IDEAS home Printed from https://ideas.repec.org/r/bes/jnlasa/v96y2001mdecemberp1387-1396.html
   My bibliography  Save this item

A Note on the Efficiency of Sandwich Covariance Matrix Estimation

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Zhang, Yan-Qing & Tian, Guo-Liang & Tang, Nian-Sheng, 2016. "Latent variable selection in structural equation models," Journal of Multivariate Analysis, Elsevier, vol. 152(C), pages 190-205.
  2. Walter Krämer, 2020. "Interview mit Göran Kauermann," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 14(3), pages 305-312, December.
  3. Masahiko Gosho & Hisashi Noma & Kazushi Maruo, 2021. "Practical Review and Comparison of Modified Covariance Estimators for Linear Mixed Models in Small‐sample Longitudinal Studies with Missing Data," International Statistical Review, International Statistical Institute, vol. 89(3), pages 550-572, December.
  4. Chronopoulos, Ilias & Kapetanios, George & Petrova, Katerina, 2021. "Kernel-based Volatility Generalised Least Squares," Econometrics and Statistics, Elsevier, vol. 20(C), pages 2-11.
  5. Blackburn, McKinley L., 2022. "Testing for coefficient differences across nested linear regression specifications," Econometrics and Statistics, Elsevier, vol. 23(C), pages 1-18.
  6. Paniagua, Victoria, 2022. "When clients vote for brokers: How elections improve public goods provision in urban slums," World Development, Elsevier, vol. 158(C).
  7. Weidner, Martin & Zylkin, Thomas, 2021. "Bias and consistency in three-way gravity models," Journal of International Economics, Elsevier, vol. 132(C).
  8. Sara Sauer & Bethany Hedt‐Gauthier & Claudia Rivera‐Rodriguez & Sebastien Haneuse, 2022. "Small‐sample inference for cluster‐based outcome‐dependent sampling schemes in resource‐limited settings: Investigating low birthweight in Rwanda," Biometrics, The International Biometric Society, vol. 78(2), pages 701-715, June.
  9. Chen‐Ti Chen & John M. Crespi & William Hahn & Lee L. Schulz & Fawzi Taha, 2020. "Long‐run impacts of trade shocks and export competitiveness: Evidence from the U.S. BSE event," Agricultural Economics, International Association of Agricultural Economists, vol. 51(6), pages 941-958, November.
  10. Godfrey, L.G., 2006. "Tests for regression models with heteroskedasticity of unknown form," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2715-2733, June.
  11. Parsons, Nick R. & Costa, Matthew L. & Achten, Juul & Stallard, Nigel, 2009. "Repeated measures proportional odds logistic regression analysis of ordinal score data in the statistical software package R," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 632-641, January.
  12. Romano, Joseph P. & Wolf, Michael, 2017. "Resurrecting weighted least squares," Journal of Econometrics, Elsevier, vol. 197(1), pages 1-19.
  13. Zhang, Qiang & Ip, Edward H. & Pan, Junhao & Plemmons, Robert, 2017. "Individual-specific, sparse inverse covariance estimation in generalized estimating equations," Statistics & Probability Letters, Elsevier, vol. 122(C), pages 96-103.
  14. Djogbenou, Antoine A. & MacKinnon, James G. & Nielsen, Morten Ørregaard, 2019. "Asymptotic theory and wild bootstrap inference with clustered errors," Journal of Econometrics, Elsevier, vol. 212(2), pages 393-412.
  15. Westgate, Philip M., 2013. "A bias-corrected covariance estimator for improved inference when using an unstructured correlation with quadratic inference functions," Statistics & Probability Letters, Elsevier, vol. 83(6), pages 1553-1558.
  16. Carrillo, Paul E. & Onofa, Mercedes & Ponce, Juan, 2010. "Information Technology and Student Achievement: Evidence from a Randomized Experiment in Ecuador," IDB Publications (Working Papers) 3094, Inter-American Development Bank.
  17. Glass, Anthony J. & Kenjegalieva, Karligash & Sickles, Robin C., 2016. "A spatial autoregressive stochastic frontier model for panel data with asymmetric efficiency spillovers," Journal of Econometrics, Elsevier, vol. 190(2), pages 289-300.
  18. Nauro F. Campos & Dean Jolliffe, 2002. "After, Before and During: Returns to Education in the Hungarian Transition," William Davidson Institute Working Papers Series 475, William Davidson Institute at the University of Michigan.
  19. Boris Branisa & Maria Ziegler, 2010. "Reexamining the link between gender and corruption: The role of social institutions," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 24, Courant Research Centre PEG.
  20. Di Shu & Jessica G. Young & Sengwee Toh & Rui Wang, 2021. "Variance estimation in inverse probability weighted Cox models," Biometrics, The International Biometric Society, vol. 77(3), pages 1101-1117, September.
  21. Cheng, Guang & Yu, Zhuqing & Huang, Jianhua Z., 2013. "The cluster bootstrap consistency in generalized estimating equations," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 33-47.
  22. Jiming Jiang & Mahmoud Torabi, 2022. "Goodness-of-fit test with a robustness feature," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 76-100, March.
  23. Maximiliano Lizana & Juan-Antonio Carrasco & Alejandro Tudela, 2020. "Studying the relationship between activity participation, social networks, expenditures and travel behavior on leisure activities," Transportation, Springer, vol. 47(4), pages 1765-1786, August.
  24. A. Colin Cameron & Douglas L. Miller, 2010. "Robust Inference with Clustered Data," Working Papers 107, University of California, Davis, Department of Economics.
  25. Germán Aneiros-Pérez & Philippe Vieu, 2013. "Testing linearity in semi-parametric functional data analysis," Computational Statistics, Springer, vol. 28(2), pages 413-434, April.
  26. Wei Wang & Shou‐En Lu & Jerry Q. Cheng & Minge Xie & John B. Kostis, 2022. "Multivariate survival analysis in big data: A divide‐and‐combine approach," Biometrics, The International Biometric Society, vol. 78(3), pages 852-866, September.
  27. Brice Ozenne & Patrick M. Fisher & Esben Budtz‐J⊘rgensen, 2020. "Small sample corrections for Wald tests in latent variable models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(4), pages 841-861, August.
  28. Fan, Chunpeng & Zhang, Donghui, 2014. "Wald-type rank tests: A GEE approach," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 1-16.
  29. Dale W. R. Rosenthal, 2012. "Modeling Trade Direction," Journal of Financial Econometrics, Oxford University Press, vol. 10(2), pages 390-415, 2012 04.
  30. Dateng Li & Jing Cao & Song Zhang, 2020. "Power analysis for cluster randomized trials with multiple binary co‐primary endpoints," Biometrics, The International Biometric Society, vol. 76(4), pages 1064-1074, December.
  31. Signe M Jensen & Hanne Hauger & Christian Ritz, 2018. "Mediation analysis for logistic regression with interactions: Application of a surrogate marker in ophthalmology," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-7, February.
  32. Hartigan, Luke, 2018. "Alternative HAC covariance matrix estimators with improved finite sample properties," Computational Statistics & Data Analysis, Elsevier, vol. 119(C), pages 55-73.
  33. Hammill, Bradley G. & Preisser, John S., 2006. "A SAS/IML software program for GEE and regression diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1197-1212, November.
  34. Rachel MacKay Altman & Andrew Henrey, 2018. "Practical considerations when analyzing discrete survival times using the grouped relative risk model," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(3), pages 532-547, July.
  35. Howlett, P.G. & Torokhti, A. & Pearce, C.E.M., 2007. "Optimal multilinear estimation of a random vector under constraints of causality and limited memory," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 869-878, October.
  36. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
  37. Lam, Clifford & Fan, Jianqing, 2008. "Profile-kernel likelihood inference with diverging number of parameters," LSE Research Online Documents on Economics 31548, London School of Economics and Political Science, LSE Library.
  38. Dale Poirier, 2008. "Bayesian Interpretations of Heteroskedastic Consistent Covariance Estimators Using the Informed Bayesian Bootstrap," Working Papers 080905, University of California-Irvine, Department of Economics.
  39. Fried, Roland & Kuhls, Silvia & Molina, Isabel, 2006. "Analyzing Associations in Multivariate Binary Time Series," Technical Reports 2006,18, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  40. Antoine A. Djogbenou & James G. MacKinnon & Morten Ø. Nielsen, 2017. "Validity Of Wild Bootstrap Inference With Clustered Errors," Working Paper 1383, Economics Department, Queen's University.
  41. Manor, Orly & Zucker, D.M.David M., 2004. "Small sample inference for the fixed effects in the mixed linear model," Computational Statistics & Data Analysis, Elsevier, vol. 46(4), pages 801-817, July.
  42. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.