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Citations for "Bootstrap Methods for Median Regression Models"

by Joel L. Horowitz

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  1. Yoshihiko Nishiyama & Peter M Robinson, 2005. "The Bootstrap and the Edgeworth Correction for Semiparametric Averaged Derivatives," STICERD - Econometrics Paper Series /2005/483, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  2. Kaplan, David M. & Sun, Yixiao, 2012. "Smoothed Estimating Equations For Instrumental Variables Quantile Regression," University of California at San Diego, Economics Working Paper Series qt888657tp, Department of Economics, UC San Diego.
  3. Gong, X. & Soest, A.H.O. van & Zhang, P., 2000. "Sexual Bias and Household Consumption: A Semiparametic Analysis of Engel curves in Rural China," Discussion Paper 2000-45, Tilburg University, Center for Economic Research.
  4. J. Carlos Escanciano & Carlos Velasco, 2010. "Specification tests of parametric dynamic conditional quantiles," Post-Print peer-00732534, HAL.
  5. Dimitris Politis, 2013. "Model-free model-fitting and predictive distributions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 22(2), pages 183-221, June.
  6. Oliver Linton, 2000. "Edgeworth approximations for semiparametric instrumental variable estimators and test statistics," LSE Research Online Documents on Economics 2156, London School of Economics and Political Science, LSE Library.
  7. Horowitz, Joel L., 2002. "Bootstrap critical values for tests based on the smoothed maximum score estimator," Journal of Econometrics, Elsevier, vol. 111(2), pages 141-167, December.
  8. Juan Carlos Escanciano & Chuan Goh, 2010. "Specification Analysis of Structural Quantile Regression Models," Working Papers tecipa-415, University of Toronto, Department of Economics.
  9. Marcus Alexander & Matthew Harding & Carlos Lamarche, 2008. "The Political Economy of Heterogeneous Development: Quartile Effects of Income and Education," Discussion Papers 07-052, Stanford Institute for Economic Policy Research.
  10. Huixia Judy Wang & Leonard A. Stefanski & Zhongyi Zhu, 2012. "Corrected-loss estimation for quantile regression with covariate measurement errors," Biometrika, Biometrika Trust, vol. 99(2), pages 405-421.
  11. Hidehiko Ichimura & Sokbae Lee, 2010. "Characterization of the asymptotic distribution of semiparametric M-estimators," Post-Print hal-00741628, HAL.
  12. Roger Koenker, 2000. "Inference on the Quantile Regression Process," Econometric Society World Congress 2000 Contributed Papers 0886, Econometric Society.
  13. Wolfgang Karl Härdle & Ya’acov Ritov & Song Song, 2010. "Partial Linear Quantile Regression and Bootstrap Confidence Bands," SFB 649 Discussion Papers SFB649DP2010-002, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  14. Otsu, Taisuke, 2008. "Conditional empirical likelihood estimation and inference for quantile regression models," Journal of Econometrics, Elsevier, vol. 142(1), pages 508-538, January.
  15. Xiaohong Chen & Oliver Linton & Ingrid Van Keilegom, 2003. "Estimation of semiparametric models when the criterion function is not smooth," LSE Research Online Documents on Economics 2167, London School of Economics and Political Science, LSE Library.
  16. Parente, Paulo M.D.C. & Smith, Richard J., 2011. "Gel Methods For Nonsmooth Moment Indicators," Econometric Theory, Cambridge University Press, vol. 27(01), pages 74-113, February.
  17. Xiaofeng Lv & Rui Li, 2013. "Smoothed empirical likelihood analysis of partially linear quantile regression models with missing response variables," AStA Advances in Statistical Analysis, Springer, vol. 97(4), pages 317-347, October.
  18. Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Mishra, Santosh, 2004. "Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood," International Journal of Forecasting, Elsevier, vol. 20(4), pages 629-645.
  19. Yoon-Jae Whang, 2003. "Smoothed Empirical Likelihood Methods for Quantile Regression Models," Econometrics 0310005, EconWPA.
  20. Komunjer, Ivana, 2002. "Quasi-Maximum Likelihood Estimation for Conditional Quantiles," Working Papers 1139, California Institute of Technology, Division of the Humanities and Social Sciences.
  21. Wang, Yafeng & Graham, Brett, 2009. "Generalized Maximum Entropy estimation of discrete sequential move games of perfect information," MPRA Paper 21331, University Library of Munich, Germany.
  22. repec:wyi:wpaper:002036 is not listed on IDEAS
  23. Lamarche, Carlos, 2011. "Measuring the incentives to learn in Colombia using new quantile regression approaches," Journal of Development Economics, Elsevier, vol. 96(2), pages 278-288, November.
  24. Liu, Z. J. & Rao, C. R., 2001. "MU-Estimation and Smoothing," Journal of Multivariate Analysis, Elsevier, vol. 76(2), pages 277-293, February.
  25. Oliver Linton & Myunghwan Seo, 2005. "A smoothed least squares estimator for threshold regression models," LSE Research Online Documents on Economics 4434, London School of Economics and Political Science, LSE Library.
  26. White, Halbert & Kim, Tae-Hwan, 2002. "Estimation, Inference, and Specification Testing for Possibly Misspecified Quantile Regression," University of California at San Diego, Economics Working Paper Series qt1s38s0dn, Department of Economics, UC San Diego.
  27. Escanciano, J.C. & Goh, S.C., 2014. "Specification analysis of linear quantile models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 495-507.
  28. Olivier Armantier & Amadou Boly, 2008. "Can Corruption Be Studied in the Lab? Comparing a Field and a Lab Experiment," CIRANO Working Papers 2008s-26, CIRANO.
  29. Yang Yang & Tae-Hwy Lee, 2004. "Bagging Binary Predictors for Time Series," Econometric Society 2004 Far Eastern Meetings 512, Econometric Society.
  30. George Anastassopoulos & Fragkiskos Filippaios & Paul Phillips, 2007. "An ‘eclectic’ investigation of tourism multinationals’ activities: Evidence from the Hotels and Hospitality Sector in Greece," GreeSE – Hellenic Observatory Papers on Greece and Southeast Europe 08, Hellenic Observatory, LSE.