Jun Ma, Vadim Marmer, Zhengfei Yu
arXiv 12 Jul 2021 · Econometrics · publishedJournal of Econometrics (2023) · 1 citations (OpenAlex)
arXiv:2107.05559 · PDF · DOI · OpenAlex · Extracted main text
In nonseparable triangular models with a binary endogenous treatment and a binary instrumental variable, Vuong and Xu (2017) established identification results for individual treatment effects (ITEs) under the rank invariance assumption. Using their approach, Feng, Vuong, and Xu (2019) proposed a uniformly consistent kernel estimator for the density of the ITE that utilizes estimated ITEs. In this paper, we establish the asymptotic normality of the density estimator of Feng, Vuong, and Xu (2019) and show that the ITE estimation errors have a non-negligible effect on the asymptotic distribution of the estimator. We propose asymptotically valid standard errors that account for ITEs estimation, as well as a bias correction. Furthermore, we develop uniform confidence bands for the density of the ITE using the jackknife multiplier or nonparametric bootstrap critical values.
appendix boundary found by appendix_titled_section at “\label{sec:Appendix A}Proofs of Theorems in Section \ref{sec:Asymptotic-properties}” · 59% 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 | Chen, X. and K. Kato (2020) Jackknife multiplier bootstrap: finite sample approximations to the $U$-process supremum with applications | 1.000 | 5 | 3 | 100% |
| 2 | Ma, J., V. Marmer, and A. Shneyerov (2019) Inference for first-price auctions with Guerre, Perrigne, and Vuong's estimator self | 0.874 | 5 | 2 | 100% |
| 3 | Chernozhukov, V., D. Chetverikov, and K. Kato (2014) Anti-concentration and honest, adaptive confidence bands | 0.830 | 7 | 4 | 57% |
| 4 | Calonico, S., M. D. Cattaneo, and R. Titiunik (2014) Robust nonparametric confidence intervals for regression-discontinuity designs | 0.811 | 4 | 2 | 100% |
| 5 | Chernozhukov, V., D. Chetverikov, and K. Kato (2016) Empirical and multiplier bootstraps for suprema of empirical processes of increasing complexity, and related gaussian couplings | 0.737 | 5 | 3 | 40% |
| 6 | Cheng, G. and Y.-C. Chen (2019) Nonparametric inference via bootstrapping the debiased estimator | 0.737 | 3 | 2 | 100% |
| 7 | Guerre, E., I. Perrigne, and Q. Vuong (2000) Optimal nonparametric estimation of first-price auctions | 0.737 | 3 | 2 | 100% |
| 8 | Li, D. and Q. Li (2010) Nonparametric/semiparametric estimation and testing of econometric models with data dependent smoothing parameters | 0.737 | 3 | 2 | 100% |
| 9 | Feng, Q., Q. Vuong, and H. Xu (2019) Estimation of heterogeneous individual treatment effects with endogenous treatments | 0.737 | 3 | 2 | 100% |
| 10 | Abadie, A., J. Angrist, and G. Imbens (2002) Instrumental variables estimates of the effect of subsidized training on the quantiles of trainee earnings | 0.644 | 2 | 2 | 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 | Inference on the Distribution of Individual Treatment Effects in Nonseparable Triangular ModelsDate | 1.000 | 15 | 4 |
| 2 | Empirical Likelihood Covariate Adjustment for Regression Discontinuity Designs This version: April 22, 2024 | 0.405 | 1 | 1 |