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Bias in Regressions With a Lagged Dependent Variable

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Author Info
Grubb, David
Symons, James
Abstract

We give an expression to order O(T-1), where T is the sample size, for bias to the estimated coefficient on a lagged dependent variable when all other regressors are exogenous. The general expression is a nonlinear function of the coefficient on the lagged dependent variable, the autoregressive structure of the exogenous variables, and the coefficients on the exogenous variables. The maximum bias that can arise is a linear function of the number of exogenous regressors in the estimating equation.

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Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 3 (1987)
Issue (Month): 03 (June)
Pages: 371-386
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Handle: RePEc:cup:etheor:v:3:y:1987:i:03:p:371-386_01

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  1. Jan F. Kiviet & Garry D. A. Phillips, 2000. "Improved Coefficient and Variance Estimation in Stable First-Order Dynamic Regression Models," Econometric Society World Congress 2000 Contributed Papers 0631, Econometric Society. [Downloadable!]
  2. Adriana Di Liberto & J. Symons, 1999. "Some Econometric Issues In Convergence Regressions," Working Paper CRENoS 199904, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia. [Downloadable!]
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  3. Allan Timmermann & M. Hashem Pesaran, 2003. "Small Sample Properties of Forecasts from Autoregressive Models under Structural Breaks," CESifo Working Paper Series CESifo Working Paper No. , CESifo Group Munich. [Downloadable!]
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