ÿþ<html xmlns:v="urn:schemas-microsoft-com:vml" xmlns:o="urn:schemas-microsoft-com:office:office" xmlns="http://www.w3.org/TR/REC-html40"> <head> <meta http-equiv="Content-Type" content="text/html; charset=windows-1252"> <meta name="GENERATOR" content="Microsoft FrontPage 5.0"> <meta name="ProgId" content="FrontPage.Editor.Document"> <title>Econometrica 2005</title> <style> <!-- div.Section1 {page:Section1;} --> </style> <meta name="Microsoft Theme" content="expedition-modified 011, default"> </head> <body background="../_themes/expedition-modified/exptextb.jpg" bgcolor="#FFFFFF" text="#000000" link="#993300" vlink="#666600" alink="#CC3300"><!--mstheme--><font face="Comic Sans MS"> <div class="Section1"> <h2 style="MARGIN-BOTTOM: 12pt; TEXT-ALIGN: center" align="center"><!--mstheme--><font color="#660033"> <span lang="EN-US" style="font-weight: 400">GMM, GEL, serial correlation, and asymptotic bias</span><!--mstheme--></font></h2> <p style="MARGIN: 4pt 0cm 0pt"><span lang="EN-US">Citation:</span></p> <blockquote> <p style="MARGIN: 4pt 0cm 0pt"><span lang="EN-US">Anatolyev, Stanislav (2005)  <i>GMM, GEL, serial correlation, and asymptotic bias</i> , Econometrica, Vol. 73, No. 3, pp. 983 1002</span></p> </blockquote> <p style="MARGIN: 4pt 0cm 0pt"><span lang="EN-US">Abstract:</span></p> <blockquote> <p>For stationary time series models with serial correlation, we consider generalized method of moments (GMM) estimators that use heteroskedasticity and autocorrelation consistent (HAC) positive definite weight matrices, and generalized empirical likelihood (GEL) estimators based on smoothed moment conditions. Following the analysis of Newey and Smith (2004) for independent observations, we derive second order asymptotic biases of these estimators. The inspection of bias expressions reveals that the use of smoothed GEL, in contrast to GMM, removes the bias component associated with the correlation between the moment function and its derivative, while the bias component associated with third moments depends on the employed kernel function. We also analyze the case of no serial correlation, and find that the seemingly unnecessary smoothing and HAC estimation can reduce the bias for some of the estimators.</p> </blockquote> <p style="MARGIN: 4pt 0cm 0pt"><span lang="EN-US">Paper in RePEc:</span></p> <blockquote> <p style="MARGIN: 4pt 0cm 0pt"><span lang="EN-US"> <a style="color: red; text-decoration: underline; text-underline: single" target="_blank" href="http://econpapers.repec.org/article/ecmemetrp/v_3a73_3ay_3a2005_3ai_3a3_3ap_3a983-1002.htm"> Econometrica, 73:3, 983-1002 </a></span></p> </blockquote> <p style="MARGIN: 4pt 0cm 0pt"><span lang="EN-US">Paper in accepted version:</span></p> <blockquote> <p style="MARGIN: 4pt 0cm 0pt"><span lang="EN-US"> <a target="_blank" href="GmmGel.pdf">GmmGel.pdf</a></span></p> </blockquote> <p style="MARGIN: 4pt 0cm 0pt"><span lang="EN-US">Presented at:</span></p> <blockquote> <p><a target="_blank" href="http://www.eea-esem2003.org/">European Economic Association annual congress</a>, Stockholm, Sweden, August 20-24, 2003<br> <a target="_blank" href="http://www.kellogg.northwestern.edu/meds/deptinfo/econometrics_society.htm">North American summer meeting of Econometric Society</a>, Evanston, USA, June 26-29, 2003<br> <a target="_blank" href="http://www.econ.kuleuven.be/eng/">Catholic University of Leuven</a>, Belgium, April 3, 2003 <br> <a target="_blank" href="http://les1.man.ac.uk/sapcourses/esgc/ann.html">Econometric Study Group annual conference</a>, Bristol, UK, July 18 20, 2002<br> <a target="_blank" href="http://www.nes.ru/english/research/confprog/conf12_2002.htm">XII New Economic School research conference</a>, Moscow, Russia, October 3-5, 2002</p> </blockquote> <p style="MARGIN: 4pt 0cm 0pt"><span lang="en-us">Cited by</span><span lang="EN-US">:</span></p> <blockquote> <p>Allen, J., Gregory, A.W. and Shimotsu, K. (2011) <i>&quot;Empirical likelihood block bootstrapping&quot;</i>, Journal of Econometrics, Vol. 161, pp. 110-121.<br> Vasco J. Gabriel and Luis F. Martins (2010) <i>&quot;The cost channel reconsidered: A comment using an identification-robust approach&quot;</i>, Journal of Money, Credit and Banking, Vol. 42, pp. 1703-1712.<br> Pierre Chaussé (2010) <i>&quot;Computing generalized method of moments and generalized empirical likelihood with R&quot;</i>, Journal of Statistical Software, Vol. 34, pp. 1-35.<br> Francesco Bravo (2009) <i>&quot;Blockwise generalized empirical likelihood inference for non-linear dynamic moment conditions models&quot;</i>, Econometrics Journal, Vol. 12, pp. 208-231.<br> Luis F. Martins and Vasco J. Gabriel (2009) <i>&quot;New Keynesian Phillips Curves and potential identification failures: A Generalized Empirical Likelihood analysis&quot;</i>, Journal of Macroeconomics, Vol. 31, pp. 561-571.<br> Yuichi Kitamura (2009) <i>&quot;Empirical Likelihood Methods in Econometrics: Theory and Practice&quot;</i>, in: <i>&quot;Advances in Economics and Econometrics, Theory and Applications, Ninth World Congress&quot;</i>, by R. Blundell, W. Newey and T. Persson (eds.).<br> Fernanda P.M. Peixe, Alastair R. Hall, and Kostas Kyriakoulis (2006) <i>&quot;The mean squared error of the instrumental variables estimator when the disturbance has an elliptical distribution&quot;</i>, Econometric Reviews, Vol. 25, pp. 117-138.<br> Ivan Fernandez-Val (2005) <i>&quot;Bias correction in panel data models with individual specific parameters&quot;</i>, Manuscript, Boston University.<br> Pierre Chaussé (2005) <i>&quot;La Vraisemblance Empirique et la Méthode des Moments Généralisés: Survol de la Littérature et Extensions&quot;</i>, Manuscript, Université du Québec à Montréal.<br> Alain Guay and Florian Pelgrin (2005) <i>&quot;The U.S. New Keynesian Phillips Curve: An Empirical Assessment&quot;</i>, Manuscript, Université du Québec à Montréal.</p> </blockquote> </div> <!--mstheme--></font></body> </html>