Yu-Chin Hsu
Citations
Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.Working papers
- Yu-Chin Hsu & Robert P. Lieli, 2021.
"Inference for ROC Curves Based on Estimated Predictive Indices,"
Papers
2112.01772, arXiv.org.
Cited by:
- Kajal Lahiri & Cheng Yang, 2023. "A tale of two recession-derivative indicators," Empirical Economics, Springer, vol. 65(2), pages 925-947, August.
- Qingliang Fan & Yu-Chin Hsu & Robert P. Lieli & Yichong Zhang, 2019.
"Estimation of Conditional Average Treatment Effects with High-Dimensional Data,"
Papers
1908.02399, arXiv.org, revised Jul 2021.
- Qingliang Fan & Yu-Chin Hsu & Robert P. Lieli & Yichong Zhang, 2022. "Estimation of Conditional Average Treatment Effects With High-Dimensional Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 313-327, January.
Cited by:
- Riccardo Di Francesco, 2022. "Aggregation Trees," CEIS Research Paper 546, Tor Vergata University, CEIS, revised 20 Nov 2023.
- Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP54/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Kyle Colangelo & Ying-Ying Lee, 2020. "Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments," Papers 2004.03036, arXiv.org, revised Sep 2023.
- Michael C. Knaus, 2020.
"Double Machine Learning based Program Evaluation under Unconfoundedness,"
Papers
2003.03191, arXiv.org, revised Jun 2022.
- Knaus, Michael C., 2020. "Double Machine Learning Based Program Evaluation under Unconfoundedness," IZA Discussion Papers 13051, Institute of Labor Economics (IZA).
- Michael C Knaus, 2022. "Double machine learning-based programme evaluation under unconfoundedness [Econometric methods for program evaluation]," The Econometrics Journal, Royal Economic Society, vol. 25(3), pages 602-627.
- Knaus, Michael C., 2020. "Double Machine Learning based Program Evaluation under Unconfoundedness," Economics Working Paper Series 2004, University of St. Gallen, School of Economics and Political Science.
- Arthur Charpentier & Emmanuel Flachaire & Ewen Gallic, 2023. "Optimal Transport for Counterfactual Estimation: A Method for Causal Inference," Papers 2301.07755, arXiv.org.
- Masahiro Kato, 2024. "Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects," Papers 2403.03240, arXiv.org.
- Gregory Faletto, 2023. "Fused Extended Two-Way Fixed Effects for Difference-in-Differences with Staggered Adoptions," Papers 2312.05985, arXiv.org, revised Apr 2024.
- Agboola, Oluwagbenga David & Yu, Han, 2023. "Neighborhood-based cross fitting approach to treatment effects with high-dimensional data," Computational Statistics & Data Analysis, Elsevier, vol. 186(C).
- Phillip Heiler & Michael C. Knaus, 2021.
"Effect or Treatment Heterogeneity? Policy Evaluation with Aggregated and Disaggregated Treatments,"
Papers
2110.01427, arXiv.org, revised Aug 2023.
- Heiler, Phillip & Knaus, Michael C., 2022. "Effect or Treatment Heterogeneity? Policy Evaluation with Aggregated and Disaggregated Treatments," IZA Discussion Papers 15580, Institute of Labor Economics (IZA).
- Kazuhiko Shinoda & Takahiro Hoshino, 2022. "Orthogonal Series Estimation for the Ratio of Conditional Expectation Functions," Papers 2212.13145, arXiv.org.
- Yang Ning & Sida Peng & Jing Tao, 2020. "Doubly Robust Semiparametric Difference-in-Differences Estimators with High-Dimensional Data," Papers 2009.03151, arXiv.org.
- Michael Zimmert & Michael Lechner, 2019. "Nonparametric estimation of causal heterogeneity under high-dimensional confounding," Papers 1908.08779, arXiv.org.
- Zimmert, Franziska & Zimmert, Michael, 2020. "Paid parental leave and maternal reemployment: Do part-time subsidies help or harm?," Economics Working Paper Series 2002, University of St. Gallen, School of Economics and Political Science.
- 'Agoston Reguly, 2021. "Heterogeneous Treatment Effects in Regression Discontinuity Designs," Papers 2106.11640, arXiv.org, revised Oct 2021.
- Claudia Noack & Tomasz Olma & Christoph Rothe, 2021. "Flexible Covariate Adjustments in Regression Discontinuity Designs," Papers 2107.07942, arXiv.org, revised May 2023.
- Daniel Jacob, 2019. "Group Average Treatment Effects for Observational Studies," Papers 1911.02688, arXiv.org, revised Mar 2020.
- Huang, W. & Linton, O. & Zhang, Z., 2021.
"A Unified Framework for Specification Tests of Continuous Treatment Effect Models,"
Cambridge Working Papers in Economics
2113, Faculty of Economics, University of Cambridge.
- Wei Huang & Oliver Linton & Zheng Zhang, 2021. "A Unified Framework for Specification Tests of Continuous Treatment Effect Models," Papers 2102.08063, arXiv.org, revised Sep 2021.
- Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
- Adam Baybutt & Manu Navjeevan, 2023. "Doubly-Robust Inference for Conditional Average Treatment Effects with High-Dimensional Controls," Papers 2301.06283, arXiv.org.
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2019.
"Testing identifying assumptions in fuzzy regression discontinuity designs,"
CeMMAP working papers
CWP10/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Yoichi Arai & Yu‐Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2022. "Testing identifying assumptions in fuzzy regression discontinuity designs," Quantitative Economics, Econometric Society, vol. 13(1), pages 1-28, January.
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifie & Yuanyuan Wan, 2018. "Testing Identifying Assumptions In Fuzzy Regression Discontinuity Designs," Working Papers tecipa-623, University of Toronto, Department of Economics.
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2021. "Testing identifying assumptions in fuzzy regression discontinuity designs," CeMMAP working papers CWP16/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2018. "Testing identifying assumptions in fuzzy regression discontinuity designs," CeMMAP working papers CWP50/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
Cited by:
- Abdulkadiroglu, Atila & Angrist, Joshua & Narita, Yusuke & Pathak, Parag A., 2019.
"Breaking Ties: Regression Discontinuity Design Meets Market Design,"
IZA Discussion Papers
12205, Institute of Labor Economics (IZA).
- Atila Abdulkadiroglu & Joshua Angrist & Yusuke Narita & Parag Pathak, 2019. "Breaking Ties: Regression Discontinuity Design Meets Market Design," Working Papers 2019-024, Human Capital and Economic Opportunity Working Group.
- Atila Abdulkadiroglu & Joshua D. Angrist & Yusuke Narita & Parag Pathak, 2020. "Breaking Ties: Regression Discontinuity Design Meets Market Design," Papers 2101.01093, arXiv.org.
- Atı̇la Abdulkadı̇roğlu & Joshua D. Angrist & Yusuke Narita & Parag Pathak, 2022. "Breaking Ties: Regression Discontinuity Design Meets Market Design," Econometrica, Econometric Society, vol. 90(1), pages 117-151, January.
- Atila Abdulkadiroglu & Joshua D. Angrist & Yusuke Narita & Parag A. Pathak, 2019. "Breaking Ties: Regression Discontinuity Design Meets Market Design," Cowles Foundation Discussion Papers 2170, Cowles Foundation for Research in Economics, Yale University.
- Atila Abdulkadiroglu & Joshua D. Angrist & Yusuke Narita & Parag A. Pathak, 2019. "Breaking Ties: Regression Discontinuity Design Meets Market Design," Cowles Foundation Discussion Papers 2170R Publication Status:, Cowles Foundation for Research in Economics, Yale University, revised Dec 2020.
- Takuya Ishihara & Masayuki Sawada, 2020. "Manipulation-Robust Regression Discontinuity Designs," Papers 2009.07551, arXiv.org, revised Oct 2023.
- Colubi, Ana & Ramos-Guajardo, Ana Belén, 2023. "Fuzzy sets and (fuzzy) random sets in Econometrics and Statistics," Econometrics and Statistics, Elsevier, vol. 26(C), pages 84-98.
- Matias D. Cattaneo & Rocio Titiunik & Gonzalo Vazquez-Bare, 2019.
"The Regression Discontinuity Design,"
Papers
1906.04242, arXiv.org, revised Jun 2020.
- Matias D. Cattaneo & Rocio Titiunik, 2021. "Regression Discontinuity Designs," Papers 2108.09400, arXiv.org, revised Feb 2022.
- Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.
- Joshua D. Angrist, 2022.
"Empirical Strategies in Economics: Illuminating the Path From Cause to Effect,"
Econometrica, Econometric Society, vol. 90(6), pages 2509-2539, November.
- Joshua Angrist, 2022. "Empirical Strategies in Economics: Illuminating the Path from Cause to Effect," NBER Working Papers 29726, National Bureau of Economic Research, Inc.
- Angrist, Joshua, 2021. "Empirical strategies in economics: Illuminating the path from cause to effect," Nobel Prize in Economics documents 2021-4, Nobel Prize Committee.
- Acerenza, Santiago & Bartalotti, Otávio & Kedagni, Desire, 2021.
"Testing Identifying Assumptions in Bivariate Probit Models,"
ISU General Staff Papers
202103290700001124, Iowa State University, Department of Economics.
- Santiago Acerenza & Otávio Bartalotti & Désiré Kédagni, 2023. "Testing identifying assumptions in bivariate probit models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 407-422, April.
- 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).
- Blaise Melly & Rafael Lalive, 2020. "Estimation, Inference, and Interpretation in the Regression Discontinuity Design," Diskussionsschriften dp2016, Universitaet Bern, Departement Volkswirtschaft.
- Mario Fiorini & Katrien Stevens, 2021.
"Scrutinizing the Monotonicity Assumption in IV and fuzzy RD designs,"
Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(6), pages 1475-1526, December.
- Fiorini, Mario & Stevens, Katrien, 2021. "Scrutinizing the Monotonicity Assumption in IV and fuzzy RD designs," Working Papers 2021-01, University of Sydney, School of Economics.
- Matias D. Cattaneo & Luke Keele & Rocio Titiunik, 2023. "A Guide to Regression Discontinuity Designs in Medical Applications," Papers 2302.07413, arXiv.org, revised May 2023.
- Hsu, Yu-Chin & Huber, Martin & Lee, Ying-Ying & Pipoz, Layal, 2018.
"Direct and indirect effects of continuous treatments based on generalized propensity score weighting,"
FSES Working Papers
495, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
- Martin Huber & Yu‐Chin Hsu & Ying‐Ying Lee & Layal Lettry, 2020. "Direct and indirect effects of continuous treatments based on generalized propensity score weighting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(7), pages 814-840, November.
Cited by:
- Yu-Chin Hsu & Martin Huber & Ying-Ying Lee & Chu-An Liu, 2021. "Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment with High-Dimensional Data," Papers 2106.04237, arXiv.org, revised Aug 2022.
- Huber, Martin & Solovyeva, Anna, 2018.
"Direct and indirect effects under sample selection and outcome attrition,"
FSES Working Papers
496, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
- Martin Huber & Anna Solovyeva, 2020. "Direct and Indirect Effects under Sample Selection and Outcome Attrition," Econometrics, MDPI, vol. 8(4), pages 1-25, December.
- Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP54/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
- Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP72/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Stefan Tubbicke, 2020.
"Entropy Balancing for Continuous Treatments,"
Papers
2001.06281, arXiv.org, revised May 2020.
- Stefan Tübbicke, 2020. "Entropy Balancing for Continuous Treatments," CEPA Discussion Papers 21, Center for Economic Policy Analysis.
- Tübbicke Stefan, 2022. "Entropy Balancing for Continuous Treatments," Journal of Econometric Methods, De Gruyter, vol. 11(1), pages 71-89, January.
- Yuya Sasaki & Takuya Ura & Yichong Zhang, 2020.
"Unconditional Quantile Regression with High Dimensional Data,"
Papers
2007.13659, arXiv.org, revised Feb 2022.
- Yuya Sasaki & Takuya Ura & Yichong Zhang, 2022. "Unconditional quantile regression with high‐dimensional data," Quantitative Economics, Econometric Society, vol. 13(3), pages 955-978, July.
- Huang, W. & Linton, O. & Zhang, Z., 2021.
"A Unified Framework for Specification Tests of Continuous Treatment Effect Models,"
Cambridge Working Papers in Economics
2113, Faculty of Economics, University of Cambridge.
- Wei Huang & Oliver Linton & Zheng Zhang, 2021. "A Unified Framework for Specification Tests of Continuous Treatment Effect Models," Papers 2102.08063, arXiv.org, revised Sep 2021.
- Numair Sani & Yizhen Xu & AmirEmad Ghassami & Ilya Shpitser, 2021. "Multiply Robust Causal Mediation Analysis with Continuous Treatments," Papers 2105.09254, arXiv.org, revised Feb 2024.
- Isaac Meza & Rahul Singh, 2021. "Nested Nonparametric Instrumental Variable Regression: Long Term, Mediated, and Time Varying Treatment Effects," Papers 2112.14249, arXiv.org, revised Mar 2024.
- Robert Pal Lieli & Yu-Chin Hsu, 2018.
"Using the Area Under an Estimated ROC Curve to Test the Adequacy of Binary Predictors,"
CEU Working Papers
2018_1, Department of Economics, Central European University.
- Robert P. Lieli & Yu-Chin Hsu, 2019. "Using the area under an estimated ROC curve to test the adequacy of binary predictors," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 31(1), pages 100-130, January.
Cited by:
- Kajal Lahiri & Cheng Yang, 2023.
"ROC and PRC Approaches to Evaluate Recession Forecasts,"
Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(2), pages 119-148, September.
- Kajal Lahiri & Cheng Yang, 2023. "ROC and PRC Approaches to Evaluate Recession Forecasts," CESifo Working Paper Series 10449, CESifo.
- Halko, Marja-Liisa & Lappalainen, Olli & Sääksvuori, Lauri, 2021. "Do non-choice data reveal economic preferences? Evidence from biometric data and compensation-scheme choice," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 87-104.
- Christiansen, Charlotte & Eriksen, Jonas N. & Møller, Stig V., 2019. "Negative house price co-movements and US recessions," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 382-394.
- Saldarriaga, Miguel, 2018.
"Credit Booms in Commodity Exporters,"
Working Papers
2018-008, Banco Central de Reserva del Perú.
- Miguel Angel Saldarriaga, 2017. "Credit Booms in Commodity Exporters," Working Papers 98, Peruvian Economic Association.
- Robert P. Lieli & Yu-Chin Hsu, 2019.
"Using the area under an estimated ROC curve to test the adequacy of binary predictors,"
Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 31(1), pages 100-130, January.
- Robert Pal Lieli & Yu-Chin Hsu, 2018. "Using the Area Under an Estimated ROC Curve to Test the Adequacy of Binary Predictors," CEU Working Papers 2018_1, Department of Economics, Central European University.
- Hsu, Yu-Chin & Huber, Martin & Lai, Tsung Chih, 2017.
"Nonparametric estimation of natural direct and indirect effects based on inverse probability weighting,"
FSES Working Papers
482, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
- Hsu Yu-Chin & Huber Martin & Lai Tsung-Chih, 2019. "Nonparametric estimation of natural direct and indirect effects based on inverse probability weighting," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-20, January.
Cited by:
- Wunsch, Conny & Strobl, Renate, 2018.
"Identification of Causal Mechanisms Based on Between-Subject Double Randomization Designs,"
IZA Discussion Papers
11626, Institute of Labor Economics (IZA).
- Strobl, Renate & Wunsch, Conny, 2018. "Identification of causal mechanisms based on between-subject double randomization designs," Working papers 2018/19, Faculty of Business and Economics - University of Basel.
- Conny Wunsch & Renate Strobl, 2018. "Identification of Causal Mechanisms Based on Between-Subject Double Randomization Design," CESifo Working Paper Series 7142, CESifo.
- Wunsch, Conny & Strobl, Renate, 2018. "Identification of causal mechanisms based on between-subject double randomization designs," CEPR Discussion Papers 13028, C.E.P.R. Discussion Papers.
- Yu-Chin Hsu & Martin Huber & Yu-Min Yen, 2023. "Doubly Robust Estimation of Direct and Indirect Quantile Treatment Effects with Machine Learning," Papers 2307.01049, arXiv.org.
- Hsu, Yu-Chin & Huber, Martin & Lee, Ying-Ying & Pipoz, Layal, 2018.
"Direct and indirect effects of continuous treatments based on generalized propensity score weighting,"
FSES Working Papers
495, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
- Martin Huber & Yu‐Chin Hsu & Ying‐Ying Lee & Layal Lettry, 2020. "Direct and indirect effects of continuous treatments based on generalized propensity score weighting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(7), pages 814-840, November.
- Yu-Chin Hsu & Hsiou-Wei Lin & Kendro Vincent, 2017.
"Do Cross-Sectional Stock Return Predictors Pass the Test without Data-Snooping Bias?,"
IEAS Working Paper : academic research
17-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.
Cited by:
- Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
- Yu-Chin Hsu, 2016.
"Multiplier Bootstrap for Empirical Processes,"
IEAS Working Paper : academic research
16-A010, Institute of Economics, Academia Sinica, Taipei, Taiwan.
Cited by:
- Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2021.
"Testing identifying assumptions in fuzzy regression discontinuity designs,"
CeMMAP working papers
CWP16/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2019. "Testing identifying assumptions in fuzzy regression discontinuity designs," CeMMAP working papers CWP10/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifie & Yuanyuan Wan, 2018. "Testing Identifying Assumptions In Fuzzy Regression Discontinuity Designs," Working Papers tecipa-623, University of Toronto, Department of Economics.
- Yoichi Arai & Yu‐Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2022. "Testing identifying assumptions in fuzzy regression discontinuity designs," Quantitative Economics, Econometric Society, vol. 13(1), pages 1-28, January.
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2018. "Testing identifying assumptions in fuzzy regression discontinuity designs," CeMMAP working papers CWP50/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Hsu, Yu-Chin & Shen, Shu, 2019. "Testing treatment effect heterogeneity in regression discontinuity designs," Journal of Econometrics, Elsevier, vol. 208(2), pages 468-486.
- Yu-Chin Hsu & Chu-An Liu & Xiaoxia Shi, 2016.
"Testing Generalized Regression Monotonicity,"
IEAS Working Paper : academic research
16-A009, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Hsu, Yu-Chin & Liu, Chu-An & Shi, Xiaoxia, 2019. "Testing Generalized Regression Monotonicity," Econometric Theory, Cambridge University Press, vol. 35(6), pages 1146-1200, December.
Cited by:
- Yu-Chin Hsu & Martin Huber & Ying-Ying Lee & Chu-An Liu, 2021. "Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment with High-Dimensional Data," Papers 2106.04237, arXiv.org, revised Aug 2022.
- Kedagni, Desire & Li, Lixiong & Mourifie, Ismael, 2021.
"Discordant Relaxations of Misspecified Models,"
ISU General Staff Papers
202107280700001131, Iowa State University, Department of Economics.
- Lixiong Li & D'esir'e K'edagni & Ismael Mourifi'e, 2020. "Discordant Relaxations of Misspecified Models," Papers 2012.11679, arXiv.org, revised Dec 2022.
- Ismael Mourifie & Marc Henry & Romuald Meango, 2017.
"Sharp bounds and testability of a Roy model of STEM major choices,"
Papers
1709.09284, arXiv.org, revised Nov 2019.
- Ismaël Mourifié & Marc Henry & Romuald Méango, 2020. "Sharp Bounds and Testability of a Roy Model of STEM Major Choices," Journal of Political Economy, University of Chicago Press, vol. 128(8), pages 3220-3283.
- Ismael Mourifié & Marc Henry & Romuald Méango, 2018. "Sharp Bounds and Testability of a Roy Model of STEM Major Choices," Working Papers 2018-084, Human Capital and Economic Opportunity Working Group.
- Ismael Mourifie & Marc Henry & Romuald Meango, 2018. "Sharp Bounds And Testability Of A Roy Model Of Stem Major Choices," Working Papers tecipa-624, University of Toronto, Department of Economics.
- Zheng Fang & Juwon Seo, 2019. "A Projection Framework for Testing Shape Restrictions That Form Convex Cones," Papers 1910.07689, arXiv.org, revised Sep 2021.
- Matthew A. Masten & Alexandre Poirier, 2018. "Interpreting Quantile Independence," Papers 1804.10957, arXiv.org.
- Yoici Arai & Taisuke Otsu & Mengshan Xu, 2022.
"GLS under monotone heteroskedasticity,"
STICERD - Econometrics Paper Series
625, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Yoichi Arai & Taisuke Otsu & Mengshan Xu, 2022. "GLS under Monotone Heteroskedasticity," Papers 2210.13843, arXiv.org, revised Jan 2024.
- Chetverikov, Denis & Wilhelm, Daniel & Kim, Dongwoo, 2021.
"An Adaptive Test Of Stochastic Monotonicity,"
Econometric Theory, Cambridge University Press, vol. 37(3), pages 495-536, June.
- Denis Chetverikov & Daniel Wilhelm & Dongwoo Kim, 2020. "An Adaptive Test of Stochastic Monotonicity," CeMMAP working papers CWP17/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Denis Chetverikov & Daniel Wilhelm & Dongwoo Kim, 2018. "An adaptive test of stochastic monotonicity," CeMMAP working papers CWP24/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Denis Chetverikov & Daniel Wilhelm & Dongwoo Kim, 2019. "An adaptive test of stochastic monotonicity," CeMMAP working papers CWP49/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Yu‐Chin Hsu & Shu Shen, 2021. "Testing monotonicity of conditional treatment effects under regression discontinuity designs," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 346-366, April.
- Yu-Chin Hsu & Shu Shen, 2016.
"Testing for Treatment Effect Heterogeneity in Regression Discontinuity Design,"
IEAS Working Paper : academic research
16-A005, Institute of Economics, Academia Sinica, Taipei, Taiwan.
Cited by:
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2021.
"Testing identifying assumptions in fuzzy regression discontinuity designs,"
CeMMAP working papers
CWP16/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2019. "Testing identifying assumptions in fuzzy regression discontinuity designs," CeMMAP working papers CWP10/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifie & Yuanyuan Wan, 2018. "Testing Identifying Assumptions In Fuzzy Regression Discontinuity Designs," Working Papers tecipa-623, University of Toronto, Department of Economics.
- Yoichi Arai & Yu‐Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2022. "Testing identifying assumptions in fuzzy regression discontinuity designs," Quantitative Economics, Econometric Society, vol. 13(1), pages 1-28, January.
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2018. "Testing identifying assumptions in fuzzy regression discontinuity designs," CeMMAP working papers CWP50/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Köppl-Turyna, Monika & Kantorowicz, Jarosław, 2017.
"Disentangling fiscal effects of local constitutions,"
VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking
168163, Verein für Socialpolitik / German Economic Association.
- Kantorowicz, Jarosław & Köppl–Turyna, Monika, 2019. "Disentangling the fiscal effects of local constitutions," Journal of Economic Behavior & Organization, Elsevier, vol. 163(C), pages 63-87.
- Kantorowicz, Jarosław & Köppl-Turyna, Monika, 2017. "Disentangling fiscal effects of local constitutions," Working Papers 06, Agenda Austria.
- Yu-Chin Hsu & Chung-Ming Kuan & Giorgio Teng-Yu Lo, 2017. "Quantile Treatment Effects in Regression Discontinuity Designs with Covariates," IEAS Working Paper : academic research 17-A009, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Maria Paula Gerardino & Stephan Litschig & Dina Pomeranz, 2017.
"Distortion by Audit: Evidence from Public Procurement,"
NBER Working Papers
23978, National Bureau of Economic Research, Inc.
- Pomeranz, Dina & Gerardino, Maria Paula & Litschig, Stephan, 2017. "Distortion by Audit: Evidence from Public Procurement," CEPR Discussion Papers 12529, C.E.P.R. Discussion Papers.
- Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2021.
"Testing identifying assumptions in fuzzy regression discontinuity designs,"
CeMMAP working papers
CWP16/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Yu-Chin Hsu & Robert P. Lieli & Tsung-Chih Lai, 2015.
"Estimation and Inference for Distribution Functions and Quantile Functions in Endogenous Treatment Effect Models,"
IEAS Working Paper : academic research
15-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.
Cited by:
- Huber Martin & Wüthrich Kaspar, 2019.
"Local Average and Quantile Treatment Effects Under Endogeneity: A Review,"
Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
- Huber, Martin & Wüthrich, Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," University of California at San Diego, Economics Working Paper Series qt4j29d8sc, Department of Economics, UC San Diego.
- 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 23/17, 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 CWP23/17, Centre for Microdata Methods and Practice, 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 W thrich, 2016. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," Diskussionsschriften dp1607, Universitaet Bern, Departement Volkswirtschaft.
- 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.
- 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 & 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.
- Wüthrich, Kaspar, 2019.
"A closed-form estimator for quantile treatment effects with endogeneity,"
Journal of Econometrics, Elsevier, vol. 210(2), pages 219-235.
- Wüthrich, Kaspar, 2019. "A closed-form estimator for quantile treatment effects with endogeneity," University of California at San Diego, Economics Working Paper Series qt99n9197q, Department of Economics, UC San Diego.
- Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
- Blaise Melly und Kaspar W thrich, 2016. "Local quantile treatment effects," Diskussionsschriften dp1605, Universitaet Bern, Departement Volkswirtschaft.
- Huber Martin & Wüthrich Kaspar, 2019.
"Local Average and Quantile Treatment Effects Under Endogeneity: A Review,"
Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
- Yu-Chin Hsu & Kamhon Kan & Tsung-Chih Lai, 2015.
"Distribution and Quantile Structural Functions in Treatment Effect Models: Application to Smoking Effects on Wages,"
IEAS Working Paper : academic research
15-A001, Institute of Economics, Academia Sinica, Taipei, Taiwan, revised Apr 2016.
Cited by:
- Maasoumi, Esfandiar & Wang, Le, 2017. "What can we learn about the racial gap in the presence of sample selection?," Journal of Econometrics, Elsevier, vol. 199(2), pages 117-130.
- Garry F. Barrett & Stephen G. Donald & Yu-Chin Hsu, 2015.
"Consistent Tests for Poverty Dominance Relations,"
IEAS Working Paper : academic research
15-A002, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Barrett, Garry F. & Donald, Stephen G. & Hsu, Yu-Chin, 2016. "Consistent tests for poverty dominance relations," Journal of Econometrics, Elsevier, vol. 191(2), pages 360-373.
Cited by:
- Tahsin Mehdi, 2020. "Testing for Stochastic Dominance up to a Common Relative Poverty Line," Econometrics, MDPI, vol. 8(1), pages 1-9, February.
- Greg Kaplan & Gianni La Cava & Tahlee Stone, 2018.
"Household Economic Inequality in Australia,"
The Economic Record, The Economic Society of Australia, vol. 94(305), pages 117-134, June.
- Rosetta Dollman & Greg Kaplan & Gianni La Cava & Tahlee Stone, 2015. "Household Economic Inequality in Australia," RBA Research Discussion Papers rdp2015-15, Reserve Bank of Australia.
- Edwin Fourrier-Nicolai & Michel Lubrano, 2017.
"Bayesian Inference for TIP curves: An Application to Child Poverty in Germany,"
AMSE Working Papers
1710, Aix-Marseille School of Economics, France.
- Edwin Fourrier-Nicolai & Michel Lubrano, 2020. "Bayesian inference for TIP curves: an application to child poverty in Germany," Post-Print hal-02477216, HAL.
- Edwin Fourrier-Nicolaï & Michel Lubrano, 2020. "Bayesian inference for TIP curves: an application to child poverty in Germany," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(1), pages 91-111, March.
- Edwin Fourrier-Nicolai & Michel Lubrano, 2017. "Bayesian Inference for TIP curves: An Application to Child Poverty in Germany," Working Papers halshs-01494354, HAL.
- Naouel Chtioui & Mohamed Ayadi, 2018. "Rank-based poverty measures and poverty ordering with an application to Tunisia," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 17(2), pages 117-139, July.
- David Lander & David Gunawan & William Griffiths & Duangkamon Chotikapanich, 2020.
"Bayesian assessment of Lorenz and stochastic dominance,"
Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(2), pages 767-799, May.
- David Lander & David Gunawan & William Griffiths & Duangkamon Chotikapanich, 2017. "Bayesian Assessment of Lorenz and Stochastic Dominance," Department of Economics - Working Papers Series 2029, The University of Melbourne.
- David Lander & David Gunawan & William Griffiths & Duangkamon Chotikapanich, 2017. "Bayesian assessment of Lorenz and stochastic dominance," Monash Econometrics and Business Statistics Working Papers 15/17, Monash University, Department of Econometrics and Business Statistics.
- Mariateresa Ciommi & Chiara Gigliarano & Francesco M. Chelli, 2021. "Incidence, intensity and inequality of poverty in Italy," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 75(4), pages 31-41, October-D.
- David Lander & David Gunawan & William E. Griffiths & Duangkamon Chotikapanich, 2016. "Bayesian Assessment of Lorenz and Stochastic Dominance Using a Mixture of Gamma Densities," Department of Economics - Working Papers Series 2023, The University of Melbourne.
- Stephen G. Donald & Yu-Chin Hsu & Robert P. Lieli, 2014.
"Inverse Probability Weighted Estimation of Local Average Treatment Effects: A Higher Order MSE Expansion,"
IEAS Working Paper : academic research
14-A002, Institute of Economics, Academia Sinica, Taipei, Taiwan, revised Aug 2014.
- Donald, Stephen G. & Hsu, Yu-Chin & Lieli, Robert P., 2014. "Inverse probability weighted estimation of local average treatment effects: A higher order MSE expansion," Statistics & Probability Letters, Elsevier, vol. 95(C), pages 132-138.
Cited by:
- Huber Martin & Wüthrich Kaspar, 2019.
"Local Average and Quantile Treatment Effects Under Endogeneity: A Review,"
Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
- Huber, Martin & Wüthrich, Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," University of California at San Diego, Economics Working Paper Series qt4j29d8sc, Department of Economics, UC San Diego.
- Sloczynski, Tymon & Uysal, Derya & Wooldridge, Jeffrey M., 2022.
"Abadie's Kappa and Weighting Estimators of the Local Average Treatment Effect,"
IZA Discussion Papers
15241, Institute of Labor Economics (IZA).
- Tymon Sloczynski & Derya Uysal & Jeffrey Wooldridge, 2023. "Abadie's Kappa and Weighting Estimators of the Local Average Treatment Effect," Rationality and Competition Discussion Paper Series 424, CRC TRR 190 Rationality and Competition.
- Tymon Sloczynski & S. Derya Uysal & Jeffrey M. Wooldridge & Derya Uysal, 2022. "Abadie's Kappa and Weighting Estimators of the Local Average Treatment Effect," CESifo Working Paper Series 9715, CESifo.
- Huber, Martin, 2019.
"An introduction to flexible methods for policy evaluation,"
FSES Working Papers
504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
- Martin Huber, 2019. "An introduction to flexible methods for policy evaluation," Papers 1910.00641, arXiv.org.
- Jason Abrevaya & Yu-Chin Hsu & Robert P. Lieli, 2012.
"Estimating Conditional Average Treatment Effects,"
CEU Working Papers
2012_16, Department of Economics, Central European University, revised 20 Jul 2012.
- Jason Abrevaya & Yu-Chin Hsu & Robert P. Lieli, 2015. "Estimating Conditional Average Treatment Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 485-505, October.
- Hsu Yu-Chin & Huber Martin & Lai Tsung-Chih, 2019.
"Nonparametric estimation of natural direct and indirect effects based on inverse probability weighting,"
Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-20, January.
- Hsu, Yu-Chin & Huber, Martin & Lai, Tsung Chih, 2017. "Nonparametric estimation of natural direct and indirect effects based on inverse probability weighting," FSES Working Papers 482, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
- Tymon S{l}oczy'nski & S. Derya Uysal & Jeffrey M. Wooldridge, 2022. "Abadie's Kappa and Weighting Estimators of the Local Average Treatment Effect," Papers 2204.07672, arXiv.org, revised Feb 2024.
- Tesfaye, Wondimagegn & Tirivayi, Nyasha, 2016. "The effect of improved storage innovations on food security and welfare in Ethiopia," MERIT Working Papers 2016-063, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
- Tesfaye, Wondimagegn & Tirivayi, Nyasha, 2018. "The impacts of postharvest storage innovations on food security and welfare in Ethiopia," Food Policy, Elsevier, vol. 75(C), pages 52-67.
- Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
- Phillip Heiler, 2020. "Efficient Covariate Balancing for the Local Average Treatment Effect," Papers 2007.04346, arXiv.org.
- Yi-Ting Chen & Yu-Chin Hsu & Hung-Jen Wang, 2014.
"A Stochastic Frontier Model with an Effect Stochastic Frontier Models with Endogenous Selection,"
IEAS Working Paper : academic research
14-A006, Institute of Economics, Academia Sinica, Taipei, Taiwan, revised Sep 2015.
Cited by:
- Mattsson, Pontus, 2019. "The impact of labour subsidies on total factor productivity and profit per employee," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 325-341.
- Tsung-Hsun Lu & Yi-Chi Chen & Yu-Chin Hsu, 2014.
"Trend Definition or Holding Strategy: What Determines the Profitability of Candlestick Technical Trading Strategies?,"
IEAS Working Paper : academic research
14-A010, Institute of Economics, Academia Sinica, Taipei, Taiwan, revised Jul 2015.
Cited by:
- Kevin Rink, 2023. "The predictive ability of technical trading rules: an empirical analysis of developed and emerging equity markets," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 403-456, December.
- Shangkun Deng & Zhihao Su & Yanmei Ren & Haoran Yu & Yingke Zhu & Chenyang Wei, 2022. "Can Japanese Candlestick Patterns be Profitable on the Component Stocks of the SSE50 Index?," SAGE Open, , vol. 12(3), pages 21582440221, August.
- Wei-Ming Lee & Yu-Chin Hsu & Chung-Ming Kuan, 2014.
"Robust Hypothesis Tests for M-Estimators with Possibly Non-differentiable Estimating Functions,"
IEAS Working Paper : academic research
14-A004, Institute of Economics, Academia Sinica, Taipei, Taiwan, revised Oct 2014.
- Wei‐Ming Lee & Yu‐Chin Hsu & Chung‐Ming Kuan, 2015. "Robust hypothesis tests for M‐estimators with possibly non‐differentiable estimating functions," Econometrics Journal, Royal Economic Society, vol. 18(1), pages 95-116, February.
Cited by:
- Wei-Ming Lee & Chung-Ming Kuan & Yu-Chin Hsu, 2014.
"Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix,"
IEAS Working Paper : academic research
14-A001, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Lee, Wei-Ming & Kuan, Chung-Ming & Hsu, Yu-Chin, 2014. "Testing over-identifying restrictions without consistent estimation of the asymptotic covariance matrix," Journal of Econometrics, Elsevier, vol. 181(2), pages 181-193.
- Wei-Ming Lee & Chung-Ming Kuan, 2006. "Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix," IEAS Working Paper : academic research 06-A009, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Wei-Ming Lee & Chung-Ming Kuan & Yu-Chin Hsu, 2014.
"Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix,"
IEAS Working Paper : academic research
14-A001, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Lee, Wei-Ming & Kuan, Chung-Ming & Hsu, Yu-Chin, 2014. "Testing over-identifying restrictions without consistent estimation of the asymptotic covariance matrix," Journal of Econometrics, Elsevier, vol. 181(2), pages 181-193.
- Wei-Ming Lee & Chung-Ming Kuan, 2006. "Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix," IEAS Working Paper : academic research 06-A009, Institute of Economics, Academia Sinica, Taipei, Taiwan.
Cited by:
- Wei-Ming Lee & Chung-Ming Kuan & Yu-Chin Hsu, 2014.
"Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix,"
IEAS Working Paper : academic research
14-A001, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Lee, Wei-Ming & Kuan, Chung-Ming & Hsu, Yu-Chin, 2014. "Testing over-identifying restrictions without consistent estimation of the asymptotic covariance matrix," Journal of Econometrics, Elsevier, vol. 181(2), pages 181-193.
- Wei-Ming Lee & Chung-Ming Kuan, 2006. "Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix," IEAS Working Paper : academic research 06-A009, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Yu-Chin Hsu & Xiaoxia Shi, 2013.
"Model Selection Tests for Conditional Moment Inequality Models,"
IEAS Working Paper : academic research
13-A004, Institute of Economics, Academia Sinica, Taipei, Taiwan.
Cited by:
- Susanne M. Schennach & Daniel Wilhelm, 2016.
"A simple parametric model selection test,"
CeMMAP working papers
CWP30/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Susanne M. Schennach & Daniel Wilhelm, 2016. "A simple parametric model selection test," CeMMAP working papers 30/16, Institute for Fiscal Studies.
- Susanne M. Schennach & Daniel Wilhelm, 2014. "A simple parametric model selection test," CeMMAP working papers 10/14, Institute for Fiscal Studies.
- Susanne M. Schennach & Daniel Wilhelm, 2017. "A Simple Parametric Model Selection Test," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1663-1674, October.
- Susanne M. Schennach & Daniel Wilhelm, 2014. "A simple parametric model selection test," CeMMAP working papers CWP10/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Shi, Xiaoxia, 2015. "Model selection tests for moment inequality models," Journal of Econometrics, Elsevier, vol. 187(1), pages 1-17.
- Susanne M. Schennach & Daniel Wilhelm, 2016.
"A simple parametric model selection test,"
CeMMAP working papers
CWP30/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Yu-Chin Hsu & Chung-Ming Kuan & Meng-Feng Yen, 2013.
"A Generalized Stepwise Procedure with Improved Power for Multiple Inequalities Testing,"
IEAS Working Paper : academic research
13-A001, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Yu-Chin Hsu & Chung-Ming Kuan & Meng-Feng Yen, 2014. "A Generalized Stepwise Procedure with Improved Power for Multiple Inequalities Testing," Journal of Financial Econometrics, Oxford University Press, vol. 12(4), pages 730-755.
Cited by:
- Hubert Dichtl, 2020. "Investing in the S&P 500 index: Can anything beat the buy‐and‐hold strategy?," Review of Financial Economics, John Wiley & Sons, vol. 38(2), pages 352-378, April.
- Yu-Chin Hsu & Hsiou-Wei Lin & Kendro Vincent, 2017. "Do Cross-Sectional Stock Return Predictors Pass the Test without Data-Snooping Bias?," IEAS Working Paper : academic research 17-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Baur, Dirk G. & Dichtl, Hubert & Drobetz, Wolfgang & Wendt, Viktoria-Sophie, 2020. "Investing in gold – Market timing or buy-and-hold?," International Review of Financial Analysis, Elsevier, vol. 71(C).
- Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
- Hubert Dichtl & Wolfgang Drobetz & Viktoria‐Sophie Wendt, 2021. "How to build a factor portfolio: Does the allocation strategy matter?," European Financial Management, European Financial Management Association, vol. 27(1), pages 20-58, January.
- Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos, 2021. "Trading the foreign exchange market with technical analysis and Bayesian Statistics," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 230-251.
- Chiang, Mi-Hsiu & Chiu, Hsin-Yu & Kuo, Wei-Yu, 2021. "Predictive ability of similarity-based futures trading strategies," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
- Minyou Fan & Youwei Li & Ming Liao & Jiadong Liu, 2022. "A reexamination of factor momentum: How strong is it?," The Financial Review, Eastern Finance Association, vol. 57(3), pages 585-615, August.
- Hsu, Po-Hsuan & Han, Qiheng & Wu, Wensheng & Cao, Zhiguang, 2018. "Asset allocation strategies, data snooping, and the 1 / N rule," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 257-269.
- Vincent, Kendro & Hsu, Yu-Chin & Lin, Hsiou-Wei, 2021. "Investment styles and the multiple testing of cross-sectional stock return predictability," Journal of Financial Markets, Elsevier, vol. 56(C).
- Yang, Junmin & Cao, Zhiguang & Han, Qiheng & Wang, Qiyu, 2019. "Tactical asset allocation on technical trading rules and data snooping," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
- Yu-Chin Hsu, 2013.
"Consistent Tests for Conditional Treatment Effects,"
IEAS Working Paper : academic research
13-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan, revised Sep 2015.
- Yu‐Chin Hsu, 2017. "Consistent tests for conditional treatment effects," Econometrics Journal, Royal Economic Society, vol. 20(1), pages 1-22, February.
Cited by:
- Yu-Chin Hsu & Martin Huber & Ying-Ying Lee & Chu-An Liu, 2021. "Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment with High-Dimensional Data," Papers 2106.04237, arXiv.org, revised Aug 2022.
- Pedro H. C. Sant’Anna, 2021.
"Nonparametric Tests for Treatment Effect Heterogeneity With Duration Outcomes,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 816-832, July.
- Pedro H. C. Sant'Anna, 2016. "Nonparametric Tests for Treatment Effect Heterogeneity with Duration Outcomes," Papers 1612.02090, arXiv.org, revised Feb 2020.
- Masahiro Kato, 2024. "Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects," Papers 2403.03240, arXiv.org.
- Hsu Yu-Chin & Huber Martin & Lai Tsung-Chih, 2019.
"Nonparametric estimation of natural direct and indirect effects based on inverse probability weighting,"
Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-20, January.
- Hsu, Yu-Chin & Huber, Martin & Lai, Tsung Chih, 2017. "Nonparametric estimation of natural direct and indirect effects based on inverse probability weighting," FSES Working Papers 482, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
- Hsu, Yu-Chin & Shen, Shu, 2019. "Testing treatment effect heterogeneity in regression discontinuity designs," Journal of Econometrics, Elsevier, vol. 208(2), pages 468-486.
- Shi, Chengchun & Luo, Shikai & Zhu, Hongtu & Song, Rui, 2021. "An online sequential test for qualitative treatment effects," LSE Research Online Documents on Economics 112521, London School of Economics and Political Science, LSE Library.
- Sungwon Lee, 2021. "Partial Identification and Inference for Conditional Distributions of Treatment Effects," Papers 2108.00723, arXiv.org, revised Nov 2023.
- Yu‐Chin Hsu & Shu Shen, 2021. "Testing monotonicity of conditional treatment effects under regression discontinuity designs," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(3), pages 346-366, April.
- Shi, Chengchun & Lu, Wenbin & Song, Rui, 2019. "A sparse random projection-based test for overall qualitative treatment effects," LSE Research Online Documents on Economics 102107, London School of Economics and Political Science, LSE Library.
- Sungwon Lee, 2024. "Partial identification and inference for conditional distributions of treatment effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 107-127, January.
- Stephen G. Donald & Yu-Chin Hsu, 2012.
"Estimation and Inference for Distribution Functions and Quantile Functions in Treatment Effect Models,"
IEAS Working Paper : academic research
12-A016, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Donald, Stephen G. & Hsu, Yu-Chin, 2014. "Estimation and inference for distribution functions and quantile functions in treatment effect models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 383-397.
Cited by:
- Zongwu Cai & Ying Fang & Ming Lin & Shengfang Tang, 2021. "Estimating Partially Conditional Quantile Treatment Effects," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202103, University of Kansas, Department of Economics, revised Jan 2021.
- Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
- Cécile Couharde & Rémi Generoso, 2024. "Assessing the Impact of National Air Quality Standards on Agricultural Land Values: Insights from Corn and Soybean Regions," EconomiX Working Papers 2024-9, University of Paris Nanterre, EconomiX.
- 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.
- 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).
- Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2019.
"A Unified Framework for Efficient Estimation of General Treatment Models,"
CeMMAP working papers
CWP64/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Ai, C. & Linton, O. & Motegi, K. & Zhang, Z., 2019. "A Unified Framework for Efficient Estimation of General Treatment Models," Cambridge Working Papers in Economics 1934, Faculty of Economics, University of Cambridge.
- Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2018. "A Unified Framework for Efficient Estimation of General Treatment Models," Papers 1808.04936, arXiv.org, revised Aug 2018.
- Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2021. "A unified framework for efficient estimation of general treatment models," Quantitative Economics, Econometric Society, vol. 12(3), pages 779-816, July.
- Hamori, Shigeyuki & Motegi, Kaiji & Zhang, Zheng, 2019. "Calibration estimation of semiparametric copula models with data missing at random," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 85-109.
- 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 23/17, 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 CWP23/17, Centre for Microdata Methods and Practice, 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 W thrich, 2016. "Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes," Diskussionsschriften dp1607, Universitaet Bern, Departement Volkswirtschaft.
- 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.
- 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 & 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.
- Yu-Chin Hsu & Martin Huber & Yu-Min Yen, 2023. "Doubly Robust Estimation of Direct and Indirect Quantile Treatment Effects with Machine Learning," Papers 2307.01049, arXiv.org.
- Pedro H. C. Sant’Anna, 2021.
"Nonparametric Tests for Treatment Effect Heterogeneity With Duration Outcomes,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 816-832, July.
- Pedro H. C. Sant'Anna, 2016. "Nonparametric Tests for Treatment Effect Heterogeneity with Duration Outcomes," Papers 1612.02090, arXiv.org, revised Feb 2020.
- Yu-Chin Hsu & Robert P. Lieli, 2021. "Inference for ROC Curves Based on Estimated Predictive Indices," Papers 2112.01772, arXiv.org.
- Ai, Chunrong & Linton, Oliver & Zhang, Zheng, 2022. "Estimation and inference for the counterfactual distribution and quantile functions in continuous treatment models," Journal of Econometrics, Elsevier, vol. 228(1), pages 39-61.
- Brantly Callaway & Tong Li, 2019.
"Quantile treatment effects in difference in differences models with panel data,"
Quantitative Economics, Econometric Society, vol. 10(4), pages 1579-1618, November.
- Brantly Callaway & Tong Li, 2017. "Quantile Treatment Effects in Difference in Differences Models with Panel Data," DETU Working Papers 1701, Department of Economics, Temple University.
- Ying-Ying Lee, 2015. "Efficient propensity score regression estimators of multi-valued treatment effects for the treated," Economics Series Working Papers 738, University of Oxford, Department of Economics.
- Zequn Jin & Lihua Lin & Zhengyu Zhang, 2022. "Identification and Auto-debiased Machine Learning for Outcome Conditioned Average Structural Derivatives," Papers 2211.07903, arXiv.org.
- Huber, Martin, 2019.
"An introduction to flexible methods for policy evaluation,"
FSES Working Papers
504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
- Martin Huber, 2019. "An introduction to flexible methods for policy evaluation," Papers 1910.00641, arXiv.org.
- Pedro H. C. Sant'Anna & Xiaojun Song, 2016.
"Specification Tests for the Propensity Score,"
Papers
1611.06217, arXiv.org, revised Feb 2019.
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Journal of Econometrics, Elsevier, vol. 178(P3), pages 383-397.
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- Stéphane Girard & Gilles Stupfler & Antoine Usseglio‐Carleve, 2022. "Nonparametric extreme conditional expectile estimation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(1), pages 78-115, March.
- Yen, Yu-Min & Yen, Tso-Jung, 2021. "Testing forecast accuracy of expectiles and quantiles with the extremal consistent loss functions," International Journal of Forecasting, Elsevier, vol. 37(2), pages 733-758.
- Song, Song & Ritov, Ya’acov & Härdle, Wolfgang K., 2012. "Bootstrap confidence bands and partial linear quantile regression," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 244-262.
- Antonio Rubia Serrano & Lidia Sanchis-Marco, 2015. "Measuring Tail-Risk Cross-Country Exposures in the Banking Industry," Working Papers. Serie AD 2015-01, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
- Ren, Rui & Lu, Meng-Jou & Li, Yingxing & Härdle, Wolfgang, 2021. "Financial Risk Meter based on expectiles," IRTG 1792 Discussion Papers 2021-008, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
- Marcel, Bräutigam & Marie, Kratz, 2018. "On the Dependence between Quantiles and Dispersion Estimators," ESSEC Working Papers WP1807, ESSEC Research Center, ESSEC Business School.
- Daouia, Abdelaati & Girard, Stéphane & Stupfler, Gilles, 2018. "Tail expectile process and risk assessment," TSE Working Papers 18-944, Toulouse School of Economics (TSE).
- Daouia, Abdelaati & Paindaveine, Davy, 2019. "Multivariate Expectiles, Expectile Depth and Multiple-Output Expectile Regression," TSE Working Papers 19-1022, Toulouse School of Economics (TSE), revised Feb 2023.
- Shih-Kang Chao & Wolfgang Karl Härdle & Weining Wang, 2012. "Quantile Regression in Risk Calibration," SFB 649 Discussion Papers SFB649DP2012-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Gilles Stupfler & Fan Yang, 2018.
"Analyzing and Predicting CAT Bond Premiums: a Financial Loss Premium Principle and Extreme Value Modeling,"
Post-Print
hal-04464416, HAL.
- Hsu, Yu-Chin & Kuan, Chung-Ming, 2008.
"Change-point estimation of nonstationary I(d) processes,"
Economics Letters, Elsevier, vol. 98(2), pages 115-121, February.
See citations under working paper version above.
- Yu-Chin Hsu & Chung-Ming Kuan, 2006. "Change-Point Estimation of Nonstationary I(d) Processes," IEAS Working Paper : academic research 06-A007, Institute of Economics, Academia Sinica, Taipei, Taiwan.
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