In this lecture we apply the techniques of statistical inference to the linear regression model. Additionally, the assumptions of homoskedasticity and heteroskedasticity and their consequences are discussed 00:00 Introduction 05:57 Homoskedasticity and heteroskedasticity 12:53 Heteroskedasticity-robust estimation of the OLS estimators variance 20:32 Homoskedasticity-only estimation of the OLS estimators variance 22:58 Standard errors 24:59 Python regression results output 30:40 Comparison of homoskedastic and robust standard errors 32:30 Testing hypotheses about regression coefficients 1:00:33 Confidence intervals for regression coefficients 1:16:14 Practical remarks 1:25:15 Conclusion The course “Econometrics“ for the 2nd year bachelors in Economics Taught at BRICS institute, Irkutsk National Research Technical University, Spring semester 2022
Hide player controls
Hide resume playing