Quasi ML Estimation of the Panel AR(1) Model with Arbitrary Initial Conditions

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Quasi ML Estimation of the Panel AR(1) Model with Arbitrary Initial Conditions

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Hugo Kruiniger () (Queen Mary, University of London)

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Hugo Kruiniger

Abstract

In this paper we show that the Quasi ML estimation method yields consistent Random and Fixed Effects estimators for the autoregression parameter ρ in the panel AR(1) model with arbitrary initial conditions even when the errors are drawn from heterogenous distributions. We compare both analytically and by means of Monte Carlo simulations the QML estimators with the GMM estimator proposed by Arellano and Bond (1991) [AB], which ignores some of the moment conditions implied by the model. Unlike the AB GMM estimator, the QML estimators for ρ only suffer from a weak instruments problem when ρ is close to one if the cross-sectional average of the variances of the errors is constant over time, e.g. under time-series homoskedasticity. However, even in this case the QML estimators are still consistent when ρ is equal to one and they display only a relatively small bias when ρ is close to one. In contrast, the AB GMM estimator is inconsistent when ρ is equal to one, and is severly biased when ρ is close to one. Finally, we study the finite sample properties of two types of estimators for the standard errors of the QML estimators for ρ, and the bounds of QML based confidence intervals for ρ.

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Paper provided by Queen Mary, University of London, Department of Economics in its series Working Papers with number 582.

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Date of creation: Dec 2006
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Handle: RePEc:qmw:qmwecw:wp582

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Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data

This paper has been announced in the following NEP Reports:

NEP-ALL-2007-01-13 (All new papers)
NEP-ECM-2007-01-13 (Econometrics)
NEP-ETS-2007-01-13 (Econometric Time Series)

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