A New Index to Value In - Kind Benefits

This paper presents a new approach to valuing in-kind benefits and a new index for that valuation. This approach is both individual (or family) specific and assigns a value to benefits for all those eligible for them, whether or not the benefits are actually used. The value is based on observed characteristics of the individual (and family) and location-specific factors likely to influence the value. The index is created for individuals and can be aggregated to obtain a familyspecific value. An example of health insurance is used to demonstrate the approach. It is found that the value that single women with children place on health insurance depends on their own health status, the health status of their children, and their poverty status, among other factors. A New Index to Value In-Kind Benefits Valuing in-kind benefits such as those for medical care, food, and pensions is a difficult task. Many problems arise even in the valuation of fringe benefits in the private sector, and the problems are multiplied in the public sector. For example, in the private sector most medical insurance benefits are provided through the workplace and are valued differently from their cost to individuals on the open market because of differences in tax treatment, risk pooling, overhead, and coverage options. In the case of public coverage, the valuation task is even more difficult because recipients do not pay for coverage. Three methods for valuing such coverage, especially medical coverage, have been suggested (Smeeding and Moon, 1980; Smeeding, 1982). The first, and most common, is the method of "government cost." Here a value of Medicaid benefits, for example, is obtained by dividing government expenditures, including administrative costs, by the number of recipients. This method overvalues benefits because it fails to address their in-kind nature--that is, the recipients cannot sell the coverage--and because it includes expenditures other than for medical care. A variant of this method divides expenditures by the number of eligibles rather than the number of users, for presumably even nonrecipient eligibles receive an implicit insurance benefit from the program. The second method calculates a cash-equivalent value of in-kind care by assuming a particular utility function and then imputing to broad groups of individuals--by income, for example--an average amount they would be willing to pay for the care. The second method is preferable but requires estimation of the parameters of the utility function, a difficult task. A third method values in-kind benefits by the amount of funds released for the purchase of other goods should the in-kind program be eliminated, and undervalues such benefits. An alternative valuation approach is proposed here whose main objective is to address a major difficulty with all three approaches, which is their use of average values over large groups when calculating benefit values. While none of the approaches requires such large-group averaging in theory, the available data usually dictate such averaging. For example, in the first method, available statistics for Medicaid expenditures are only available by state and sometimes for the aged and nonaged, and in the second and third methods, values can be generally calculated for only two or so demographic characteristics. For private sector fringe benefits, values may be available on a firm or union level or a more aggregated level. The values so obtained miss many important interfamily differences that affect valuations--for health insurance these include health status, the number of persons covered, expected utilization of medical care, the cost of medical care in the community (and to those with particular forms of coverage), and intensity of coverage; for life insurance, these include marital status, number and ages of children, assets, and health status. These concerns are particularly important for valuing health insurance, since such valuation depends on expected utilization (expected loss), which differs substantially across the population.' In the sections below we first present our methodology for valuing in-kind or fringe benefits using health insurance as our example. Second we present empirical estimates of public health insurance and of private insurance for a particular population--single mothers and their children. They are a unique group, since they are potentially eligible for public coverage, if they meet the incomelasset test, or for private coverage, should they secure a job at a firm offering such coverage or buy it directly. This is a particularly interesting group in that their potential eligibility for public coverage--Medicaid--may influence their welfare and labor force participation. The basic idea of this Index is to create an expected value of benefits based on observed characteristics of an individual and of location-specific factors likely to influence utilization and costs of care. The index is created for individuals. and can also be aggregated to a family specific value. The basic underlying equation is where V = the value of health insurance for an individual (defined below); X is a vector of health characteristics, Z is a vector of other individual characteristics such as education, number of children, race; S is a vector of location-specific variables such as per capita health expenditures in the area and eligibility standards for Medicaid; Li are dummy variables for type of insurance coverage (L, for Medicaid, L, for private coverage) while P, 6, I , y, 4 are vectors of coefficients to be estimated and e is the error term. This equation could be estimated directly if there were a data set with appropriate information on V, X, Z, and S, and if type of insurance coverage (Li) could be treated as exogenous. Evidence suggests, however, that the decision on type of insurance coverage purchased, if any, is endogenous (see, for example, Feldman, et al., 1989). Therefore, as a first step an equation for type of coverage should be estimated. and (1) is thus modified to include predicted probabilities of types of insurance coverage L rather than actual coverage (L): The coefficients from equation (1') can be used along with the individual's characteristics and those of the state to obtain a predicted value for each individual. An advantage to this index, in addition to its capturing individual heterogeneity, is that it predicts a positive value even for those who happen not to have had care in the past (for example, those eligible for Medicaid but who are not current recipients). It is undesirable to assume that a person with no medical care utilization in the past assigns zero value to health insurance; this proposed index assigns to an individual an expected value dependent upon his or her characteristics. Another advantage is that the index is a function of state Medicaid and medical-supply characteristics, and so will be partly state-specific and partly individual-specific. It should be stressed that this index is not equal to an insurance value for many reasons. It does not include loading factors and other administrative costs; it does not represent an attempt to gauge the open-market price of the bundle of services provided by Medicaid or private insurance; and it does not attempt to gauge the cash-equivalent value of the care. Among the three traditional methods of valuation mentioned above, it comes closest to the method of government cost, using eligibles rather than recipients as the population base; there are as well important conceptual differences between that measure and the one proposed here. Our measure should be thought of as a proxy for the true value of in-kind benefits, a proxy that should be highly positively correlated with that true value. Because it captures interfamily heterogeneity to a much greater extent than have past measures, we believe that it is a better proxy than those measures.'