The impending health care reform will most likely include some form of employer mandate to provide health insurance to most employees. There is concern among a wide array of policymakers and researchers that these mandates will adversely affect employment. Attention focuses on tahe most vulnerable sector of the workforce--namely, those individuals earning less than the sum of the minimum wage plus the hourly cost to the employer of the mandate. For this at-risk population, the employer cannot legally shift any of the burden of these cost increases to the employee. Because of this concern for low wage worker, previous investigations of employer mandates draw on an important analogy with the statutory minimum wage. This research uses the elasticity of teenage and young adult employment with respect to changes in the minimum wage to predict the employment effects of a mandate. Unfortunately, the application of these elasticities to the uninsured population may be suspect. Further, these predictions uniformly suffer from undue sensitivity to the choice of elasticity estimates. We propose to re-estimate a class of models developed to study the employment effects of the minimum wage. This body of work simultaneously estimates the effect the minimum wage on the joint distribution of employment and hourly wages. Our updated model will enable us to compute the probability that each individual in our data will no longer be employed due to a mandate. We will then aggregate these estimates to simulate the impact of employer mandates on this at-risk population. The project will proceed in four stages; First, we will estimate the effect of changes in the minimum wage on employment and wages using data from the Survey of Income and Program Participation. Next, we will explore the robustness of this model by explicitly comparing the model fit across binding changes in state and federal minima. Third, we will identify the subpopulation of the uninsured most likely to experience adverse employment effects. Finally, we will simulate the employment effects of a wide array of financing arrangement for employer mandates, including direct employer contributions, payroll tax financing, and employer subsidies. Together, this research will allow us to generate superior microsimulation estimates of the effects of different mandated health insurance plans on the employment of Americans.

Agency
National Institute of Health (NIH)
Institute
Agency for Healthcare Research and Quality (AHRQ)
Type
Small Research Grants (R03)
Project #
1R03HS008219-01
Application #
2236624
Study Section
Special Emphasis Panel (NSS)
Project Start
1994-05-01
Project End
1996-04-30
Budget Start
1994-05-01
Budget End
1996-04-30
Support Year
1
Fiscal Year
1994
Total Cost
Indirect Cost
Name
Rand Corporation
Department
Type
DUNS #
City
Santa Monica
State
CA
Country
United States
Zip Code
90401