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Nonparametric estimation and inference on conditional quantile processes
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Cited by:
- Goldman, Matt & Kaplan, David M., 2018.
"Comparing distributions by multiple testing across quantiles or CDF values,"
Journal of Econometrics, Elsevier, vol. 206(1), pages 143-166.
- David M. Kaplan & Matt Goldman, 2016. "Comparing distributions by multiple testing across quantiles or CDF values," Working Papers 1619, Department of Economics, University of Missouri, revised 22 Feb 2018.
- David M. Kaplan & Matt Goldman, 2018. "Comparing distributions by multiple testing across quantiles or CDF values," Working Papers 1801, Department of Economics, University of Missouri.
- Matt Goldman & David M. Kaplan, 2017. "Comparing distributions by multiple testing across quantiles or CDF values," Papers 1708.04658, arXiv.org.
- Graham, Bryan S. & Hahn, Jinyong & Poirier, Alexandre & Powell, James L., 2018.
"A quantile correlated random coefficients panel data model,"
Journal of Econometrics, Elsevier, vol. 206(2), pages 305-335.
- Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers CWP34/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers 34/16, Institute for Fiscal Studies.
- Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
- Ferreira, Francisco H. G. & Firpo, Sergio & Galvao, Antonio F., 2017.
"Estimation and Inference for Actual and Counterfactual Growth Incidence Curves,"
IZA Discussion Papers
10473, Institute of Labor Economics (IZA).
- Ferreira,Francisco H. G. & Firpo,Sergio & Galvao,Antonio F., 2017. "Estimation and inference for actual and counterfactual growth incidence curves," Policy Research Working Paper Series 7933, The World Bank.
- Chiang, Harold D. & Hsu, Yu-Chin & Sasaki, Yuya, 2019. "Robust uniform inference for quantile treatment effects in regression discontinuity designs," Journal of Econometrics, Elsevier, vol. 211(2), pages 589-618.
- Matt Goldman & David M. Kaplan, 2018.
"Non‐parametric inference on (conditional) quantile differences and interquantile ranges, using L‐statistics,"
Econometrics Journal, Royal Economic Society, vol. 21(2), pages 136-169, June.
- David M. Kaplan & Matt Goldman, 2015. "Nonparametric inference on conditional quantile differences and linear combinations, using L-statistics," Working Papers 1503, Department of Economics, University of Missouri.
- David M. Kaplan & Matt Goldman, 2016. "Nonparametric inference on conditional quantile differences and linear combinations, using L-statistics," Working Papers 1620, Department of Economics, University of Missouri.
- Hao, Meiling & Lin, Yuanyuan & Shen, Guohao & Su, Wen, 2023. "Nonparametric inference on smoothed quantile regression process," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
- Victor Chernozhukov & Iván Fernández-Val & Blaise Melly & Kaspar Wüthrich, 2020.
"Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(529), pages 123-137, January.
- Victor Chernozhukov & Iv'an Fern'andez-Val & Blaise Melly & Kaspar Wuthrich, 2016. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," Papers 1608.05142, arXiv.org, revised Aug 2018.
- Chernozhukov, Victor & Fernández-Val, Iván & Melly, Blaise & Wüthrich, Kaspar, 2020. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," University of California at San Diego, Economics Working Paper Series qt5zm6m9rq, Department of Economics, UC San Diego.
- Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly & Kaspar Wüthrich, 2017. "Generic inference on quantile and quantile effect functions for discrete outcomes," CeMMAP working papers CWP23/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly & Kaspar Wüthrich, 2017. "Generic inference on quantile and quantile effect functions for discrete outcomes," CeMMAP working papers 23/17, Institute for Fiscal Studies.
- Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly & Kaspar Wüthrich, 2016. "Generic inference on quantile and quantile effect functions for discrete outcomes," CeMMAP working papers 35/16, Institute for Fiscal Studies.
- Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly & Kaspar Wüthrich, 2016. "Generic inference on quantile and quantile effect functions for discrete outcomes," CeMMAP working papers CWP35/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly & Kaspar W thrich, 2016. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," Diskussionsschriften dp1607, Universitaet Bern, Departement Volkswirtschaft.
- Xu, Ke-Li, 2020. "Inference of local regression in the presence of nuisance parameters," Journal of Econometrics, Elsevier, vol. 218(2), pages 532-560.
- Valentina Corradi & Daniel Gutknecht, 2019. "Testing for Quantile Sample Selection," Papers 1907.07412, arXiv.org, revised Jan 2021.
- Zongwu Cai & Xiyuan Liu, 2020. "A Functional-Coefficient VAR Model for Dynamic Quantiles with Constructing Financial Network," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202017, University of Kansas, Department of Economics, revised Oct 2020.
- Manuel Arellano & Stéphane Bonhomme, 2016.
"Nonlinear panel data estimation via quantile regressions,"
Econometrics Journal, Royal Economic Society, vol. 19(3), pages 61-94, October.
- Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear panel data estimation via quantile regressions," CeMMAP working papers CWP40/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear panel data estimation via quantile regressions," CeMMAP working papers 40/15, Institute for Fiscal Studies.
- Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear Panel Data Estimation via Quantile Regression," Working Papers wp2015_1505, CEMFI.
- Yunyun Wang & Tatsushi Oka & Dan Zhu, 2024. "Inflation Target at Risk: A Time-varying Parameter Distributional Regression," Papers 2403.12456, arXiv.org.
- Belloni, Alexandre & Chernozhukov, Victor & Chetverikov, Denis & Fernández-Val, Iván, 2019.
"Conditional quantile processes based on series or many regressors,"
Journal of Econometrics, Elsevier, vol. 213(1), pages 4-29.
- Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val, 2011. "Conditional quantile processes based on series or many regressors," CeMMAP working papers CWP19/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Ivan Fernandez-Val, 2016. "Conditional quantile processes based on series or many regressors," CeMMAP working papers 46/16, Institute for Fiscal Studies.
- Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Ivan Fernandez-Val, 2016. "Conditional quantile processes based on series or many regressors," CeMMAP working papers CWP46/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Iv'an Fern'andez-Val, 2011. "Conditional Quantile Processes based on Series or Many Regressors," Papers 1105.6154, arXiv.org, revised Aug 2018.
- Arie Beresteanu, 2016.
"Quantile Regression with Interval Data,"
Working Paper
5991, Department of Economics, University of Pittsburgh.
- Arie Beresteanu, 2020. "Quantile Regression with Interval Data," Working Paper 6899, Department of Economics, University of Pittsburgh.
- Goldman, Matt & Kaplan, David M., 2017.
"Fractional order statistic approximation for nonparametric conditional quantile inference,"
Journal of Econometrics, Elsevier, vol. 196(2), pages 331-346.
- David M. Kaplan & Matt Goldman, 2015. "Fractional order statistic approximation for nonparametric conditional quantile inference," Working Papers 1502, Department of Economics, University of Missouri.
- Matt Goldman & David M. Kaplan, 2016. "Fractional order statistic approximation for nonparametric conditional quantile inference," Papers 1609.09035, arXiv.org.
- Goldman, Matt & Kaplan, David M., 2018.
"Comparing distributions by multiple testing across quantiles or CDF values,"
Journal of Econometrics, Elsevier, vol. 206(1), pages 143-166.
- David M. Kaplan & Matt Goldman, 2013. "Comparing distributions by multiple testing across quantiles," Working Papers 1319, Department of Economics, University of Missouri, revised Feb 2018.
- David M. Kaplan & Matt Goldman, 2016. "Comparing distributions by multiple testing across quantiles or CDF values," Working Papers 1619, Department of Economics, University of Missouri, revised 22 Feb 2018.
- Yijian Huang, 2017. "Restoration of Monotonicity Respecting in Dynamic Regression," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 613-622, April.
- Christis Katsouris, 2023. "Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates," Papers 2302.05193, arXiv.org.
- Racine, Jeffrey S. & Li, Kevin, 2017. "Nonparametric conditional quantile estimation: A locally weighted quantile kernel approach," Journal of Econometrics, Elsevier, vol. 201(1), pages 72-94.
- Liang Chen, 2019. "Nonparametric Quantile Regressions for Panel Data Models with Large T," Papers 1911.01824, arXiv.org, revised Sep 2020.
- Yingying DONG & Ying-Ying LEE & Michael GOU, 2019. "Regression Discontinuity Designs with a Continuous Treatment," Discussion papers 19058, Research Institute of Economy, Trade and Industry (RIETI).
- Feng, Xingdong & Liu, Qiaochu & Wang, Caixing, 2023. "A lack-of-fit test for quantile regression process models," Statistics & Probability Letters, Elsevier, vol. 192(C).
- Junquera, Álvaro F., 2024. "More money, more effect? Employment effects of job search programs in Veneto," SocArXiv rjshu, Center for Open Science.
- Xie, Haitian, 2024. "Nonlinear and nonseparable structural functions in regression discontinuity designs with a continuous treatment," Journal of Econometrics, Elsevier, vol. 242(1).
- Zhongjun Qu & Jungmo Yoon, 2019.
"Uniform Inference on Quantile Effects under Sharp Regression Discontinuity Designs,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 625-647, October.
- Zhongjun Qu & Jungmo Yoon, 2015. "Uniform Inference on Quantile Effects under Sharp Regression Discontinuity Designs," Boston University - Department of Economics - Working Papers Series wp2015-009, Boston University - Department of Economics.
- Chiang, Harold D. & Sasaki, Yuya, 2019. "Causal inference by quantile regression kink designs," Journal of Econometrics, Elsevier, vol. 210(2), pages 405-433.
- Daniel Hlubinka & Lukáš Kotík & Miroslav Šiman, 2022. "Multivariate quantiles with both overall and directional probability interpretation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(4), pages 1586-1604, December.
- Karen X. Yan & Qi Li, 2018. "Nonparametric Estimation of a Conditional Quantile Function in a Fixed Effects Panel Data Model," JRFM, MDPI, vol. 11(3), pages 1-10, August.
- Haitian Xie, 2022. "Nonlinear and Nonseparable Structural Functions in Fuzzy Regression Discontinuity Designs," Papers 2204.08168, arXiv.org, revised Jul 2022.