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史若瑶
(Ruoyao Shi)

Personal Details

First Name:Ruoyao
Middle Name:
Last Name:Shi
Suffix:
RePEc Short-ID:psh1012
http://ruoyaoshi.github.io

Affiliation

Department of Economics
University of California-Riverside

Riverside, California (United States)
https://economics.ucr.edu/
RePEc:edi:deucrus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Ruoyao Shi, 2021. "An Averaging Estimator for Two Step M Estimation in Semiparametric Models," Working Papers 202105, University of California at Riverside, Department of Economics.
  2. Jinyong Hahn & Ruoyao Shi, 2021. "Breusch and Pagan’s (1980) Test Revisited," Working Papers 202110, University of California at Riverside, Department of Economics.
  3. Jinyong Hahn & Zhipeng Liao & Geert Ridder & Ruoyao Shi, 2021. "The Influence Function of Semiparametric Two-step Estimators with Estimated Control Variables," Working Papers 202107, University of California at Riverside, Department of Economics.
  4. Cheng Chou & Ruoyao Shi, 2020. "Utilizing Two Types of Survey Data to Enhance the Accuracy of Labor Supply Elasticity Estimation," Working Papers 202018, University of California at Riverside, Department of Economics.
  5. Ruoyao Shi & Cheng Chou, 2019. "What Time Use Surveys Can (And Cannot) Tell Us about Labor Supply," Working Papers 201912, University of California at Riverside, Department of Economics.
  6. Ruoyao Shi, 2018. "Identification and Estimation of Nonparametric Hedonic Equilibrium Model with Unobserved Quality," Working Papers 201914, University of California at Riverside, Department of Economics.
  7. Ruoyao Shi & Jinyong Hahn, 2016. "Synthetic Control and Inference," Working Papers 201802, University of California at Riverside, Department of Economics, revised Nov 2017.
  8. Xu Cheng & Zhipeng Liao & Ruoyao Shi, 2013. "Uniform Asymptotic Risk of Averaging GMM Estimator Robust to Misspecification, Second Version," PIER Working Paper Archive 15-017, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 25 Mar 2015.

Articles

  1. Xu Cheng & Zhipeng Liao & Ruoyao Shi, 2019. "On uniform asymptotic risk of averaging GMM estimators," Quantitative Economics, Econometric Society, vol. 10(3), pages 931-979, July.
  2. Jinyong Hahn & Ruoyao Shi, 2017. "Synthetic Control and Inference," Econometrics, MDPI, vol. 5(4), pages 1-12, November.

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. Ruoyao Shi & Cheng Chou, 2019. "What Time Use Surveys Can (And Cannot) Tell Us about Labor Supply," Working Papers 201912, University of California at Riverside, Department of Economics.

    Cited by:

    1. Cheng Chou & Ruoyao Shi, 2019. "What Time Use Surveys Can (And Cannot) Tell Us About Labor Supply," Working Papers 202017, University of California at Riverside, Department of Economics, revised Jul 2020.
    2. Cheng Chou & Ruoyao Shi, 2020. "Utilizing Two Types of Survey Data to Enhance the Accuracy of Labor Supply Elasticity Estimation," Working Papers 202018, University of California at Riverside, Department of Economics.

  2. Ruoyao Shi & Jinyong Hahn, 2016. "Synthetic Control and Inference," Working Papers 201802, University of California at Riverside, Department of Economics, revised Nov 2017.

    Cited by:

    1. Jianfei Cao & Connor Dowd, 2019. "Estimation and Inference for Synthetic Control Methods with Spillover Effects," Papers 1902.07343, arXiv.org, revised Nov 2019.
    2. Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2019. "Synthetic Difference in Differences," Working Papers wp2019_1907, CEMFI.
    3. Ferman, Bruno & Pinto, Cristine & Possebom, Vitor, 2017. "Cherry Picking with Synthetic Controls," MPRA Paper 78213, University Library of Munich, Germany.
    4. Yi‐Ting Chen, 2020. "A distributional synthetic control method for policy evaluation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 505-525, August.
    5. Manuel Funke & Moritz Schularick & Christoph Trebesch, 2023. "Populist Leaders and the Economy," American Economic Review, American Economic Association, vol. 113(12), pages 3249-3288, December.
    6. Maximiliano Marzetti & Rok Spruk, 2023. "Long-Term Economic Effects of Populist Legal Reforms: Evidence from Argentina," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 65(1), pages 60-95, March.
    7. Born, Benjamin & Müller, Gernot & Schularick, Moritz & SedlÃ¡Ä ek, Petr, 2017. "The Costs of Economic Nationalism: Evidence from the Brexit Experiment," CEPR Discussion Papers 12454, C.E.P.R. Discussion Papers.
    8. Jason Poulos & Shuxi Zeng, 2021. "RNN‐based counterfactual prediction, with an application to homestead policy and public schooling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1124-1139, August.
    9. Chung, Bobby W., 2022. "The costs and potential benefits of occupational licensing: A case of real estate license reform," Labour Economics, Elsevier, vol. 76(C).
    10. Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," Post-Print hal-03098058, HAL.
    11. Denis Fougère & Nicolas Jacquemet, 2019. "Causal Inference and Impact Evaluation," SciencePo Working papers Main hal-02866828, HAL.
    12. James Gaughan & Nils Gutacker & Katja Grasic & Noemi Kreif & Luigi Siciliani & Andrew Street, 2018. "Paying for Efficiency: Incentivising same-day discharges in the English NHS," Working Papers 157cherp, Centre for Health Economics, University of York.
    13. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
    14. Ferman, Bruno, 2017. "Matching Estimators with Few Treated and Many Control Observations," MPRA Paper 78940, University Library of Munich, Germany.
    15. Benjamin Born & Gernot J. Müller & Moritz Schularick & Petr Sedláček, 2021. "The macroeconomic impact of Trump," Policy Studies, Taylor & Francis Journals, vol. 42(5-6), pages 580-591, November.
    16. Cordeiro Guerra, Susana & Lastra-Anadón, Carlos Xabel, 2019. "The quality-access tradeoff in decentralizing public services: Evidence from education in the OECD and Spain," Journal of Comparative Economics, Elsevier, vol. 47(2), pages 295-316.
    17. Fredriksen, Kaja & Runst, Petrik, 2018. "Are estimates of the "natural experiment" in the German crafts sector causal?," ifh Working Papers 16/2018, Volkswirtschaftliches Institut für Mittelstand und Handwerk an der Universität Göttingen (ifh).
    18. Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2018. "The Augmented Synthetic Control Method," Papers 1811.04170, arXiv.org, revised Jul 2020.
    19. Giovanni Peri & Derek Rury & Justin C. Wiltshire, 2020. "The Economic Impact of Migrants from Hurricane Maria," NBER Working Papers 27718, National Bureau of Economic Research, Inc.
    20. Christian Beer & Janine Maniora & Christiane Pott, 2023. "COVID-19 pandemic and capital markets: the role of government responses," Journal of Business Economics, Springer, vol. 93(1), pages 11-57, January.
    21. Nikolay Doudchenko & Guido W. Imbens, 2016. "Balancing, Regression, Difference-In-Differences and Synthetic Control Methods: A Synthesis," NBER Working Papers 22791, National Bureau of Economic Research, Inc.
    22. Bruno Ferman & Gaute Torsvik & Kjell Vaage, 2023. "Skipping the doctor: evidence from a case with extended self-certification of paid sick leave," Journal of Population Economics, Springer;European Society for Population Economics, vol. 36(2), pages 935-971, April.
    23. David Gilchrist & Thomas Emery & Nuno Garoupa & Rok Spruk, 2023. "Synthetic Control Method: A tool for comparative case studies in economic history," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 409-445, April.
    24. Chen, Qiang & Yan, Guanpeng, 2023. "A mixed placebo test for synthetic control method," Economics Letters, Elsevier, vol. 224(C).
    25. Ferman, Bruno & Pinto, Cristine, 2017. "Placebo Tests for Synthetic Controls," MPRA Paper 78079, University Library of Munich, Germany.
    26. Guido W. Imbens & Davide Viviano, 2023. "Identification and Inference for Synthetic Controls with Confounding," Papers 2312.00955, arXiv.org.
    27. Wenyuan Hua & Zhihan Chen & Liangguo Luo, 2022. "The Effect of the Major-Grain-Producing-Areas Oriented Policy on Crop Production: Evidence from China," Land, MDPI, vol. 11(9), pages 1-28, August.
    28. Justin Wiltshire, 2021. "allsynth: Synthetic control bias-corrections utilities for Stata," 2021 Stata Conference 15, Stata Users Group.
    29. Samuel Verevis & Murat Üngör, 2021. "What has New Zealand gained from The FTA with China?: Two counterfactual analyses†," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(1), pages 20-50, February.
    30. Marina Dias & Demian Pouzo, 2021. "Inference for multi-valued heterogeneous treatment effects when the number of treated units is small," Papers 2105.10965, arXiv.org.
    31. Ahmed Hanifi, S.M. Manzoor & Menon, Nidhiya & Quisumbing, Agnes, 2022. "The impact of climate change on children's nutritional status in coastal Bangladesh," Social Science & Medicine, Elsevier, vol. 294(C).
    32. Giulio Grossi & Marco Mariani & Alessandra Mattei & Patrizia Lattarulo & Ozge Oner, 2020. "Direct and spillover effects of a new tramway line on the commercial vitality of peripheral streets. A synthetic-control approach," Papers 2004.05027, arXiv.org, revised Nov 2023.

  3. Xu Cheng & Zhipeng Liao & Ruoyao Shi, 2013. "Uniform Asymptotic Risk of Averaging GMM Estimator Robust to Misspecification, Second Version," PIER Working Paper Archive 15-017, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 25 Mar 2015.

    Cited by:

    1. Phillip Heiler & Jana Mareckova, 2019. "Shrinkage for Categorical Regressors," Papers 1901.01898, arXiv.org.
    2. Toru Kitagawa & Chris Muris, 2015. "Model averaging in semiparametric estimation of treatment effects," CeMMAP working papers CWP46/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Francis J. DiTraglia, 2011. "Using Invalid Instruments on Purpose: Focused Moment Selection and Averaging for GMM, Second Version," PIER Working Paper Archive 14-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 09 Dec 2014.

Articles

  1. Xu Cheng & Zhipeng Liao & Ruoyao Shi, 2019. "On uniform asymptotic risk of averaging GMM estimators," Quantitative Economics, Econometric Society, vol. 10(3), pages 931-979, July.

    Cited by:

    1. David M. Kaplan, 2023. "Smoothed instrumental variables quantile regression," Papers 2310.09013, arXiv.org.
    2. Yong Bao & Xiaotian Liu & Lihong Yang, 2020. "Indirect Inference Estimation of Spatial Autoregressions," Econometrics, MDPI, vol. 8(3), pages 1-26, September.
    3. Zhang, Xinyu & Liu, Chu-An, 2023. "Model averaging prediction by K-fold cross-validation," Journal of Econometrics, Elsevier, vol. 235(1), pages 280-301.
    4. Ruoyao Shi, 2021. "An Averaging Estimator for Two Step M Estimation in Semiparametric Models," Working Papers 202105, University of California at Riverside, 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. Xin Liu, 2019. "Averaging estimation for instrumental variables quantile regression," Working Papers 1907, Department of Economics, University of Missouri.
    7. Cheng Chou & Ruoyao Shi, 2020. "Utilizing Two Types of Survey Data to Enhance the Accuracy of Labor Supply Elasticity Estimation," Working Papers 202018, University of California at Riverside, Department of Economics.
    8. Bruce E. Hansen & Seojeong Lee, 2021. "Inference for Iterated GMM Under Misspecification," Econometrica, Econometric Society, vol. 89(3), pages 1419-1447, May.
    9. David M. Kaplan, 2019. "Unbiased Estimation as a Public Good," Working Papers 1911, Department of Economics, University of Missouri.
    10. Heiler, Phillip & Mareckova, Jana, 2021. "Shrinkage for categorical regressors," Journal of Econometrics, Elsevier, vol. 223(1), pages 161-189.
    11. Cl'ement de Chaisemartin & Xavier D'Haultf{oe}uille, 2020. "Empirical MSE Minimization to Estimate a Scalar Parameter," Papers 2006.14667, arXiv.org.
    12. Edvard Bakhitov, 2020. "Frequentist Shrinkage under Inequality Constraints," Papers 2001.10586, arXiv.org.
    13. Boot, Tom, 2023. "Joint inference based on Stein-type averaging estimators in the linear regression model," Journal of Econometrics, Elsevier, vol. 235(2), pages 1542-1563.

  2. Jinyong Hahn & Ruoyao Shi, 2017. "Synthetic Control and Inference," Econometrics, MDPI, vol. 5(4), pages 1-12, November.
    See citations under working paper version above.

More information

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Statistics

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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 9 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 (7) 2015-04-02 2018-02-05 2019-11-04 2020-08-17 2021-03-01 2021-05-31 2021-07-12. Author is listed
  2. NEP-ORE: Operations Research (6) 2018-02-05 2019-11-04 2019-11-04 2020-08-24 2021-05-31 2021-07-12. Author is listed
  3. NEP-NET: Network Economics (1) 2021-07-12

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