On the Heterogeneity Bias of Pooled Estimators in Stationary VAR Specifications

This paper studies asymptotically the bias of the fixed effect (FE) estimator induced by cross-section heterogeneity in the slope parameters of stationary vector autoregressions (VARs). The paper also compares the FE, the mean group estimator (MG), and a simple instrumental variable alternative (IV)...

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Bibliographic Details
Main Author: Rebucci, Alessandro
Format: eBook
Language:English
Published: Washington, D.C. International Monetary Fund 2003
Series:IMF Working Papers
Subjects:
Online Access:
Collection: International Monetary Fund - Collection details see MPG.ReNa
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300 |a 45 pages 
653 |a Multiple or Simultaneous Equation Models 
653 |a Vector error correction models 
653 |a Dynamic Treatment Effect Models 
653 |a Diffusion Processes 
653 |a Vector autoregression 
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653 |a Time-Series Models 
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653 |a Econometric models 
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653 |a Econometrics & economic statistics 
653 |a Multiple Variables: General 
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520 |a This paper studies asymptotically the bias of the fixed effect (FE) estimator induced by cross-section heterogeneity in the slope parameters of stationary vector autoregressions (VARs). The paper also compares the FE, the mean group estimator (MG), and a simple instrumental variable alternative (IV) in Monte Carlo simulations. The main results are: (i) asymptotically, the heterogeneity bias of the FE may be more or less severe in VAR specifications than in standard dynamic panel data specifications; (ii) in Monte Carlo simulations, slope heterogeneity must be relatively high to be a source of concern for pooled estimators; (iii) when this happens, the panel must be longer than a typical macro dataset for the MG to be a viable solution