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Yong Bao
Yong Bao
Purdue University, USA
A General Result on the Estimation Bias of ARMA Models
I derive a general result on the finite-sample approximate bias of the Gaussian maximum likelihood estimator of the full vector of parameters in ARMA models when the error term may be nonnormally distributed and exogenous regressors may be included. It is found that the estimator of parameters associated with the exogenous regressors is approximately unbiased and the error variance estimator is downward biased, proportional to the number of exogenous regressors and ARMA orders in the model. There is typically estimation bias for the ARMA parameters and it depends only on the ARMA parameters themselves and the exogenous regressors. The distributional assumption on the error term does not affect the general bias result. I provide a simulation study to show that the general bias result is extremely helpful to design a bias-corrected estimator.

Dr. Yong Bao is an Associate Professor of Economics in the Krannert School of Management at Purdue University, USA. (Currently he is on leave with Purdue and is a Professor of Economics at the University of Macau.) He received his BA in economics (with honor) from the University of International Business and Economics in 1998. During 1999-2004 he studied at the University of California, Riverside (UCR) and received his PhD in economics in 2004. His dissertation won the Graduate Research Award, the highest recognition of outstanding PhD dissertations at UCR. After graduation, Dr. Bao taught at the University of Texas at San Antonio (2004-2006) and Temple University (2007-2008) and joined Purdue University in 2008. His main research and teaching interests are in econometrics, empirical finance, and macroeconomics. Dr. Bao has published more than thirty research articles in leading economics journals. He has presented in many international conferences and given seminar talks at various institutions.  

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