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Lecture "Applied econometrics course - Chapter 1: Simple regression model" has content: What is simple regression model, how to estimate simple regression model, R – Square, assumption, variance and standard error of parameters,. and other contents. | APPLIED ECONOMETRICS COURSE CHAPTER I SIMPLE REGRESSION MODEL NGUYEN BA TRUNG - 2016 TODAY’S TALK What is simple regression model How to estimate simple regression model R – Square Assumption Variance and Standard Error of Parameters Measurement Unit Function Form Illustration by Computer NGUYEN BA TRUNG - 2016 I. WHAT IS SIMPLE REGRESSION MODEL? Linear simple regression: Y i 0 1 X i ui (1.1) Y: Dependent variable, Explained variable X: Independent variable, Explanatory variable U: Error term, disturbance β: Parameters need to be estimated SIMPLE regression model = AN independent variable (X) Why does error term (U) exist? NGUYEN BA TRUNG - 2016 I. WHAT IS SIMPLE REGRESSION MODEL? An important assumption: E(u/ x) 0 (1.2) Take the expectation of (1.1) and use equation (1.2), we have: E (Y/ X) 0 1 X (1.3) Equation (1.3) is so called population regression function (PRF) Attention: distinction between PRF and SRF NGUYEN BA TRUNG - 2016 II. ESTIMATION: ORDINARY LEAST SQUARE (OLS) OLS method: ˆ , u 2 (Y X ) 2 MIN (1.4) ˆ ˆ f 0 ˆ1 ˆ 0 1 Take derivative (1.4) respect to the parameters, we have: f f ˆ ˆ ( 0 , 1 ) 0 ˆ 0 ˆ ˆ ( 0 , 1 ) 0 ˆ 1 ➨ n n ˆ ˆ n 0 1 X i Yi i 1 i 1 n n n 2 ˆ ˆ X i 1 X i X i .Yi 0 i 1 i 1 i 1 NGUYEN BA TRUNG - .
