Working Paper: NBER ID: w19397
Authors: Neeraj Sood; Yanyu Wu
Abstract: This paper investigates the effects of health insurance and new antiviral treatments on HIV testing rates among the U.S. general population using nationally representative data from the Behavioral Risk Factor Surveillance Survey (BRFSS) for the years 1993 to 2002. We estimate recursive bivariate probit models with insurance coverage and HIV testing as the dependent variables. We use changes in Medicaid eligibility and distribution of firm size over time within a state as instruments for insurance coverage. The results suggest that (a) insurance coverage increases HIV testing rates, (b) insurance coverage increases HIV testing rates more among the high risk population, and (c) the advent of Highly Active Antiretroviral Therapy (HAART) increases the effects of insurance coverage on HIV testing for high risk populations.
Keywords: HIV Testing; Health Insurance; HAART; Public Health
JEL Codes: I12; I13
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Health insurance coverage (I13) | Probability of undergoing HIV testing (C12) |
| Health insurance coverage (I13) | Probability of undergoing HIV testing (high risk) (C12) |
| Health insurance coverage (I13) | Probability of undergoing HIV testing (low risk) (C12) |
| HAART introduction (Y20) | Effect of insurance on HIV testing (high risk) (G52) |
| HAART introduction (Y20) | Effect of insurance on HIV testing (low risk) (G52) |