Extremal quantile regression: an overview
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- Victor Chernozhukov & Iv'an Fern'andez-Val & Tetsuya Kaji, 2016. "Extremal Quantile Regression: An Overview," Papers 1612.06850, arXiv.org, revised Feb 2017.
- Victor Chernozhukov & Ivan Fernandez-Val & Tetsuya Kaji, 2017. "Extremal quantile regression: an overview," CeMMAP working papers 65/17, Institute for Fiscal Studies.
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Cited by:
- Chao, Shih-Kang & Härdle, Wolfgang K. & Yuan, Ming, 2021.
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- Chao, Shih-Kang & Härdle, Wolfgang Karl & Yuan, Ming, 2016. "Factorisable multi-task quantile regression," SFB 649 Discussion Papers 2016-057, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- Chao, Shih-Kang & Härdle, Wolfgang Karl & Yuan, Ming, 2020. "Factorisable Multitask Quantile Regression," IRTG 1792 Discussion Papers 2020-004, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
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- Matthew A. Masten & Alexandre Poirier, 2022. "Choosing Exogeneity Assumptions in Potential Outcome Models," Papers 2205.02288, arXiv.org.
- D’Haultfœuille, Xavier & Maurel, Arnaud & Zhang, Yichong, 2018.
"Extremal quantile regressions for selection models and the black–white wage gap,"
Journal of Econometrics, Elsevier, vol. 203(1), pages 129-142.
- Xavier D'Haultfoeuille & Arnaud Maurel & Yichong Zhang, 2014. "Extremal Quantile Regressions for Selection Models and the Black-White Wage Gap," NBER Working Papers 20257, National Bureau of Economic Research, Inc.
- D'Haultfoeuille, Xavier & Maurel, Arnaud & Zhang, Yichong, 2014. "Extremal Quantile Regressions for Selection Models and the Black-White Wage Gap," IZA Discussion Papers 8256, Institute of Labor Economics (IZA).
- Matthew A. Masten & Alexandre Poirier & Linqi Zhang, 2024.
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- Matthew A. Masten & Alexandre Poirier & Linqi Zhang, 2020. "Assessing Sensitivity to Unconfoundedness: Estimation and Inference," Papers 2012.15716, arXiv.org.
- Matthew A. Masten & Alexandre Poirier & Linqi Zhang, 2021. "Assessing Sensitivity to Unconfoundedness: Estimation and Inference," Working Papers gueconwpa~21-21-08, Georgetown University, Department of Economics.
- Yuya Sasaki & Yulong Wang, 2022.
"Fixed-k Inference for Conditional Extremal Quantiles,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(2), pages 829-837, April.
- Yuya Sasaki & Yulong Wang, 2019. "Fixed-k Inference for Conditional Extremal Quantiles," Papers 1909.00294, arXiv.org, revised Jul 2020.
- Xavier D’Haultfoeuille & Arnaud Maurel & Xiaoyun Qiu & Yichong Zhang, 2020.
"Estimating selection models without an instrument with Stata,"
Stata Journal, StataCorp LP, vol. 20(2), pages 297-308, June.
- D'Haultfoeuille, Xavier & Maurel, Arnaud & Qiu, Xiaoyun & Zhang, Yichong, 2019. "Estimating Selection Models without Instrument with Stata," IZA Discussion Papers 12486, Institute of Labor Economics (IZA).
- Xavier D'Haultfoeuille & Arnaud Maurel & Xiaoyun Qiu & Yichong Zhang, 2019. "Estimating Selection Models without Instrument with Stata," NBER Working Papers 25823, National Bureau of Economic Research, Inc.
- Firpo, Sergio & Galvao, Antonio F. & Pinto, Cristine & Poirier, Alexandre & Sanroman, Graciela, 2022. "GMM quantile regression," Journal of Econometrics, Elsevier, vol. 230(2), pages 432-452.
- Marian Vavra, 2023. "Bias-Correction in Time Series Quantile Regression Models," Working and Discussion Papers WP 3/2023, Research Department, National Bank of Slovakia.
- Matthias Fischer & Daniel Kraus & Marius Pfeuffer & Claudia Czado, 2017. "Stress Testing German Industry Sectors: Results from a Vine Copula Based Quantile Regression," Risks, MDPI, vol. 5(3), pages 1-13, July.
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