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An Unhealthy America: The Economic Burden of ... - Milken Institute

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<strong>An</strong> <strong>Unhealthy</strong> <strong>America</strong><strong>Milken</strong> <strong>Institute</strong>Comparison Tables<strong>The</strong> baseline intergenerational model is built on the projection <strong>of</strong> independent variables, given the same growth trend(1970–2003) and baseline PRC projections. <strong>The</strong> projections themselves represent the embedded investment from futureimprovements in health.Inserting the variable life expectancy at 65 into the optimistic projections, we use the most recently available six years(1997–2003) <strong>of</strong> NCHS life table data. We insert the optimistic projections for the two leading causes <strong>of</strong> chronic diseasedeath—cancer and heart disease—to obtain expected mortality rates for the over-65 population. By computing thecoefficients between life expectancy and mortality rates, along with forty-year historical trends, we find that in 2023,the optimistic life expectancy will be roughly 0.7 year longer than that <strong>of</strong> the baseline projection. By 2050, optimistic lifeexpectancy at 65 will increase 1.7 years over the 2050 baseline.<strong>The</strong> impact <strong>of</strong> life expectancy on the percentage <strong>of</strong> population with a bachelor’s degree varies over time. Generally,the greater impact should occur within the first twenty years, from 2003 to 2023, and increase at a slower rate until 2050.We control for median earnings by educational attainment, since higher relative incomes will make the acquisition <strong>of</strong>higher degrees more appealing. We plug this newly created optimistic projection <strong>of</strong> the percentage <strong>of</strong> populationwith a bachelor’s degree variable into a reaction function to calculate the optimistic capital stock output. Decisions toinvest in capital stock (s<strong>of</strong>tware, equipment, and structures) are determined by the percentage <strong>of</strong> the population withhigher education degrees.<strong>The</strong> percentage <strong>of</strong> population with a bachelor’s degree and life expectancy at 65 both have impacts on the laborforce size, whose magnitude for each will vary according to an “S” curve. This reaction function shows that decisions toinvest in better health will have a positive and significant impact on a person’s life, as well as work force longevity.This model design departs from existing literature by not just projecting domestic regional markets. It also relays thespillover effects <strong>of</strong> health that have not been captured in any previous models. Better health enables a worker to remainin the labor pool longer. Feedback into the production function will demonstrate by how much this will increase eachstate’s productivity.Now that we have optimistic data from 2004 through 2050 for each variable, we can use the coefficients from theproduction function to generate optimistic output (state GDP) from 2004 to 2050. <strong>The</strong> gap between optimistic andbaseline presents a difference <strong>of</strong> 17.59 percent by 2050. This gap totals $1.201 trillion by 2023 and widens to $5.668trillion by 2050. We can also compare this gap with that in the baseline/optimistic scenarios for indirect impacts anddirect costs from previous chapters.When other models fail to account for the interaction <strong>of</strong> health with other variables, they risk a pervasive understating<strong>of</strong> GDP—by double-digit percentages. Such errors underscore the importance and potential contribution <strong>of</strong> thisresearch in the field <strong>of</strong> health economics.[ 176 ]

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