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Who Did the Affordable Care Act Medicaid Expansion Impact? Using Linear Discriminant Analysis to Estimate the Probability of Being a Complier

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  • Benjamin C. Chu

    (University of Hawaii)

Abstract

What is the likelihood of being a complier in the ACA Medicaid expansion? Using linear discriminant analysis (LDA), I estimate how characteristics relating to socioeconomic status and race/ethnicity affect the likelihood that an individual will be a complier, defined as those induced by the expansion to obtain Medicaid coverage. Across multiple specifications, part-time and full-time workers are more likely than non-workers to be compliers. Not only is this result more prominent for Black individuals, but they are also more likely to be compliers compared to other racial/ethnic groups. This paper not only serves to identify the types of individuals who were directly impacted by the expansion, but it also introduces a new approach that combines complier analysis with techniques from machine learning.

Suggested Citation

  • Benjamin C. Chu, 2022. "Who Did the Affordable Care Act Medicaid Expansion Impact? Using Linear Discriminant Analysis to Estimate the Probability of Being a Complier," Working Papers 202202, University of Hawaii at Manoa, Department of Economics.
    • Handle: RePEc:hai:wpaper:202202
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    File URL: http://www.economics.hawaii.edu/research/workingpapers/WP_22-02.pdf
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Medicaid; ACA; Complier; Linear discriminant analysis;
    All these keywords.

    JEL classification:

    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private

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