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t-Statistic Based Correlation and Heterogeneity Robust Inference

Citations

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Cited by:

  1. Gary Charness & Ramón Cobo-Reyes & Erik Eyster & Gabriel Katz & Ángela Sánchez & Matthias Sutter, 2020. "Improving healthy eating in children: Experimental evidence," ECONtribute Discussion Papers Series 047, University of Bonn and University of Cologne, Germany.
  2. Dagaev, Dmitry & Stoyan, Egor, 2020. "Parimutuel betting on the eSports duels: Evidence of the reverse favourite-longshot bias," Journal of Economic Psychology, Elsevier, vol. 81(C).
  3. Antonio Gargano & Davide Pettenuzzo & Allan Timmermann, 2019. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," Management Science, INFORMS, vol. 65(2), pages 508-540, February.
  4. A. Colin Cameron & Douglas L. Miller, 2010. "Robust Inference with Clustered Data," Working Papers 318, University of California, Davis, Department of Economics.
  5. Herwartz Helmut & Roestel Jan, 2018. "Local/import – and foreign currency prices: inflation, uncertainty and pass through endogeneity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(3), pages 1-17, June.
  6. Jungbin Hwang, 2017. "Simple and Trustworthy Cluster-Robust GMM Inference," Working papers 2017-19, University of Connecticut, Department of Economics, revised Aug 2020.
  7. Kaplan, David M., 2015. "Improved quantile inference via fixed-smoothing asymptotics and Edgeworth expansion," Journal of Econometrics, Elsevier, vol. 185(1), pages 20-32.
  8. Falck, Oliver & Heimisch-Roecker, Alexandra & Wiederhold, Simon, 2021. "Returns to ICT skills," Research Policy, Elsevier, vol. 50(7).
  9. Hammer, Jeffrey & Spears, Dean, 2013. "Village sanitation and children's human capital : evidence from a randomized experiment by the Maharashtra government," Policy Research Working Paper Series 6580, The World Bank.
  10. Wang, Wenjie, 2021. "Wild Bootstrap for Instrumental Variables Regression with Weak Instruments and Few Clusters," MPRA Paper 106227, University Library of Munich, Germany.
  11. Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Ernst Schaumburg, 2020. "Characteristic-Sorted Portfolios: Estimation and Inference," The Review of Economics and Statistics, MIT Press, vol. 102(3), pages 531-551, July.
  12. Zhang, Xianyang, 2016. "Fixed-smoothing asymptotics in the generalized empirical likelihood estimation framework," Journal of Econometrics, Elsevier, vol. 193(1), pages 123-146.
  13. Ivan A. Canay & Andres Santos & Azeem M. Shaikh, 2018. "The wild bootstrap with a "small" number of "large" clusters," CeMMAP working papers CWP27/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  14. Filip Stanek, 2021. "Optimal Out-of-Sample Forecast Evaluation under Stationarity," CERGE-EI Working Papers wp712, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
  15. Andreas Hagemann, 2019. "Permutation inference with a finite number of heterogeneous clusters," Papers 1907.01049, arXiv.org.
  16. Hansen, Bruce E. & Lee, Seojeong, 2019. "Asymptotic theory for clustered samples," Journal of Econometrics, Elsevier, vol. 210(2), pages 268-290.
  17. Nagler, Thomas & Krüger, Daniel & Min, Aleksey, 2022. "Stationary vine copula models for multivariate time series," Journal of Econometrics, Elsevier, vol. 227(2), pages 305-324.
  18. Oriana Bandiera & Iwan Barankay & Imran Rasul, 2011. "Field Experiments with Firms," Journal of Economic Perspectives, American Economic Association, vol. 25(3), pages 63-82, Summer.
  19. Zhang, Xianyang & Shao, Xiaofeng, 2013. "On a general class of long run variance estimators," Economics Letters, Elsevier, vol. 120(3), pages 437-441.
  20. repec:pri:cheawb:tscjeff2013%20paper is not listed on IDEAS
  21. Harold E. Cuffe & Glen R. Waddell & Wesley Bignell, 2017. "Can School Sports Reduce Racial Gaps In Truancy And Achievement?," Economic Inquiry, Western Economic Association International, vol. 55(4), pages 1966-1985, October.
  22. Matthew D. Webb & James MacKinnon & Morten Nielsen, 2021. "Cluster–robust inference: A guide to empirical practice," Economics Virtual Symposium 2021 6, Stata Users Group.
  23. Boodoo, Muhammad Umar, 2016. "Does mandatory CSR reporting regulation lead to improved Corporate Social Performance? Evidence from India," LSE Research Online Documents on Economics 67559, London School of Economics and Political Science, LSE Library.
  24. Preinerstorfer, David & Pötscher, Benedikt M., 2016. "On Size And Power Of Heteroskedasticity And Autocorrelation Robust Tests," Econometric Theory, Cambridge University Press, vol. 32(2), pages 261-358, April.
  25. Pesaran, M. Hashem & Tosetti, Elisa, 2011. "Large panels with common factors and spatial correlation," Journal of Econometrics, Elsevier, vol. 161(2), pages 182-202, April.
  26. Hwang, Jungbin, 2021. "Simple and trustworthy cluster-robust GMM inference," Journal of Econometrics, Elsevier, vol. 222(2), pages 993-1023.
  27. Kim, Min Seong & Sun, Yixiao, 2013. "Heteroskedasticity and spatiotemporal dependence robust inference for linear panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 177(1), pages 85-108.
  28. Alberto Abadie & Susan Athey & Guido Imbens & Jeffrey Wooldridge, 2017. "When Should You Adjust Standard Errors for Clustering?," Papers 1710.02926, arXiv.org, revised May 2022.
  29. Davide Viviano, 2020. "Policy design in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised Feb 2022.
  30. Chen, Zhimin & Ibragimov, Rustam, 2019. "One country, two systems? The heavy-tailedness of Chinese A- and H- share markets," Emerging Markets Review, Elsevier, vol. 38(C), pages 115-141.
  31. Sun, Yu & Yan, Karen X., 2019. "Inference on Difference-in-Differences average treatment effects: A fixed-b approach," Journal of Econometrics, Elsevier, vol. 211(2), pages 560-588.
  32. Rustam Ibragimov & Marat Ibragimov & Jovlon Karimov & Galiya Yuldasheva, 2012. "Robust Analysis of Income Inequality Dynamics in Russia: t-Statistic Based Approaches," wiiw Balkan Observatory Working Papers 105, The Vienna Institute for International Economic Studies, wiiw.
  33. Peter Van Tassel, 2017. "Global Variance Term Premia and Intermediary Risk Appetite," 2017 Meeting Papers 149, Society for Economic Dynamics.
  34. Tobias Pfaff & Johannes Hirata, 2013. "Testing the Easterlin Hypothesis with Panel Data: The Dynamic Relationship between Life Satisfaction and Economic Growth in Germany and the UK," SOEPpapers on Multidisciplinary Panel Data Research 554, DIW Berlin, The German Socio-Economic Panel (SOEP).
  35. Hagemann, Andreas, 2019. "Placebo inference on treatment effects when the number of clusters is small," Journal of Econometrics, Elsevier, vol. 213(1), pages 190-209.
  36. Matthew D. Webb, 2014. "Reworking Wild Bootstrap Based Inference For Clustered Errors," Working Paper 1315, Economics Department, Queen's University.
  37. Bohl Martin T., 2016. "Treiben Indexfonds Agrarrohstoffpreise? Nein!," Perspektiven der Wirtschaftspolitik, De Gruyter, vol. 17(2), pages 155-171, July.
  38. Alan S. Blinder & Mark W. Watson, 2016. "Presidents and the US Economy: An Econometric Exploration," American Economic Review, American Economic Association, vol. 106(4), pages 1015-1045, April.
  39. Sun, Yixiao & Yang, Jingjing, 2020. "Testing-optimal kernel choice in HAR inference," Journal of Econometrics, Elsevier, vol. 219(1), pages 123-136.
  40. Victor Chernozhukov & Kaspar Wuthrich & Yinchu Zhu, 2018. "A $t$-test for synthetic controls," Papers 1812.10820, arXiv.org, revised Jul 2022.
  41. Anna Gloria Billé & Samantha Leorato, 2017. "Quasi-ML estimation, Marginal Effects and Asymptotics for Spatial Autoregressive Nonlinear Models," BEMPS - Bozen Economics & Management Paper Series BEMPS44, Faculty of Economics and Management at the Free University of Bozen.
  42. Peter Van Tassel & Erik Vogt, 2016. "Global variance term premia and intermediary risk appetite," Staff Reports 789, Federal Reserve Bank of New York.
  43. repec:udt:wpecon:2017_2 is not listed on IDEAS
  44. Anatolyev Stanislav, 2019. "Volatility filtering in estimation of kurtosis (and variance)," Dependence Modeling, De Gruyter, vol. 7(1), pages 1-23, February.
  45. Rho, Seunghwa & Vogelsang, Timothy J., 2021. "Inference in time series models using smoothed-clustered standard errors," Journal of Econometrics, Elsevier, vol. 224(1), pages 113-133.
  46. Sun, Yixiao, 2013. "Fixed-smoothing Asymptotics in a Two-step GMM Framework," University of California at San Diego, Economics Working Paper Series qt64x4z265, Department of Economics, UC San Diego.
  47. James G. MacKinnon & Matthew D. Webb, 2017. "Wild Bootstrap Inference for Wildly Different Cluster Sizes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 233-254, March.
  48. Petar Stankov, 2018. "The Political Economy of Populism: An Empirical Investigation," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 60(2), pages 230-253, June.
  49. Hwang, Jungbin & Sun, Yixiao, 2018. "Should we go one step further? An accurate comparison of one-step and two-step procedures in a generalized method of moments framework," Journal of Econometrics, Elsevier, vol. 207(2), pages 381-405.
  50. Pfaff, Tobias & Hirata, Johannes, 2013. "Testing the Easterlin hypothesis with panel data: The dynamic relationship between life satisfaction and economic growth in Germany and in the UK," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79965, Verein für Socialpolitik / German Economic Association.
  51. Benedikt M. Potscher & David Preinerstorfer, 2021. "Valid Heteroskedasticity Robust Testing," Papers 2104.12597, arXiv.org.
  52. Vogelsang, Timothy J., 2012. "Heteroskedasticity, autocorrelation, and spatial correlation robust inference in linear panel models with fixed-effects," Journal of Econometrics, Elsevier, vol. 166(2), pages 303-319.
  53. Zhang, Jingsi & Jiang, Wenxin & Shao, Xiaofeng, 2013. "Bayesian model selection based on parameter estimates from subsamples," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 979-986.
  54. Bobonis, Gustavo J. & Stabile, Mark & Tovar, Leonardo, 2020. "Military training exercises, pollution, and their consequences for health," Journal of Health Economics, Elsevier, vol. 73(C).
  55. Pfaff, Tobias & Hirata, Johannes, 2013. "Testing the Easterlin hypothesis with panel data: The dynamic relationship between life satisfaction and economic growth in Germany and in the UK," CIW Discussion Papers 4/2013, University of Münster, Center for Interdisciplinary Economics (CIW).
  56. Valentin Verdier, 2020. "Estimation and Inference for Linear Models with Two-Way Fixed Effects and Sparsely Matched Data," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 1-16, March.
  57. Dwight R. Sanders & Scott H. Irwin, 2017. "Bubbles, Froth and Facts: Another Look at the Masters Hypothesis in Commodity Futures Markets," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(2), pages 345-365, June.
  58. A. Colin Cameron & Douglas L. Miller, 2010. "Robust Inference with Clustered Data," Working Papers 107, University of California, Davis, Department of Economics.
  59. Irwin, Scott H. & Sanders, Dwight R., 2012. "Testing the Masters Hypothesis in commodity futures markets," Energy Economics, Elsevier, vol. 34(1), pages 256-269.
  60. Skrobotov, Anton, 2022. "On robust testing for trend," Economics Letters, Elsevier, vol. 212(C).
  61. Brown, Donald & Ibragimov, Rustam, 2019. "Sign tests for dependent observations," Econometrics and Statistics, Elsevier, vol. 10(C), pages 1-8.
  62. Walter Distaso & Rustam Ibragimov & Alexander Semenov & Anton Skrobotov, 2020. "COVID-19: Tail Risk and Predictive Regressions," Papers 2009.02486, arXiv.org, revised Oct 2021.
  63. Huang Zibin & Ibragimov Rustam, 2022. "Equity returns and sentiment," Dependence Modeling, De Gruyter, vol. 10(1), pages 159-176, January.
  64. Victor Chernozhukov & Kaspar Wüthrich & Yinchu Zhu, 2019. "Inference on average treatment effects in aggregate panel data settings," CeMMAP working papers CWP32/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  65. Hartmann, Matthias & Roestel, Jan, 2013. "Inflation, output and uncertainty in the era of inflation targeting – A multi-economy view on causal linkages," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 98-112.
  66. Yong Cai & Ivan A. Canay & Deborah Kim & Azeem M. Shaikh, 2021. "On the implementation of Approximate Randomization Tests in Linear Models with a Small Number of Clusters," Papers 2102.09058, arXiv.org, revised Mar 2022.
  67. Andreas Hagemann, 2020. "Inference with a single treated cluster," Papers 2010.04076, arXiv.org.
  68. Pakel, Cavit, 2019. "Bias reduction in nonlinear and dynamic panels in the presence of cross-section dependence," Journal of Econometrics, Elsevier, vol. 213(2), pages 459-492.
  69. Bester, C. Alan & Conley, Timothy G. & Hansen, Christian B., 2011. "Inference with dependent data using cluster covariance estimators," Journal of Econometrics, Elsevier, vol. 165(2), pages 137-151.
  70. Spears, Dean, 2014. "Decision costs and price sensitivity: Field experimental evidence from India," Journal of Economic Behavior & Organization, Elsevier, vol. 97(C), pages 169-184.
  71. Dmitry Arkhangelsky & Vasily Korovkin, 2020. "On Policy Evaluation with Aggregate Time-Series Shocks," CERGE-EI Working Papers wp657, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
  72. Timmermann, Allan & Zhu, Yinchu, 2019. "Comparing Forecasting Performance with Panel Data," CEPR Discussion Papers 13746, C.E.P.R. Discussion Papers.
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