计量经济学Ch_05_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 5 Multiple Regression Analysis: OLS Asymptotics 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 5 Multiple Regression Analysis: OLS Asymptotics Consistency Asymptotic Normality and Large Sample Inference Asymptotic Efficiency of OLS Introduction Assignments : Computer Exercises C2 ? 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. So far we focused on properties of OLS that hold for any sample Properties of OLS that hold for any sample/ sample size Expected values/unbiasedness under – Variance formulas under – Gauss-Markov Theorem under – Exact sampling distributions/tests under – Properties of OLS that hold in large samples Consistency under – Asymptotic normality/tests under – Without assuming nor- mality of the error term! Chapter 5 Multiple Regression Analysis: OLS Asymptotics Introduction 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. Consistency Interpretation: Consistency means that the probability that the estimate is arbitrari- ly close to the true population value can be made arbitrarily high by increasing the sample size Consistency is a minimum requirement for sensible estimators An estimator is consistent for a population parameter if for arbitrary and . Alternative notation: The estimate converges in proba- bility to the true population value Chapter 5 Multiple