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Journal of Business & Economic Statistics Volume 37, 2019 - Issue 4
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Original Articles

Uniform Inference on Quantile Effects under Sharp Regression Discontinuity Designs

Zhongjun Qua Department of Economics, Boston University, Boston, MA02215 ([email protected])
&
Jungmo Yoonb College of Economics and Finance, Hanyang University, 222 Wangsimni-Ro, Seongdong-Gu, Seoul, Korea ([email protected])
Pages 625-647 | Received 01 Jul 2016, Published online: 04 Jun 2018

Citations (8)

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Read on this site (3)

Yuya Sasaki & Yulong Wang. (2022) Fixed-k Inference for Conditional Extremal Quantiles. Journal of Business & Economic Statistics 40:2, pages 829-837.
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Degui Li, Qi Li & Zheng Li. (2021) Nonparametric Quantile Regression Estimation With Mixed Discrete and Continuous Data. Journal of Business & Economic Statistics 39:3, pages 741-756.
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Mingfeng Zhan & Karen X. Yan. On the estimation of quantile treatment effects using a semiparametric propensity score. Econometric Reviews 0:0, pages 1-22.
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Articles from other publishers (6)

Zhongjun Qu, Jungmo Yoon & Pierre Perron. (2024) Inference on Conditional Quantile Processes in Partially Linear Models with Applications to the Impact of Unemployment Benefits. Review of Economics and Statistics 106:2, pages 521-541.
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Matias D. CattaneoRocío Titiunik. (2022) Regression Discontinuity Designs. Annual Review of Economics 14:1, pages 821-851.
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Blaise Melly & Rafael Lalive. 2020. Handbook of Labor, Human Resources and Population Economics. Handbook of Labor, Human Resources and Population Economics 1 32 .
Shaojun Guo, Yu Han & Qingsong Wang. (2021) Better nonparametric confidence intervals via robust bias correction for quantile regression. Stat 10:1.
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Heng Chen, Harold D. Chiang & Yuya Sasaki. (2020) QUANTILE TREATMENT EFFECTS IN REGRESSION KINK DESIGNS. Econometric Theory 36:6, pages 1167-1191.
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Yingying Dong, Ying-Ying Lee & Michael Gou. (2018) Regression Discontinuity Designs with a Continuous Treatment. SSRN Electronic Journal.
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