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Ryo Okui

Personal Details

First Name:Ryo
Middle Name:
Last Name:Okui
Suffix:
RePEc Short-ID:pok36
https://sites.google.com/site/okuiryoeconomics/
Terminal Degree:2005 Department of Economics; University of Pennsylvania (from RePEc Genealogy)

Affiliation

Division of Economics
Seoul National University

Seoul, South Korea
http://econ.snu.ac.kr/

: 880-6360
886-4231

RePEc:edi:desnukr (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Dzemski, Andreas & Okui, Ryo, 2018. "Confidence Set for Group Membership," Working Papers in Economics 727, University of Gothenburg, Department of Economics.
  2. Ryo Okui & Wendun Wang, 2018. "Heterogeneous structural breaks in panel data models," Papers 1801.04672, arXiv.org, revised Nov 2018.
  3. Ryo Okui & Takahide Yanagi, 2018. "Kernel Estimation for Panel Data with Heterogeneous Dynamics," Papers 1802.08825, arXiv.org, revised May 2019.
  4. Yanchun Jin & Ryo Okui, 2018. "Testing for Overconfidence Statistically: A Moment Inequality Approach," KIER Working Papers 984, Kyoto University, Institute of Economic Research.
  5. Andreas Dzemski & Ryo Okui, 2017. "Confidence set for group membership," Papers 1801.00332, arXiv.org, revised Dec 2018.
  6. Sokbae Lee & Ryo Okui & Yoon-Jae Whang, 2016. "Doubly Robust Uniform Confidence Band For The Conditional Average Treatment Effect Function," KIER Working Papers 931, Kyoto University, Institute of Economic Research.
  7. OGURA Yoshiaki & OKUI Ryo & SAITO Yukiko, 2015. "Network-motivated Lending Decisions," Discussion papers 15057, Research Institute of Economy, Trade and Industry (RIETI).
  8. Ryo Okui & Takahide Yanagi, 2014. "Panel Data Analysis with Heterogeneous Dynamics," KIER Working Papers 906, Kyoto University, Institute of Economic Research.
  9. Haruo Iwakura & Ryo Okui, 2014. "Asymptotic Efficiency in Factor Models and Dynamic Panel Data Models," KIER Working Papers 887, Kyoto University, Institute of Economic Research.
  10. Qingfeng Liu & Ryo Okui & Arihiro Yoshimura, 2013. "Generalized Least Squares Model Averaging," KIER Working Papers 855, Kyoto University, Institute of Economic Research.
  11. Yoon-Jin Lee & Ryo Okui & Mototsugu Shintani, 2013. "Asymptotic Inference for Dynamic Panel Estimators of In nite Order Autoregressive Processes," KIER Working Papers 879, Kyoto University, Institute of Economic Research.
  12. Yoonseok Lee & Ryo Okui, 2009. "A Specification Test for Instrumental Variables Regression with Many Instruments," Cowles Foundation Discussion Papers 1741, Cowles Foundation for Research in Economics, Yale University.
  13. Kohtarro Hitomi & Yoshinori Kawasaki & Ryo Okui & Yoshihiko Nishiyama, 2005. "A Consistent Nonparametric Test for Causality," KIER Working Papers 602, Kyoto University, Institute of Economic Research.
  14. Ryo Okui, 2004. "Shrinkage methods for instrumental variable estimation," Econometric Society 2004 Far Eastern Meetings 678, Econometric Society.

Articles

  1. Lee, Yoon-Jin & Okui, Ryo & Shintani, Mototsugu, 2018. "Asymptotic inference for dynamic panel estimators of infinite order autoregressive processes," Journal of Econometrics, Elsevier, vol. 204(2), pages 147-158.
  2. Ryo Okui, 2017. "Misspecification in Dynamic Panel Data Models and Model-Free Inferences," The Japanese Economic Review, Japanese Economic Association, vol. 68(3), pages 283-304, September.
  3. Sokbae Lee & Ryo Okui & Yoon†Jae Whang, 2017. "Doubly robust uniform confidence band for the conditional average treatment effect function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(7), pages 1207-1225, November.
  4. Qingfeng Liu & Ryo Okui & Arihiro Yoshimura, 2016. "Generalized Least Squares Model Averaging," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1692-1752, December.
  5. Okui Ryo, 2014. "Asymptotically Unbiased Estimation of Autocovariances and Autocorrelations with Panel Data in the Presence of Individual and Time Effects," Journal of Time Series Econometrics, De Gruyter, vol. 6(2), pages 1-53, July.
  6. Tanjim Hossain & Ryo Okui, 2013. "The Binarized Scoring Rule," Review of Economic Studies, Oxford University Press, vol. 80(3), pages 984-1001.
  7. Qingfeng Liu & Ryo Okui, 2013. "Heteroscedasticity‐robust C(p) model averaging," Econometrics Journal, Royal Economic Society, vol. 16(3), pages 463-472, October.
  8. Lee, Yoonseok & Okui, Ryo, 2012. "Hahn–Hausman test as a specification test," Journal of Econometrics, Elsevier, vol. 167(1), pages 133-139.
  9. Okui, Ryo, 2011. "Asymptotically unbiased estimation of autocovariances and autocorrelations for panel data with incidental trends," Economics Letters, Elsevier, vol. 112(1), pages 49-52, July.
  10. Okui, Ryo, 2011. "Instrumental variable estimation in the presence of many moment conditions," Journal of Econometrics, Elsevier, vol. 165(1), pages 70-86.
  11. Guido Kuersteiner & Ryo Okui, 2010. "Constructing Optimal Instruments by First-Stage Prediction Averaging," Econometrica, Econometric Society, vol. 78(2), pages 697-718, March.
  12. Okui, Ryo, 2010. "Asymptotically Unbiased Estimation Of Autocovariances And Autocorrelations With Long Panel Data," Econometric Theory, Cambridge University Press, vol. 26(05), pages 1263-1304, October.
  13. Okui, Ryo, 2009. "Testing serial correlation in fixed effects regression models based on asymptotically unbiased autocorrelation estimators," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2897-2909.
  14. Hizen Yoichi & Okui Ryo, 2009. "Olympic Athlete Selection," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 9(1), pages 1-49, October.
  15. Okui, Ryo, 2009. "The optimal choice of moments in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 151(1), pages 1-16, July.
  16. Okui, Ryo, 2008. "Panel AR(1) estimators under misspecification," Economics Letters, Elsevier, vol. 101(3), pages 210-213, December.
  17. Hitomi, Kohtaro & Nishiyama, Yoshihiko & Okui, Ryo, 2008. "A Puzzling Phenomenon In Semiparametric Estimation Problems With Infinite-Dimensional Nuisance Parameters," Econometric Theory, Cambridge University Press, vol. 24(06), pages 1717-1728, December.

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. Ryo Okui & Takahide Yanagi, 2018. "Kernel Estimation for Panel Data with Heterogeneous Dynamics," Papers 1802.08825, arXiv.org, revised May 2019.

    Cited by:

    1. Jochmans, K., & Weidner, M., 2019. "Inference on a distribution from noisy draws," Cambridge Working Papers in Economics 1946, Faculty of Economics, University of Cambridge.
    2. Ryo Okui & Takahide Yanagi, 2014. "Panel Data Analysis with Heterogeneous Dynamics," KIER Working Papers 906, Kyoto University, Institute of Economic Research.

  2. Sokbae Lee & Ryo Okui & Yoon-Jae Whang, 2016. "Doubly Robust Uniform Confidence Band For The Conditional Average Treatment Effect Function," KIER Working Papers 931, Kyoto University, Institute of Economic Research.

    Cited by:

    1. Lechner, Michael, 2019. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," CEPR Discussion Papers 13430, C.E.P.R. Discussion Papers.
    2. Pedro H. C. Sant'Anna & Jun B. Zhao, 2018. "Doubly Robust Difference-in-Differences Estimators," Papers 1812.01723, arXiv.org.
    3. Knaus, Michael C. & Lechner, Michael & Strittmatter, Anthony, 2018. "Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence," CEPR Discussion Papers 13402, C.E.P.R. Discussion Papers.
    4. Zongwu Cai & Ying Fang & Ming Lin & Shengfang Tang, 2019. "Testing Unconfoundedness Assumption Using Auxiliary Variables," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201905, University of Kansas, Department of Economics, revised Mar 2019.
    5. Pedro H. C. Sant'Anna, 2016. "Nonparametric Tests for Treatment Effect Heterogeneity with Duration Outcomes," Papers 1612.02090, arXiv.org, revised Sep 2017.
    6. Strittmatter, Anthony, 2019. "What Is the Value Added by Using Causal Machine Learning Methods in a Welfare Experiment Evaluation?," GLO Discussion Paper Series 336, Global Labor Organization (GLO).
    7. Anthony Strittmatter, 2018. "What Is the Value Added by Using Causal Machine Learning Methods in a Welfare Experiment Evaluation?," Papers 1812.06533, arXiv.org, revised Mar 2019.

  3. OGURA Yoshiaki & OKUI Ryo & SAITO Yukiko, 2015. "Network-motivated Lending Decisions," Discussion papers 15057, Research Institute of Economy, Trade and Industry (RIETI).

    Cited by:

    1. Jiangtao FU & OGURA Yoshiaki, 2017. "Product Network Connectivity and Information for Loan Pricing," Discussion papers 17028, Research Institute of Economy, Trade and Industry (RIETI).
    2. Inoue, Hitoshi & Nakashima, Kiyotaka & Takahashi, Koji, 2018. "The Interaction Effect in a Nonlinear Specification of Bank Lending: A Reexamination of ``Unnatural Selection"," MPRA Paper 89087, University Library of Munich, Germany.
    3. Inoue, Hitoshi & Nakashima, Kiyotaka & Takahashi, Koji, 2016. "Comment on Peek and Rosengren (2005) “Unnatural Selection: Perverse Incentives and the Allocation of Credit in Japan”," MPRA Paper 72726, University Library of Munich, Germany.
    4. Jiangtao Fu & Yoshiaki Ogura, 2017. "Product Network Connectivity and Information for Loan Pricing," Working Papers 1703, Waseda University, Faculty of Political Science and Economics.

  4. Ryo Okui & Takahide Yanagi, 2014. "Panel Data Analysis with Heterogeneous Dynamics," KIER Working Papers 906, Kyoto University, Institute of Economic Research.

    Cited by:

    1. Ryo Okui & Takahide Yanagi, 2018. "Kernel Estimation for Panel Data with Heterogeneous Dynamics," Papers 1802.08825, arXiv.org, revised May 2019.
    2. Jochmans, K., & Weidner, M., 2019. "Inference on a distribution from noisy draws," Cambridge Working Papers in Economics 1946, Faculty of Economics, University of Cambridge.
    3. Ryo Okui & Takahide Yanagi, 2014. "Panel Data Analysis with Heterogeneous Dynamics," KIER Working Papers 906, Kyoto University, Institute of Economic Research.
    4. Ryo Okui, 2017. "Misspecification in Dynamic Panel Data Models and Model-Free Inferences," The Japanese Economic Review, Japanese Economic Association, vol. 68(3), pages 283-304, September.

  5. Haruo Iwakura & Ryo Okui, 2014. "Asymptotic Efficiency in Factor Models and Dynamic Panel Data Models," KIER Working Papers 887, Kyoto University, Institute of Economic Research.

    Cited by:

    1. Hayakawa, Kazuhiko, 2016. "Improved GMM estimation of panel VAR models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 240-264.
    2. Bai, Jushan & Liao, Yuan, 2017. "Inferences in panel data with interactive effects using large covariance matrices," Journal of Econometrics, Elsevier, vol. 200(1), pages 59-78.

  6. Qingfeng Liu & Ryo Okui & Arihiro Yoshimura, 2013. "Generalized Least Squares Model Averaging," KIER Working Papers 855, Kyoto University, Institute of Economic Research.

    Cited by:

    1. Cong Li & Qi Li & Jeffrey Racine & DAIQIANG ZHANG, 2017. "Optimal Model Averaging Of Varying Coefficient Models," Department of Economics Working Papers 2017-01, McMaster University.
    2. Steel, Mark F. J., 2017. "Model Averaging and its Use in Economics," MPRA Paper 90110, University Library of Munich, Germany, revised 16 Nov 2018.

  7. Yoon-Jin Lee & Ryo Okui & Mototsugu Shintani, 2013. "Asymptotic Inference for Dynamic Panel Estimators of In nite Order Autoregressive Processes," KIER Working Papers 879, Kyoto University, Institute of Economic Research.

    Cited by:

    1. Ryo Okui & Takahide Yanagi, 2014. "Panel Data Analysis with Heterogeneous Dynamics," KIER Working Papers 906, Kyoto University, Institute of Economic Research.
    2. Juan Sebastian Cubillos-Rocha & Luis Fernando Melo-Velandia, 2018. "Asymptotically unbiased inference for a panel VAR model with p lags," Borradores de Economia 1059, Banco de la Republica de Colombia.

  8. Yoonseok Lee & Ryo Okui, 2009. "A Specification Test for Instrumental Variables Regression with Many Instruments," Cowles Foundation Discussion Papers 1741, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Norman R. Swanson & John C. Chao & Jerry A. Hausman & Whitney K. Newey & Tiemen Woutersen, 2011. "Testing Overidentifying Restrictions with Many Instruments and Heteroskedasticity," Departmental Working Papers 201118, Rutgers University, Department of Economics.
    2. Lee, Yoonseok & Okui, Ryo, 2012. "Hahn–Hausman test as a specification test," Journal of Econometrics, Elsevier, vol. 167(1), pages 133-139.
    3. C. J. Krizan & Adela Luque & Alice Zawacki, 2014. "The Effect Of Employer Health Insurance Offering On The Growth And Survival Of Small Business Prior To The Affordable Care Act," Working Papers 14-22, Center for Economic Studies, U.S. Census Bureau.

Articles

  1. Lee, Yoon-Jin & Okui, Ryo & Shintani, Mototsugu, 2018. "Asymptotic inference for dynamic panel estimators of infinite order autoregressive processes," Journal of Econometrics, Elsevier, vol. 204(2), pages 147-158.
    See citations under working paper version above.
  2. Sokbae Lee & Ryo Okui & Yoon†Jae Whang, 2017. "Doubly robust uniform confidence band for the conditional average treatment effect function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(7), pages 1207-1225, November.
    See citations under working paper version above.
  3. Qingfeng Liu & Ryo Okui & Arihiro Yoshimura, 2016. "Generalized Least Squares Model Averaging," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1692-1752, December.
    See citations under working paper version above.
  4. Okui Ryo, 2014. "Asymptotically Unbiased Estimation of Autocovariances and Autocorrelations with Panel Data in the Presence of Individual and Time Effects," Journal of Time Series Econometrics, De Gruyter, vol. 6(2), pages 1-53, July.

    Cited by:

    1. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and Time Effects in Nonlinear Panel Models with Large N, T," Papers 1311.7065, arXiv.org, revised Dec 2018.
    2. Andreas Joseph, 2019. "Shapley regressions: A framework for statistical inference on machine learning models," Papers 1903.04209, arXiv.org.
    3. Ryo Okui & Takahide Yanagi, 2018. "Kernel Estimation for Panel Data with Heterogeneous Dynamics," Papers 1802.08825, arXiv.org, revised May 2019.
    4. Ryo Okui & Takahide Yanagi, 2014. "Panel Data Analysis with Heterogeneous Dynamics," KIER Working Papers 906, Kyoto University, Institute of Economic Research.
    5. Haruo Iwakura & Ryo Okui, 2014. "Asymptotic Efficiency in Factor Models and Dynamic Panel Data Models," KIER Working Papers 887, Kyoto University, Institute of Economic Research.
    6. Ryo Okui, 2017. "Misspecification in Dynamic Panel Data Models and Model-Free Inferences," The Japanese Economic Review, Japanese Economic Association, vol. 68(3), pages 283-304, September.
    7. Joseph, Andreas, 2019. "Shapley regressions: a framework for statistical inference on machine learning models," Bank of England working papers 784, Bank of England.
    8. Timothy J. Vogelsang & Jingjing Yang, 2016. "Exactly/Nearly Unbiased Estimation of Autocovariances of a Univariate Time Series With Unknown Mean," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 723-740, November.

  5. Tanjim Hossain & Ryo Okui, 2013. "The Binarized Scoring Rule," Review of Economic Studies, Oxford University Press, vol. 80(3), pages 984-1001.

    Cited by:

    1. Harrison, Glenn W. & Martínez-Correa, Jimmy & Swarthout, J. Todd, 2013. "Inducing risk neutral preferences with binary lotteries: A reconsideration," Journal of Economic Behavior & Organization, Elsevier, vol. 94(C), pages 145-159.
    2. von Gaudecker, Hans-Martin & Drerup, Tilman & Enke, Benjamin, 2015. "Measurement Error in Subjective Expectations and the Empirical Content of Economic Models," Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112871, Verein für Socialpolitik / German Economic Association.
    3. Thomas Buser & Leonie Gerhards & Joël J. van der Weele, 2016. "Measuring Responsiveness to Feedback as a Personal Trait," Tinbergen Institute Discussion Papers 16-043/I, Tinbergen Institute.
    4. Barron, Kai, 2019. "Belief updating: Does the 'good-news, bad-news' asymmetry extend to purely financial domains?," Discussion Papers, Research Unit: Economics of Change SP II 2016-309r, WZB Berlin Social Science Center.
    5. Karl Schlag & James Tremewan & Joel van der Weele, 2014. "A Penny for Your Thoughts:A Survey of Methods for Eliciting Beliefs," Vienna Economics Papers 1401, University of Vienna, Department of Economics.
    6. Aidas Masiliunas, 2016. "Overcoming Coordination Failure in a Critical Mass Game: Strategic Motives and Action Disclosure," AMSE Working Papers 1609, Aix-Marseille School of Economics, France.
    7. Markus Eyting & Patrick Schmidt, 2019. "Belief Elicitation with Multiple Point Predictions," Working Papers 1818, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    8. Mitchell Hoffman, 2014. "Training Contracts, Worker Overconfidence, and the Provision of Firm-Sponsored General Training," 2014 Meeting Papers 203, Society for Economic Dynamics.
    9. Stefan T. Trautmann & Gijs Kuilen, 2015. "Belief Elicitation: A Horse Race among Truth Serums," Economic Journal, Royal Economic Society, vol. 125(589), pages 2116-2135, December.
    10. Li Hao & Daniel Houser, 2012. "Belief elicitation in the presence of naïve respondents: An experimental study," Journal of Risk and Uncertainty, Springer, vol. 44(2), pages 161-180, April.
    11. Nisvan Erkal & Lata Gangadharan & Boon Han Koh, 2018. "Attribution biases in Leadership: Is it effort or luck ?," Department of Economics - Working Papers Series 2040, The University of Melbourne.
    12. Karl H. Schlag & Joël J. van der Weele, 2015. "A method to elicit beliefs as most likely intervals," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 10(5), pages 456-468, September.
    13. Dominik Bauer & Irenaeus Wolff, 2018. "Biases in Beliefs: Experimental Evidence," TWI Research Paper Series 109, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    14. Victor Aguirregabiria & Erhao Xie, 2016. "Identification of Biased Beliefs in Games of Incomplete Information Using Experimental Data," Working Papers tecipa-560, University of Toronto, Department of Economics.
    15. Armenak Antinyan & Luca Corazzini & Elena D'Agostino & Filippo Pavesi, 2017. "Watch your Words: an Experimental Study on Communication and the Opportunity Cost of Delegation," Working Papers 18/2017, University of Verona, Department of Economics.
    16. Robertson, Matthew J., 2018. "Contests with Ex-Ante Target Setting," CRETA Online Discussion Paper Series 47, Centre for Research in Economic Theory and its Applications CRETA.
    17. Alvaro Sandroni & Eran Shmaya, 2013. "Eliciting beliefs by paying in chance," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 1(1), pages 33-37, May.
    18. Irenaeus Wolff & Dominik Bauer, 2018. "Elusive Beliefs: Why Uncertainty Leads to Stochastic Choice and Errors," TWI Research Paper Series 111, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    19. Patrick Schmidt, 2019. "Elicitation of ambiguous beliefs with mixing bets," Papers 1902.07447, arXiv.org.
    20. Sandro Ambuehl, 2017. "An Offer You Can't Refuse? Incentives Change How We Inform Ourselves and What We Believe," CESifo Working Paper Series 6296, CESifo Group Munich.
    21. Arthur Carvalho & Stanko Dimitrov & Kate Larson, 2018. "On proper scoring rules and cumulative prospect theory," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 6(3), pages 343-376, November.
    22. Tsakas, Elias, 2018. "Robust scoring rules," Research Memorandum 023, Maastricht University, Graduate School of Business and Economics (GSBE).
    23. Harrison, Glenn W. & Martínez-Correa, Jimmy & Swarthout, J. Todd, 2014. "Eliciting subjective probabilities with binary lotteries," Journal of Economic Behavior & Organization, Elsevier, vol. 101(C), pages 128-140.
    24. Demuynck, Thomas, 2013. "A mechanism for eliciting the mean and quantiles of a random variable," Economics Letters, Elsevier, vol. 121(1), pages 121-123.
    25. Barron, Kai, 2016. "Belief updating: Does the 'good-news, bad-news' asymmetry extend to purely financial domains?," Discussion Papers, Research Unit: Economics of Change SP II 2016-309, WZB Berlin Social Science Center.
    26. Drerup, Tilman & Enke, Benjamin & von Gaudecker, Hans-Martin, 2017. "The precision of subjective data and the explanatory power of economic models," Journal of Econometrics, Elsevier, vol. 200(2), pages 378-389.
    27. Alvaro Sandroni & Eran Shmaya, 2013. "Eliciting Beliefs by Paying in Chance," Discussion Papers 1565, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    28. Oechssler, Jörg & Sofianos, Andis, 2019. "The Binary Lottery Procedure does not induce risk neutrality in the Holt-Laury and Eckel-Grossman tasks," Working Papers 0663, University of Heidelberg, Department of Economics.

  6. Qingfeng Liu & Ryo Okui, 2013. "Heteroscedasticity‐robust C(p) model averaging," Econometrics Journal, Royal Economic Society, vol. 16(3), pages 463-472, October.

    Cited by:

    1. Yin, Anwen, 2015. "Forecasting and model averaging with structural breaks," ISU General Staff Papers 201501010800005727, Iowa State University, Department of Economics.
    2. Zhao, Shangwei & Zhou, Jianhong & Li, Hongjun, 2016. "Model averaging with high-dimensional dependent data," Economics Letters, Elsevier, vol. 148(C), pages 68-71.
    3. Shangwei Zhao & Aman Ullah & Xinyu Zhang, 2018. "A Class of Model Averaging Estimators," Working Paper series 18-11, Rimini Centre for Economic Analysis.
    4. Cong Li & Qi Li & Jeffrey Racine & DAIQIANG ZHANG, 2017. "Optimal Model Averaging Of Varying Coefficient Models," Department of Economics Working Papers 2017-01, McMaster University.
    5. Zhang, Xinyu & Ullah, Aman & Zhao, Shangwei, 2016. "On the dominance of Mallows model averaging estimator over ordinary least squares estimator," Economics Letters, Elsevier, vol. 142(C), pages 69-73.
    6. Tadao Hoshino, 2018. "Semiparametric Spatial Autoregressive Models With Endogenous Regressors: With an Application to Crime Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 160-172, January.
    7. Zhao, Shangwei & Zhang, Xinyu & Gao, Yichen, 2016. "Model averaging with averaging covariance matrix," Economics Letters, Elsevier, vol. 145(C), pages 214-217.
    8. Qingfeng Liu & Ryo Okui & Arihiro Yoshimura, 2013. "Generalized Least Squares Model Averaging," KIER Working Papers 855, Kyoto University, Institute of Economic Research.
    9. Kitagawa, Toru & Muris, Chris, 2016. "Model averaging in semiparametric estimation of treatment effects," Journal of Econometrics, Elsevier, vol. 193(1), pages 271-289.
    10. Xinyu Zhang & Dalei Yu & Guohua Zou & Hua Liang, 2016. "Optimal Model Averaging Estimation for Generalized Linear Models and Generalized Linear Mixed-Effects Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1775-1790, October.
    11. Cheng, Tzu-Chang F. & Ing, Ching-Kang & Yu, Shu-Hui, 2015. "Toward optimal model averaging in regression models with time series errors," Journal of Econometrics, Elsevier, vol. 189(2), pages 321-334.
    12. Lu, Xun & Su, Liangjun, 2015. "Jackknife model averaging for quantile regressions," Journal of Econometrics, Elsevier, vol. 188(1), pages 40-58.
    13. Zhao, Shangwei & Ullah, Aman & Zhang, Xinyu, 2018. "A class of model averaging estimators," Economics Letters, Elsevier, vol. 162(C), pages 101-106.
    14. Yan Gao & Xinyu Zhang & Shouyang Wang & Terence Tai-leung Chong & Guohua Zou, 2019. "Frequentist model averaging for threshold models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(2), pages 275-306, April.
    15. Shou-Yung Yin & Chu-An Liu & Chang-Ching Lin, 2016. "Focused Information Criterion and Model Averaging for Large Panels with a Multifactor Error Structure," IEAS Working Paper : academic research 16-A016, Institute of Economics, Academia Sinica, Taipei, Taiwan.
    16. Zhang, Xinyu & Yu, Jihai, 2018. "Spatial weights matrix selection and model averaging for spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 203(1), pages 1-18.
    17. Zhang, Xinyu, 2015. "Consistency of model averaging estimators," Economics Letters, Elsevier, vol. 130(C), pages 120-123.
    18. Aman Ullah & Xinyu Zhang, 2015. "Grouped Model Averaging for Finite Sample Size," Working Papers 201501, University of California at Riverside, Department of Economics.
    19. Liao, Jun & Zong, Xianpeng & Zhang, Xinyu & Zou, Guohua, 2019. "Model averaging based on leave-subject-out cross-validation for vector autoregressions," Journal of Econometrics, Elsevier, vol. 209(1), pages 35-60.
    20. Xie, Tian, 2017. "Heteroscedasticity-robust model screening: A useful toolkit for model averaging in big data analytics," Economics Letters, Elsevier, vol. 151(C), pages 119-122.

  7. Lee, Yoonseok & Okui, Ryo, 2012. "Hahn–Hausman test as a specification test," Journal of Econometrics, Elsevier, vol. 167(1), pages 133-139.

    Cited by:

    1. Tae-Hwan Kim & Christophe Muller, 2017. "A Robust Test of Exogeneity Based on Quantile Regressions," Working Papers halshs-01508067, HAL.
    2. Kolesár, Michal, 2018. "Minimum distance approach to inference with many instruments," Journal of Econometrics, Elsevier, vol. 204(1), pages 86-100.
    3. Tae-Hwan Kim & Christophe Muller, 2013. "A Test for Endogeneity in Conditional Quantiles," AMSE Working Papers 1342, Aix-Marseille School of Economics, France, revised Aug 2013.
    4. Firmin DOKO TCHATOKA & Jean-Marie DUFOUR, 2016. "Exogeneity Tests, Incomplete Models, Weak Identification and Non-Gaussian Distributions : Invariance and Finite-Sample Distributional Theory," Cahiers de recherche 14-2016, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    5. Byunghoon Kang, 2018. "Higher Order Approximation of IV Estimators with Invalid Instruments," Working Papers 257105320, Lancaster University Management School, Economics Department.
    6. Yoonseok Lee & Yu Zhou, 2015. "Averaged Instrumental Variables Estimators," Center for Policy Research Working Papers 180, Center for Policy Research, Maxwell School, Syracuse University.
    7. Yoonseok Lee & Mehmet Caner & Xu Han, 2015. "Adaptive Elastic Net GMM Estimation with Many Invalid Moment Conditions: Simultaneous Model and Moment Selection," Center for Policy Research Working Papers 177, Center for Policy Research, Maxwell School, Syracuse University.
    8. Guo, Zijian & Kang, Hyunseung & Cai, T. Tony & Small, Dylan S., 2018. "Testing endogeneity with high dimensional covariates," Journal of Econometrics, Elsevier, vol. 207(1), pages 175-187.
    9. Kohtaro Hitomi & Masamune Iwasawa & Yoshihiko Nishiyama, 2018. "Rate Optimal Specification Test When the Number of Instruments is Large," KIER Working Papers 986, Kyoto University, Institute of Economic Research.

  8. Okui, Ryo, 2011. "Asymptotically unbiased estimation of autocovariances and autocorrelations for panel data with incidental trends," Economics Letters, Elsevier, vol. 112(1), pages 49-52, July.

    Cited by:

    1. Ryo Okui & Takahide Yanagi, 2018. "Kernel Estimation for Panel Data with Heterogeneous Dynamics," Papers 1802.08825, arXiv.org, revised May 2019.
    2. Ryo Okui & Takahide Yanagi, 2014. "Panel Data Analysis with Heterogeneous Dynamics," KIER Working Papers 906, Kyoto University, Institute of Economic Research.
    3. Haruo Iwakura & Ryo Okui, 2014. "Asymptotic Efficiency in Factor Models and Dynamic Panel Data Models," KIER Working Papers 887, Kyoto University, Institute of Economic Research.
    4. Ryo Okui, 2017. "Misspecification in Dynamic Panel Data Models and Model-Free Inferences," The Japanese Economic Review, Japanese Economic Association, vol. 68(3), pages 283-304, September.
    5. Timothy J. Vogelsang & Jingjing Yang, 2016. "Exactly/Nearly Unbiased Estimation of Autocovariances of a Univariate Time Series With Unknown Mean," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 723-740, November.

  9. Okui, Ryo, 2011. "Instrumental variable estimation in the presence of many moment conditions," Journal of Econometrics, Elsevier, vol. 165(1), pages 70-86.

    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
    2. Cheng, Xu & Liao, Zhipeng, 2015. "Select the valid and relevant moments: An information-based LASSO for GMM with many moments," Journal of Econometrics, Elsevier, vol. 186(2), pages 443-464.
    3. Carrasco, Marine & Tchuente, Guy, 2015. "Regularized LIML for many instruments," Journal of Econometrics, Elsevier, vol. 186(2), pages 427-442.
    4. Hansen, Christian & Kozbur, Damian, 2014. "Instrumental variables estimation with many weak instruments using regularized JIVE," Journal of Econometrics, Elsevier, vol. 182(2), pages 290-308.
    5. Liu, Chu-An & Tao, Jing, 2016. "Model selection and model averaging in nonparametric instrumental variables models," MPRA Paper 69492, University Library of Munich, Germany.
    6. A. Belloni & D. Chen & V. Chernozhukov & C. Hansen, 2012. "Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain," Econometrica, Econometric Society, vol. 80(6), pages 2369-2429, November.
    7. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments," Papers 1501.03185, arXiv.org.
    8. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers CWP36/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Naoto Kunitomo & Michael McAleer & Yoshihiko Nishiyama, 2010. "Moment Restriction-based Econometric Methods: An Overview," KIER Working Papers 734, Kyoto University, Institute of Economic Research.
    10. Carrasco, Marine, 2012. "A regularization approach to the many instruments problem," Journal of Econometrics, Elsevier, vol. 170(2), pages 383-398.
    11. Byunghoon Kang, 2018. "Higher Order Approximation of IV Estimators with Invalid Instruments," Working Papers 257105320, Lancaster University Management School, Economics Department.
    12. Kuersteiner, Guido M., 2012. "Kernel-weighted GMM estimators for linear time series models," Journal of Econometrics, Elsevier, vol. 170(2), pages 399-421.
    13. Yoonseok Lee & Yu Zhou, 2015. "Averaged Instrumental Variables Estimators," Center for Policy Research Working Papers 180, Center for Policy Research, Maxwell School, Syracuse University.
    14. Denis Heng-Yan Leung & Dylan S. Small & Jing Qin & Min Zhu, 2013. "Shrinkage Empirical Likelihood Estimator in Longitudinal Analysis with Time-Dependent Covariates—Application to Modeling the Health of Filipino Children," Biometrics, The International Biometric Society, vol. 69(3), pages 624-632, September.
    15. Hujer Reinhard & Rodrigues Paulo J. M. & Wolf Katja, 2008. "Dynamic Panel Data Models with Spatial Correlation," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(5-6), pages 612-629, October.
    16. Guy Tchuente, 2016. "Estimation of social interaction models using regularization," Studies in Economics 1607, School of Economics, University of Kent.
    17. Eric Gautier & Alexandre Tsybakov, 2011. "High-Dimensional Instrumental Variables Regression and Confidence Sets," Working Papers 2011-13, Center for Research in Economics and Statistics.
    18. Kazuhiko Hayakawa, 2006. "Efficient GMM Estimation of Dynamic Panel Data Models Where Large Heterogeneity May Be Present," Hi-Stat Discussion Paper Series d05-130, Institute of Economic Research, Hitotsubashi University.
    19. Martins, Luis F. & Gabriel, Vasco J., 2014. "Linear instrumental variables model averaging estimation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 709-724.
    20. Kazuhiko Hayakawa, 2008. "On the Effect of Nonstationary Initial Conditions in Dynamic Panel Data Models," Hi-Stat Discussion Paper Series d07-245, Institute of Economic Research, Hitotsubashi University.
    21. Xu Cheng & Zhipeng Liao, 2012. "Select the Valid and Relevant Moments: A One-Step Procedure for GMM with Many Moments," PIER Working Paper Archive 12-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

  10. Guido Kuersteiner & Ryo Okui, 2010. "Constructing Optimal Instruments by First-Stage Prediction Averaging," Econometrica, Econometric Society, vol. 78(2), pages 697-718, March.

    Cited by:

    1. Michel Berthélemy & Petyo Bonev & Damien Dussaux & Magnus Söderberg, 2018. "Methods for strengthening a weak instrument in the case of a persistent treatment," Post-Print hal-01829558, HAL.
    2. Cheng, Xu & Liao, Zhipeng, 2015. "Select the valid and relevant moments: An information-based LASSO for GMM with many moments," Journal of Econometrics, Elsevier, vol. 186(2), pages 443-464.
    3. Liu, Chu-An & Tao, Jing, 2016. "Model selection and model averaging in nonparametric instrumental variables models," MPRA Paper 69492, University Library of Munich, Germany.
    4. Zhang, Xinyu & Ullah, Aman & Zhao, Shangwei, 2016. "On the dominance of Mallows model averaging estimator over ordinary least squares estimator," Economics Letters, Elsevier, vol. 142(C), pages 69-73.
    5. Jeffrey S. Racine & Qi Li & Li Zheng, 2018. "Optimal Model Averaging of Mixed-Data Kernel-Weighted Spline Regressions," Department of Economics Working Papers 2018-10, McMaster University.
    6. Aman Ullah & Huansha Wang, 2013. "Parametric and Nonparametric Frequentist Model Selection and Model Averaging," Econometrics, MDPI, Open Access Journal, vol. 1(2), pages 1-23, September.
    7. Caner, Mehmet & Fan, Qingliang, 2015. "Hybrid generalized empirical likelihood estimators: Instrument selection with adaptive lasso," Journal of Econometrics, Elsevier, vol. 187(1), pages 256-274.
    8. 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.
    9. Zhang, Xinyu & Wan, Alan T.K. & Zou, Guohua, 2013. "Model averaging by jackknife criterion in models with dependent data," Journal of Econometrics, Elsevier, vol. 174(2), pages 82-94.
    10. Byunghoon Kang, 2018. "Higher Order Approximation of IV Estimators with Invalid Instruments," Working Papers 257105320, Lancaster University Management School, Economics Department.
    11. Wang, Wenjie & Kaffo, Maximilien, 2016. "Bootstrap inference for instrumental variable models with many weak instruments," Journal of Econometrics, Elsevier, vol. 192(1), pages 231-268.
    12. Lu, Xun & Su, Liangjun, 2015. "Jackknife model averaging for quantile regressions," Journal of Econometrics, Elsevier, vol. 188(1), pages 40-58.
    13. Kuersteiner, Guido M., 2012. "Kernel-weighted GMM estimators for linear time series models," Journal of Econometrics, Elsevier, vol. 170(2), pages 399-421.
    14. Yoonseok Lee & Yu Zhou, 2015. "Averaged Instrumental Variables Estimators," Center for Policy Research Working Papers 180, Center for Policy Research, Maxwell School, Syracuse University.
    15. DiTraglia, Francis J., 2016. "Using invalid instruments on purpose: Focused moment selection and averaging for GMM," Journal of Econometrics, Elsevier, vol. 195(2), pages 187-208.
    16. Aman Ullah & Xinyu Zhang, 2015. "Grouped Model Averaging for Finite Sample Size," Working Papers 201501, University of California at Riverside, Department of Economics.
    17. Moral-Benito, Enrique, 2010. "Model averaging in economics," MPRA Paper 26047, University Library of Munich, Germany.
    18. Xiaohong Chen & David Jacho-Chávez & Oliver Linton, 2012. "Averaging of moment condition estimators," CeMMAP working papers CWP26/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Seojeong Lee & Youngki Shin, 2018. "Optimal Estimation with Complete Subsets of Instruments," Papers 1811.08083, arXiv.org, revised Dec 2018.
    20. Francis DiTraglia, 2011. "Using Invalid Instruments on Purpose: Focused Moment Selection and Averaging for GMM, Second Version," PIER Working Paper Archive 15-027, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 10 Aug 2015.
    21. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.
    22. Martins, Luis F. & Gabriel, Vasco J., 2014. "Linear instrumental variables model averaging estimation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 709-724.
    23. Xu Cheng & Zhipeng Liao, 2012. "Select the Valid and Relevant Moments: A One-Step Procedure for GMM with Many Moments," PIER Working Paper Archive 12-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

  11. Okui, Ryo, 2010. "Asymptotically Unbiased Estimation Of Autocovariances And Autocorrelations With Long Panel Data," Econometric Theory, Cambridge University Press, vol. 26(05), pages 1263-1304, October.

    Cited by:

    1. Okui, Ryo, 2009. "Testing serial correlation in fixed effects regression models based on asymptotically unbiased autocorrelation estimators," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2897-2909.
    2. Lee, Yoon-Jin & Okui, Ryo & Shintani, Mototsugu, 2018. "Asymptotic inference for dynamic panel estimators of infinite order autoregressive processes," Journal of Econometrics, Elsevier, vol. 204(2), pages 147-158.
    3. Yang, Jingjing & Vogelsang, Timothy J., 2018. "Finite sample performance of a long run variance estimator based on exactly (almost) unbiased autocovariance estimators," Economics Letters, Elsevier, vol. 165(C), pages 21-27.
    4. Ryo Okui & Takahide Yanagi, 2014. "Panel Data Analysis with Heterogeneous Dynamics," KIER Working Papers 906, Kyoto University, Institute of Economic Research.
    5. Haruo Iwakura & Ryo Okui, 2014. "Asymptotic Efficiency in Factor Models and Dynamic Panel Data Models," KIER Working Papers 887, Kyoto University, Institute of Economic Research.
    6. Okui, Ryo, 2011. "Asymptotically unbiased estimation of autocovariances and autocorrelations for panel data with incidental trends," Economics Letters, Elsevier, vol. 112(1), pages 49-52, July.
    7. Ryo Okui, 2017. "Misspecification in Dynamic Panel Data Models and Model-Free Inferences," The Japanese Economic Review, Japanese Economic Association, vol. 68(3), pages 283-304, September.
    8. Timothy J. Vogelsang & Jingjing Yang, 2016. "Exactly/Nearly Unbiased Estimation of Autocovariances of a Univariate Time Series With Unknown Mean," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 723-740, November.

  12. Okui, Ryo, 2009. "Testing serial correlation in fixed effects regression models based on asymptotically unbiased autocorrelation estimators," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2897-2909.

    Cited by:

    1. Su, Liangjun & Lu, Xun, 2013. "Nonparametric dynamic panel data models: Kernel estimation and specification testing," Journal of Econometrics, Elsevier, vol. 176(2), pages 112-133.
    2. Jochmans, K., 2018. "A Portmanteau Test for Correlation in Short Panels," Cambridge Working Papers in Economics 1886, Faculty of Economics, University of Cambridge.
    3. Du, Zaichao, 2014. "Testing for serial independence of panel errors," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 248-261.

  13. Okui, Ryo, 2009. "The optimal choice of moments in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 151(1), pages 1-16, July.

    Cited by:

    1. von Gaessler, Anne Edle & Ziesemer, Thomas, 2016. "Optimal education in times of ageing: The dependency ratio in the Uzawa–Lucas growth model," The Journal of the Economics of Ageing, Elsevier, vol. 7(C), pages 125-142.
    2. Salima Bouayad-Agha & Nadine Turpin & Lionel Védrine, 2010. "Fostering the potential endogenous development of European regions: a spatial dynamic panel data analysis of the Cohesion Policy on regional convergence over the period 1980-2005," TEPP Working Paper 2010-17, TEPP.
    3. Augustin Kwasi Fosu & Yoseph Yilma Getachew & Thomas Ziesemer, 2012. "Optimal public investment, growth and consumption: evidence from African countries," Global Development Institute Working Paper Series 16412, GDI, The University of Manchester.
    4. Ziesemer, T., 2014. "Country Terms of Trade 1960-2012: Trends, unit roots, over-differencing, endogeneity, time dummies, and heterogeneity," MERIT Working Papers 027, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    5. Eva Barteková & Thomas H. W Ziesemer, 2019. "The impact of electricity prices on foreign direct investment: evidence from the European Union," Applied Economics, Taylor & Francis Journals, vol. 51(11), pages 1183-1198, March.
    6. Meijer, Erik & Spierdijk, Laura & Wansbeek, Tom, 2017. "Consistent estimation of linear panel data models with measurement error," Journal of Econometrics, Elsevier, vol. 200(2), pages 169-180.
    7. Magnac, Thierry & Pistolesi, Nicolas & Roux, Sébastien, 2013. "Post schooling human capital investments and the life cycle variance of earnings," IDEI Working Papers 765, Institut d'Économie Industrielle (IDEI), Toulouse.
    8. Miyazaki, Tomomi, 2013. "Fiscal Policy and Regional Business Cycle Fluctuations in Japan," Discussion Paper Series 583, Institute of Economic Research, Hitotsubashi University.
    9. Jan Kiviet & Milan Pleus & Rutger Poldermans, 2017. "Accuracy and Efficiency of Various GMM Inference Techniques in Dynamic Micro Panel Data Models," Econometrics, MDPI, Open Access Journal, vol. 5(1), pages 1-54, March.
    10. Manuel Arellano, 2003. "Modelling Optimal Instrumental Variables for Dynamic Panel Data Models," Working Papers wp2003_0310, CEMFI.
    11. Lee, Nayoung & Moon, Hyungsik Roger & Weidner, Martin, 2012. "Analysis of interactive fixed effects dynamic linear panel regression with measurement error," Economics Letters, Elsevier, vol. 117(1), pages 239-242.
    12. Ziesemer, Thomas, 2012. "The impact of development aid on education and health: Survey and new evidence from dynamic models," MERIT Working Papers 057, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    13. Bohdan Yu. Kyshakevych & Anatoliy K. Prykarpatsky & Denis Blackmore & Ivan P. Tverdokhlib, 2010. "Statistically Optimal Strategy Analysis of a Competing Portfolio Market with a Polyvariant Profit Function," Papers 1005.2661, arXiv.org.
    14. Makram El-Shagi & Steven Yamarik, 2018. "State-Level Capital and Investment: Refinements and Update," CFDS Discussion Paper Series 2018/1, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
    15. Hujer Reinhard & Rodrigues Paulo J. M. & Wolf Katja, 2008. "Dynamic Panel Data Models with Spatial Correlation," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(5-6), pages 612-629, October.
    16. Mariangela Bonasia, 2012. "Twenty years of internal migration in Italy. Answers from some economic and non-economic determinants," Discussion Papers 6_2012, CRISEI, University of Naples "Parthenope", Italy.
    17. Tomomi Miyazaki, 2016. "Interactions between Regional Public and Private Investment: Evidence from Japanese Prefectures," Discussion Papers 1608, Graduate School of Economics, Kobe University.
    18. Ivan Savin & Peter Winker, 2012. "Heuristic Optimization Methods for Dynamic Panel Data Model Selection: Application on the Russian Innovative Performance," Computational Economics, Springer;Society for Computational Economics, vol. 39(4), pages 337-363, April.
    19. Jan F. Kiviet & Milan Pleus & Rutger Poldermans, 2014. "Accuracy and efficiency of various GMM inference techniques in dynamic micro panel data models," UvA-Econometrics Working Papers 14-09, Universiteit van Amsterdam, Dept. of Econometrics.
    20. Tomomi Miyazaki, 2018. "Interactions between regional public and private investment: evidence from Japanese prefectures," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 60(1), pages 195-211, January.
    21. Tomomi Miyazaki & Haruo Kondoh, 2016. "Local Public Investment and Regional Business Cycle Fluctuations in Japan," Discussion Papers 1624, Graduate School of Economics, Kobe University.
    22. Kazuhiko Hayakawa, 2008. "On the Effect of Nonstationary Initial Conditions in Dynamic Panel Data Models," Hi-Stat Discussion Paper Series d07-245, Institute of Economic Research, Hitotsubashi University.

  14. Okui, Ryo, 2008. "Panel AR(1) estimators under misspecification," Economics Letters, Elsevier, vol. 101(3), pages 210-213, December.

    Cited by:

    1. Ryo Okui & Takahide Yanagi, 2018. "Kernel Estimation for Panel Data with Heterogeneous Dynamics," Papers 1802.08825, arXiv.org, revised May 2019.
    2. Lee, Yoonseok, 2012. "Bias in dynamic panel models under time series misspecification," Journal of Econometrics, Elsevier, vol. 169(1), pages 54-60.
    3. Ryo Okui & Takahide Yanagi, 2014. "Panel Data Analysis with Heterogeneous Dynamics," KIER Working Papers 906, Kyoto University, Institute of Economic Research.
    4. Ryo Okui, 2017. "Misspecification in Dynamic Panel Data Models and Model-Free Inferences," The Japanese Economic Review, Japanese Economic Association, vol. 68(3), pages 283-304, September.

  15. Hitomi, Kohtaro & Nishiyama, Yoshihiko & Okui, Ryo, 2008. "A Puzzling Phenomenon In Semiparametric Estimation Problems With Infinite-Dimensional Nuisance Parameters," Econometric Theory, Cambridge University Press, vol. 24(06), pages 1717-1728, December.

    Cited by:

    1. Bryan S. Graham & Cristine Campos de Xavier Pinto, 2018. "Semiparametrically efficient estimation of the average linear regression function," Papers 1810.12511, arXiv.org.
    2. Otávio Bartalotti, 2013. "GMM Efficiency and IPW Estimation for Nonsmooth Functions," Working Papers 1301, Tulane University, Department of Economics.
    3. Han, Chirok & Kim, Beomsoo, 2011. "A GMM interpretation of the paradox in the inverse probability weighting estimation of the average treatment effect on the treated," Economics Letters, Elsevier, vol. 110(2), pages 163-165, February.
    4. Prokhorov, Artem & Schmidt, Peter, 2009. "GMM redundancy results for general missing data problems," Journal of Econometrics, Elsevier, vol. 151(1), pages 47-55, July.

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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 16 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 (10) 2009-12-11 2013-04-06 2013-10-18 2014-02-21 2014-12-24 2016-02-23 2018-01-22 2018-01-29 2018-03-26 2019-01-14. Author is listed
  2. NEP-ETS: Econometric Time Series (5) 2013-10-18 2014-12-24 2018-01-29 2018-03-26 2018-04-16. Author is listed
  3. NEP-EXP: Experimental Economics (4) 2016-02-23 2018-01-22 2018-03-12 2019-01-14
  4. NEP-NET: Network Economics (2) 2015-05-22 2015-11-15
  5. NEP-BAN: Banking (1) 2015-05-22
  6. NEP-CFN: Corporate Finance (1) 2015-11-15
  7. NEP-COM: Industrial Competition (1) 2015-11-15
  8. NEP-DEV: Development (1) 2004-04-11
  9. NEP-EDU: Education (1) 2004-04-11
  10. NEP-ORE: Operations Research (1) 2013-04-06

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