# Consequences what does it do to my ols output

This preview shows page 1. Sign up to view the full content.

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

Unformatted text preview: Wednesday 15:00-17:00): Heteroscedasticity 3 May 7 (Friday 14:00-16:00): Measurement Error & Simultaneous Equations All lectures take place in E171 (New Theater) Past Exam Practice Question Introduction Measurement Error Simultaneous Equations Past Exam Practice Question Setup Of Review Lectures Sick Regressions: The Key Questions Common pattern in econometrics: start with basic OLS regression and then analyse what’s wrong Deﬁnition: What’s the disease? Consequences: What does it do to my OLS output? Detection: How can I ﬁnd out if my regression is suffering from the disease? Remedy: What can I do to get rid of the disease? Introduction Measurement Error Simultaneous Equations Past Exam Practice Question Today’s Lecture Difference Between Model A and Model B Up until Chapter 8, we assumed that regressors were nonstochastic. Introduction Measurement Error Simultaneous Equations Past Exam Practice Question Today’s Lecture Difference Between Model A and Model B Up until Chapter 8, we assumed that regressors were nonstochastic. Hence their values were treated like constants. Introduction Measurement Error Simultaneous Equations Past Exam Practice Question Today’s Lecture Difference Between Model A and Model B Up until Chapter 8, we assumed that regressors were nonstochastic. Hence their values were treated like constants. Now introduce stochastic regressors. Introduction Measurement Error Simultaneous Equations Past Exam Practice Question Today’s Lecture Difference Between Model A and Model B Up until Chapter 8, we assumed that regressors were nonstochastic. Hence their values were treated like constants. Now introduce stochastic regressors. Hence their values are treated like realizations of a random variable. Introduction Measurement Error Simultaneous Equations Past Exam Practice Question Today’s Lecture Difference Between Model A and Model B Up until Chapter 8, we assumed that regressors were nonstochastic. Hence their values were treated like constants. Now introduce stochastic regressors. Hence their values are treated like realizations of a random variable. Model A was introduced for analytic simplicity while Model B is more realistic. Introduction Measurement Error Simultaneous Equations Past Exam Practice Question Today’s Lecture Assumptions of Model B Below are the 8 assumptions of Model B: B.1 The model is linear in parameters and correctly speciﬁed.(A.1) Introduction Measurement Error Simultaneous Equations Past Exam Practice Question Today’s Lecture Assumptions of Model B Below are the 8 assumptions of Model B: B.1 The model is linear in parameters and correctly speciﬁed.(A.1) B.2 Values of regressors are drawn randomly from ﬁxed populations. New! Introduction Measurement Error Simultaneous Equations Past Exam Practice Question Today’s Lecture Assumptions of Model B Below are the 8 assumptions of Model B: B.1 The model is linear in parameters and correctly speciﬁed.(A.1) B.2 Values of regressors are drawn rand...
View Full Document

## This document was uploaded on 03/12/2014 for the course ECON 202 at University of London University of London International Programmes (Distance Learning).

Ask a homework question - tutors are online