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Ruoyao Shi
(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)
http://www.economics.ucr.edu/

(951) 827-3266
(951) 827-5685
4128 Sproul Hall, Riverside, CA 92521-0427
RePEc:edi:deucrus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

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.
  2. Ruoyao Shi & Zhipeng Liao, 2018. "An Averaging GMM Estimator Robust to Misspecification," Working Papers 201803, University of California at Riverside, Department of Economics.
  3. 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.
  4. Ruoyao Shi & Jinyong Hahn, 2016. "Synthetic Control and Inference," Working Papers 201802, University of California at Riverside, Department of Economics, revised Nov 2017.
  5. 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, Open Access Journal, 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, 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. 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. 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. Bruno Ferman & Cristine Pinto & Vitor Possebom, 2020. "Cherry Picking with Synthetic Controls," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(2), pages 510-532, March.
    2. 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.
    3. Born, Benjamin & M�ller, Gernot & Schularick, Moritz & Sedlacek, Petr, 2017. "The Economic Consequences of the Brexit Vote," CEPR Discussion Papers 12454, C.E.P.R. Discussion Papers.
    4. 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.
    5. Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2019. "Synthetic Difference In Differences," NBER Working Papers 25532, National Bureau of Economic Research, Inc.
    6. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org.
    7. Ferman, Bruno, 2017. "Matching Estimators with Few Treated and Many Control Observations," MPRA Paper 78940, University Library of Munich, Germany.
    8. 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.
    9. 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).
    10. Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2018. "The Augmented Synthetic Control Method," Papers 1811.04170, arXiv.org, revised Jul 2020.
    11. Funke, Manuel & Schularick, Moritz & Trebesch, Christoph, 2020. "Populist leaders and the economy," Kiel Working Papers 2169, Kiel Institute for the World Economy (IfW).
    12. Jianfei Cao & Connor Dowd, 2019. "Estimation and Inference for Synthetic Control Methods with Spillover Effects," Papers 1902.07343, arXiv.org, revised Nov 2019.
    13. Born, Benjamin & Müller, Gernot & Schularick, Moritz & Sedlacek, Petr, 2019. "Stable genius? The macroeconomic impact of Trump," CEPR Discussion Papers 13798, C.E.P.R. Discussion Papers.
    14. 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.
    15. 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.
    16. Manuel Funke & Moritz Schularick & Christoph Trebesch, 2020. "Populist Leaders and the Economy," ECONtribute Discussion Papers Series 036, University of Bonn and University of Cologne, Germany.
    17. Ferman, Bruno & Pinto, Cristine, 2017. "Placebo Tests for Synthetic Controls," MPRA Paper 78079, University Library of Munich, Germany.

  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. Yong Bao & Xiaotian Liu & Lihong Yang, 2020. "Indirect Inference Estimation of Spatial Autoregressions," Econometrics, MDPI, Open Access Journal, vol. 8(3), pages 1-26, September.
    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.
    3. Xin Liu, 2019. "Averaging estimation for instrumental variables quantile regression," Papers 1910.04245, arXiv.org.
    4. David M. Kaplan, 2019. "Unbiased Estimation as a Public Good," Working Papers 1911, Department of Economics, University of Missouri.
    5. Xin Liu, 2019. "Averaging estimation for instrumental variables quantile regression," Working Papers 1907, Department of Economics, University of Missouri.
    6. Cl'ement de Chaisemartin & Xavier D'Haultf{oe}uille, 2020. "Empirical MSE Minimization to Estimate a Scalar Parameter," Papers 2006.14667, arXiv.org.
    7. Andrews, Donald W.K. & Cheng, Xu & Guggenberger, Patrik, 2020. "Generic results for establishing the asymptotic size of confidence sets and tests," Journal of Econometrics, Elsevier, vol. 218(2), pages 496-531.
    8. Edvard Bakhitov, 2020. "Frequentist Shrinkage under Inequality Constraints," Papers 2001.10586, arXiv.org.

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

More information

Research fields, statistics, top rankings, if available.

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 5 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 (4) 2015-04-02 2018-02-05 2018-02-05 2019-11-04. Author is listed
  2. NEP-ORE: Operations Research (3) 2018-02-05 2019-11-04 2019-11-04. Author is listed

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