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Zhengfei Yu

Personal Details

First Name:Zhengfei
Middle Name:
Last Name:Yu
Suffix:
RePEc Short-ID:pyu219
[This author has chosen not to make the email address public]
http://zhengfeiyu.weebly.com/

Affiliation

Faculty of Humanities and Social Sciences
University of Tsukuba

Ibaraki, Japan
https://www.jinsha.tsukuba.ac.jp/
RePEc:edi:iptsujp (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. Jun Ma & Zhengfei Yu, 2020. "Empirical Likelihood Covariate Adjustment for Regression Discontinuity Designs," Papers 2008.09263, arXiv.org, revised May 2024.
  2. Hugo Jales & Zhengfei Yu, 2020. "Labor Market Policies in a Roy-Rosen Bargaining Economy," Center for Policy Research Working Papers 231, Center for Policy Research, Maxwell School, Syracuse University.
  3. Ruixuan Liu & Zhengfei Yu, 2019. "Simple Semiparametric Estimation of Ordered Response Models: with an Application to the Interdependence Duration Models," Tsukuba Economics Working Papers 2019-004, Faculty of Humanities and Social Sciences, University of Tsukuba.
  4. Ruixuan Liu & Zhengfei Yu, 2019. "Accelerated Failure Time Models with Log-concave Errors," Tsukuba Economics Working Papers 2019-003, Faculty of Humanities and Social Sciences, University of Tsukuba.
  5. Donald W.K. Andrews & Vadim Marmer & Zhengfei Yu, 2017. "On Optimal Inference in the Linear IV Model," Cowles Foundation Discussion Papers 2073R, Cowles Foundation for Research in Economics, Yale University, revised Feb 2018.
  6. Donald W.K. Andrews & Vadim Marmer & Zhengfei Yu, 2017. "A Note on Optimal Inference in the Linear IV Model," Cowles Foundation Discussion Papers 2073, Cowles Foundation for Research in Economics, Yale University.
  7. Marmer, Vadim & Yu, Zhengfei, 2015. "Efficient Inference in the Classical IV Regression Model with Weak Identification: Asymptotic Power Against Arbitrarily Large Deviations from the Null Hypothesis," Microeconomics.ca working papers vadim_marmer-2015-17, Vancouver School of Economics, revised 02 Sep 2015.

Articles

  1. Jun Ma & Hugo Jales & Zhengfei Yu, 2020. "Minimum Contrast Empirical Likelihood Inference of Discontinuity in Density," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(4), pages 934-950, October.
  2. Donald W. K. Andrews & Vadim Marmer & Zhengfei Yu, 2019. "On optimal inference in the linear IV model," Quantitative Economics, Econometric Society, vol. 10(2), pages 457-485, May.
  3. Jales, Hugo & Ma, Jun & Yu, Zhengfei, 2017. "Optimal bandwidth selection for local linear estimation of discontinuity in density," Economics Letters, Elsevier, vol. 153(C), pages 23-27.
  4. Fan, Yanqin & Yu, Zhengfei, 2012. "Partial identification of distributional and quantile treatment effects in difference-in-differences models," Economics Letters, Elsevier, vol. 115(3), pages 511-515.

Chapters

  1. Hugo Jales & Zhengfei Yu, 2017. "Identification and Estimation Using a Density Discontinuity Approach," Advances in Econometrics, in: Regression Discontinuity Designs, volume 38, pages 29-72, Emerald Group Publishing Limited.

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. Jun Ma & Zhengfei Yu, 2020. "Empirical Likelihood Covariate Adjustment for Regression Discontinuity Designs," Papers 2008.09263, arXiv.org, revised May 2024.

    Cited by:

    1. Matias D. Cattaneo & Rocio Titiunik, 2021. "Regression Discontinuity Designs," Papers 2108.09400, arXiv.org, revised Feb 2022.

  2. Hugo Jales & Zhengfei Yu, 2020. "Labor Market Policies in a Roy-Rosen Bargaining Economy," Center for Policy Research Working Papers 231, Center for Policy Research, Maxwell School, Syracuse University.

    Cited by:

    1. Rodrigo Ceni & Gabriel Merlo, 2021. "Twenty years of job flows in an emerging country," Documentos de Trabajo (working papers) 21-10, Instituto de Economía - IECON.

  3. Ruixuan Liu & Zhengfei Yu, 2019. "Simple Semiparametric Estimation of Ordered Response Models: with an Application to the Interdependence Duration Models," Tsukuba Economics Working Papers 2019-004, Faculty of Humanities and Social Sciences, University of Tsukuba.

    Cited by:

    1. Tatiana Komarova & William Matcham, 2022. "Multivariate ordered discrete response models," Papers 2205.05779, arXiv.org, revised Mar 2023.

  4. Donald W.K. Andrews & Vadim Marmer & Zhengfei Yu, 2017. "On Optimal Inference in the Linear IV Model," Cowles Foundation Discussion Papers 2073R, Cowles Foundation for Research in Economics, Yale University, revised Feb 2018.

    Cited by:

    1. Tetsuya Kaji, 2019. "Theory of Weak Identification in Semiparametric Models," Papers 1908.10478, arXiv.org, revised Aug 2020.
    2. Marcelo Moreira & Geert Ridder, 2019. "Efficiency loss of asymptotically efficient tests in an instrumental variables regression," CeMMAP working papers CWP03/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Antoine, Bertille & Lavergne, Pascal, 2023. "Identification-robust nonparametric inference in a linear IV model," Journal of Econometrics, Elsevier, vol. 235(1), pages 1-24.
    4. Jan F. Kiviet, 2020. "Instrument-free inference under confined regressor endogeneity; derivations and applications," Working Papers 09/2020, Stellenbosch University, Department of Economics.
    5. Donald W.K. Andrews & Xu Cheng & Patrik Guggenberger, 2011. "Generic Results for Establishing the Asymptotic Size of Confidence Sets and Tests," Cowles Foundation Discussion Papers 1813, Cowles Foundation for Research in Economics, Yale University.
    6. Johannes W. Ligtenberg, 2023. "Inference in IV models with clustered dependence, many instruments and weak identification," Papers 2306.08559, arXiv.org, revised Mar 2024.
    7. Donald W. K. Andrews & Patrik Guggenberger, 2015. "Identification- and Singularity-Robust Inference for Moment Condition," Cowles Foundation Discussion Papers 1978R2, Cowles Foundation for Research in Economics, Yale University, revised Jan 2019.
    8. Kiviet, Jan F., 2023. "Instrument-free inference under confined regressor endogeneity and mild regularity," Econometrics and Statistics, Elsevier, vol. 25(C), pages 1-22.
    9. Nicolas Van de Sijpe & Frank Windmeijer, 2021. "On the Power of the Conditional Likelihood Ratio and Related Tests for Weak-Instrument Robust Inference," Economics Papers 2020-W09, Economics Group, Nuffield College, University of Oxford.
    10. Patrik Guggenberger & Frank Kleibergen & Sophocles Mavroeidis, 2021. "A Powerful Subvector Anderson Rubin Test in Linear Instrumental Variables Regression with Conditional Heteroskedasticity," Papers 2103.11371, arXiv.org, revised Oct 2022.
    11. Olatunji Abdul Shobande & Mobolaji Daniel Akinbomi, 2020. "Competition dynamics in Nigerian aviation industry: a game theoretic approach," Future Business Journal, Springer, vol. 6(1), pages 1-8, December.
    12. Horowitz, Joel L., 2021. "Bounding the difference between true and nominal rejection probabilities in tests of hypotheses about instrumental variables models," Journal of Econometrics, Elsevier, vol. 222(2), pages 1057-1082.

Articles

  1. Jun Ma & Hugo Jales & Zhengfei Yu, 2020. "Minimum Contrast Empirical Likelihood Inference of Discontinuity in Density," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(4), pages 934-950, October.

    Cited by:

    1. Matias D. Cattaneo & Rocio Titiunik, 2021. "Regression Discontinuity Designs," Papers 2108.09400, arXiv.org, revised Feb 2022.
    2. Jun Ma & Vadim Marmer & Artyom Shneyerov & Pai Xu, 2019. "Monotonicity-Constrained Nonparametric Estimation and Inference for First-Price Auctions," Papers 1909.12974, arXiv.org.
    3. Fitzgerald, Jack, 2024. "Manipulation Tests in Regression Discontinuity Design: The Need for Equivalence Testing," I4R Discussion Paper Series 136, The Institute for Replication (I4R).
    4. Jun Ma & Zhengfei Yu, 2020. "Empirical Likelihood Covariate Adjustment for Regression Discontinuity Designs," Papers 2008.09263, arXiv.org, revised May 2024.

  2. Donald W. K. Andrews & Vadim Marmer & Zhengfei Yu, 2019. "On optimal inference in the linear IV model," Quantitative Economics, Econometric Society, vol. 10(2), pages 457-485, May.
    See citations under working paper version above.
  3. Jales, Hugo & Ma, Jun & Yu, Zhengfei, 2017. "Optimal bandwidth selection for local linear estimation of discontinuity in density," Economics Letters, Elsevier, vol. 153(C), pages 23-27.

    Cited by:

    1. Matias D. Cattaneo & Rocio Titiunik, 2021. "Regression Discontinuity Designs," Papers 2108.09400, arXiv.org, revised Feb 2022.
    2. Jun Ma & Vadim Marmer & Artyom Shneyerov & Pai Xu, 2019. "Monotonicity-Constrained Nonparametric Estimation and Inference for First-Price Auctions," Papers 1909.12974, arXiv.org.
    3. Rajesh, Richu & G., Rajesh & Sunoj, S.M., 2022. "Kernel estimation of extropy function under length-biased sampling," Statistics & Probability Letters, Elsevier, vol. 181(C).

  4. Fan, Yanqin & Yu, Zhengfei, 2012. "Partial identification of distributional and quantile treatment effects in difference-in-differences models," Economics Letters, Elsevier, vol. 115(3), pages 511-515.

    Cited by:

    1. 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.
    2. David Bounie & Youssouf Camara, 2020. "Card-Sales Response to Merchant Contactless Payment Acceptance," Post-Print hal-02296302, HAL.
    3. Callaway, Brantly & Li, Tong & Oka, Tatsushi, 2018. "Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods," Journal of Econometrics, Elsevier, vol. 206(2), pages 395-413.
    4. Andrea Ciaccio, 2024. "Distributional Difference-in-Differences Models with Multiple Time Periods: A Monte Carlo Analysis," Papers 2408.01208, arXiv.org.
    5. Bounie, David & Camara, Youssouf, 2020. "Card-sales response to merchant contactless payment acceptance," Journal of Banking & Finance, Elsevier, vol. 119(C).
    6. Wang, Zheng-Xin & Jv, Yue-Qi, 2022. "A smooth difference-in-differences model for assessing gradual policy effects: Revisiting the impact of banking deregulation on income distribution," Finance Research Letters, Elsevier, vol. 50(C).

Chapters

  1. Hugo Jales & Zhengfei Yu, 2017. "Identification and Estimation Using a Density Discontinuity Approach," Advances in Econometrics, in: Regression Discontinuity Designs, volume 38, pages 29-72, Emerald Group Publishing Limited.

    Cited by:

    1. Francisco J.M Costa & João S. De Faria & Felipe S. Iachan & Bárbara Caballero, 2018. "Homicides and the Age of Criminal Responsibility: A Density Discontinuity Approach," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Fall 2018), pages 59-92, November.
    2. Jales, Hugo & Jiang, Boqian & Rosenthal, Stuart S., 2023. "JUE Insight: Using the mode to test for selection in city size wage premia," Journal of Urban Economics, Elsevier, vol. 133(C).
    3. Jales, Hugo & Ma, Jun & Yu, Zhengfei, 2017. "Optimal bandwidth selection for local linear estimation of discontinuity in density," Economics Letters, Elsevier, vol. 153(C), pages 23-27.
    4. Matias D. Cattaneo & Rocio Titiunik, 2021. "Regression Discontinuity Designs," Papers 2108.09400, arXiv.org, revised Feb 2022.
    5. Marinho Bertanha & Andrew H. McCallum & Nathan Seegert, 2021. "Better Bunching, Nicer Notching," Finance and Economics Discussion Series 2021-002, Board of Governors of the Federal Reserve System (U.S.).
    6. Marinho Bertanha & Andrew H. McCallum & Alexis Payne & Nathan Seegert, 2022. "Bunching estimation of elasticities using Stata," Stata Journal, StataCorp LP, vol. 22(3), pages 597-624, September.
    7. Johansson, Naimi & de New, Sonja C. & Kunz, Johannes S. & Petrie, Dennis & Svensson, Mikael, 2023. "Reductions in out-of-pocket prices and forward-looking moral hazard in health care demand," Journal of Health Economics, Elsevier, vol. 87(C).
    8. Emmanuel Guerre & Yao Luo, 2019. "Nonparametric Identification of First-Price Auction with Unobserved Competition: A Density Discontinuity Framework," Papers 1908.05476, arXiv.org, revised Jan 2022.
    9. Rodrigo Carril & Andres Gonzalez-Lira & Michael S. Walker, 2022. "Competition under incomplete contracts and the design of procurement policies," Economics Working Papers 1824, Department of Economics and Business, Universitat Pompeu Fabra.
    10. Zhuan Pei & Yi Shen, 2016. "The Devil is in the Tails: Regression Discontinuity Design with Measurement Error in the Assignment Variable," Working Papers 606, Princeton University, Department of Economics, Industrial Relations Section..
    11. Jun Ma & Zhengfei Yu, 2020. "Empirical Likelihood Covariate Adjustment for Regression Discontinuity Designs," Papers 2008.09263, arXiv.org, revised May 2024.

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 7 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 (6) 2015-09-18 2015-09-26 2017-02-12 2019-12-16 2019-12-16 2020-09-14. Author is listed
  2. NEP-IUE: Informal and Underground Economics (2) 2020-07-20 2020-08-17
  3. NEP-LMA: Labor Markets - Supply, Demand, and Wages (1) 2020-07-20
  4. NEP-ORE: Operations Research (1) 2019-12-16

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