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Introduction to the Linear Regression Model
Uses of Summary Statistics in Linear Regression
Bias and Precision of the Regression Estimates
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applied econometrics bias biased causal relation co's computed constant term corresponding critical value defined degrees of freedom demand curve direct least squares distributed lag effect distributed lag scheme dummy variable error terms estimated equation estimation procedure example exogenous variables expressed F-statistic functional form given hence HN is false implies increase independent variables indirect interpretation irrelevant variable least squares estimate left-out variable let us consider linear regression mean square error measured minimum-variance unbiased estimates misspecification null hypothesis number of degrees observations obtained ordinary least squares parameter value period PiXu precision problem production function proxy variable regression coefficients regression estimates reject the null residual sum sample serial correlation serially independent sets of data simultaneous-equations specification standard errors statistical distribution sum of squares summary statistics supply curve test procedure test statistic theory tion true relation two-stage least squares Type I error unbiased estimates unity yield zero