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Section_6_Spring2008

Section_6_Spring2008 - Ashenfelter and Krueger(1994 Econ...

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Ashenfelter and Krueger (1994) Econ 142 Spring 2008 Raymundo M. Campos-Vazquez February 27, 2008 Contents 1 Ashenfelter and Krueger (1994) 1 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Ignoring Biases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3.1 OLS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3.2 GLS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3.3 Measurement Error . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.4 Solving Biases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.4.1 Measurement Error: Average . . . . . . . . . . . . . . . . . . . . . . 4 1.4.2 Fixed E/ects - First Di/erencing . . . . . . . . . . . . . . . . . . . . 5 1.4.3 IV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.4.4 IV+Fixed E/ects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.5 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1 Ashenfelter and Krueger (1994) 1.1 Motivation Ashenfelter and Krueger (1994) is a famous and interesting paper in economics. The paper is famous because the methodology is clean and the identi°cation strategy is very interesting 1
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(i.e. they collected their data, etc). I strongly recommend reading carefully this paper as well as to spend time understanding Problem Set 2. We are interested in the causal e/ect of education on earnings. Suppose we have the following regression: Y i = ° + ±S i + e i (1) where Y is log wages and S is years of schooling. In order to °nd the causal e/ect of schooling on wages we need Cov ( e; S ) = 0 : This is a strong assumption. The assumption is not satis°ed because Schooling is not exogenous. You pick your own level of schooling, and you decide your level of schooling for some reason and probably this reason is correlated with other components that determine earnings at the same time. If this is the case, the OLS estimators are biased. Ashenfelter and Krueger (1994) [AK] try to disentangle di/erent biases in order to obtain the causal e/ect of education on earnings. 1.2 Estimation We may think in two type of biases in Equation (1). These are not the only ones but are the ones that AK deal with. On one hand, ability or family background is often taken as the principal determinant in biasing the returns to education. On the other hand, the second bias is measurement error in schooling. We know that classical measurement error in the independent variable biases the OLS estimator towards zero. We will deal with the consequences of doing nothing and then we will move on to possible solutions.
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