Small-Sample Estimation of a Structural Equation with Autocorrelated Errors

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Abstract
Many time series models have autocorrelated errors. A further problem may be that some of the right-hand variables are correlated with the error. Using Monte Carlo methods we investigated several estimators of such a model. We found that a transformation to correct the autocorrelation often improved matters, but that techniques to correct the other problems such as instrumental variables were usually ineffective. In many cases ordinary least squares had the smallest mean squared error.

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