patterns. The empirical analysis suggests that as the world population ages, total consumption will decrease, as will most categories of consumption.

The proportion of the U.S. population 65 years of age and older was 8.6% in 1960 (U.S. Bureau of the Census 1989a, p. 36) but increased to 12.6% by 1991 (U.S. Bureau of the Census 1992, p. 26). By 2080, the percentage is projected to rise to 23% (U.S. Bureau of Census 1989b, p. 9). The proportion of the population over 65 in the United States was over twice the proportion for the entire world, but less than the proportion of many European countries, such as the United Kingdom with 15.7% (U.S. Bureau of the Census 1992, p. 823). The developing countries are expected to follow the trend of the United States and Europe, so that an increasing proportion of the world population will be age 65 and over. For instance, the proportion of the population of Singapore 65 and older may rise from 6% today to 19% forty years from now (Wall Street Journal 1994, p. A10).

The consequences of such a trend may have important implications for consumer spending patterns. Elderly households normally experience a reduction in income upon retirement, an increase in time available for consumption activities, and a cessation of an assortment of job-related expenses. Overall, this adjustment process accompanying retirement is expected to entail significant changes in the final composition of purchases, as well as the household's consumption response to future variation in its income (McConnel and Deljavan 1983). Elderly households not only spend considerably less than non-elderly households, both in terms of total consumption and most components of spending, but also have substantially lower incomes (Hitschler 1993).

As such, understanding the determinants of consumption behavior by the elderly is of considerable interest for marketing, as well as policy analysis. For example, the level of consumption in early retirement will have an important influence on economic status late in retirement. It may also provide direction for the practical policy issues of allocation of society's scarce resources, such as the allocation of federal resources towards the funds for congregate meals for the elderly.

The purpose of this study is to examine the effects of age and other socio-demographic variables on the consumption patterns of elderly households. A version of the life-cycle model of savings is used to generate hypotheses about consumption patterns. The primary hypothesis is that the total consumption of elderly household decreases with the average death rate of the age of the household, even after controlling for family size, current income and levels of assets.

REVIEW OF LITERATURE

According to the conventional life-cycle consumption hypothesis, the rational family adopts a lifetime consumption plan that balances the utility gained from acquiring additional financial assets against expenditures on current consumption across all stages of the life-cycle (Ando and Modigliani 1963). Previous life-cycle consumption research can be generally classified into two broad classes: descriptive presentations of empirical observations on income, expenditures and savings; and theoretical developments of the life-cycle hypothesis (Chen and Chu 1982).

Hammermesh (1982) found effects of life expectancy on consumption patterns. The results indicated that increased longevity would enable the elderly to maintain, rather than decrease, their consumption levels. However, Stoller (1987) pointed out that due to the uncertainties regarding health and financial security, elderly people continued to save.

Crockett (1963) and Goldstein (1965) further confirmed that the elderly not only consumed less, but they allocated lower proportions of their income to apparel, transportation, and recreation. In contrast, higher proportions of elderly households' total consumption were used for food, housing and medical care. Using the 1972-1973 Consumer Expenditure Survey, Lamale (1973) found that higher proportions of retirees' total current expenditures were used for food, housing and medical care; and less on apparel and upkeep, transportation, recreation, and personal care than did all families, wage earners and clerical workers' family.

In view of the likelihood that retirement status substantially alters consumption choices, McConnel and Deljavan (1983) used a life-stage consumption model which restricted its focus to the relevant range of retirement ages and treated the retired and non-retired elderly groups separately. The findings suggested that retired households committed a smaller proportion of additional income to necessities, a much larger proportion to gifts and contributions, and an equal proportion to transportation, in comparison to non-retired households. Consumption patterns also showed that medical care and energy-related expenses emerged as budgetary problems for the average retired households.

THEORETICAL BACKGROUND

Since the pioneering articles by Modigliani and Brumberg (1954), the life-cycle hypothesis has been the fundamental analysis for consumption and saving behaviors. Older people generally have shorter life spans, tend to save less and to spend more than younger people. From another point of view, the elderly may have experienced a decrease in income with pension being the major source of money income, and, as such, face the decision of how to allocate money during the late period of the life stage. According to the life-cycle hypothesis, although consumption may vary with time, it is not related directly to transitory changes of income. To maximize satisfaction, households may borrow during the early period of life-cycle to maintain a high level of consumption, repay the debt and accumulate wealth during the middle age, and borrow from savings to adjust for the decreased income during retirement.

Modigliani and Brumberg (1954) used a utility function to analyze consumption patterns for consumers. Consumers are assumed to maximize the total utility subject to budget constraint, where utility is the function of total consumption in the present and future periods. The consumption of an individual is a function of resources and the rate of return on capital depending on the age parameter. The simple assumptions of early formulations of the life-cycle model (Ando and Modigliani 1963) have been extended by many authors (e.g., see review by Hanna, Chang and Fan 1991).

THEORETICAL MODEL

Life-Cycle Consumption Model

Households are assumed to maximize utility through the life-cycle subject to budget constraints, where utility is assumed to be a function of total consumption (Ando and Modigliani 1963). Budget constraints are related to net financial assets, net equity of the home, and after-tax income of that year. Using a two-period model, then extended to lifetime, the lifetime utility can be regarded as the utility from year 1 plus utility from year 2. Results of the two-period model can be extended to a lifetime model (Fan, Chang and Hanna 1993).

Discounting of the utility received from future consumption may depend upon personal factors, such as the risk of death or disability. The most common intertemporal utility function used (Hurd 1990) has constant elasticity and is time separable.

The parameter of the utility function is the elasticity of marginal utility with respect to consumption, e. It can be shown (Fan, Chang and Hanna 1993) that the growth rate of consumption will depend on the real interest rate faced by the consumer, r, the personal discount factor, Q , and the elasticity of marginal utility with respect to consumption, e.

EQUATION    (1)

Consumers under the age of 60 may face higher real interest rates, either because they have consumer debt or because, in the United States, they can shelter the earnings from their investments from income taxes if in tax-sheltered retirement funds. A consumer who has money in a tax-sheltered form with some stock equities may have a real rate of return of 6% or more per year. If the personal discount factor is based on the death rate of the consumer (Fan, Chang and Hanna 1993), then the real growth rate of consumption will be positive, because the annual death rate is approximately 0.1% for consumers under the age of 30 and gradually increases to about 1% by age 60 (U. S. Center for Health Statistics 1986). The real growth rate of consumption predicted by the model depends on the elasticity of marginal utility with respect to consumption, which has a wide range of theoretical and empirical estimates, with typical estimates in the range of -1 to -10 (Hanna, Chang and Fan 1991).

Elderly consumers who invest conservatively and cannot shelter investment income from income taxes may face lower real interest rates, perhaps near zero. Elderly consumers also face increasing higher death rates, for instance, 3% at age 72 and 6% at age 80 (U. S. Center for Health Statistics 1986). It is plausible that the personal discount factor, Q, is approximately equal to the annual risk of death (Hanna, Chang and Fan 1991). Given this assumption, a consumer might rationally plan to have decreasing consumption in the future, especially after age 60, as the risk of death starts increasing rapidly.

Consumption Function

Household total expenditures are determined by several factors, such as the price of the commodities, the relevant need and taste of consumers, and most of all - money income. Total expenditure is a better proxy for permanent income than is current income (Cramer 1969). However, the allocation of income among different consumption categories is constrained by the level of total expenditures. The estimated expenditure on specific items may bring unambiguous results, which means that an increase expenditure in one item results in a decrease expenditure in another category (Prais and Houthakker 1955). Using permanent income with a two-stage least square model can correct the bias produced from correlated error terms in the system equations (Liviatan 1961).

Consumer demand theory assumes that consumers maximize total utility subject to budget constraints. In empirical analysis, the effects of change in income on expenditure patterns may have different functional forms. In this study, the dependent variable, total consumption, was converted into logarithmic form in order to capture existing nonlinear relationships between the dependent variable and related independent variables (Abdel-Ghany and Schwenk 1993).

Spending patterns of elderly households are different from those of non-elderly households, both in terms of total consumption and components of spending (Hitschler 1993). Some spending changes may be due to changes in household composition and preferences, such as decreases in spending on entertainment and increases in cash contributions. However, the focus of this study is on whether total consumption decreases with the death rate as people age. A set of demographic variables will be included in the analysis to control for changes in household composition and other factors. If household behavior is consistent with the life cycle model, annual consumption will decrease with the expected death rate (and therefore with age), even if income and assets stay constant. If there is a negative relationship between total consumption and the average death rate, even after controlling for income, assets, and other variables, the lifecycle hypothesis would not be rejected. The analysis reported in this paper is unique because it uses the average death rate for each age, rather than age itself, as an independent variable. This method is more appropriate than using age itself to test the economic model described.

DATA AND VARIABLES

The data used in this study are from the 1990 and 1991 Consumer Expenditure Interview Surveys of the U.S. Bureau of Labor Statistics (BLS). One of the public use tapes from the BLS, the EXPN tape, contains a number of files containing information about vehicle purchases and other information, which can allow a researcher to construct a measure of spending which corresponds more closely to consumption than does the published measure of total expenditures provided by BLS. Files from the quarterly expenditures files were merged to construct a file with all households with four quarters of interviews in 1990 and 1991. For the purposes of this analysis, elderly households were selected. Elderly households were defined as: (1) two-person household (including husband and wife family) with both being 60 or over; (2) one-person household with reference person 60 or over. Elderly people living in nursing homes or living with people who are less than 60 are excluded from the study. Given these restrictions, the sample size is 896 households.

The dependent variable is total consumption, which is defined as the sum of the following expenditure categories: food at home, food away from home, alcohol and beverage, shelter which is adjusted for owned housing with or without mortgage, utilities, transportation which is adjusted for monthly installment of vehicle purchasing, household operations, household equipment, apparel, health, entertainment, personal care, reading and education, tobacco, miscellaneous, and cash contributions.

TABLE 1

QUARTILES FOR INCOME, CONSUMPTION, NET FINANCIAL ASSETS AND AVERAGE PROPENSITIES TO CONSUME (APC) OF ELDERLY HOUSEHOLD, 1990-91

The independent variables used in the estimation comprise five sets of socio-demographic variables, a net financial asset variable, a net equity in home variable, and two income variables. The income variables include: (1) after-tax income which represents the amount households can spend on present consumption, saving, and repayment of debts and loans, and (2) other income receipts which indicate the total amount of other money receipts excluded from family income. The socio-demographic variables are the age of reference person which is reflected by the death rate, number of earners, household size, and dummy variables for the race of reference person and education level.

RESULTS AND DISCUSSION

Empirical Analysis

Table 1 shows the quartiles for income, total consumption, net financial assets and average propensity to consume of elderly households for single-person households and two-person households. There was a smaller interquartile range for consumption than for income. The median level for net financial assets was substantially lower for 1-person households than 2-person households. Average propensity to consume was calculated by dividing total consumption by total income (Danziger, Gaag, Smolensky, and Taussig 1982-1983). Average propensity to consume was greater than 1.0 for most 1-person households, with a median level representing spending at 133% of income. The proportion of households overspending is consistent with the life cycle model, although further analysis would be required to ascertain whether the overspending is sustainable for most households. Most 2-person households spent less than 100% of income, with the median age level of the average propensity to consume equal to 97%. Presumably, in order to maintain consumption, some elderly households drew upon assets.

The inverse-log regression model was used, with the dependent variable specified as the log of total consumption. Table 2 summarizes the coefficients and significance levels from the regression analyses. Total consumption was significantly and positively related to after-tax income, net equity of home, number of earners, family size, and the dummy variables for some college education and college graduate or more. Total consumption was also found to be significantly and negatively related to death rate and the dummy variable for Black race.

The effect of the death rate on predicted consumption based on these regression results is illustrated in Figure 1, with the death rate replaced by the equivalent age. The graph suggests that all other things equal (including income and financial assets,) age had a substantial effect on consumption. At the mean values of other variables, predicted annual consumption drops from $23,538 per year at age 60 to $21,375 at age 70, $18,879 at age 80, $13,174 at age 90, and $6,455 at age 100. This effect is consistent with recent versions of the life-cycle model, although the size of the effect is somewhat surprising. Figure 2 compares annual percentage changes in consumption as estimated from the regression presented in Table 2 to the theoretical rates predicted assuming that the personal discount rate depended on the death rate, and assuming a real interest rate of zero. The value of e (the elasticity of marginal utility with respect to consumption) which best matches the empirical results is -2.8.

Increased income was associated with higher levels of consumption, although the marginal effect was small, as shown in Figure 3. The marginal propensity to consume out of current income at mean values of all variables was 0.14, and the elasticity of total expenditure with respect to current income was 0.12.

Higher values of home equity were related to increased levels of consumption, although the effect was not substantial. Figure 4 shows the effect of net home equity on annual consumption, as estimated from the regression in Table 2. The marginal propensity to consume out of home equity was 0.011, which might be related to the elderly reducing expenditures on maintenance and improvements.

Higher values of net financial assets were related to increased consumption, although the effect was small, as shown in Figure 5. The marginal propensity to consume out of net financial assets was 0.024, which would be consistent with maintaining real asset levels if the real aftertax rate of return were equal to 2.4%.

The effect of family size was significant, with one-person households having predicted consumption at a level 71% of the level predicted for two-person households, at the mean values of other variables. The effect of the college education dummy variables was significant and strong. At the mean values of other variables, the predicted consumption of a household whose respondent had a college degree was 69% higher than a similar household whose respondent had just a high school diploma. At the mean values of other variables, the predicted consumption of Black households was about 73% of the level of similar households headed by whites or other races.

In analyzing influences on specific expenditure categories for the elderly households, ordinary least square (OLS) was used for seven expenditure categories: food at home, food away from home, apparel, net transportation, health, entertainment, and shelter. An OLS regression may produce biased results if the dependent variable is at zero or some other limit for a large proportion of the observations (Tobin 1958). Based on a formula for estimating the bias from OLS (Greene 1981), the Tobit procedure was used to analyze six expenditure categories: household utility, household operation, household equipment, personal care, reading and education, and cash contribution. In the OLS and Tobit equations, independent variables used were the same as those shown in Table 2, except that total expenditure (as a proxy for permanent income) was used instead of current income. The natural logarithm of each expenditure was used as the dependent variable.

Results of OLS and Tobit analyses are presented in Table 3 and Table 4. The effects of permanent income were positive and significant for all 13 expenditure categories. There was a negative relationship between the death rate (and therefore age) and spending on food away home, apparel, transportation, entertainment, household equipment, and reading and education; and a positive relationship between the death rate and spending on health and household operations. All other things equal, households with a Black head spent less on food away from home, transportation, entertainment, shelter, household equipment, reading and education, and personal care, compared to otherwise similar households with a head who was white or other race. Compared to one-person households, two-person households allocated more of their budgets to food at home, transportation, health care, utilities, reading and education, and personal care, and less on shelter and household operations. Elderly people with lower than high school education level allocated a lower proportion of their budgets to food away from home, entertainment, shelter, utilities, reading and education, cash contributions, and personal care than did those with a high school diploma, but spent more on health care.

TABLE 2

REGRESSION OF TOTAL CONSUMPTION AS A FUNCTION OF AFTER-TAX INCOME, NET FINANCIAL ASSET, AND OTHER DEMOGRAPHIC VARIABLES, 1990-91 (n=896)

FIGURE 1

PREDICTED ANNUAL CONSUMPTION BY AGE, AT MEAN VALUES OF OTHER VARIABLES BASED ON REGRESSION IN TABLE 2

FIGURE 2

PREDICTED ANNUAL RATE OF CHANGE IN CONSUMPTION BY AGE, EMPIRICAL PREDICTION BASED ON REGRESSION INTABLE 2. THEORETICAL PREDICTION BASED ON EQUATION 1

FIGURE 3

PREDICTED ANNUAL CONSUMPTION BY INCOME, AT MEAN VALUES OF OTHER VARIABLES BASED ON REGRESSION IN TABLE 2

FIGURE 4

PREDICTED ANNUAL CONSUMPTION BY NET EQUITY IN HOME, AT MEAN VALUES OF OTHER VARIABLES, BASED ON REGRESSION IN TABLE 2

FIGURE 5

PREDICTED ANNUAL COMSUMPTION BY NET FINANCIAL ASSETS, AT MEAN VALUES OF OTHER VARIABLES, BASED ON REGRESSION IN TABLE 2

TABLE 3

NATURAL LOGARITM OF SPENDING FOR SEVEN DIFFERENT EXPENDITURE CATEGORIES AS A FUNCTION OF INCOME AND OTHER VARIABLES (OLS), 1990-91

For the expenditure equations estimated with OLS, the elasticity with respect to permanent income (total expenditures) was less than 1.0 for food at home, health and shelter and greater than 1.0 for food away from home, apparel, transportation, and entertainment (Table 3). Goods with income elasticities less than one are considered by economists to be necessities, and those with elasticities greater than one are considered luxuries (Magrabi, et al. 1991, p. 92). The marginal propensity to consume out of permanent income ranged from 0.03 for health care to 0.18 for shelter. For the expenditure equations estimated with Tobit, the elasticity with respect to permanent income was less than 1.0 for utilities and reading and education, and greater than 1.0 for household operations, household equipment, personal care and cash contributions.

CONCLUSION

Summary

An economic model of life-cycle savings was tested to analyze consumption patterns of U.S. households over the age of 60, using a sample from the 1990 and 1991 BLS Interview Survey of Consumer Expenditures. The model implies substantial, planned decreases in consumption after retirement, regardless of income patterns. The empirical analysis suggests that the independent effect of age, as modeled by the economic model, is very strong. Based on the empirical analysis, the hypothesis in this paper can be verified. Total consumption of elderly households decreases with the average death rate, and the equivalent relationship between consumption and age is as strong as would be predicted from a life-cycle savings model. Total spending may decrease substantially. The utility function parameter estimated (the elasticity of marginal utility with respect to consumption) could allow for predictions and extrapolations to other times and countries.

Implications for Marketing

As the world population ages, there will be some changes in the composition of consumer spending. Spending on health and household operations may increase, while spending on food away from home, apparel, transportation, entertainment, household equipment and reading and education may decrease. Consumer spending may become less responsive to the business cycle, as the elasticity of total consumption with respect to current income is very low for this sample of elderly households. Within the elderly population, the high income elasticities for food away from home, entertainment and transportation imply that higher income elderly consumers may provide a good market for these items.

TABLE 4

NATURAL LOGARITM OF SPENDING FOR SIX DIFFERENT EXPENDITURE CATEGORIES AS A FUNCTION OF INCOME AND OTHER VARIABLES (TOBIT), 1990-91

Implications for Future Research

It would be useful to add explanatory variables, such as Hispanic ethnic status, to the analysis. It would be useful to test interaction terms between the death rate and dummy variables for single males and single females, so that those types of households could be compared to married couples. Theoretically, there should be a difference in the effect of the death rate, between couples and single people, and among single people, between males and females. It might also be useful to add location variables, although, unfortunately, the U.S. Bureau of Labor Statistics suppresses some location information.

The research reported in this paper is unique in using recent data (1990-91) from a nationally representative sample of households headed by someone age 60 or over. It is also unique in using the average death rate for each age (based on an economic model), rather than age as an explanatory variable for consumption. The results are consistent with the economic model, so future research on consumption patterns of elderly households should consider operationalizing age in this way.

REFERENCES

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Authors

Chiu Fui Joyce Mok, Ohio State University
Hui Wang, Ohio State University
Sherman D. Hanna, Ohio State University



Volume

AP - Asia Pacific Advances in Consumer Research Volume 1 | 1994



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