# ie_Slide02 - Introductory Econometrics ECON2206/ECON3209...

This preview shows pages 1–7. Sign up to view the full content.

Introductory Econometrics ECON2206/ECON3209 Slides02 Lecturer: Rachida Ouysse ie_Slides02 R. Ouysse, School of Economics, UNSW 1

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
2. Simple Regression Model (Ch2) 2. Simple Regression Model • Lecture plan otivation and definitions Motivation and definitions – ZCM assumption stimation method: OLS – Estimation method: OLS – Units of measurement onlinear relationships – Nonlinear relationships – Underlying assumptions of simple regression model xpected values and variances of OLS estimators – Expected values and variances of OLS estimators – Regression with STATA ie_Slides02 R. Ouysse, School of Economics, UNSW 2
2. Simple Regression Model (Ch2) • Motivation – Example 1. Ceteris paribus effect of fertiliser on soybean yield yield = β 0 + β 1 ferti + u . – Example 2. Ceteris paribus effect of education on wage wage = β 0 + β 1 educ + u . – In general, y = β 0 + β 1 x + u, where u represents factors other than x that affect y . p – We are interested in •explaining y in terms of x , • how y responds to changes in x, holding other factors fixed. ie_Slides02 R. Ouysse, School of Economics, UNSW 3

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
2. Simple Regression Model (Ch2) Simple regression model – Definition = β β +u y = 0 + 1 x + u , y : dependent variable (observable) independent variable (observable) x : β 1 : slope parameter, “ partial effect ,” (to be estimated) β 0 : intercept parameter (to be estimated) u : error term or disturbance (unobservable) – The disturbance u represents all factors other than x . – With the intercept β 0 , the population average of u can always be set to zero (without losing anything) = = + E + β + E E ( u ) 0 . y β 0 E ( u ) 1 x u E ( u ) ie_Slides02 R. Ouysse, School of Economics, UNSW 4
2. Simple Regression Model (Ch2) = β + β + u • Zero conditional mean assumption – If other factors in u are held fixed ( Δ u = 0), the ceteris y 0 1 x u y + Δ y = β 0 + β 1 ( x+ Δ x ) + u + Δ u paribus effect of x on y is β 1 : Δ y = β 1 Δ x . Δ = “change” – But under what condition u can be held fixed while x changes? •As x and u are treated as random variables, u is fixed while x varying ” is described as the mean of u for any given x is the same (zero) ”. – The required condition is X = X 1 X 2 X 3 ... E ( u | x ) = E ( u ) = 0 , known as zero-conditional-mean (ZCM) assumption. E(u |X) = 0 0 0 0 ie_Slides02 R. Ouysse, School of Economics, UNSW 5

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
2. Simple Regression Model (Ch2) • Zero conditional mean assumption – Example 2. wage = β 0 + β 1 educ + u Suppose u represents ability . Then ZCM assumption amounts to E ( ability | educ ) = 0 , ie, the average ability is the same irrespective of the years of education. This is not true • if people choose the education level to suit their ability; • or if more ability is associated with less (or more) education. In practice, we do not know if ZCM holds and have to eal with this issue deal with this issue.
This is the end of the preview. Sign up to access the rest of the document.

## This note was uploaded on 02/29/2012 for the course ECON 2206 taught by Professor Yang during the One '11 term at University of New South Wales.

### Page1 / 30

ie_Slide02 - Introductory Econometrics ECON2206/ECON3209...

This preview shows document pages 1 - 7. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online