42 Statistical Properties Assumption 7

In this video, Lydia revisits the core assumptions of econometrics, summarizing the statistical properties covered thus far. She explains how the initial assumptions establish Ordinary Least Squares (OLS) as unbiased, and with the addition of homoscedasticity, we gain a formula for the variance of beta hat and confirm OLS as the best linear unbiased estimator. However, without further assumptions, the distribution of beta hat remains largely unknown, which is crucial for statistical inference. This leads to the introduction of the final assumption: that error terms are normally and independently distributed. While this assumption may not always hold true in practice, the Central Limit Theorem ensures that for a sufficiently large sample size, the error terms can be approximated as normally distributed, enabling reliable inference. Subscribe to @AxiomTutoringCourses for more econometrics tutorials.