Estimating the Counterfactual: How Many Uninsured Adults Would There Be Today Without the ACA?

Inquiry. 2016 Apr 13:53:0046958016634991. doi: 10.1177/0046958016634991. Print 2016.


Time lags in receiving data from long-standing, large federal surveys complicate real-time estimation of the coverage effects of full Affordable Care Act (ACA) implementation. Fast-turnaround household surveys fill some of the void in data on recent changes to insurance coverage, but they lack the historical data that allow analysts to account for trends that predate the ACA, economic fluctuations, and earlier public program expansions when predicting how many people would be uninsured without comprehensive health care reform. Using data from the Current Population Survey (CPS) from 2000 to 2012 and the Health Reform Monitoring Survey (HRMS) data for 2013 and 2015, this article develops an approach to estimate the number of people who would be uninsured in the absence of the ACA and isolates the change in coverage as of March 2015 that can be attributed to the ACA. We produce counterfactual forecasts of the number of uninsured absent the ACA for 9 age-income groups and compare these estimates with 2015 estimates based on HRMS relative coverage changes applied to CPS-based population estimates. As of March 2015, we find the ACA has reduced the number of uninsured adults by 18.1 million compared with the number who would have been uninsured at that time had the law not been implemented. That decline represents a 46% reduction in the number of nonelderly adults without insurance. The approach developed here can be applied to other federal data and timely surveys to provide a range of estimates of the overall effects of reform.

Keywords: ACA; estimates; forecast; insurance coverage; uninsured.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Female
  • Humans
  • Income
  • Insurance Coverage / statistics & numerical data*
  • Insurance, Health / statistics & numerical data*
  • Male
  • Medically Uninsured / statistics & numerical data*
  • Middle Aged
  • Models, Statistical*
  • Patient Protection and Affordable Care Act / legislation & jurisprudence*
  • United States
  • Young Adult