Ch12ivPart2

# Ch12ivPart2 - Midterm 2 Thursday November 18 Closed book...

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1 Midterm 2 Thursday November 18 Closed book except for 1 2-sided sheet of notes? The notes must be turned in with the exam. Covers through Chapter 12 in the text, and will concentrate on Chapters 10-12. Calculators are OK, but no cell phones, pagers, PDAs or anything else with an “ON” button. Bring picture UCI ID, blank paper, and dark blue or black writing implements. Please show up with name and ID on each piece of paper, and only write on one side! 2 The General IV Regression Model (SW Section 12.2) So far we have considered IV regression with a single endogenous regressor ( X ) and a single instrument ( Z ). We need to extend this to: multiple endogenous regressors ( X 1 ,…, X k ) multiple included exogenous variables ( W 1 ,…, W r ) These need to be included for the usual OV reason multiple instrumental variables ( Z 1 ,…, Z m ) More (relevant) instruments can produce a smaller variance of TSLS: the R 2 of the first stage increases, so you have more variation in ˆ X . Terminology: identification & overidentification 3 Identification In general, a parameter is said to be identified if different values of the parameter would produce different distributions of the data. Suppose 01 1 2 2 1 2 a nd 2 3 ii i i i i YX X X X β ββυ =+ + + = + Is 1 identified? A. Yes B. No 4 Identification in IV models In IV regression, whether the coefficients are identified depends on the relation between the number of instruments ( m ) and the number of endogenous regressors ( k ) Intuitively, if there are fewer instruments than endogenous regressors, we can’t estimate 1 ,…, k For example, suppose k = 1 but m = 0 (no instruments)!

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5 Identification, ctd. The coefficients β 1 ,…, k are said to be: exactly identified if m = k . There are just enough instruments to estimate 1 ,…, k . overidentified if m > k . There are more than enough instruments to estimate 1 ,…, k . If so, you can test whether the instruments are valid ( a test of the “overidentifying restrictions ”) – we’ll return to this later underidentified if m < k . There are too few instruments to estimate 1 ,…, k . If so, you need to get more instruments! 6 The general IV regression model: Summary of jargon Y i = 0 + 1 X 1 i + … + k X ki + k +1 W 1 i + … + k+r W ri + u i Y i is the dependent variable X 1 i ,…, X ki are the endogenous regressors (potentially correlated with u i ) W 1 i ,…, W ri are the included exogenous variables or included exogenous regressors (uncorrelated with u i ) 0 , 1 ,…, k+r are the unknown regression coefficients Z 1 i ,…, Z mi are the m instrumental variables (the excluded exogenous variables ) The coefficients are overidentified if m > k ; exactly identified if m = k; and underidentified if m < k . 7 TSLS with a single endogenous regressor Y i = 0 + 1 X 1 i + 2 W 1 i + … + 1 +r W ri + u i m instruments: Z 1 i ,…, Z m First stage Regress X 1 on all the exogenous regressors: regress X 1 on W 1 ,…, W r , Z 1 ,…, Z m by OLS Compute predicted values 1 ˆ i X , i = 1,…, n Second stage Regress Y on 1 ˆ X , W 1 ,…, W r by OLS
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## This note was uploaded on 11/28/2010 for the course ECON Economics taught by Professor Davidbrownstone during the Spring '10 term at UC Irvine.

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Ch12ivPart2 - Midterm 2 Thursday November 18 Closed book...

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