Abstract
The recent attention to the role of expectations in economic theory has increased the use of empirical models in which a regressor is generated by an “auxiliary” equation specifying the expectations formation rule. Pagan (1984) shows that the widely used two-step ordinary least squares (OLS) procedures for estimating such models produce biased estimates of the covariance matrix of parameter estimates and may lead to erroneous conclusions in hypothesis tests. This research examines the impacts upon test conclusions of a generalized least squares (GLS) correction proposed by Hoffman (1987). The evaluation is based upon an economic model representative of the one used in many of the existing studies utilizing generated regressors. Test conclusions from uncorrected OLS and corrected GLS procedures are compared for four specifications of the auxiliary equation. Results indicate that the impact of the correction procedure is substantial when the specification of the auxiliary equation is relatively simple.
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