arXiv 23 May 2021 · Econometrics
arXiv:2105.10965 · PDF · DOI · OpenAlex · Extracted main text
We propose a method for conducting asymptotically valid inference for treatment effects in a multi-valued treatment framework where the number of units in the treatment arms can be small and do not grow with the sample size. We accomplish this by casting the model as a semi-/non-parametric conditional quantile model and using known finite sample results about the law of the indicator function that defines the conditional quantile. Our framework allows for structural functions that are non-additively separable, with flexible functional forms and heteroskedasticy in the residuals, and it also encompasses commonly used designs like difference in difference. We study the finite sample behavior of our test in a Monte Carlo study and we also apply our results to assessing the effect of weather events on GDP growth.
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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 | X. Chen, O. Linton, and I. Van Keilegom (2003) Estimation of semiparametric models when the criterion function is not smooth | 0.909 | 8 | 3 | 75% |
| 2 | M. Dell, B. F. Jones, and B. A. Olken (2012) Temperature shocks and economic growth: Evidence from the last half century | 0.874 | 8 | 2 | 100% |
| 3 | X. Chen and D. Pouzo (2012) Estimation of nonparametric conditional moment models with possibly nonsmooth generalized residuals | 0.874 | 6 | 2 | 100% |
| 4 | B. Ferman and C. Pinto (2019) Inference in differences-in-differences with few treated groups and heteroskedasticity | 0.874 | 5 | 2 | 100% |
| 5 | V. Chernozhukov, C. Hansen, and M. Jansson (2009) Finite sample inference for quantile regression models | 0.811 | 4 | 2 | 100% |
| 6 | V. Chernozhukov and C. Hansen (2005) An iv model of quantile treatment effects | 0.737 | 4 | 2 | 75% |
| 7 | B. Callaway and P. H. Sant'Anna (2018) Difference-in-differences with multiple time periods and an application on the minimum wage and employment | 0.737 | 3 | 2 | 100% |
| 8 | S. Han (2018) Identification in nonparametric models for dynamic treatment effects | 0.737 | 3 | 2 | 100% |
| 9 | C. de Chaisemartin and X. D'Haultfœuille (2020) Two-way fixed effects estimators with heterogeneous treatment effects | 0.644 | 2 | 2 | 100% |
| 10 | L. Sun and S. Abraham (2020) Estimating dynamic treatment effects in event studies with heterogeneous treatment effects | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 34 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Stable Probability Weighting Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap | 0.693 | 5 | 1 |