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Lecture Applied econometrics course - Chapter 2: Multiple regression model

Lecture "Applied econometrics course - Chapter 2: Multiple regression model" has content: Why we need multiple regression model, estimation, R – Square, assumption, variance and standard error of parameters, the issues of multiple regression model, Illustration by Computer. | APPLIED ECONOMETRICS COURSE CHAPTER II MULTIPLE REGRESSION MODEL NGUYEN BA TRUNG - 2016 Today’s talk Why we need multiple regression model Estimation R – Square Assumption Variance and Standard Error of Parameters The issues of multiple regression model Illustration by Computer NGUYEN BA TRUNG - 2016 I. WHY WE NEED MULTIPLE REGRESSION MODEL? Reality and flexibility Avoid the biasedness caused by omitted variables Generally, multiple regression model is written by Yi 0 1 X 1i . k X k u (2.1) The terminology in (2.1) is similar as simple regression model NGUYEN BA TRUNG - 2016 II. ESTIMATION: OLS The matrix form of multiple regression model: Y1 1 Y2 1 . . Yn 1 1 Y 1 n X 21 . X 22 . . . X 2 n 1 . X 2n . X k1 u1 1 X k 2 u2 2 . . . X kn 1 un 1 k u X kn n Compactness: Y X u (2.2) NGUYEN BA TRUNG - 2016 II. ESTIMATION: OLS ˆˆ RSS uu ˆ ˆ (Y X ) (Y X ) ˆ ˆ ˆ Y Y X Y Y XX X ˆ ˆ ˆ ˆ YY 2 X XX Y Take derivative respect to parameters, we have: ˆ RSS ( ) 2 X 2 X 0 Y X ˆ ˆ X X X ˆ Y NGUYEN BA TRUNG - .