Duke 2008 | ASHE | Equity and Efficiency in Health and Healthcare

While economic theory predicts that workers bear the cost of rising health insurance premiums with reductions in wages and/or other benefits, empirical evidence on the existence of a wage-health insurance tradeoff has been mixed. Empirical analyses have been hampered by the fact that individuals with employer-sponsored insurance are usually more skilled and have higher wages than those without insurance. For instance, a simple regression of wages on the presence of health insurance typically leads to a positive, rather than a negative relationship.

Several recent studies have used difference-in-differences strategies to explore this topic across geographic areas with differing health care costs or inflation rates. For instance, Sheiner (1999) finds evidence that age-wage profiles are flattest in high-health cost areas, reflecting the incidence of health costs on workers’ wages. Sommers (2005) finds evidence that when employers are faced with rising premiums, the increased insurance costs can be better absorbed through wage adjustments in areas with high general inflation or by high wage workers. Both of these studies analyzed household level survey data.

We extend this literature using employer level data from the 1999-2005 Medical Expenditure Panel Survey – Insurance Component (MEPS-IC), a large, nationally representative survey of employers and their health insurance plans. We also extend prior work in that we use difference-in-differences strategies to examine the effect of high premium growth on a wider set of health insurance outcomes: the likelihood that an employer will offer insurance, employee premium contribution levels and benefit generosity. Our strategies involve comparing areas with varying levels of premium growth and general inflation and employers with different wage distributions and number of employees.

To form premium-specific inflation measures, we predict values from a hedonic regression of MEPS-IC premiums on various MSA-level measures of health care costs as well as plan type and benefits. MSA-level predictions are then formed by fixing plan type and benefits, so that the only source of variation is health care costs. To identify areas with varying levels of inflation, we combine the MEPS-IC data with the following price information: 1) the CPI for Metropolitan Statistical Areas (which provides MSA-specific inflation rates over time), 2) price data from the American Chamber of Commerce Researchers’ Association (which provides price level data by MSA for comparisons across MSAs and across time), 3) Geographic Practice Cost Indices from CMS and 4) the Hospital Wage Index from CMS.

Our preliminary results indicate that it is important to examine a range of health insurance outcomes to obtain a full picture of the different methods employers may use to respond to rising health care costs. We find that low wage establishments may respond to increased premium inflation by switching plan types (i.e. towards HMOs and therefore lower deductibles). While they also appear to shift towards FFS plans, further research is needed to examine if this result reflects a shift to high deductible FFS plans. Small employers may adjust to increased cost pressures by increasing employee contributions towards family plans and being less likely to offer family coverage.