IDEAS home Printed from https://ideas.repec.org/f/pch780.html
   My authors  Follow this author

Le-Yu Chen

Personal Details

First Name:Le-Yu
Middle Name:
Last Name:Chen
Suffix:
RePEc Short-ID:pch780
[This author has chosen not to make the email address public]
http://www.econ.sinica.edu.tw/LeYu_Chen/index_en1.php?lang=en
Institute of Economics, Academia Sinica 128 Academia Road, Section 2, Nankang, Taipei, 115 Taiwan
Terminal Degree:2009 Department of Economics; University College London (UCL) (from RePEc Genealogy)

Affiliation

Institute of Economics
Academia Sinica

Taipei, Taiwan
http://www.econ.sinica.edu.tw/
RePEc:edi:sinictw (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Le-Yu Chen & Yu-Min Yen, 2021. "Estimations of the Conditional Tail Average Treatment Effect," Papers 2109.08793, arXiv.org, revised Sep 2021.
  2. Le-Yu Chen & Sokbae Lee, 2020. "Sparse Quantile Regression," Papers 2006.11201, arXiv.org, revised Mar 2023.
  3. Chen, Le-Yu & Oparina, Ekaterina & Powdthavee, Nattavudh & Srisuma, Sorawoot, 2019. "Have Econometric Analyses of Happiness Data Been Futile? A Simple Truth about Happiness Scales," IZA Discussion Papers 12152, Institute of Labor Economics (IZA).
  4. Le-Yu Chen & Ekaterina Oparina & Nattavudh Powdthavee & Sorawoot Srisuma, 2019. "Robust Ranking of Happiness Outcomes: A Median Regression Perspective," Papers 1902.07696, arXiv.org, revised Jun 2022.
  5. Le-Yu Chen & Sokbae Lee, 2018. "High Dimensional Classification through $\ell_0$-Penalized Empirical Risk Minimization," Papers 1811.09540, arXiv.org.
  6. Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Breaking the curse of dimensionality in conditional moment inequalities for discrete choice models," CeMMAP working papers 51/17, Institute for Fiscal Studies.
  7. Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Exact computation of GMM estimators for instrumental variable quantile regression models," CeMMAP working papers 52/17, Institute for Fiscal Studies.
  8. Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Exact computation of GMM estimators for instrumental variable quantile regression models," CeMMAP working papers CWP52/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  9. Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers 50/17, Institute for Fiscal Studies.
  10. Le-Yu Chen & Sokbae Lee, 2016. "Best Subset Binary Prediction," Papers 1610.02738, arXiv.org, revised May 2018.
  11. Le-Yu Chen & Sokbae (Simon) Lee, 2015. "Breaking the curse of dimensionality in conditional moment inequalities for discrete choice models," CeMMAP working papers CWP26/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  12. Le-Yu Chen & Sokbae (Simon) Lee, 2015. "Breaking the curse of dimensionality in conditional moment inequalities for discrete choice models," CeMMAP working papers 26/15, Institute for Fiscal Studies.
  13. Le-Yu Chen & Sokbae (Simon) Lee & Myung Jae Sung, 2014. "Maximum score estimation with nonparametrically generated regressors," CeMMAP working papers CWP27/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  14. Le-Yu Chen & Sokbae (Simon) Lee & Myung Jae Sung, 2014. "Maximum score estimation with nonparametrically generated regressors," CeMMAP working papers 27/14, Institute for Fiscal Studies.
  15. Le-Yu Chen & Sokbae (Simon) Lee & Myung Jae Sung, 2013. "Maximum score estimation of preference parameters for a binary choice model under uncertainty," CeMMAP working papers CWP14/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  16. Le-Yu Chen & Sokbae (Simon) Lee & Myung Jae Sung, 2013. "Maximum score estimation of preference parameters for a binary choice model under uncertainty," CeMMAP working papers 14/13, Institute for Fiscal Studies.
  17. Le-Yu Chen & Jerzy Szroeter, 2012. "Testing multiple inequality hypotheses: a smoothed indicator approach," CeMMAP working papers 16/12, Institute for Fiscal Studies.
  18. Le-Yu Chen & Jerzy Szroeter, 2012. "Testing multiple inequality hypotheses: a smoothed indicator approach," CeMMAP working papers CWP16/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  19. Le-Yu Chen & Jerzy Szroeter, 2009. "Hypothesis testing of multiple inequalities: the method of constraint chaining," CeMMAP working papers CWP13/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  20. Le-Yu Chen, 2009. "Identification of structural dynamic discrete choice models," CeMMAP working papers CWP08/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  21. Le-Yu Chen & Jerzy Szroeter, 2009. "Hypothesis testing of multiple inequalities: the method of constraint chaining," CeMMAP working papers 13/09, Institute for Fiscal Studies.
  22. Le-Yu Chen, 2007. "Semiparametric identification of structural dynamic optimal stopping time models," CeMMAP working papers CWP06/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

Articles

  1. Chen, Le-Yu & Lee, Sokbae, 2023. "Sparse quantile regression," Journal of Econometrics, Elsevier, vol. 235(2), pages 2195-2217.
  2. Chen, Le-Yu & Oparina, Ekaterina & Powdthavee, Nattavudh & Srisuma, Sorawoot, 2022. "Robust Ranking of Happiness Outcomes: A Median Regression Perspective," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 672-686.
  3. Le-Yu Chen & Sokbae Lee, 2021. "Binary classification with covariate selection through ℓ0-penalised empirical risk minimisation," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 103-120.
  4. Chen, Le-Yu & Lee, Sokbae, 2019. "Breaking the curse of dimensionality in conditional moment inequalities for discrete choice models," Journal of Econometrics, Elsevier, vol. 210(2), pages 482-497.
  5. Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
  6. Le‐Yu Chen & Sokbae Lee, 2018. "Exact computation of GMM estimators for instrumental variable quantile regression models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 553-567, June.
  7. Chen, Le-Yu, 2017. "Identification Of Discrete Choice Dynamic Programming Models With Nonparametric Distribution Of Unobservables," Econometric Theory, Cambridge University Press, vol. 33(3), pages 551-577, June.
  8. Chen, Le-Yu & Szroeter, Jerzy, 2014. "Testing multiple inequality hypotheses: A smoothed indicator approach," Journal of Econometrics, Elsevier, vol. 178(P3), pages 678-693.
  9. Le‐Yu Chen & Sokbae Lee & Myung Jae Sung, 2014. "Maximum score estimation with nonparametrically generated regressors," Econometrics Journal, Royal Economic Society, vol. 17(3), pages 271-300, October.

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

  1. Le-Yu Chen & Sokbae Lee, 2020. "Sparse Quantile Regression," Papers 2006.11201, arXiv.org, revised Mar 2023.

    Cited by:

    1. HONDA, Toshio & 本田, 敏雄, 2023. "Sparse quantile regression via ℓ0-penalty," Discussion Papers 2023-03, Graduate School of Economics, Hitotsubashi University.

  2. Chen, Le-Yu & Oparina, Ekaterina & Powdthavee, Nattavudh & Srisuma, Sorawoot, 2019. "Have Econometric Analyses of Happiness Data Been Futile? A Simple Truth about Happiness Scales," IZA Discussion Papers 12152, Institute of Labor Economics (IZA).

    Cited by:

    1. Junxing Chay & Seonghoon Kim, 2022. "Heterogeneous health effects of medical marijuana legalization: Evidence from young adults in the United States," Health Economics, John Wiley & Sons, Ltd., vol. 31(2), pages 269-283, February.
    2. Valérie Bérenger & Jacques Silber, 2022. "On the Measurement of Happiness and of its Inequality," Journal of Happiness Studies, Springer, vol. 23(3), pages 861-902, March.
    3. Loschiavo, David, 2021. "Big-city life (dis)satisfaction? The effect of urban living on subjective well-being," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 740-764.
    4. Seonghoon Kim & Kanghyock Koh, 2022. "Health insurance and subjective well‐being: Evidence from two healthcare reforms in the United States," Health Economics, John Wiley & Sons, Ltd., vol. 31(1), pages 233-249, January.
    5. O'Connor, Kelsey J., 2020. "The effect of immigration on natives’ well-being in the European Union," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 257-274.
    6. Ekaterina Oparina & Sorawoot Srisuma, 2019. "Analyzing Subjective Well-Being Data with Misclassification," Papers 1905.06037, arXiv.org.
    7. Yamamura, Eiji & Brunello, Giorgio, 2021. "The Effect of Grandchildren on the Happiness of Grandparents: Does the Grandparent's Child's Gender Matter?," IZA Discussion Papers 14081, Institute of Labor Economics (IZA).
    8. Cheng, Terence Chai & Kim, Seonghoon & Koh, Kanghyock, 2020. "The Impact of COVID-19 on Subjective Well-Being: Evidence from Singapore," IZA Discussion Papers 13702, Institute of Labor Economics (IZA).
    9. Andrew Chesher & Adam Rosen & Zahra Siddique, 2019. "Estimating Endogenous Effects on Ordinal Outcomes," CeMMAP working papers CWP66/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Bloem, Jeffrey R. & Oswald, Andrew J., 2021. "The Analysis of Human Feelings: A Practical Suggestion for a Robustness Test," IZA Discussion Papers 14632, Institute of Labor Economics (IZA).
    11. Robson Morgan & Kelsey J. O’Connor, 2022. "Labor Market Policy and Subjective Well-Being During the Great Recession," Journal of Happiness Studies, Springer, vol. 23(2), pages 391-422, February.
    12. Nicholas Gunby & Tom Coupé, 2023. "Weather-Related Home Damage and Subjective Well-Being," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 84(2), pages 409-438, February.
    13. Ivanov, Boris & Pfeiffer, Friedhelm & Pohlan, Laura, 2020. "Do job creation schemes improve the social integration and well-being of the long-term unemployed?," Labour Economics, Elsevier, vol. 64(C).
    14. Bucciol, Alessandro & Zarri, Luca, 2020. "Wounds that time can’t heal: Life satisfaction and exposure to traumatic events," Journal of Economic Psychology, Elsevier, vol. 76(C).
    15. Kanninen, Ohto & Böckerman, Petri & Suoniemi, Ilpo, 2022. "Income–well-being gradient in sickness and health," MPRA Paper 113269, University Library of Munich, Germany.
    16. Montgomery, Mallory, 2022. "Reversing the gender gap in happiness," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 65-78.
    17. Alberto Prati, 2024. "The Well‐Being Cost of Inflation Inequalities," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 70(1), pages 213-238, March.
    18. Shuo Liu & Nick Netzer, 2023. "Happy Times: Measuring Happiness Using Response Times," American Economic Review, American Economic Association, vol. 113(12), pages 3289-3322, December.
    19. Kim, Seonghoon & Koh, Kanghyock, 2019. "The Effects of the Affordable Care Act Medicaid Expansion on Subjective Well-being," IZA Discussion Papers 12636, Institute of Labor Economics (IZA).
    20. O'Connor, Kelsey J., 2022. "Measuring Progress," IZA Policy Papers 194, Institute of Labor Economics (IZA).
    21. Nikolova, Milena & Graham, Carol, 2020. "The Economics of Happiness," GLO Discussion Paper Series 640, Global Labor Organization (GLO).
    22. Sechel, Cristina, 2021. "The share of satisfied individuals: A headcount measure of aggregate subjective well-being," Journal of Economic Behavior & Organization, Elsevier, vol. 186(C), pages 373-394.
    23. Caspar Kaiser, 2022. "Whence the Happiness Revolution? A Book Review of Richard Easterlin’s An Economist’s Lessons on Happiness," Journal of Happiness Studies, Springer, vol. 23(6), pages 3095-3098, August.
    24. Frijters, Paul & Krekel, Christian & Ulker, Aydogan, 2023. "Should bads be inflicted all at once, like Machiavelli said? Evidence from life-satisfaction data," Journal of Economic Behavior & Organization, Elsevier, vol. 205(C), pages 1-27.
    25. Bucciol, Alessandro & Burro, Giovanni, 2022. "Is there a happiness premium for working in the public sector? Evidence from Italy," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 97(C).
    26. Brunello, Giorgio, 2020. "Happier with Vocational Education?," IZA Discussion Papers 13739, Institute of Labor Economics (IZA).
    27. Tahir Mahmood, 2023. "He said, she said: Unpacking the determinants of Pakistan’s Intra-household gender differences," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(1), pages 213-237, February.

  3. Le-Yu Chen & Ekaterina Oparina & Nattavudh Powdthavee & Sorawoot Srisuma, 2019. "Robust Ranking of Happiness Outcomes: A Median Regression Perspective," Papers 1902.07696, arXiv.org, revised Jun 2022.

    Cited by:

    1. David W. Johnston & Olena Stavrunova, 2021. "Subjective Wellbeing Dynamics," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 54(4), pages 518-529, December.
    2. O'Connor, Kelsey J., 2020. "The effect of immigration on natives’ well-being in the European Union," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 257-274.
    3. Leonard Goff, 2022. "Causal identification with subjective outcomes," Papers 2212.14622, arXiv.org, revised Feb 2023.
    4. Hock‐Eam Lim & Daigee Shaw & Le‐Yu Chen & Pei‐Shan Liao, 2023. "Distributional Effects of Freedom and Income on Life Satisfaction: Evidence from East Asian Chinese Societies," Asian Economic Journal, East Asian Economic Association, vol. 37(1), pages 113-143, March.
    5. Andrew Chesher & Adam Rosen & Zahra Siddique, 2019. "Estimating Endogenous Effects on Ordinal Outcomes," CeMMAP working papers CWP66/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Ivanov, Boris & Pfeiffer, Friedhelm & Pohlan, Laura, 2020. "Do job creation schemes improve the social integration and well-being of the long-term unemployed?," Labour Economics, Elsevier, vol. 64(C).
    7. David G. Blanchflower & Alex Bryson, 2022. "Wellbeing Rankings," DoQSS Working Papers 22-09, Quantitative Social Science - UCL Social Research Institute, University College London.
    8. Bucciol, Alessandro & Zarri, Luca, 2020. "Wounds that time can’t heal: Life satisfaction and exposure to traumatic events," Journal of Economic Psychology, Elsevier, vol. 76(C).
    9. Stöckel, Jannis & van Exel, Job & Brouwer, Werner B.F., 2023. "Adaptation in life satisfaction and self-assessed health to disability - Evidence from the UK," Social Science & Medicine, Elsevier, vol. 328(C).
    10. Shuo Liu & Nick Netzer, 2023. "Happy Times: Measuring Happiness Using Response Times," American Economic Review, American Economic Association, vol. 113(12), pages 3289-3322, December.
    11. Kim, Seonghoon & Koh, Kanghyock, 2019. "The Effects of the Affordable Care Act Medicaid Expansion on Subjective Well-being," IZA Discussion Papers 12636, Institute of Labor Economics (IZA).
    12. O'Connor, Kelsey J., 2022. "Measuring Progress," IZA Policy Papers 194, Institute of Labor Economics (IZA).
    13. Nikolova, Milena & Graham, Carol, 2020. "The Economics of Happiness," GLO Discussion Paper Series 640, Global Labor Organization (GLO).
    14. Bucciol, Alessandro & Burro, Giovanni, 2022. "Is there a happiness premium for working in the public sector? Evidence from Italy," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 97(C).
    15. Brunello, Giorgio, 2020. "Happier with Vocational Education?," IZA Discussion Papers 13739, Institute of Labor Economics (IZA).
    16. Costi, Chiara & Clark, Andrew E. & Lepinteur, Anthony & D'Ambrosio, Conchita, 2023. "Healthcare Workers and Life Satisfaction during the Pandemic," IZA Discussion Papers 16680, Institute of Labor Economics (IZA).
    17. Daniel J. Benjamin & Kristen Cooper & Ori Heffetz & Miles S. Kimball, 2023. "From Happiness Data to Economic Conclusions," NBER Working Papers 31727, National Bureau of Economic Research, Inc.

  4. Le-Yu Chen & Sokbae Lee, 2018. "High Dimensional Classification through $\ell_0$-Penalized Empirical Risk Minimization," Papers 1811.09540, arXiv.org.

    Cited by:

    1. Sokbae Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2020. "Sparse HP Filter: Finding Kinks in the COVID-19 Contact Rate," Working Paper Series no136, Institute of Economic Research, Seoul National University.
    2. Su, Jiun-Hua, 2021. "Model selection in utility-maximizing binary prediction," Journal of Econometrics, Elsevier, vol. 223(1), pages 96-124.

  5. Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Exact computation of GMM estimators for instrumental variable quantile regression models," CeMMAP working papers CWP52/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Youngki Shin & Zvezdomir Todorov, 2021. "Exact computation of maximum rank correlation estimator," The Econometrics Journal, Royal Economic Society, vol. 24(3), pages 589-607.
    2. Kaido, Hiroaki & Wüthrich, Kaspar, 2021. "Decentralization estimators for instrumental variable quantile regression models," University of California at San Diego, Economics Working Paper Series qt362921wv, Department of Economics, UC San Diego.
    3. Wüthrich, Kaspar, 2020. "A Comparison of Two Quantile Models With Endogeneity," University of California at San Diego, Economics Working Paper Series qt0q43931f, Department of Economics, UC San Diego.
    4. Hjertstrand, Per & Swofford, James L. & Whitney, Gerald A., 2023. "Testing for Weak Separability and Utility Maximization with Incomplete Adjustment," Journal of Economic Dynamics and Control, Elsevier, vol. 152(C).
    5. Jau-er Chen & Chien-Hsun Huang & Jia-Jyun Tien, 2021. "Debiased/Double Machine Learning for Instrumental Variable Quantile Regressions," Econometrics, MDPI, vol. 9(2), pages 1-18, April.
    6. Koki Fusejima, 2020. "Identification of multi-valued treatment effects with unobserved heterogeneity," Papers 2010.04385, arXiv.org, revised Apr 2023.
    7. Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2018. "Smoothed GMM for quantile models," Working Papers 1803, Department of Economics, University of Missouri.
    8. He, Xuming & Pan, Xiaoou & Tan, Kean Ming & Zhou, Wen-Xin, 2023. "Smoothed quantile regression with large-scale inference," Journal of Econometrics, Elsevier, vol. 232(2), pages 367-388.
    9. Canepa, Alessandra & de la O. González, María & Skinner, Frank S., 2020. "Hedge fund strategies: A non-parametric analysis," International Review of Financial Analysis, Elsevier, vol. 67(C).
    10. Grigory Franguridi & Bulat Gafarov & Kaspar Wuthrich, 2020. "Bias correction for quantile regression estimators," Papers 2011.03073, arXiv.org, revised Jan 2024.
    11. Nahid Farnaz, 2023. "Does Financial Development Relieve or Exacerbate Income Inequality? A Quantile Regression Approach," Economics Discussion Paper Series 2311, Economics, The University of Manchester.
    12. Xin Liu, 2019. "Averaging estimation for instrumental variables quantile regression," Papers 1910.04245, arXiv.org.
    13. Machado, José A.F. & Santos Silva, J.M.C., 2019. "Quantiles via moments," Journal of Econometrics, Elsevier, vol. 213(1), pages 145-173.
    14. 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.
    15. Yinchu Zhu, 2018. "Learning non-smooth models: instrumental variable quantile regressions and related problems," Papers 1805.06855, arXiv.org, revised Sep 2019.
    16. Grigory Franguridi & Bulat Gafarov & Kaspar Wüthrich, 2021. "Conditional Quantile Estimators: A Small Sample Theory," CESifo Working Paper Series 9046, CESifo.
    17. Bin Xu & Boqiang Lin, 2021. "Large fluctuations of China's commodity prices: Main sources and heterogeneous effects," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2074-2089, April.

  6. Le-Yu Chen & Sokbae Lee, 2016. "Best Subset Binary Prediction," Papers 1610.02738, arXiv.org, revised May 2018.

    Cited by:

    1. Susan Athey & Stefan Wager, 2017. "Policy Learning with Observational Data," Papers 1702.02896, arXiv.org, revised Sep 2020.
    2. Chen, Le-Yu & Lee, Sokbae, 2023. "Sparse quantile regression," Journal of Econometrics, Elsevier, vol. 235(2), pages 2195-2217.
    3. Youngki Shin & Zvezdomir Todorov, 2021. "Exact computation of maximum rank correlation estimator," The Econometrics Journal, Royal Economic Society, vol. 24(3), pages 589-607.
    4. Le‐Yu Chen & Sokbae Lee, 2018. "Exact computation of GMM estimators for instrumental variable quantile regression models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 553-567, June.
    5. Chen, Le-Yu & Oparina, Ekaterina & Powdthavee, Nattavudh & Srisuma, Sorawoot, 2022. "Robust Ranking of Happiness Outcomes: A Median Regression Perspective," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 672-686.
    6. Jiun-Hua Su, 2021. "No-Regret Forecasting with Egalitarian Committees," Papers 2109.13801, arXiv.org.
    7. Le-Yu Chen & Sokbae Lee, 2018. "High Dimensional Classification through $\ell_0$-Penalized Empirical Risk Minimization," Papers 1811.09540, arXiv.org.
    8. Eric Mbakop & Max Tabord‐Meehan, 2021. "Model Selection for Treatment Choice: Penalized Welfare Maximization," Econometrica, Econometric Society, vol. 89(2), pages 825-848, March.
    9. Max Tabord-Meehan, 2018. "Stratification Trees for Adaptive Randomization in Randomized Controlled Trials," Papers 1806.05127, arXiv.org, revised Jul 2022.
    10. Jiun-Hua Su, 2019. "Model Selection in Utility-Maximizing Binary Prediction," Papers 1903.00716, arXiv.org, revised Jul 2020.
    11. Davide Viviano & Jelena Bradic, 2020. "Fair Policy Targeting," Papers 2005.12395, arXiv.org, revised Jun 2022.
    12. Sokbae Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2020. "Sparse HP Filter: Finding Kinks in the COVID-19 Contact Rate," Working Paper Series no136, Institute of Economic Research, Seoul National University.
    13. Su, Jiun-Hua, 2021. "Model selection in utility-maximizing binary prediction," Journal of Econometrics, Elsevier, vol. 223(1), pages 96-124.
    14. Adam M. Rosen & Takuya Ura, 2019. "Finite Sample Inference for the Maximum Score Estimand," Papers 1903.01511, arXiv.org, revised May 2020.
    15. Bilias, Yannis & Florios, Kostas & Skouras, Spyros, 2019. "Exact computation of Censored Least Absolute Deviations estimator," Journal of Econometrics, Elsevier, vol. 212(2), pages 584-606.
    16. Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Jan 2023.

  7. Le-Yu Chen & Sokbae (Simon) Lee, 2015. "Breaking the curse of dimensionality in conditional moment inequalities for discrete choice models," CeMMAP working papers CWP26/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Le-Yu Chen & Sokbae Lee, 2016. "Best Subset Binary Prediction," Papers 1610.02738, arXiv.org, revised May 2018.
    2. Adam M. Rosen & Takuya Ura, 2019. "Finite Sample Inference for the Maximum Score Estimand," Papers 1903.01511, arXiv.org, revised May 2020.
    3. Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers 50/17, Institute for Fiscal Studies.

  8. Le-Yu Chen & Sokbae (Simon) Lee & Myung Jae Sung, 2014. "Maximum score estimation with nonparametrically generated regressors," CeMMAP working papers CWP27/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Chen, Songnian & Zhang, Hanghui, 2015. "Binary quantile regression with local polynomial smoothing," Journal of Econometrics, Elsevier, vol. 189(1), pages 24-40.
    2. Botosaru, Irene, 2020. "Nonparametric analysis of a duration model with stochastic unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 217(1), pages 112-139.
    3. Liu, Ruixuan & Yu, Zhengfei, 2022. "Sample selection models with monotone control functions," Journal of Econometrics, Elsevier, vol. 226(2), pages 321-342.
    4. Le-Yu Chen & Sokbae Lee, 2016. "Best Subset Binary Prediction," Papers 1610.02738, arXiv.org, revised May 2018.
    5. Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers 50/17, Institute for Fiscal Studies.

  9. Le-Yu Chen & Jerzy Szroeter, 2012. "Testing multiple inequality hypotheses: a smoothed indicator approach," CeMMAP working papers CWP16/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Frölich, Markus & Huber, Martin, 2015. "Direct and indirect treatment effects: causal chains and mediation analysis with instrumental variables," Working Paper Series 2025:12, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    2. Markus Frölich & Martin Huber, 2014. "Direct and indirect treatment effects: causal chains and mediation analysis with instrumental variables," CeMMAP working papers 31/14, Institute for Fiscal Studies.
    3. 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.
    4. Martin Huber & Giovanni Mellace, 2014. "Testing exclusion restrictions and additive separability in sample selection models," Empirical Economics, Springer, vol. 47(1), pages 75-92, August.
    5. Hock‐Eam Lim & Daigee Shaw & Le‐Yu Chen & Pei‐Shan Liao, 2023. "Distributional Effects of Freedom and Income on Life Satisfaction: Evidence from East Asian Chinese Societies," Asian Economic Journal, East Asian Economic Association, vol. 37(1), pages 113-143, March.
    6. Schmieder, Julia, 2021. "Fertility as a driver of maternal employment," Labour Economics, Elsevier, vol. 72(C).
    7. Christina Felfe & Martin Huber, 2017. "Does preschool boost the development of minority children?: the case of Roma children," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 475-502, February.
    8. Kedagni, Desire, 2021. "Identifying treatment effects in the presence of confounded types," ISU General Staff Papers 202106050700001056, Iowa State University, Department of Economics.
    9. Fiorini, Mario & Katrien Stevens, 2014. "Assessing the Monotonicity Assumption in IV and fuzzy RD designs," Working Papers 2014-13, University of Sydney, School of Economics.
    10. Bolzern, Benjamin & Huber, Martin, 2017. "Testing the validity of the compulsory schooling law instrument," FSES Working Papers 480, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    11. Carolina Castagnetti & Luisa Rosti & Marina Töpfer, 2020. "Discriminate me — If you can! The disappearance of the gender pay gap among public‐contest selected employees in Italy," Gender, Work and Organization, Wiley Blackwell, vol. 27(6), pages 1040-1076, November.
    12. Töpfer, Marina & Castagnetti, Carolina & Rosti, Luisa, 2016. "Discriminate me - if you can! The Disappearance of the Gender Pay Gap among Public-Contest Selected Employees," VfS Annual Conference 2016 (Augsburg): Demographic Change 145905, Verein für Socialpolitik / German Economic Association.
    13. Salm, Martin & Siflinger, Bettina & Xie, Mingjia, 2021. "The Effect of Retirement on Mental Health: Indirect Treatment Effects and Causal Mediation," Other publications TiSEM e28efa7f-8219-437c-a26d-2, Tilburg University, School of Economics and Management.
    14. M. Azhar Hussain & Nikolaj Siersbæk & Lars Peter Østerdal, 2020. "Multidimensional welfare comparisons of EU member states before, during, and after the financial crisis: a dominance approach," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 55(4), pages 645-686, December.

  10. Le-Yu Chen & Jerzy Szroeter, 2009. "Hypothesis testing of multiple inequalities: the method of constraint chaining," CeMMAP working papers CWP13/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Huber, Martin, 2012. "Statistical verification of a natural "natural experiment": Tests and sensitivity checks for the sibling sex ratio instrument," Economics Working Paper Series 1219, University of St. Gallen, School of Economics and Political Science.
    2. Le-Yu Chen & Jerzy Szroeter, 2012. "Testing multiple inequality hypotheses: a smoothed indicator approach," CeMMAP working papers 16/12, Institute for Fiscal Studies.
    3. Le-Yu Chen & Jerzy Szroeter, 2012. "Testing multiple inequality hypotheses: a smoothed indicator approach," CeMMAP working papers CWP16/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Christina Felfe & Martin Huber, 2017. "Does preschool boost the development of minority children?: the case of Roma children," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 475-502, February.
    5. Donald W.K. Andrews, 2011. "Similar-on-the-Boundary Tests for Moment Inequalities Exist, But Have Poor Power," Cowles Foundation Discussion Papers 1815R, Cowles Foundation for Research in Economics, Yale University, revised Mar 2012.
    6. Chuang, O-Chia & Kuan, Chung-Ming & Tzeng, Larry Y., 2017. "Testing for central dominance: Method and application," Journal of Econometrics, Elsevier, vol. 196(2), pages 368-378.
    7. Huber, Martin & Mellace, Giovanni, 2011. "Testing instrument validity in sample selection models," Economics Working Paper Series 1145, University of St. Gallen, School of Economics and Political Science.
    8. Huber, Martin & Mellace, Giovanni, 2011. "Testing instrument validity for LATE identification based on inequality moment constraints," Economics Working Paper Series 1143, University of St. Gallen, School of Economics and Political Science.
    9. Jeffrey M. Wooldridge, 2002. "Inverse probability weighted M-estimators for sample selection, attrition and stratification," CeMMAP working papers 11/02, Institute for Fiscal Studies.

Articles

  1. Chen, Le-Yu & Lee, Sokbae, 2023. "Sparse quantile regression," Journal of Econometrics, Elsevier, vol. 235(2), pages 2195-2217.
    See citations under working paper version above.
  2. Chen, Le-Yu & Oparina, Ekaterina & Powdthavee, Nattavudh & Srisuma, Sorawoot, 2022. "Robust Ranking of Happiness Outcomes: A Median Regression Perspective," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 672-686.
    See citations under working paper version above.
  3. Le-Yu Chen & Sokbae Lee, 2021. "Binary classification with covariate selection through ℓ0-penalised empirical risk minimisation," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 103-120.

    Cited by:

    1. Dai, Sheng, 2023. "Variable selection in convex quantile regression: L1-norm or L0-norm regularization?," European Journal of Operational Research, Elsevier, vol. 305(1), pages 338-355.

  4. Chen, Le-Yu & Lee, Sokbae, 2019. "Breaking the curse of dimensionality in conditional moment inequalities for discrete choice models," Journal of Econometrics, Elsevier, vol. 210(2), pages 482-497.
    See citations under working paper version above.
  5. Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
    See citations under working paper version above.
  6. Le‐Yu Chen & Sokbae Lee, 2018. "Exact computation of GMM estimators for instrumental variable quantile regression models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 553-567, June.
    See citations under working paper version above.
  7. Chen, Le-Yu, 2017. "Identification Of Discrete Choice Dynamic Programming Models With Nonparametric Distribution Of Unobservables," Econometric Theory, Cambridge University Press, vol. 33(3), pages 551-577, June.

    Cited by:

    1. Aguirregabiria, Victor & Collard-Wexler, Allan & Ryan, Stephen, 2021. "Dynamic Games in Empirical Industrial Organization," CEPR Discussion Papers 16514, C.E.P.R. Discussion Papers.
    2. Schneider, Ulrich, 2019. "Identification of Time Preferences in Dynamic Discrete Choice Models: Exploiting Choice Restrictions," MPRA Paper 102137, University Library of Munich, Germany, revised 29 Jul 2020.
    3. Erhao Xie, 2022. "Nonparametric Identification of Incomplete Information Discrete Games with Non-equilibrium Behaviors," Staff Working Papers 22-22, Bank of Canada.
    4. Myrto Kalouptsidi & Paul T. Scott & Eduardo Souza‐Rodrigues, 2021. "Identification of counterfactuals in dynamic discrete choice models," Quantitative Economics, Econometric Society, vol. 12(2), pages 351-403, May.
    5. Komarova, Tatiana & Sanches, Fábio Adriano & Silva Junior, Daniel & Srisuma, Sorawoot, 2018. "Joint analysis of the discount factor and payoff parameters in dynamic discrete choice games," LSE Research Online Documents on Economics 86858, London School of Economics and Political Science, LSE Library.
    6. Buchholz, Nicholas & Shum, Matthew & Xu, Haiqing, 2021. "Semiparametric estimation of dynamic discrete choice models," Journal of Econometrics, Elsevier, vol. 223(2), pages 312-327.
    7. Schiraldi, Pasquale & Levy, Matthew R., 2020. "Identification of intertemporal preferences in history-dependent dynamic discrete choice models," CEPR Discussion Papers 14447, C.E.P.R. Discussion Papers.
    8. Kalouptsidi, Myrto & Souza-Rodrigues, Eduardo & Scott, Paul, 2017. "Identification of Counterfactuals in Dynamic Discrete Choice Models," CEPR Discussion Papers 12470, C.E.P.R. Discussion Papers.

  8. Chen, Le-Yu & Szroeter, Jerzy, 2014. "Testing multiple inequality hypotheses: A smoothed indicator approach," Journal of Econometrics, Elsevier, vol. 178(P3), pages 678-693.
    See citations under working paper version above.
  9. Le‐Yu Chen & Sokbae Lee & Myung Jae Sung, 2014. "Maximum score estimation with nonparametrically generated regressors," Econometrics Journal, Royal Economic Society, vol. 17(3), pages 271-300, October.
    See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 17 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (13) 2007-04-09 2009-08-22 2009-08-22 2012-08-23 2013-05-05 2015-08-13 2016-03-06 2018-01-15 2018-01-15 2018-12-17 2020-07-20 2021-09-27 2024-02-19. Author is listed
  2. NEP-DCM: Discrete Choice Models (6) 2007-04-09 2009-08-22 2013-05-05 2015-08-13 2018-01-15 2019-03-04. Author is listed
  3. NEP-HAP: Economics of Happiness (3) 2019-02-25 2019-03-04 2024-02-19
  4. NEP-LTV: Unemployment, Inequality & Poverty (3) 2019-02-25 2019-03-04 2024-02-19
  5. NEP-HPE: History & Philosophy of Economics (2) 2019-02-25 2019-03-04
  6. NEP-ORE: Operations Research (2) 2018-01-15 2021-07-19
  7. NEP-UPT: Utility Models & Prospect Theory (2) 2009-08-22 2013-05-05
  8. NEP-ISF: Islamic Finance (1) 2021-09-27
  9. NEP-MIC: Microeconomics (1) 2009-08-22
  10. NEP-RMG: Risk Management (1) 2020-07-20

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Le-Yu Chen should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.