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

2. 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?

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

4. 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

5. 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?”

6. 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?”

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

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

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

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

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

12. 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*

13. 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*

14. 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

15. Conclusions
Unsurprisingly, ideology and party registration were predictors of favorability towards the Affordable Care Act  both in 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.

16. 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 )
Thank you for your interest in this work.