Model Variances in Assessing the Present Value of Future Medical Care
Anderson, Gary A., Journal of Legal Economics
Abstract This research investigates four alternative models for computing the present value of future medical care and illustrates the valuation differences among the alternatives. The four models are the life expectancy model, the expected med cost model, the expected present value model, and the no tax expected med cost model. Models 1 through 3 integrate tax liability on the basis of an allocated award. Valuation comparisons among the models are presented for variations across the most critical valuation parameters including, age, base level of medical care, and real future medical care growth rates. Results show only modest differences, less than 2.0%, across the first three models when the med cost growth rate approaches the before tax interest rate for all age and base level med care comparisons. Differences among models 1 to 3 increase as the net before tax discount rate departs from approximately zero. Differences of 5% to 8% result with approximate minus one and minus two net discount rates, respectively. At a plus one approximate net discount rate, the differences among models one to three are less than 2%. Omission of taxes in model 4 results in substantially lower present values with the differences increasing as the years of loss and the base level medical care increase.
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For severely injured parties, future medical care often constitutes the greatest component of economic loss in a personal injury case. Catastrophic injuries often result in life care plans projecting future medical care needs in the hundreds of thousands to millions of dollars. The economist's task in assessing the present value of future medical care requires integration of the elements of projected future medical care needs with projected rates of growth, discount rates, tax liabilities on interest to be received on the invested award, and statistics of mortality. There are three alternative models for the integration of mortality statistics into the valuation process. These models are the Life Expectancy Model, the Expected Future Medical Care Model, and the Expected Present Value Model. This is the first research to introduce the Expected Present Value Model. The literature regarding the modeling of the present value of medical care has been limited to the Life Expectancy and the Expected Future Medical Care Models. Slesnick was one of the first to introduce some of the complexities of valuing medical care but did not address the unique IRS rulings regarding tax effects on the valuation. Anderson and Roberts (1989), Syderhoud and Chun (1996), and Ireland (1989) introduce the unique tax modeling issues of medical care, but are limited in scope to single illustrations and general discussions of the structure of the medical cost present value modeling.
In the sections to follow these models are presented along with a model of losses without taxes. Numerical illustrations of differences among the models are presented for variations across the valuation parameters, number of years of loss (age of the injured party), annual base level of medical care needs, and growth rate of future medical care. With the exception of the no tax analysis, all tax liabilities are integrated assuming that medical care is identified with specificity, i.e., an IRS allocated award. The paper concludes with a summary of findings.
Present Value Models of Future Medical Care
In many cases a life-care plan defines for the economist the base medical care costs, frequency, and needs. The economist integrates growth rates, mortality statistics, and tax liabilities on interest to be received on the invested award in computing the present value of future medical care. The two most frequently employed methods of valuation are the Life Expectancy and the Expected Medical Cost Present Value Models. The Life Expectancy Model, Model 1, front loads future medical care costs into the years of remaining life expectancy by weighting each year's future medical care with probability one to the period of life expectancy. …