Econometrics. a Regression Analysis free essay sample

In this scenario, the number of bedrooms, bathrooms, fireplaces, etc. would increase the price of the house. * The omitted variable or variables must be correlated with the included independent variable, or variables. In this scenario, as lot size increases, so will all of the other independent variables from part two. Question As mentioned in the textbook, OLS standard errors are referred to as homoskedasticity only standard errors. This is because OLS standard errors are strictly valid in the presence of homoskedasticity but they are not valid in the presence of heteroskedasticity. What is heteroscedasticity? What is the effect of heteroskedasticity on the OLS estimates and their standard errors? * Heteroskedasticity is the non-constant variance of the error term. * Homoskedasticity is the constant variance of the error term. If this is present it means there is a violation of the constant variance assumption. * The effect of heteroskedasticity on the OLS estimator is that it is still unbiased. We will write a custom essay sample on Econometrics. a Regression Analysis or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page * The effect of heteroskedasticity on the OLS estimator standard errors are that the results in adjusted robust standard errors cause the homoskedasticity results to be incorrect standard errors. Question 5: As mentioned in class, one commonly employed solution to heteroscedasticity is to adjust the standard errors for the possible presence of heteroskedasticity, i. e. we compute the heteroskedasticity-robust standard errors, which are also referred to as heteroskedasticity-consistent standard errors. Rerun the regression in part (2) with the OLS standard errors replaced by heteroskedasticity-robust standard errors. Comment on the differences between the OLS standard errors in part (2) and the heteroskedasticity-robust standard errors in this part. * With Homoskadasticity, Part 2 model, with constant variance of error term: