Santiago Acerenza, Kyunghoon Ban, Désiré Kédagni
arXiv 1 May 2021 · Econometrics · 2 citations (OpenAlex)
arXiv:2105.00358 · PDF · DOI · OpenAlex · Extracted main text
This paper studies identification of the local average and marginal treatment effects (LATE and MTE) with a misclassified binary treatment variable. We derive bounds on the (generalized) LATE and exploit its relationship with the MTE to further bound the MTE. Indeed, under some standard assumptions, the MTE is a limit of the ratio of the variation in the conditional expectation of the observed outcome given the instrument to the variation in the true propensity score, which is partially identified. We characterize the identified set for the propensity score, and then for the MTE. We show that our LATE bounds are tighter than the existing bounds and that the sign of the MTE is locally identified under some mild regularity conditions. We use our MTE bounds to derive bounds on other commonly used parameters in the literature and illustrate the practical relevance of our derived bounds through numerical and empirical results.
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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 | Ura, Takuya (2018) Heterogeneous Treatment Effects with Mismeasured Endogenous Treatment | 1.000 | 15 | 3 | 100% |
| 2 | Tommasi, D. and L. Zhang (2020) Bounding Program Benefits When Participation Is Misreported | 1.000 | 6 | 3 | 100% |
| 3 | Heckman, James J and Edward Vytlacil (2005) Structural Equations, Treatment Effects, and Econometric Policy Evaluation | 0.928 | 4 | 3 | 100% |
| 4 | Mahajan, Aprajit (2006) Identification and Estimation of Regression Models with Misclassification | 0.874 | 5 | 2 | 100% |
| 5 | Possebom, V (2021) Crime and Mismeasured Punishment: Marginal Treatment Effect with Misclassification | 0.843 | 3 | 3 | 100% |
| 6 | Calvi, C., A. Lewbel, and D. Tommasi (2022) Women’s Empowerment and Family Health: Estimating LATE with Mismeasured Treatment | 0.811 | 4 | 2 | 100% |
| 7 | Black, D., S. Sanders, and L. Taylor (2003) Measurement of Higher Education in the Census and CPS | 0.737 | 3 | 2 | 100% |
| 8 | Kreider, B., J. V. Pepper, C. Gundersen, and D. Jolliffe (2012) Identifying the effects of SNAP (food stamps) on child health outcomes when participation is endogenous and misreported | 0.737 | 3 | 2 | 100% |
| 9 | Lewbel, Arthur (2007) Estimation of Average Treatment Effects with Misclassification | 0.737 | 3 | 2 | 100% |
| 10 | Carneiro, P., M. Lokshin, and N. Umapathi (2017) Average and Marginal Returns to Upper Secondary Schooling in Indonesia | 0.693 | 8 | 1 | 100% |
Showing the top 10 of 45 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Misclassification in Difference-in-Differences Models | 0.644 | 2 | 2 |