Elliott Hill
09/27/2023 · High School

\[ y_{i}=\beta_{1}+\beta_{2} x_{i 2}+\beta_{3} x_{i 3}+\varepsilon_{i}=x_{i}^{\prime} \beta+\varepsilon_{i} \] a. Explain how the ordinary least squares estimator for \( \beta \) is determined and derive an expression for \( b \). b. Which assumptions are needed to make \( b \) an unbiased estimator for \( \beta \) ? c. Explain how a confidence interval for \( \beta_{2} \) can be constructed. Which additional d. Explain how one can test the hypothesis that \( \beta_{3}=1 \).

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a. The OLS estimator \( b \) for \( \beta \) is given by \( b = (X'X)^{-1}X'Y \). b. Assumptions for \( b \) to be unbiased include linearity, random sampling, no perfect multicollinearity, zero conditional mean, and homoscedasticity. c. A confidence interval for \( \beta_2 \) can be constructed using the standard error of \( b_2 \) and the t-distribution. d. To test \( \beta_3 = 1 \), use a t-test with the test statistic \( t = \frac{b_3 - 1}{SE(b_3)} \).

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