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How he won: Using machine learning to understand Trump’s 2016 victory

Author

Listed:
  • Zhaochen He

    (Christopher Newport University)

  • John Camobreco

    (Christopher Newport University)

  • Keith Perkins

    (Christopher Newport University)

Abstract

The meaning of Donald Trump’s 2016 victory has been widely debated. Some believe that Trump’s success stemmed from the decline of manufacturing and other macroeconomic changes. Others see a political strategy that exploited antagonism towards minorities and immigrants. We put both accounts to the test. Using data from the Quarterly Workforce Indicators (QWI) program, we construct a county-level metric of job decline and pair it with a large survey of political and social opinion. Using both logistic regression and random forest classification, we then estimate the impact of economics, race, and other factors on voter choice in 2016. We also perform a “what if” analysis, predicting how the election would have proceeded had voters experienced greater economic hardship, or harbored more progressive views towards race and immigration. Overall, our research indicates that attitudes towards race and immigration played a significantly larger role in the elections than economics. However, we do find evidence that deteriorating job conditions may have exacerbated the importance of racial views.

Suggested Citation

  • Zhaochen He & John Camobreco & Keith Perkins, 2022. "How he won: Using machine learning to understand Trump’s 2016 victory," Journal of Computational Social Science, Springer, vol. 5(1), pages 905-947, May.
    • Handle: RePEc:spr:jcsosc:v:5:y:2022:i:1:d:10.1007_s42001-021-00147-3
    DOI: 10.1007/s42001-021-00147-3
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    References listed on IDEAS

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    1. Hill, Daniel W. & Jones, Zachary M., 2014. "An Empirical Evaluation of Explanations for State Repression," American Political Science Review, Cambridge University Press, vol. 108(3), pages 661-687, August.
    2. Emily Oster, 2018. "Diabetes and Diet: Purchasing Behavior Change in Response to Health Information," American Economic Journal: Applied Economics, American Economic Association, vol. 10(4), pages 308-348, October.
    3. Xiaochen Hu & Xudong Zhang & Nicholas Lovrich, 2021. "Public perceptions of police behavior during traffic stops: logistic regression and machine learning approaches compared," Journal of Computational Social Science, Springer, vol. 4(1), pages 355-380, May.
    4. Justin R. Pierce & Peter K. Schott, 2020. "Trade Liberalization and Mortality: Evidence from US Counties," American Economic Review: Insights, American Economic Association, vol. 2(1), pages 47-64, March.
    5. Muchlinski, David & Siroky, David & He, Jingrui & Kocher, Matthew, 2016. "Comparing Random Forest with Logistic Regression for Predicting Class-Imbalanced Civil War Onset Data," Political Analysis, Cambridge University Press, vol. 24(1), pages 87-103, January.
    6. Jensen, J. Bradford & Quinn, Dennis P. & Weymouth, Stephen, 2017. "Winners and Losers in International Trade: The Effects on US Presidential Voting," International Organization, Cambridge University Press, vol. 71(3), pages 423-457, July.
    7. Rickard, Stephanie J., 2020. "Economic geography, politics, and policy," LSE Research Online Documents on Economics 104716, London School of Economics and Political Science, LSE Library.
    8. Bor, J., 2017. "Diverging life expectancies and voting patterns in the 2016 US Presidential Election," American Journal of Public Health, American Public Health Association, vol. 107(10), pages 1560-1562.
    9. repec:aph:ajpbhl:10.2105/ajph.2017.303945_8 is not listed on IDEAS
    10. Jacob M. Montgomery & Santiago Olivella, 2018. "Tree‐Based Models for Political Science Data," American Journal of Political Science, John Wiley & Sons, vol. 62(3), pages 729-744, July.
    Full references (including those not matched with items on IDEAS)

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