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Book chapter
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Reference no. MHE0011BC
Chapter from: "Econometrics"
Published by: McGraw Hill Education
Published in: 2005

Abstract

Chapter 11. The book aims to introduce students with little or no previous experience in econometrics to this important discipline. This text focuses on explaining why econometrics exists and how it can be used in everyday life. This text adopts a strong student-focused approach to the discipline. In doing so, it aims to address fundamental issues in econometrics in an accessible manner for students, who are often put off by the difficult nature of the subject. f The learning objectives of this chapter are: (1) be aware that heteroscedasticity does not alter the unbiasedness property of OLS (ordinary least squares) estimators but does alter the ''best'' property; (2) understand the rationale for using weighted least squares or heteroscedasticity corrected standard error; (3) know the factors that may cause heteroscedasticity to be present in OLS residuals; and (4) be able to estimate and interpret GLS (generalized least squares) equations or those with heteroscedasticity corrected standard errors.

About

Abstract

Chapter 11. The book aims to introduce students with little or no previous experience in econometrics to this important discipline. This text focuses on explaining why econometrics exists and how it can be used in everyday life. This text adopts a strong student-focused approach to the discipline. In doing so, it aims to address fundamental issues in econometrics in an accessible manner for students, who are often put off by the difficult nature of the subject. f The learning objectives of this chapter are: (1) be aware that heteroscedasticity does not alter the unbiasedness property of OLS (ordinary least squares) estimators but does alter the ''best'' property; (2) understand the rationale for using weighted least squares or heteroscedasticity corrected standard error; (3) know the factors that may cause heteroscedasticity to be present in OLS residuals; and (4) be able to estimate and interpret GLS (generalized least squares) equations or those with heteroscedasticity corrected standard errors.

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