计量经济学Ch_08_Wooldridge_5e_PPT.ppt

? 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Chapter 8 Heteroscedasticity Wooldridge: Introductory Econometrics: A Modern Approach, 5e ? 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Chapter 8 Multiple Regression Analysis: Heteroscedasticity Consequences of Heteroskedasticity for OLS Heteroskedasticity-Robust Inference after OLS Estimation Testing for Heteroskedasticity Weighted Least Squares Estimation The Linear Probability Model Revisited Assignments: Promblems 7 Computer Exercises C2, C5, C9, C11 ? 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Unaffected properties: OLS still unbiased and consistent under heteroscedastictiy! Also, interpretation of R-squared is not changed. Affected properties: Heteroscedasticity invalidates variance formulas for OLS estimators. The usual F-tests and t-tests are not valid under heteroscedasticity. Under heteroscedasticity, OLS is no longer the best linear unbiased estimator (BLUE); there may be more efficient linear estimators. OLS is asymptotically efficient in the class of estimators. With relatively large sample sizes, it might no be so important to obtain an efficient estimator. Unconditional error variance is unaffected by heteroscedasticity (which refers to the conditional error variance) Chapter 8 Multiple Regression Analysis: Heteroscedasticity Consequences of Heteroskedasticity for OLS Chapter ? 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part. Formulas for OLS standard errors and related statistics have been developed that are rob