arXiv 17 Apr 2020 · Econometrics · publishedJournal of Business and Economic Statistics (2023) · 1 citations (OpenAlex)
arXiv:2004.08318 · PDF · DOI · OpenAlex · Extracted main text
We study causal inference under case-control and case-population sampling. Specifically, we focus on the binary-outcome and binary-treatment case, where the parameters of interest are causal relative and attributable risks defined via the potential outcome framework. It is shown that strong ignorability is not always as powerful as it is under random sampling and that certain monotonicity assumptions yield comparable results in terms of sharp identified intervals. Specifically, the usual odds ratio is shown to be a sharp identified upper bound on causal relative risk under the monotone treatment response and monotone treatment selection assumptions. We offer algorithms for inference on the causal parameters that are aggregated over the true population distribution of the covariates. We show the usefulness of our approach by studying three empirical examples: the benefit of attending private school for entering a prestigious university in Pakistan; the relationship between staying in school and getting involved with drug-trafficking gangs in Brazil; and the link between physicians' hours and size of the group practice in the United States.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Carvalho \ Soares (2016) `Living on the edge: Youth entry, career and exit in drug-selling gangs', Journal of Economic Behavior & Organization 121, 77–98 | 1.000 | 5 | 3 | 100% |
| 2 | Lancaster \ Imbens (1996) `Case-control studies with contaminated controls', Journal of Econometrics 71(1-2), 145–160 | 0.843 | 3 | 3 | 100% |
| 3 | Delavande \ Zafar (2019) `University choice: The role of expected earnings, nonpecuniary outcomes, and financial constraints', Journal of Political Econo… | 0.811 | 4 | 2 | 100% |
| 4 | Holland \ Rubin (1988) `Causal inference in retrospective studies', Evaluation Review 12(3), 203–231 | 0.811 | 4 | 2 | 100% |
| 5 | Manski \ Pepper (2000) `Monotone instrumental variables: With an application to the returns to schooling', Econometrica 68(4), 997–1010 | 0.737 | 3 | 2 | 100% |
| 6 | Manski (1997) `Monotone treatment response', Econometrica 65(6), 1311–1334 | 0.644 | 2 | 2 | 100% |
| 7 | Fang \ Gong (2017) `Detecting potential overbilling in medicare reimbursement via hours worked', American Economic Review 107(2), 562–91 | 0.585 | 3 | 1 | 100% |
| 8 | Kuroki, Cai \ Geng (2010) `Sharp bounds on causal effects in case-control and cohort studies', Biometrika 97(1), 123–132 | 0.585 | 3 | 1 | 100% |
| 9 | Gabriel, Sachs \ Sjölander (2022) `Causal bounds for outcome-dependent sampling in observational studies', Journal of the American Statistical Association 117(538… | 0.511 | 2 | 1 | 100% |
| 10 | Manski (2007) Identification for prediction and decision, Harvard University Press | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 55 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | 2503.06046 | 0.644 | 2 | 2 |
| 2 | The role of the geometric mean in case-control studies | 0.511 | 2 | 1 |
| 3 | Average Adjusted Association: Efficient Estimation with High Dimensional Confounders | 0.405 | 1 | 1 |
| 4 | 2509.26517 | 0.405 | 1 | 1 |