The effect of the Affordable Care Act Medicaid expansion on consumer bankruptcies
Bibliographic record
Abstract
Abstract Medical expenses have been associated with a large proportion of consumer bankruptcies in the United States. The objective of this study is to examine the relationship between the Medicaid expansion implemented in the context of the Affordable Care Act and consumer bankruptcy, overall and by chapter filing. We used a longitudinal study design with a study period of 2008–2017. We tested three approaches: difference‐in‐differences, fixed effect panel linear regression, and triple difference. We constructed a panel dataset from 2008 to 2017 with states’ data using data from various sources on insurance, bankruptcy filings, and characteristics that may affect bankruptcy, such as income and ethnicity. The outcomes were the annual rates of consumer bankruptcies overall and by chapter at the state level. Between 2008 and 2017, the overall unadjusted bankruptcy filing rate fell from 0.36% to 0.24%. We found that the expansion was associated with a decrease in overall consumer bankruptcy varying between 0.035 and 0.039 percentage points and that the intensity of the effect was modulated by the intensity of the treatment. Results were consistent across models and suggest that the Medicaid expansion had a significant negative effect on overall bankruptcy filings and specifically on Chapter 7 filings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".