Californians and the Affordable Care Act December 15, 2017 Lunna Lopes

Research Questions What are the demographic predictors of favorability towards the Affordable Care Act among Californians? Have the predictors of favorability towards the Affordable Care Act changed since 2013?

Outline Data and Methods Context of Californians and Health Care Reform Findings Conclusions

Data and Methods PPIC Statewide Surveys: 2013, 2017 1700 California adults; >1,000 likely voters RDD on landline and cell phones Logit regression models for predictors of favorability towards the Affordable Care Act Linear probability model with year interaction term for difference in coefficients between 2013 and 2017 Briefly, the primary data for this paper come from pooled Public Policy Institute of California surveys conducted between 2012 and 2015. The survey, directed by Mark Baldassare, monitors political, social, and economic trends and public policy preferences in California. All of our surveys are RDD, and we interview approximately 17,00 adult residents for each survey. We do not limit our interviews to likely, registered, or even eligible voters, or apply any other screen on our samples. --California voter file ----imputed propensity score --Linear regression of vote propensity

Two-thirds of Californians say health care coverage is a responsibility of the federal government “Do you think it is the responsibility of the federal government to make sure all Americans have health care coverage or is that not the responsibility of the federal government?”

Californians are now more likely to have a favorable opinion of the ACA “Given what you know about the health reform law, do you have a generally favorable generally unfavorable opinion of it?”

Support for the ACA: 2013 vs 2017 – Gender and Parents % favorable

Support for the ACA: 2013 vs 2017 – Race/Ethnicity % favorable

Support for the ACA: 2013 vs 2017 – Income % favorable

Support for the ACA: 2013 vs 2017 – Age and Education % favorable

Support for the ACA: 2013 vs 2017 – Party and Ideology % favorable

Results of Logistic Regressions 2013 ACA Favorability 2017 ACA Favorability Age -.046 -.026 Female .089 -.309 Income .069 -.142* Education .008 .013 White -.228 -.247 Born in the US -.030 .293 Parent -.051 .274 Ideology (Very Con – Very Lib) .487* .528* Party (Strong Rep – Strong Dem) .449* .500*

Results of linear probability model Year (2017) .116* Age -.005 Female -.018 Income -.008 Education .001 White -.039 Born in the US .022 Parent .017 Ideology (Very Con – Very Lib) .085* Party (Strong Rep – Strong Dem) .094*

Results of linear probability model with year interaction Age .002 Female -.071 Income -.033* Education -.003 White -.006 Born in the US .049 Parent .059 Ideology (Very Con – Very Lib) -.004 Party (Strong Rep – Strong Dem) .010

Conclusions Unsurprisingly, ideology and party registration were predictors of favorability towards the Affordable Care Act  both in 2013 and 2017. When comparing 2017 to 2013, support for the ACA has increased across party, ideology, and demographic groups. However, when we look at the difference in the coefficients between 2013 and 2017, only income is significant.

Notes on the use of these slides These slides were created to accompany a presentation. They do not include full documentation of sources, data samples, methods, and interpretations. To avoid misinterpretations, please contact: Lunna Lopes (lopes@ppic.org; 415-291-4492) Thank you for your interest in this work.