Training the Next Generation

Using Big Data to Solve Economic and Social Problems

 

A central part of Opportunity Insights’ mission is to train the next generation of researchers and policy leaders on methods to study and improve economic opportunity and related social problems. This page provides lecture materials and videos for a course entitled “Using Big Data Solve Economic and Social Problems,” taught by Raj Chetty and Greg Bruich at Harvard University.

This course provides an introduction to modern applied economics in a manner that does not require any prior background in economics or statistics. It is intended to complement traditional Principles of Economics (Econ 101) courses. Topics include equality of opportunity, education, health, the environment, and criminal justice. In the context of these topics, the course provides an introduction to basic statistical methods and data analysis techniques, including regression analysis, causal inference, quasi-experimental methods, and machine learning.

The course was most recently taught at Harvard in Spring 2019, and, with an enrollment of 375 students, was one of the largest classes in the university. The course also increased gender diversity in Economics: 49% of the students who took the course were women, higher than in any other undergraduate Economics course taught at Harvard in the past academic year (among classes with at least 20 students). To learn more about the motivation for this class and its impact, see this article.Partner With Us to Train the Next Generation. Opportunity Insights is eager to partner with and support college professors and high school teachers who may be interested in using these teaching materials in their own courses. If you are interested in joining a network of peers working together to scale this new approach to teaching social science, please contact Gregory Bruich. If you want to do this type of work yourself, consider applying for a two-year pre-doctoral research fellowship with our team.

 

Lecture Materials

Materials

Course Syllabus

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Complete Set of 18 Lectures

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Lecture 1
The Geography of Upward Mobility in America

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Lecture 2
Causal Effects of Neighborhoods

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Lecture 3
Moving to Opportunity vs. Place-Based Approaches

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Lecture 4
The American Dream in Historical Perspective

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Lecture 5
Upward Mobility, Innovation, and Economic Growth

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Lecture 6
Higher Education and Upward Mobility

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Lecture 7
The Causal Effect of Colleges

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Lecture 8
Primary Education

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Lecture 9
Teachers and Charter Schools

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Lecture 10
Racial Disparities in Economic Opportunity

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Lecture 11
Improving Health Outcomes

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Lecture 12
The Economics of Health Care and Insurance

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Lecture 13
Improving Judicial Decisions

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Lecture 14
Effects of Air and Water Pollution

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Lecture 15
Policies to Mitigate Climate Change

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Lecture 16
Income Taxation

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Lecture 17
Behavioral Public Economics

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Lecture 18
Institutions and Economic Development

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Empirical Project 1
Stories from the Atlas: Describing Data using Maps, Regressions, and Correlations

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Empirical Project 2
Do Smaller Classes Improve Test Scores? Evidence from a Regression Discontinuity Design

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Empirical Project 3
The Creating Moves to Opportunity (CMTO) Experiment

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Empirical Project 4
Using Google DataCommons to Predict Social Mobility

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To see the previous version of this class, taught at Stanford in 2017

Click Here
Are you interested in joining a network of peers working together to scale this approach to teaching social science?