Presenter:

Pravin Trivedi

Authors:

Fei Liu, Pravin K. Trivedi

Chair: Bruce Stuart; Discussant: William Greene Mon June 5, 2006 10:45-12:15 Room 325

With the growth of the elderly population in the United States, a major concern is the coverage of their health insurance plans. The elderly may acquire private insurance to supplement their Medicare benefits because the program does not cover commonly used services such as outpatient prescription drugs and nursing home service. These observations motivate this paper,which fills the gaps in research on the private insurance selection of elderly and the associated impacts on health care utilizations. A series of questions arise when we research this area: What are the causes and consequences of enrolling in supplementary insurance plans? Does unobserved heterogeneity, such as personal risk attitudes and life style, play a role in insurance decision and associated health use? Supplementary plans include Medigap plans and other supplemental policies, which can cover specific benefits such as long-term care. It is not hard to find that insurance enrollment decision is dependent with health care use. On one hand, these two variables are influenced by observable information, such as health status, income etc. On the other hand, latent factors, or unobservable heterogeneity, such as attitudes toward risks and life style, may also have a substantial impact on both enrollment decision and utilization. Thus the econometric modeling of the effect of insurance on health care utilization faces three challenges. First, to control for the endogeneity, we use maximum simulated likelihood estimation with latent factors. Second, the dependence between two decisions causes a simultaneity problem. The simultaneity is corrected by jointly modeling insurance enrollment decision and health care utilization. Third, this paper analyzes a five-wave panel data from Health and Retirement Study (HRS). The analysis of longitudinal data presents a challenge both to methodology and empirical application. This paper applies the joint maximum simulated likelihood estimation approach within a panel framework. We use the original HRS, which started in 1992 and surveyed subsequently every two years. However, Wave 1 (1992) questions ask about health care utilizations in the last 12 months, while questions in subsequent waves ask about the period since the previous interview or the last 2 years. In order to obtain consistent measurement of medical care utilization, we use data from wave 2 to 6 and restrict the attention to individuals who have Medicare. The final data consists of 4,541 individuals with 11,775 observations. This is an unbalanced panel because some individuals, who appear in the initial waves but not in all subsequent waves, do so due to death. Although follow-up response rates in HRS are high, attrition due to death for the elderly sample is unavoidable. And new people join HRS survey later mainly because of family reconstruction.