Is More Information a Good Thing? Bias Nonmonotonicity in Stochastic Difference Equations

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Is More Information a Good Thing? Bias Nonmonotonicity in Stochastic Difference Equations

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Abadir, Karim M
Hadri, Kaddour

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Abstract

It is shown that the bias of estimated parameters in autoregressive models can increase as the sample size grows. This bias is also a nonmonotonic function of the largest autoregressive root, contrary to what asymptotic approximations had indicated so far in the literature. These unusual results are due to the effect of the initial sample observations that are typically neglected in theoretical asymptotic analysis, in spite of their empirical relevance. Implications for practical economic modelling are considered, including a comparison of the likely inaccuracies of parameter estimates in alternative models based on competing macroeconomic theories. Copyright 2000 by Blackwell Publishing Ltd and the Board of Trustees of the Bulletin of Economic Research

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Article provided by Blackwell Publishing in its journal Bulletin of Economic Research.

Volume (Year): 52 (2000)
Issue (Month): 2 (April)
Pages: 91-100
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Handle: RePEc:bla:buecrs:v:52:y:2000:i:2:p:91-100

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Kaddour Hadri & Yao Rao, 2006. "Panel Stationarity Test with Structural Breaks," Research Papers 200615, University of Liverpool Management School. [Downloadable!]
Other versions:
- Kaddour Hadri & Yao Rao, 2008. "Panel Stationarity Test with Structural Breaks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(2), pages 245-269, 04. [Downloadable!] (restricted)
Steve Lawford & Michalis P. Stamatogiannis, 2004. "The Finite-Sample Effects of VAR Dimensions on OLS Bias, OLS Variance, and Minimum MSE Estimators: Purely Nonstationary Case," Public Policy Discussion Papers 04-05, Economics and Finance Section, School of Social Sciences, Brunel University. [Downloadable!]
Other versions:
- Steve Lawford & Michalis P. Stamatogiannis, 2004. "The Finite-Sample Effects of VAR Dimensions on OLS Bias, OLS Variance, and Minimum MSE Estimators: Purely Nonstationary Case," Economics and Finance Discussion Papers 04-05, Economics and Finance Section, School of Social Sciences, Brunel University. [Downloadable!]

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