Jad Beyhum, Jean-Pierre FLorens, Ingrid Van Keilegom
arXiv 20 Nov 2020 · Mathematics — Statistics Theory · publishedJournal of Business and Economic Statistics (2021) · 9 citations (OpenAlex)
arXiv:2011.10423 · PDF · DOI · OpenAlex · Extracted main text
This paper analyzes the effect of a discrete treatment Z on a duration T. The treatment is not randomly assigned. The confounding issue is treated using a discrete instrumental variable explaining the treatment and independent of the error term of the model. Our framework is nonparametric and allows for random right censoring. This specification generates a nonlinear inverse problem and the average treatment effect is derived from its solution. We provide local and global identification properties that rely on a nonlinear system of equations. We propose an estimation procedure to solve this system and derive rates of convergence and conditions under which the estimator is asymptotically normal. When censoring makes identification fail, we develop partial identification results. Our estimators exhibit good finite sample properties in simulations. We also apply our methodology to the Illinois Reemployment Bonus Experiment.
appendix boundary found by appendix_command · 70% of the source is main text. Read the extracted text to check this.
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 | Chernozhukov \ Hansen (2005) An IV model of quantile treatment effects, Econometrica 73(1): 245–261 | 0.811 | 4 | 2 | 100% |
| 2 | Fève, Florens \ Van Keilegom (2018) Estimation of conditional ranks and tests of exogeneity in nonparametric nonseparable models, Journal of Business & Economic Sta… | 0.811 | 4 | 2 | 100% |
| 3 | Blanco, Chen, Flores \ Flores-Lagunes (2019) Bounds on average and quantile treatment effects on duration outcomes under censoring, selection, and noncompliance, Journal of… | 0.737 | 3 | 2 | 100% |
| 4 | Bijwaard \ Ridder (2005) Correcting for selective compliance in a re-employment bonus experiment, Journal of Econometrics 125(1-2): 77–111 | 0.644 | 2 | 2 | 100% |
| 5 | Cazals, Fève, Florens \ Simar (2016) Nonparametric instrumental variables estimation for efficiency frontier, Journal of Econometrics 190(2): 349–359 | 0.644 | 2 | 2 | 100% |
| 6 | Dunker, Florens, Hohage, Johannes \ Mammen (2014) Iterative estimation of solutions to noisy nonlinear operator equations in nonparametric instrumental regression, Journal of Eco… | 0.644 | 2 | 2 | 100% |
| 7 | Andrews \ Shi (2013) Inference based on conditional moment inequalities, Econometrica 81(2): 609–666 | 0.644 | 2 | 2 | 100% |
| 8 | Manski \ Tamer (2002) Inference on regressions with interval data on a regressor or outcome, Econometrica 70(2): 519–546 | 0.644 | 2 | 2 | 100% |
| 9 | Frandsen (2015) Treatment effects with censoring and endogeneity, Journal of the American Statistical Association 110(512): 1745–1752 | 0.585 | 3 | 1 | 100% |
| 10 | Sant'Anna (2016) Program evaluation with right-censored data, arXiv preprint arXiv:1604.02642 | 0.585 | 3 | 1 | 100% |
Showing the top 10 of 31 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.