Department of Economics University of Chicago Department of Economics

Economics 312, Empirical Analysis III
Spring 2019

Instructors: Lecture times: Tuesday and Thursday, 5:00 - 6:20pm
Lecture classroom: Saieh 146
Teaching Assistants: TA session times: Wednesday, 6:30 - 7:20pm NOTE: TA Sesson on May 29 will be from 7pm - 8pm due to an event.
TA session classroom: Saieh 146

TA Office Hours: 4pm - 5pm, Monday and Friday
TA Office Hours Room: Graduate Lounge, Saieh Hall, Room 201

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Class Overview

This is the third course in the first year empirical economics sequence in the Department of Economics. The goal of this course is to teach economics students to learn from data. The course stresses the use of various econometric methodologies to explain the phenomena and test models in order to address economic policy questions, broadly defined. A variety of approaches will be presented reflecting the interests and training of the two instructors who will co-teach this quarter. They will each take roughly half of the total course time, but in various formats. Heckman will post handouts for each of his lectures. There will also be a weekly tutorial taught by the teaching assistants.

Class Requirements

A final and a series of problem sets due each week in class. Assignments will include both analytical problems and empirical problems that will require the use of statistical software. There will be no midterm exam.

Problem Set Requirements

Problem Sets will be due each week on Tuesday in the beginning of the class. Please submit both a paper copy (hand in to TA) and upload an electronic version to Canvas (no late submissions to Canvas are accepted). Any programming language is accepted for the simulation exercises. If students have any questions on Problem Sets they should first ask TAs and only ask the professors if the TAs are unable to help.

Syllabus, Part 1: Defining Parameters and Arguing Their Policy Relevance

NOTE: Readings marked with an * are essential reading.

Week 1

Defining Paramters and Arguing Their (Policy) Relevance

Randomized Controlled Trials

Week 2: Controlling for Observables


LaLonde's paper and the subsequent discussion over matching estimators

Weeks 3 and 4: Instrumental Variables

Local Average Treatment Effects (and its extensions)

A few examples of studies coming up, applying and arguing the exogeneity (and sometimes policy relevance) of the instruments:

Weak Instruments

Week 5: Analysis of Repeated Cross-Sections and Panel Data


Event Studies and Synthetic Control

More on Panel Data

Link to Part 2: Alternative Approaches to Learning from Data