chapter 1

# chapter 1 - Ordinary least squares(OLS Interpretation and R...

This preview shows pages 1–9. Sign up to view the full content.

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

View Full Document

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

View Full Document

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

View Full Document

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

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Ordinary least squares (OLS) Interpretation and R 2 Econ 281 - Chapter 1 Review - Simple Regression Analysis Richard Walker Northwestern University January 11, 2010 Econ 281 - Chapter 1 Richard Walker Ordinary least squares (OLS) Interpretation and R 2 1 Ordinary least squares (OLS) Simple linear model Least squares regression 2 Interpretation and R 2 Interpretation of results Goodness of fit: R 2 Econ 281 - Chapter 1 Richard Walker Ordinary least squares (OLS) Interpretation and R 2 1 Ordinary least squares (OLS) Simple linear model Least squares regression 2 Interpretation and R 2 Interpretation of results Goodness of fit: R 2 Econ 281 - Chapter 1 Richard Walker Ordinary least squares (OLS) Interpretation and R 2 Simple linear model 1 Ordinary least squares (OLS) Simple linear model Least squares regression 2 Interpretation and R 2 Interpretation of results Goodness of fit: R 2 Econ 281 - Chapter 1 Richard Walker Ordinary least squares (OLS) Interpretation and R 2 Simple linear model We want to start looking for relationships between economic variables We’re going to start with the most straightforward possible such relationship one dependent variable Y that we are trying to explain one explanatory variable X that might help us explain Y any relationship between X and Y is assumed a priori to be linear This is known as ‘simple linear regression’ ‘simple’ because there’s only one explanatory variable X Econ 281 - Chapter 1 Richard Walker Ordinary least squares (OLS) Interpretation and R 2 Simple linear model We will assume that the following is the ‘true’ process by which the dependent variable Y is generated: Y i = β 1 + β 2 X i + u i (1.1) β 1 and β 2 are parameters that we would like to estimate u is a disturbance term The i subscript refers to the particular observation of the variables for example, if we are examining the relationship between height and wages across people, then the i would refer to the people we only actually ‘observe’ the Y i and X i , not the u i Econ 281 - Chapter 1 Richard Walker Ordinary least squares (OLS) Interpretation and R 2 Simple linear model Y X β 1 Y = β 1 + β 2 X u i The true, data-generating model Econ 281 - Chapter 1 Richard Walker Ordinary least squares (OLS) Interpretation and R 2 Simple linear model Why is there a disturbance term? Why isn’t the relationship between Y and X ‘exact’? Omitted variables : something else also helps explain Y Aggregation : often the relationship is an aggregate one e.g. adding-up lots of little consumption functions ⇒ aggregate consumption function unlikely to be exact Model misspecification : Y might depend on yesterday’s X , or the expectation of tomorrow’s X , rather than X itself relationship between Y and X will be close, but not exact Functional misspecification : maybe the relationship is nonlinear?...
View Full Document

{[ snackBarMessage ]}

### Page1 / 37

chapter 1 - Ordinary least squares(OLS Interpretation and R...

This preview shows document pages 1 - 9. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online