This preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: Introduction to Econometrics Chapter 6: Linear Regression with Multiple Regressors Geo rey Williams [email protected] October 27, 2010 Geo rey Williams [email protected] Introduction to Econometrics Chapter 6: Linear Regression The Return of Other Factors Remember that our basic regression equation is: Y i = + 1 X i + u i We assumed that u i could be ignored  that while u i might have some relationship with Y i , and or with X i , that it was not important to the relationship that Y i and X i had with each other. Is this always true? Geo rey Williams [email protected] Introduction to Econometrics Chapter 6: Linear Regression The example of Englishlearning students Consider the percentage of Englishlearning students in a school district. It could clearly have an impact on test scores, at the very least slowing down reading comprehension, increasing the odds of misunderstanding a question.. If districts with a high percentage of Englishlearning students ALSO have large class sizes, then they might have lower test scores due to the language issues, not the class size. Omitting the variable , percentage of Englishlearners could be biasing our results Geo rey Williams [email protected] Introduction to Econometrics Chapter 6: Linear Regression Omitted Variable Bias We need two things for omitted variable bias: 1 an omitted variable that is correlated with X i 2 the same omitted variable has an in uence on Y i When both hold true, then the rst least squares assumption, E ( u i j X i ) = 0, does not hold true. Geo rey Williams [email protected] Introduction to Econometrics Chapter 6: Linear Regression Several Examples 1 Percentage of English learners Correlated with X i p In uence on Y i p 2 Time of day of test Correlated with X i In uence on Y i p 3 Parking lot space per pupil Correlated with X i p In uence on Y i Geo rey Williams [email protected] Introduction to Econometrics Chapter 6: Linear Regression Formal Description of Omitted Variable Bias...
View
Full Document
 Fall '10
 Otusbo
 Econometrics, Linear Regression, Regression Analysis, Econometrics Chapter, Geo1Brey Williams

Click to edit the document details