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Efficient Semiparametric Estimation of Expectations

Citations

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Cited by:

  1. Severini, Thomas A. & Tripathi, Gautam, 2012. "Efficiency bounds for estimating linear functionals of nonparametric regression models with endogenous regressors," Journal of Econometrics, Elsevier, vol. 170(2), pages 491-498.
  2. Whitney K. Newey & Frank Windmeijer, 2005. "GMM with many weak moment conditions," CeMMAP working papers CWP18/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  3. Joachim Inkmann, 2000. "Finite Sample Properties of One-Step, Two-Step and Bootstrap Empirical Likelihood Approaches to Efficient GMM Estimation," Econometric Society World Congress 2000 Contributed Papers 0332, Econometric Society.
  4. Lorenzo Camponovo & Taisuke Otsu, 2017. "Relative error accurate statistic based on nonparametric likelihood," STICERD - Econometrics Paper Series 593, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  5. Hill, Jonathan B. & Prokhorov, Artem, 2016. "GEL estimation for heavy-tailed GARCH models with robust empirical likelihood inference," Journal of Econometrics, Elsevier, vol. 190(1), pages 18-45.
  6. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
  7. Fan, Yanqin & Gentry, Matthew & Li, Tong, 2011. "A new class of asymptotically efficient estimators for moment condition models," Journal of Econometrics, Elsevier, vol. 162(2), pages 268-277, June.
  8. Guggenberger, Patrik & Smith, Richard J., 2005. "Generalized Empirical Likelihood Estimators And Tests Under Partial, Weak, And Strong Identification," Econometric Theory, Cambridge University Press, vol. 21(4), pages 667-709, August.
  9. Frank Kleibergen, 2004. "Expansions of GMM statistics that indicate their properties under weak and/or many instruments and the bootstrap," Econometric Society 2004 North American Summer Meetings 408, Econometric Society.
  10. Jeffrey M. Wooldridge, 2004. "Estimating average partial effects under conditional moment independence assumptions," CeMMAP working papers 03/04, Institute for Fiscal Studies.
  11. Shane M. Sherlund, 2004. "Quasi Empirical Likelihood Estimation of Moment Condition Models," Econometric Society 2004 North American Summer Meetings 507, Econometric Society.
  12. Camponovo, Lorenzo & Matsushita, Yukitoshi & Otsu, Taisuke, 2021. "Relative error accurate statistic based on nonparametric likelihood," LSE Research Online Documents on Economics 107521, London School of Economics and Political Science, LSE Library.
  13. Poirier, Alexandre, 2017. "Efficient estimation in models with independence restrictions," Journal of Econometrics, Elsevier, vol. 196(1), pages 1-22.
  14. Bryan S. Graham, 2019. "Network Data," NBER Working Papers 26577, National Bureau of Economic Research, Inc.
  15. Ai, Chunrong & Chen, Xiaohong, 2012. "The semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions," Journal of Econometrics, Elsevier, vol. 170(2), pages 442-457.
  16. Giuseppe Ragusa, 2011. "Minimum Divergence, Generalized Empirical Likelihoods, and Higher Order Expansions," Econometric Reviews, Taylor & Francis Journals, vol. 30(4), pages 406-456, August.
  17. Qihui Chen & Zheng Fang, 2019. "Inference on Functionals under First Order Degeneracy," Papers 1901.04861, arXiv.org.
  18. Almeida, Caio & Garcia, René, 2012. "Assessing misspecified asset pricing models with empirical likelihood estimators," Journal of Econometrics, Elsevier, vol. 170(2), pages 519-537.
  19. Gagliardini, Patrick & Ronchetti, Diego, 2013. "Semi-parametric estimation of American option prices," Journal of Econometrics, Elsevier, vol. 173(1), pages 57-82.
  20. Severini, Thomas A. & Tripathi, Gautam, 2001. "A simplified approach to computing efficiency bounds in semiparametric models," Journal of Econometrics, Elsevier, vol. 102(1), pages 23-66, May.
  21. Peter Woehrmann & Willi Semmler & Martin Lettau, "undated". "Nonparametric Estimation of the Time-varying Sharpe Ratio in Dynamic Asset Pricing Models," IEW - Working Papers 225, Institute for Empirical Research in Economics - University of Zurich.
  22. Lewbel, Arthur & McFadden, Daniel & Linton, Oliver, 2011. "Estimating features of a distribution from binomial data," Journal of Econometrics, Elsevier, vol. 162(2), pages 170-188, June.
  23. Aeberhard, William H. & Cantoni, Eva & Heritier, Stephane, 2017. "Saddlepoint tests for accurate and robust inference on overdispersed count data," Computational Statistics & Data Analysis, Elsevier, vol. 107(C), pages 162-175.
  24. Inkmann, J., 2005. "Inverse Probability Weighted Generalised Empirical Likelihood Estimators : Firm Size and R&D Revisited," Discussion Paper 2005-131, Tilburg University, Center for Economic Research.
  25. Zhou, Ling & Lin, Huazhen & Chen, Kani & Liang, Hua, 2019. "Efficient estimation and computation of parameters and nonparametric functions in generalized semi/non-parametric regression models," Journal of Econometrics, Elsevier, vol. 213(2), pages 593-607.
  26. Hahn, Jinyong & Newey, Whitney K. & Smith, Richard J., 2014. "Neglected heterogeneity in moment condition models," Journal of Econometrics, Elsevier, vol. 178(P1), pages 86-100.
  27. Guggenberger, Patrik & Ramalho, Joaquim J.S. & Smith, Richard J., 2012. "GEL statistics under weak identification," Journal of Econometrics, Elsevier, vol. 170(2), pages 331-349.
  28. Mikio Ito & Akihiko Noda, 2012. "The GEL estimates resolve the risk-free rate puzzle in Japan," Applied Financial Economics, Taylor & Francis Journals, vol. 22(5), pages 365-374, March.
  29. Ivan Fernandez-Val, 2005. "Estimation of Structural Parameters and Marginal Effects in Binary Choice Panel Data Models with Fixed Effects," Boston University - Department of Economics - Working Papers Series WP2005-38, Boston University - Department of Economics.
  30. Saraswata Chaudhuri & Eric Renault, 2015. "Shrinkage of Variance for Minimum Distance Based Tests," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 328-351, March.
  31. Richard Smith, 2005. "Weak instruments and empirical likelihood: a discussion of the papers by DWK Andrews and JH Stock and Y Kitamura," CeMMAP working papers CWP13/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  32. Whitney K. Newey & Richard J. Smith, 2004. "Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators," Econometrica, Econometric Society, vol. 72(1), pages 219-255, January.
  33. Komunjer, Ivana & Vuong, Quang, 2010. "Efficient estimation in dynamic conditional quantile models," Journal of Econometrics, Elsevier, vol. 157(2), pages 272-285, August.
  34. Jeon, Byung M. & Brown, Bryan, 2001. "Efficient Semiparametric Estimation of Expectations in Dynamic Nonlinear Systems," Working Papers 2001-09, Rice University, Department of Economics.
  35. Joachim Inkmann, 2010. "Estimating Firm Size Elasticities of Product and Process R&D," Economica, London School of Economics and Political Science, vol. 77(306), pages 384-402, April.
  36. Juan Carlos Escanciano & Wei Li, 2013. "On the identification of structural linear functionals," CeMMAP working papers CWP48/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  37. Alain Guay & Florian Pelgrin, 2016. "Using Implied Probabilities to Improve the Estimation of Unconditional Moment Restrictions for Weakly Dependent Data," Econometric Reviews, Taylor & Francis Journals, vol. 35(3), pages 344-372, March.
  38. Alain Guay & Florian Pelgrin, 2007. "Using Implied Probabilities to Improve Estimation with Unconditional Moment Restrictions," Cahiers de recherche 0747, CIRPEE.
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