Ononot — Consider the multiple regression Y = \beta0 + \beta1 X1 + \b

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Linear Modelinghard

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Consider the multiple regression $Y = \beta_0 + \beta_1 X_1 + \beta_2 X_2 + \epsilon$ . If $X_1$ and $X_2$ are perfectly collinear ( $X_2 = kX_1$ ), what is the mathematical consequence for the OLS estimate $\hat{\beta}$ ?