Lecture 1.5 Intro to Causal Inference PDF

Lecture 1.5 Intro - Causal Inference Introduction to Econometrics Econ 281 1 Introduction Lets take a moment and focus What is this all about

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1 Causal Inference Introduction to Econometrics Econ 281
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3 Introduction Let’s take a moment and focus……… What is this all about?? FINDING AND EXPLORING CAUSAL RELATIONSHIPS BETWEEN ECONOMIC VARIABLES USING ECONOMETRIC ANALYSIS!!
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4 Introduction Here are some questions to illustrate what we are after? Does another year of education CAUSE an increase in earnings? Does hiring more teachers per student CAUSE an increase in student test scores? Does training unemployed workers CAUSE them to have higher post-unemployment earnings? Let’s provide a more formal description…
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A simple Example Earnings/Education Hans Franz High School 20,000 College 50,000 5 Let’s look at two people (Austrian Body Builders) and their earning to figure out the returns to education 4 more years of education seem to yield $30,000 Returns to education = $7,500 per year Is this correct?
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What assumptions are necessary to interpret our estimate as the CAUSAL effect of education on earnings? A1: Hans’ college earning would be $50,000 A2: Franz’ high school earnings would be $20,000 Is this a realistic assumption? NO!!!! A simple Example Earnings/Education Hans Franz High School 20,000 20,000 College 50,000 50,000 6
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Let’s assume that Franz has more ability (motivation, IQ etc.) than Hans. Franz would probably make more money at any level of education, so the table would look like Now we can calculate the average return to education Return = ½*$2,500 + ½*$5,000 = $3,750 A simple Example Earnings/Education Hans Franz High School 20,000 30,000 College 30,000 50,000 7
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We see that our original estimate was too high and did NOT reflect the causal effect of schooling on wages We neglected the fact that, based on potential earnings, more able individuals might CHOOSE more schooling The potential outcome (earnings) determines the treatment (Education We will formalize this a little more A simple Example 8
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The example also illustrated that we need to use one individual as a counterfactual for another COUNTERFACTUAL = Describes what would have happened had an individual NOT taken a certain action Examples: My earning had I paid attention in school My life satisfaction had I not married The point here is that we DON’T EVER observe the counterfactual A simple Example 9
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10 The Roy-Rubin Potential Outcome Framework Let’s assume that there is a binary treatment (i.e. high school vs. college) We can then define the following 0 potential Earning of individual i when not treated i Y = 1 potential Earning of individual i when treated i Y = 1 if treated 0 if not treated i D =
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11 RRPOF We are interested in Problem: Unless we can observe parallel universes we can never observe an individual in both states!!
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This note was uploaded on 11/17/2009 for the course ECON 339 taught by Professor Habermalz during the Spring '09 term at Northwestern.

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Lecture 1.5 Intro - Causal Inference Introduction to Econometrics Econ 281 1 Introduction Lets take a moment and focus What is this all about

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