Long-Term Determinants of Patterns of Health Insurance Coverage In the Medicare Population 1

Transcription

1 Copyright 1997 by The Cerontological Society of America The Cerontologist Vol. 37, No. 3, Using data from the 1990 Health Supplement to the Panel Study of Income Dynamics, we examine the determinants of patterns of insurance coverage among the elderly. Among those with supplemental insurance through an employment-based source, the primary determinant of having insurance is work history, specifically job tenure and occupation of household heads and their spouses. Among those who do not have employer-provided insurance, wealth is the most important economic factor in the purchase of private insurance. Blacks, persons with less education and women household heads are less likely to purchase supplemental insurance. We find little evidence that persons in prior poor health are more likely to purchase supplemental insurance, and the most important determinant of dental or drug coverage is having employer-based insurance. The current trend toward decreased generosity of post-retirement benefits implies that fewer older Americans will have insurance for these services. Key Words: Health insurance coverage, Medicare, Medigap, Elderly employment histories Long-Term Determinants of Patterns of Health Insurance Coverage In the Medicare Population 1 Lee Lillard, PhD, 2 Jeannette Rogowski, PhD, and Raynard Kington, MD, PhD 2.2,4 The Medicare program provides health insurance coverage for virtually all elderly Americans. However, the program does not cover some important types of medical services, including prescription drugs, dental services and most long-term care. Expenditures for these services, as well as the copayments and deductibles under the Medicare program, may result in significant out-of-pocket expenditures for health care among older Americans. As a result, many have private insurance coverage that supplements Medicare. In 1987, 75% of persons aged 65 and older had private insurance coverage (Short, Monheit, & Beauregard, 1989). Employers are a major source of private insurance coverage to supplement Medicare. Thirty-five percent of the elderly in 1987 were covered by employment-based insurance (Short et al., 1989). Retiree health benefits were initially viewed by employers as an inexpensive benefit as they served primarily to supplement Medicare. However, several trends have made these benefits increasingly expensive to employers. These include the rapid rise in medical costs, the aging of the work force and the 1 This research was supported by NIA Grants P01-AC08291, R01-AG12420, and HCFA Grant 17-C-99087/9-02. The authors would like to recognize Alein Chun, Karl Schultz, and especially Patricia St. Clair for their assistance in preparing the data, and Barbara Thurston and Robin Grant for their assistance in the preparation of the manuscript. 2 RAND, Santa Monica, CA. 3 RAND, Washington, DC. Address correspondence to Dr. Jeannette A. Rogowski, RAND, 1333 H Street, NW, Washington, DC jar@rand.org. 4 UCLA School of Medicine, Division of Geriatric Medicine, Los Angeles, CA. trend toward earlier retirements. In 1993, the Federal Accounting Standards Board (FASB) required firms to include the present value of their retiree health liability as a cost against current earnings since Because these liabilities were so high and largely unfunded, many firms are now considering decreasing the generosity of their post-retirement health benefits. Post-retirement health insurance is a form of deferred compensation offered by firms to their workers. There are well known variations in the rate of offers of retiree health benefits by industry, with employers in some sectors, such as service industries, much less likely to provide these benefits than those in other sectors, such as manufacturing (Karoly & Rogowski, 1994). Larger firms are also more likely to provide these benefits to their workers than small firms. Most firms have eligibility requirements for retiree health benefits. For instance, in a 1991 survey of medium and large firms, 35% of firms have a service requirement (e.g., a minimum tenure of employment) and 32% require that the retiree also qualify for pension benefits (Bureau of Labor Statistics [BLS],1993). For those elderly who do not have access to health benefits from current or former employers, private insurance to supplement Medicare can be purchased in the Medigap market. In 1980, federal legislation was enacted which established minimum requirements for these policies after hearings in the late 1970s made it evident that there were abuses in the market for supplemental insurance. The legislation, known as the Baucus Amendment, became effective 314 The Gerontologist

2 in In addition to imposing minimum benefit requirements, it also prevented policies from excluding pre-existing conditions for more than 6 months and placed minimum limits on the amount of premiums that had to be returned to policyholders in the form of benefits (Cafferata, 1985). Recently, the Omnibus Reconciliation Act (OBRA) of 1990 further regulated the Medigap market, requiring all policies sold to conform to one of ten types. All policies contain at least core benefits which include coverage of all Part A coinsurance for hospital stays over 60 days, the 20% part B coinsurance, and the Parts A and B blood deductible. Prescription drugs are covered under the most comprehensive plans. Dental care is not included in any of the plans. The legislation also raised the loss-ratio requirements and established a sixmonth open enrollment period for policy purchase when a person turns age 65 (Rice & Thomas, 1992). Prior studies have shown that the presence of supplemental insurance among the elderly is related to sociodemographic and economic characteristics. The presence of private insurance is higher among Whites and those with higher incomes and higher levels of education, and decreases with age (Long, Settle, & Link, 1982; Carfinkel, Bonito, & McLeroy, 1987; Rice & McCall, 1985). Health status is also an important determinant of private insurance to supplement Medicare, but the findings with respect to health status are mixed. Garfinkel et al. (1987), using data from the 1980 National Medical Care Utilization and Expenditure Survey (NMCUES) find that, controlling for sociodemographic and economic factors, persons with chronic conditions are more likely to have supplemental insurance. Rice and McCall (1985), using a survey of Medicare beneficiaries in six states, found that elderly persons in poor health were less likely to have supplemental insurance than persons in better health. Because private health insurance among the elderly is obtained from two sources, employers and self-purchases, these results combine the effects of various factors on the probability of owning these types of policies. Several studies have addressed the determinants of self-purchase of supplemental insurance. Taylor, Short, and Horgan (1988), using data from the 1977 National Medical Care Expenditures Survey, showed that the probability of self-purchase was also linked to sociodemographic and economic characteristics, being higher for Whites and persons with higher incomes. They also found that, controlling for these factors, persons in fair and poor health were much less likely to purchase supplemental insurance than persons in better health. Using the 1977 and 1979 Waves of the Retirement History Survey, Wolfe and Coddeeris (1991) studied elderly persons who were retired and neither Medicaid-eligible nor receiving health benefits fully paid for by an employer or union. Private insurance for these persons was either individually purchased in the Medigap market or was a retiree health benefit in which the retiree shared in the cost of premiums. They found that, among economic factors, wealth was an important determinant of the possession of private insurance. In this article, we study the long-term determinants of insurance coverage among the elderly using a new data source, the 1990 Health Supplement to the Panel Study of Income Dynamics. Because much of the private health insurance among the elderly comes from employers, we would expect that employment histories would be an important determinant of the possession of this type of coverage. Similarly, economic theory suggests that it is permanent income, as opposed to current income, that drives consumers' purchase decisions. Another important issue with the purchase of insurance coverage is whether adverse selection occurs. Elderly persons in poor health may be more likely to purchase insurance since they anticipate having higher medical expenditures. The results by Taylor et al. (1988) suggest that adverse selection may in fact be taking place in the Medigap market. Wolfe and Coddeeris (1991) find some evidence of adverse selection but conclude that its magnitude is small. We consider the issue of adverse selection by including lagged measures of health status as explanatory variables in the insurance purchase equations. Finally, because prescription drugs and dental care are two important excluded services, we also study the determinants of having coverage for these services. Among elderly persons who use prescription drugs, a large fraction of their cost (67%) is paid for out-of-pocket, resulting in an average of 3.1% of household income being spent on out-of-pocket expenses for drugs (Rogowski, Lillard, & Kington, 1997). Similarly, most dental services are paid for outof-pocket. Among elderly users of dental care, 88% of costs are paid for out-of-pocket. This results in 1.7% of household income being spent on dental care (Kington, Rogowski, & Lillard, 1995). Thus, private insurance coverage for these uncovered services could significantly decrease out-of-pocket expenditures by elderly households. We use the Panel Study of Income Dynamics (PSID) to study the patterns of insurance coverage within the Medicare population. The PSID data we use contains longitudinal history on elderly respondents for 22 years. It is thus possible to measure employment histories, prior health status, and permanent income. In 1990, the PSID was supplemented with a survey of elderly respondents regarding their health insurance and health care expenditures. These two data sources permit the examination of the effect of long-term factors on the presence of supplemental insurance among the elderly. Methods Data This study uses longitudinal data from the Panel Study of Income Dynamics (PSID), , on work history, health history, and family demography combined with newly available information on insurance coverage and health status collected for elderly respondents as part of the 1990 wave to study the Vol. 37, No. 3,

3 long-term determinants of supplemental insurance coverage. The PSID is a nationally representative (weighted) longitudinal survey of households conducted by the Survey Research Center at the University of Michigan. Since 1968 the PSID has followed and interviewed annually a sample that began with about 5,000 families, collecting information about the original sample of respondents and members of their households. The core survey collects detailed information on income, work, unemployment, use of public programs, demographic information, and some measures of health and disability. Early waves of the PSID collected information primarily on the employment histories of household heads. In the 1976 PSID, retrospective histories were obtained for all spouses of heads of household in the survey, thus providing data for spouses that are nearly compatible to that of heads of household. In 1990 the PSID data was supplemented to collect detailed information on health status, insurance, and health care costs of the elderly. Information on health status and insurance coverage were obtained in a mail-in survey. The response rate to the mail-in survey was 74%. Combined with the 22-year panel of information in the core, it is possible to study the long-term determinants of insurance coverage in the elderly. Our analyses include 763 households for which either the head or spouse is sixty-six or older and complete data are available for insurance coverage, work history and lagged health. Of these, 193 are married couples for whom the health and insurance data are available for both spouses; there are thus 956 persons represented (763 household heads plus 193 spouses). Of the 447 unmarried persons, 373 are women. Selected socioeconomic characteristics of individuals in the sample are reported in Table 1. A small number of individuals who were known to be residents of nursing homes and not living in the household were dropped from the analyses, but their core PSID data were used in the creation of variables such as spousal employment history. Analyses are weighted to reflect (a) the original 1968 sampling weights for households, (b) panel attrition between 1968 and 1990, and (c) nonresponse to the 1990 mail-in survey. The procedure to develop weights to correct for nonresponse follows that reported in the PSID User's Guide, except that logit rather than CART probabilities are used. Analytic Measures Insurance Coverage. We have assumed that all individuals in this sample are insured by Medicare based on the evidence that in 1991, 96% of persons age 65 and older were covered by Medicare (Levitt, Olin, & Letsch, 1992). The percentage in this sample is probably even higher than in the general population because the original 1968 PSID panel underrepresents immigrants, who are more likely not to qualify for Medicare. The presence of supplemental insurance, whether the insurance is employerprovided or privately purchased, and whether it cov- Table 1. Descriptive Statistics 1990 PSID Health Supplement' (n = 956 Individuals) Variable Sample individuals' Age in 1990 Black Female Married Education: less than high school Permanent income (median dollars 1990) Wealth (median, dollars 1989) a Weighted statistics. Means (except as noted) $23,218 $74,875 ers prescription drugs and dental services, are measured by responses to the 1990 mail-in survey. Insurance coverage was ascertained separately for each spouse for married couples. All sample persons of age 50 and over who responded to the 1990 mail-in survey were asked the insurance questions, including whether insurance covers the spouse, so that data on insurance coverage for almost all spouse pairs are complete. Since insurance coverage is almost identical for matched men and women in married couples in the PSID, in the multivariate analyses we use a couple-based (household) measure of insurance coverage for married couples and an individual-based measure for unmarried men and women. There were a few inconsistencies in the reports of husbands and wives about who is covered. In these cases, we indicated coverage if either spouse reported coverage, assuming a more knowledgeable spouse would know. Work History. Employment history is a potentially important determinant of insurance coverage through its effect on health insurance provided by employers. The long history of employment and work information available in the PSID allows us to construct detailed measures based on twenty-three years (waves) of panel data. Our measures focus on the characteristics of the last job before first retirement, or the current job if never retired, and include (a) years of tenure with that employer, and (b) indicator variables for aggregated occupation groups on that job. These variables are thought to influence the probability of post-retirement health plan coverage. The last job was determined by first identifying the first survey year in which an individual reported himself or herself to be retired. The last job was then defined as the last identified job prior to that survey year. We use occupational groupings that were predictive of employer-provided insurance, with different aggregates for men and for women. We first estimated each model by gender with indicators for each of the occupational groups. We then collapsed all occupational groups with significant coefficients into a single category by gender, resulting in different groups of occupational category indicators for men and women. For men the occupational group indicated by the variable in the models includes self- 316 The Gerontologist

4 employed businessmen, operatives and kindred workers, laborers and service workers, and farmers, farm managers, and farm laborers, relative to all other occupations. For women the occupational group indicated by the variable in the models includes professional, technical, and kindred workers, and managers, officials and proprietors, relative to all other occupations. For unmarried men we use their own work history. For married couples we include the work histories of both the male head of household and of the wife. For unmarried women, we use her own work history and the work history of her former husband if she is widowed within the panel period. The distributions of years of tenure and occupational group indicators are presented in Table 2 for men and women in the sample. Women tended to have shorter periods of tenure with the last employer, and about half of the women were included in the miscellaneous occupational category including self-employed and housewives. Economic Factors. Wealth is measured in the 1989 Wealth Supplement to the PSID and represents total wealth for the couple or individual if single, including housing. Permanent income is based on the detailed longitudinal income histories in the PSID, and represents the average income for the couple or individual if single during the past five years prior to The mean weighted household wealth and permanent income for the sample of individuals (n = 956) and standard deviations (SD in parentheses) are respectively: $187,005 (SD = $427,991) and $30,604 (SD = $32,555). The median values are presented in Table 1. We include in the estimation equations log values of all positive wealth estimates, with negative and zero values set equal to zero. Based on evidence that respondents who fail to provide wealth data may be different from other respondents, we have also added to each model that includes the wealth variable a dummy variable indicating that the wealth data were missing for that observation and imputed with the sample mean. In several equations, the coefficient for this variable was significant. Data on the urbanicity of the location come from the Area Resource File of the Department of Health and Human Services. The variable measures the percent of the county population that resides in an urban area. Lagged Health Status. We include several measures of lagged health status. First, we include variables indicating the presence of seven common chronic conditions that were reported in the 1990 Health Supplement to have been present for at least five years. These conditions are (mean weighted prevalence for sample of individuals in parentheses): arthritis (.37), congestive heart failure (.08), angina (.08), lung disease (.08), ulcers (.06), diabetes (.07), and hypertension (.32). We also included a mean of three years of selfreported general health status as measured by an index of general health based on an ordinal five- Table 2. Distribution of Occupation and Tenure With Last Employer" (Weighted Sample Individuals) Fraction in indicated occupation Tenure with last employer years years years 20 years or more N.A., self-employed, housewife "Weighted statistics. Men (n = 366) Women (n = 590) point scale which was asked as part of the PSID core surveys in the years , a period of time centered at approximately five years prior to the survey. The question in each year was: Would you say your health in general is excellent (5), very good (4), good (3), fair (2), or poor (1)? The lagged general health measure is an average value of these ordinal reports with a higher score indicating better health. The weighted mean value for this measure in the total sample of male and female individual respondents were, respectively, 2.97 (SD = 1.04) and 2.83 (SD = 1.04). Finally, we included an index based on a series of questions on functional status asked in the 1986 survey. Individuals reported limitations in each of the following activities due to health: limitations walking several blocks or climbing a few flights of stairs; limitations bending, lifting, or stooping; limitations driving a car; requiring assistance traveling around the community; staying indoors most or all of the day; and confined to bed or chair most or all of the day. A simple count of these restrictions was determined for each individual with a higher score (indicating worse function). The mean score for the lagged functional status measure in the total sample of male and female individual respondents were, respectively,.91 (SD = 1.26) and 1.27 (SD = 1.56). For both the lagged general health measure and the lagged functional status measure, for insurance equations in which the unit of analysis is a household (n = 763) both measures were entered separately by gender for heads and spouses in the households. For chronic conditions, a condition was present if either spouse in the household reported the condition. For households with only a head and no spouse, the head's lagged general health, functional status, and chronic condition measures were used. Modeling Insurance Coverage Our model includes equations for four aspects of health insurance coverage. The four health insurance equations estimated the probability of reporting: (a) employer-provided health insurance, (b) privately-purchased health insurance, given no employer-provided coverage, (c) health insurance covers prescription drugs, given insurance coverage, and (d) health insurance covers dental, given insurance coverage. We consider the model for each of Vol. 37, No. 3,

5 these relationships in turn, including their interrelationships. We use a probit formulation so that each of the four binary outcomes is determined by a probit index function. Employer-Provided Health Insurance Coverage. For each household in the sample we consider whether the couple or person has employerprovided health insurance, which is denoted by a binary indicator EHj. The probit index function determining coverage is given by: eh, -0,0 + <*vk + ajjemp, + u v The household is covered if the index is positive, and zero otherwise, i.e.: km '~ 1 if eh? > 0 Explanatory variables included in vector X are education, race, and age of the head of household, marital status and female headship if unmarried. Economic factors include household income and household wealth. The measures of employment history constructed using the long history of the PSID panel are indicated by vector the EMP. These include job tenure and occupation on the last job before retirement, but the men's and women's occupational aggregates are different. For unmarried men the equation includes his last tenure and occupation. For unmarried women the equation includes her last tenure and occupation. If the observation is for a couple either currently married or for a woman widowed within the PSID panel period, both the husband's and wife's work history variables are included. We hypothesize that employment histories will be important determinants of employerprovided coverage because employer offers of postretirement health benefits vary by industry and many employers who do offer benefits have service requirements. The equations also include a variable for marital status to account for any shift due to there being two persons rather than one. Self-Purchased Health Insurance Coverage. Given that the person does not have employerprovided insurance {EH, = 0), the person has selfpurchased (Medigap) health insurance if sph? = a 20 + ci' 2,X, + is positive, and zero otherwise, i.e.: Mifsp/ifX) The decision-making model is then sequential probit, since a household purchases private health coverage only if not covered by an employer policy. The purchase of private insurance coverage is modeled as a function of economic, sociodemographic, and health factors including education, race, and age of the head of household, marital status and female headship if unmarried, and measures of wealth, permanent income, and urbanicity of the residential location for the household. We are interested in determining whether there is adverse selection into privately-purchased policies. To this end, we include the measures of lagged general health status and functional status and the lagged presence of common chronic conditions (vector Y). The decision to purchase insurance is made prior to the date at which elderly respondents were surveyed. Because of the longitudinal nature of the data used for the study, it is possible to observe health status for five years prior to the interview window. If there is adverse selection into individually-purchased policies, we would expect the purchase of these policies to be positively associated with lagged measures of poor health. The probit equations for employer-provided and for privately purchased health insurance coverage may not be independent; there may be unobserved factors which influence both, so that not having employer insurance is not a random selection with respect to private insurance purchase. We tested for correlation between the two probit equations and could not reject independence. Whether Health Insurance Coverage Includes Prescription Drugs. Given that the person has health insurance coverage (EH, = 1 or SPH, = 1), the person has coverage for prescription drugs if drg? = ^ + 0^ + 1/3, is positive, and zero otherwise, i.e.: p if drg? >0 10 if drg? sso "1 One of the key variables explaining coverage of prescription drugs is expected to be whether health insurance is employer-provided or self-purchased. There is evidence that few individually purchased policies contain prescription drug benefits. A study by Long (1994) found that among privately purchased policies, only 19% covered prescription drugs. This compared to 92% of employer-provided policies. Employer policies typically provide the same benefits to retirees as to active workers and thus tend to cover prescription drugs. We hypothesize that the majority of prescription drug coverage will be associated with the source of coverage being an employer. Whether Health Insurance Coverage Includes Dental Care. Given that the person has health insurance coverage (EH, = 1 or SPH, = 1), the person has coverage for dental care if den? = a«+ ai 1 X / +0^^ + 1/4, is positive, and zero otherwise, i.e.: Mifc/en*>0 = i One of the key variables explaining coverage of dental services is also expected to be whether health insurance is employer-provided or self-purchased. Few elderly persons (13%) have insurance coverage for dental services (Kington et al., 1995). We hypothesize the presence of dental coverage is largely asso- 318 The Gerontologist

6 Table 3. Patterns of Insurance Coverage, Age PSID Health Supplement' (n = 956 Individuals) Total sample Age Gender Female Male Race Black Non-Black Education < 12 years = 12 years > 12 years Percentages in Sample 100% 49% 51% 62% 38% 8% 92% 44% 35% 21% Any Supplemental Insurance 77% 86%*** 68% 71%*** 86% 38%*** 80% 58%*** 88% 96% If Any Supplemental Employer- Provided 40% 49%*** 30% 36%*** 46% 63%*** 39% 34%*** 39% 49% "Weighted percentages and means for individuals in sample. *chi-square p <.10 for difference across sociodemographic categories.. **chi-square p <.05. ***chi-squarep<.01. Self- Purchased 60% 51% 70% 64% 54% 37% 61% 66% 61% 51% If Any Supplemental Drug Coverage 50% 58%*** 39% 49% 54% 58% 50% 45%** 57% 45% Dental Coverage 19% 22%** 15% 17%** 25% 34%* 18% 14%** 19% 24% ciated with the source of the coverage being an employer. Results Table 3 describes the overall pattern of insurance coverage for the entire sample of individuals and by important demographic categories, including age, gender, race, and education. The table illustrates the distinctive patterns of insurance coverage among demographic groups. In general, older persons, less educated persons, and women were less likely to have any supplemental coverage and less likely to have employer-provided coverage, and older persons were less likely to have either dental or drug coverage. The pattern for Blacks compared to non-blacks was particularly noteworthy. Blacks were almost half as likely to report any supplemental insurance compared to non-blacks, but if they reported any supplemental coverage, they were almost 75% more likely to report employer-provided coverage. Although higher percentages of Blacks reported both dental and drug coverage, only the difference in dental coverage reached marginal statistical significance. The following three tables (Table 4-6) present the coefficients and standard errors for a series of probit equations that provide insights into underlying relationships that might explain some of the patterns observed in Table 3. Employer-provided Insurance Estimates of the parameters of the employerprovided insurance equation are presented in Table 4. A unique aspect of our study is the incorporation of work history information job tenure and occu- Intercept Table 4. Probit Equation for Employer-Provided Health Insurance Coverage 3 (n = 763 Households) Demographics Black Education: less than high school Education: high school only Age Married couple Female head Male employment 6 Tenure on last job Occupation last job Female employment 11 Tenure on last job In-L Occupation last job 1.548** (0.671) (0.202) *** (0.151) ** (0.144) *** (0.008) 0.571*** (0.195) (0.231) 0.142*** (0.033) *** (0.168) (0.027) 0.644*** (0.211) "Weighted MLE using 1968 family weights adjusted for nonresponse. Standard errors in ( ); Significance (H o : zero, 2-tail); ***<.01;**<.05;*<.10. b For men/husbands the occupation dummy includes selfemployed businessmen, operatives and kindred workers, laborers and service workers and farmers, farm managers, and farm laborers. For women/wives the occupation dummy includes professional, technical and kindred workers, managers, officials and proprietors. Vol. 37, No. 3,

7 pation on the last job before retirement or current job if not retired in the equation for employerprovided insurance. This information is highly significant in the determination of employer coverage for men and women. Men in their indicated occupational grouping (self-employed businessmen, operatives and kindred workers, laborers and service workers and farmers, farm managers and farm laborers, relative to all other occupations) are significantly less likely to have employer-provided insurance coverage, and women in their indicated grouping (professional, technical and kindred workers, managers, officials or proprietors, relative to all other occupations) are more likely to have employer-provided insurance coverage. The probability of receiving employer-provided benefits also increases with job tenure on the current or former job for men but not for women. These results are consistent with the fact that retiree health benefits generally have job tenure requirements associated with eligibility. There are also well known variations in employer offers of retiree health benefits by industry (Karoly & Rogowski, 1994). In addition, households headed by less educated persons are significantly less likely to have employerprovided health insurance, even after controlling for work history, and the receipt of employer-provided insurance decreases with the age of the household head. This is likely related to the fact that older cohorts of workers were less likely to have been offered these benefits by their former employers. Of the sociodemographic variables, marital status was among the strongest predictors. For example, the estimated probability of having employer-provided insurance for a household with a married head and with otherwise mean characteristics for the sample was about 36%. This probability decreased to about 18% for a household headed by a person not married and with the mean characteristics for the sample. Self-Purchased Private Insurance Estimates of the parameters of the self-purchased insurance equation are presented in Table 5. For those without employer-provided insurance, selfpurchased coverage is significantly associated with sociodemographic and economic factors. While permanent income does not have an effect on the purchase decision, wealth does have a significant effect. These findings are consistent with the hypothesis that wealth may be a better measure of financial resources than permanent income in this population (Hurd, 1989). Female household heads and blacks are less likely to obtain self-purchased insurance, and elderly persons living in more urbanized areas are more likely to purchase insurance. Households headed by less educated persons are also much less likely to purchase a private policy. Taking these results in combination with the results for employer insurance, the households headed by less educated persons are much less likely to have any private health insurance overall. The differences in estimated probabilities for having self-purchased insur- Table 5. Probit Equation for Private Self-Purchased Insurance' (n = 552 Households) Intercept Black (head) Education: high school only (head) Education: high school only (head) Age(head) Married couple Female (head) Percent urban Ln (permanent income) Ln (wealth) Missing wealth General health index (84-86; male) General health index (84-86; female) Functional status index (86; male) Functional status index (86; female) Chronic conditions Arthritis In-L Congestive heart failure Angina Lung disease Ulcer Diabetes Hypertension Base (.905) *** (0.227) *** (0.244) *** (0.253) (0.010) (0.218) *** (0.192) 0.005** (0.002) (0.019) 0.128*** (0.023) ** (0.251) _ Including Lagged Health (1.054) *** (0.237) *** (0.256) ** (0.262) (0.010) (0.336) * (0.558) 0.006*** (0.002) (0.020) 0.133*** (0.025) ** (0.276) (0.135) (0.085) (0.101) (0.052) (0.140) (0.232) (0.250) (0.251) 0.787*** (0.303) 0.578** (0.251) (0.143) "Weighted MLE using 1968 family weights adjusted for nonresponse. Standard errors in ( ); Significance (H o : zero, 2-tail); ***<.01;**<.05;*.10. ance (given no employer-provided insurance) associated with educational status were large. For example, the probability of having a self-purchased insurance policy for a household headed by a person with less than a high school education and otherwise mean characteristics for the sample was about 47%. This probability increased to about 86% for persons with a high school education or more and otherwise mean characteristics for the sample. An important part of the discussion in the literature of the exogeneity of health insurance coverage 320 The Gerontologist

8 Table 6. Probit Equations for Drug and Dental Coverage* Drugs 1 Dental 2 Drugs 1 Dental 2 Intercept Employer-provided Black (head) Education: less than high school (head) Education: high school only (head) Age (head) Married couple Female (head) Percent urban Ln (permanent income) Ln (wealth) Missing wealth General health index (84-86; male) General health index (84-86; female) Functional index status (86; male) Functional index status (86; female) Chronic conditions Arthritis In-L Congestive heart failure Angina Lung disease Ulcer Diabetes Hypertension ** (1.070) 1.254*** (0.146) (0.324) 0.389** (0.181) 0.530*** (0.169) (0.010) (0.220) (0.219) 0.007*** (0.002) (0.022) 0.071* (0.040) 0.730** (0.355) * (1.164) 1.124*** (0.158) (0.300) (0.195) (0.177) (0.012) (0.246) (0.243) (0.003) (0.023) (0.043) 0.787** (0.344) ** (1.194) 1.289*** (0.153) (0.332) 0.449** (0.190) 0.590*** (0.174) (0.011) (0.361) 1.357** (0.612) 0.007*** (0.002) (0.022) 0.080* (0.043) 0.684* (0.368) 0.231** (0.113) (0.084) (0.101) (0.061) * (0.143) (0.251) (0.247) * (0.238) (0.253) (0.230) (0.144) ** (1.334) 1.308*** (0.177) (0.314) (0.211) (0.186) (0.012) (0.380) (0.699) (0.003) (0.025) (0.047) 0.793** (0.362) 0.289** (0.131) (0.088) (0.128) (0.069) (0.163) (0.318) (0.282) (0.279) (0.291) (0.279) *** (0.174) 'Weighted MLE using 1968 family weights adjusted for nonresponse. Standard errors in ( ); Significance (H o : zero, 2-tail); *** <.01; ** <.05; * < n = 446 Households. 2 n = 481 Households. in the demand for medical care is related to the potential effects of lagged health on the decision to obtain self-purchased health insurance, since current and lagged health status are correlated. The effects of the lagged general health index, functional status, and chronic conditions on the probability of having self-purchased supplemental health insurance are reported in Table 5. Lagged general health and lagged functional status had no effect. Similarly, the presence of most common chronic conditions in either a head of household or spouse had no effect with the exceptions of having had an ulcer or diabetes five years or more. About 6% in this population had had an ulcer that long and about 7% had had diabetes that long. The Baucus Amendment, which was in effect during the study period, did not permit policies to exclude pre-existing conditions for more than 6 months. Thus, the results presented here are likely to be demand effects as opposed to supply effects. These results suggest that there is relatively little adverse selection in the self-purchase of private supplemental insurance. Vol. 37, No. 3,

9 Coverage for Prescription Drugs and Dental Services Table 6 presents coefficients for probits predicting drug and dental coverage with and without the lagged health variables. For those who do have a private health insurance policy, by far the strongest and most significant determinant of coverage of either prescription drugs or of dental services is whether the policy is employer-provided. These results are consistent with the fact that many employers structure their retiree health benefit plans to mirror benefits provided to active workers. Net of the effects of the insurance being employerprovided, elderly persons living in urban areas are more likely to have prescription drug coverage. The results for education in the equations for drug coverage were somewhat surprising. For unclear reasons, persons with less than college education were more likely to report drug coverage. For both dental and drug coverage, men with better lagged general health were more likely to report coverage, and households with hypertension were less likely to report dental coverage. Discussion This study takes advantage of the unique longitudinal employment histories and the supplemental health and insurance data of the PSID to demonstrate the importance of several dimensions of long-term employment patterns in determining the patterns of health insurance coverage among older adults. Private insurance among elderly persons derives from two primary sources employers and self-purchase of insurance in the Medigap market. For elderly persons who purchase insurance in the Medigap market, the decision to purchase is related to sociodemographic and economic factors. There are large racial differences in the probability of insurance purchase. Controlling for income and other factors known to affect insurance purchase, Blacks are less likely to buy these policies than Whites. Female household heads and elderly persons with lower educational levels are also less likely to purchase insurance. The purchase of insurance coverage is not related to permanent income but instead to wealth. This is consistent with the findings of Wolfe and Goddeeris (1991) and with the observation by Hurd (1989), that wealth may be a better overall measure of financial resources for the elderly. Elderly persons who are in poor health may be more likely to purchase private supplemental policies, as they attempt to insure against future high medical expenses. The prior literature has been inconclusive about the effect of health status on the likelihood of having private insurance in old age. We find relatively little evidence in support of adverse selection being an important factor in the purchase of insurance in older populations. Neither a lagged general measure of health nor a lagged general measure of functional status nor the presence of most common chronic conditions for at least five years are significantly related to the purchase of private insurance. The only evidence was the finding that the presence of ulcers or diabetes for more than five years in a head or spouse was predictive of a lower probability of purchasing insurance. Since the Baucus Amendment, which was in effect during our study period, prohibited Medigap policies from excluding pre-existing conditions for more than six months, this effect is likely driven by the demand side of the market rather than the supply side. Perhaps our most important finding concerns the relationship between several dimensions of longterm employment patterns and insurance. Employers are an important source of private insurance coverage for the elderly, as they are for younger populations. The primary determinant of having coverage through an employer even in this age group is work history, including both tenure and specific occupational categories. The fact that employer insurance coverage varies by current or former occupation is consistent with the fact that firm offers of postretirement insurance coverage vary by industry. Industries with high rates of health insurance offers to active workers, such as manufacturing, also have high rates of retiree health benefit offers. Those with low rates of health benefits to active workers, such as the service industries, also have low rates of retiree health offers (Karoly & Rogowski, 1994). The receipt of insurance through a current or former employer also decreases with age, probably due to the decrease in the number of active workers with age as well as the lower likelihood that retiree health benefits were an employment benefit for older cohorts of workers. Education also proved to be a consistent important predictor of coverage. Controlling for work history, persons with lower educational levels are less likely to have insurance through an employer. Combined with the fact that less educated persons are also less likely to purchase insurance, this results in lower rates of private insurance coverage for this segment of the elderly population. For those who do have a private health insurance policy, by far the strongest and most significant determinant of coverage of either prescription drugs or of dental services, two services not covered by Medicare, is whether the policy is employer-provided employer policies are much more likely to cover drugs or dental services. The evidence presented in this study suggests that employment histories are the most important longterm determinants of private insurance coverage among the elderly, and this finding may have important implications for future patterns of health insurance coverage among the elderly population. Since employers are now decreasing the generosity of their retiree health benefit offers, it is likely that future cohorts of the elderly will have to rely increasingly on the Medigap market for insurance coverage. As a result, fewer will have coverage for such excluded services as prescription drugs and dental care, which can result in significant out-of-pocket expenses for elderly households. These changes in patterns of coverage may lead to an increase in the financial burden associated with medical expenses 322 The Gerontologist

10 among older persons, most of whom live on fixed incomes. References Bureau of Labor Statistics. (1993). Employee benefits in medium and large private establishments, 1991 (Bulletin 242). Washington, DC: U.S. Government Printing Office. Cafferata, C. (1985). Private health insurance of the Medicare population and the Baucus legislation. Medical Care, 23, Garfinkel, S., Bonito, A., & McLeroy, K. (1987). Socioeconomic factors and Medicare supplemental health insurance. Health Care Financing Review, 9, Hurd, M. D. (1989). The economic status of the elderly. Science, 244, Karoly, L, & Rogowski, J. (1994). The effect of access to post-retirement health insurance on the decision to retire early. Industrial and Labor Relations Review, 48, Kington, R., Rogowski, J., & Lillard, L. (1995). Dental expenditures and insurance among the elderly. The Cerontologist, 35, Levitt, K. R., Olin, G. L., & Letsch, S. W. (1992). Americans' health insurance coverage, Health Care Financing Review, 74(1), Long, S., Settle, R., & Link, C. (1982). Who bears the burden of Medicare cost sharing? Inquiry, 19, Long, S. (1994). Prescription drugs and the elderly: Issues and options. Health Affairs, 13, Rice, T., & McCall, N. (1985). The extent of ownership and characteristics of Medicare supplemental policies. Inquiry, 22, Rice, T., & Thomas, K. (1992). Evaluating the new Medigap standardization regulations. Health Affairs, 11, Rogowski, J., Lillard, L., & Kington, R. (in press). The financial burden of prescription drug use among the elderly. The Cerontologist. Short, P., Monheit, A., & Beauregard, K. (1989). A Profile of Uninsured Americans. National Medical Expenditure Survey Research Findings 1 (DHHS Pub. No. [PHS] ). Rockville, MD: National Center for Health Services Research and Health Care Technology Assessment, Public Health Service. Taylor, A., Short, P., & Horgan, C. (1988). "Medigap insurance: Friend or foe in reducing Medicare deficits?" in H. Freeh, & R. Zeckhauser (Eds.), Health Care in America: The Political Economy of Hospitals and Health Insurance. San Francisco, CA: Pacific Research Institute for Public Policy. Wolfe, J., & Goddeeris, J. (1991). Adverse selection, moral hazard, and wealth effects in the Medigap insurance market, journal of Health Economics, 10, Received March 29, 1996 Accepted July 13, 1996 AGING AND OLD AGE RICHARD A. POSNER "Posner's book is a tour de force, embracing biology, psychology, economics, and sociology.... Readers with little interest in human capital theory will be engaged by the elegance of his debates and the breadth of material woven into his theme."times Higher Education Supplement "By writing about subjects of universal concern, Judge Posner has done more than anyone to publicize the biological and economic model of man that is the roadmap for the social sciences in the coming century."wall Street Journal Paper $16.95 Cloth edition available The University of Chicago Press 5801 South Ellis Avenue, Chicago, Illinois Visit us at Vol. 37, No. 3,