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Table of Contents

• Articles - Articles exploring the intersection of these two fields

• Academic Papers - Research papers by Economists/ Statisticians on ML and Economics

• Videos / Lectures - Lectures given by Economists on ML/ Data Science

• Economists / Data Scientists - Economists working as Data Scientists in Industry and Academia

• Program / Courses - Syllabus and courses which are at the intersection of Data Science and Economics

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Articles

Unfortunately many articles are behind paywall now, especially old Bloomberg ones.

Field Overview

• Breaking the Spell That Grips Economics Noah Smith - Bloomberg

• Economics Struggles to Cope With Reality Noah Smith - Bloomberg

• All of a Sudden, Economists Are Getting Real Jobs Noah Smith - Bloomberg

• Data Geeks Are Taking Over Economics Noah Smith - Bloomberg

• Theory Versus Data? You Shouldn’t Have to Choose Noah Smith - Bloomberg

• Goodbye, Ivory Tower. Hello, Silicon Valley Candy Store Steve Lohr - NYT

• How Economics Went From Theory to Data Justin Fox - Bloomberg

• Quora Session with Susan Athey Susan Athey- Stanford GSB Prof.

• Economics Gets Real Noah Smith - Bloomberg

• Hunting for a Hot Job in High Tech? Try ‘Digitization Economist Roberta Holland - Working Knowledge

• Uber’s secret weapon is its team of economists Alison Griswold - Quartz

• Why Uber Is an Economist’s Dream Stephen J. Dubner - Freakonomics

• Susan Athey Interview: Applying Machine Learning to the Economy Stanford GSB

• Sexy and Social Data Scientists Forbes Article

• Computer Science Is Coming for Economics Vishal Wilde

• Micro stars, macro effects Economist Article

• Economists are prone to fads, and the latest is machine learning Economist Article- 2012
  • A critical piece by Economist on the surge of ML in Econ. This was followed by counter argument by Noah Smith

• Are current trends in econ methodology just fads? Noah Smith

• Two Cousins Meet Avinash Tripathi

• Causal Inference and Machine Learning Guido Imbens

Articles by Practitioners

• Teconomics- Economists in Tech - Emily Glassberg Sands & Duncan Gilchrist

  • Machine Learning for Decision Making - Emily Glassberg Sands & Duncan Gilchrist

  • How to Use Machine Learning to Accelerate A/B Testing - Emily Glassberg Sands & Duncan Gilchrist

  • Machine Learning Meets Instrumental Variables - Emily Glassberg Sands & Duncan Gilchrist

• Stanford is Using Machine Learning on Satellite Images to Predict Poverty- Analytics Vidhya

• Economic Predictions with Big Data: The Illusion of Sparsity - NY Federal Reserve

• Refining the “science” of political science (MIT)- MIT PolSc

  • Political Methodology Lab- MIT PolSc

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Academic Papers

Journal of Economics Perspective Symposiums

• Recent Ideas in Econometrics (Spring 2017)

  • The State of Applied Econometrics: Causality and Policy Evaluation - Susan Athey & Guido W. Imbens

  • Machine Learning: An Applied Econometric Approach - Sendhil Mullainathan & Jann Spiess

  • The Use of Structural Models in Econometrics - Hamish Low & Costas Meghir

  • Twenty Years of Time Series Econometrics in Ten Pictures - James H. Stock & Mark W. Watson

  • Identification and Asymptotic Approximations: Three Examples of Progress in Econometric Theory - James L. Powell

• Big Data (Spring 2014)

  • Big Data: New Tricks for Econometrics - Hal Varian

  • High-Dimensional Methods and Inference on Structural and Treatment Effects - Alexandre Belloni, Victor Chernozhukov, Christian Hansen

  • Political Campaigns and Big Data - David W. Nickerson & Todd Rogers

  • Privacy and Data-Based Research - Ori Heffetz & Katrina Ligett

• Econometrics Tools (Fall 2011) - Various papers and authors

• Con out of Economics (Spring 2010)

  • Taking the Dogma out of Econometrics: Structural Modeling and Credible Inference - Nevo and Whinston

  • But Economics Is Not an Experimental Science - C. Sims

  • The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics - Angrist and Pischke

  • A Structural Perspective on the Experimentalist School - M.P Keane

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• Beyond Big Data - Hal Varian

Susan Athey Papers- Prof. of Economics @ Stanford Graduate School of Business

• Economists (and Economics) in Tech Companies

• The Impact of Machine Learning on Economics

• Beyond prediction: Using big data for policy problems

• Machine Learning Methods for Causal Effects

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Videos/Lectures

Susan Athey Videos - Prof. of Economics @ Stanford Graduate School of Business

• How Big Data Is Changing Economies

• Machine Learning and Causal Inference for Policy Evaluation

  • Machine Learning and Causal Inference for Policy Evaluation

• Sackler Big Data Colloquium

• Artificial Intelligence: The Economic and Policy Implications-Keynote

Hal Varian Videos - Chief Economist @ Google

• Google and social science research

• Using Google Data for Short-term Economic Forecasting

• Economics & Technology: Careers Blending Two Fields

• [**Data On Purpose

  Do Good Data: Casual Inference Meets Big Data**](http://bit.ly/2E178sG)

Sendhil Mullainathan Videos - Prof. of Economics @ Harvard University

• Machine Intelligence and Public Policy

• Machine Learning and Prediction in Economics and Finance

• Machine Learning: What’s in it for Economics - Playlist Univ. of Chicago

• Machine Learning Meets Economics: Using Theory, Data, and Experiments to Design Markets

• Smarter Algorithms, Better Policy

Other Videos

• Why Economics Needs Data Mining Cosma Shalizi(CMU)

• Machinistas meet Randomistas: useful ML tools for Empirical Researchers Esther Duflo

• The Economics of Artificial Intelligence & Income Distribution Jeffrey Sachs

• Human Decisions and Machine Predictions Jon Kleinberg (Cornell)

• The Challenge of Big Data for the Social Sciences Kenneth Benoit, Kenneth Cukier

• Data Science from the Perspective of an Applied Economist Scott Nicholson

• From Economist to Data Scientist: How our discipline can participate in the growth of analytics Kenneth Sanford

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Economists/Data Scientists

Academia

 

Person	Affiliation	Comments
Matthew Harding	University of California - Irvine	Check the Deep Data Lab
David Broockman	Stanford	-
Andrew B. Hall	Stanford	-
Ariel Procaccia	CMU	-
Dario Sansone	Georgetown University	Dario has compiled an informative list on ML and Economics
Soubhik Barari	Harvard University	-
Matteo Courthoud	University of Zurich	Matteo has very good teaching resources on his website

Industry

 

Economist	Company	Comment
Emily Glassberg Sands	Coursera	Data Science Head
Jed Kolko	Indeed	Chief Economist
David H Reiley	Pandora	Economist- Advertising Science
Jacob LaRiviere	Microsoft	Economist
Dan Goldstein	Microsoft	Economist
Matt Goldman	Microsoft	Economist - Studies online economic behavior and decision making
Justin M. Rao	Microsoft	Economist -Member of interdisciplinary research group combining social science with computational and theoretical methods

• Companies like Airbnb, Microsoft and Amazon have huge teams which is filled with Economists

• Amazon Economist Jobs
  • Also check Economics @ Amazon
• Microsoft Research: Economics Group

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Courses/ Degrees

Course/Degree	Type	Institution	Prof	Detail type
M.S. Economics & Computation	Masters Degree	Duke	-
Computer Science , Economics and Data Science	Bachelors Degree	MIT	-
Machine Learning and Data Science in Politics	Course	MIT	In Song Kim
Data Analysis for Social Scientists	Course	MIT	Esther Duflo & Sara Fisher
R-Based High Performance Computing for Social Science	Course	MIT	Soubhik Barari
Data Science for Politics	Course	Stanford
Machine Learning and Causal Inference	Course	Stanford	Susan Athey
Data for Sustainable Development	Course	Stanford	Marshall Burke, Stefano Ermon, David Lobell
Big Data	Course	Brown	Daniel Bjorkegren
Using Big Data to Solve Economic and Social Problems	Course	Harvard	Raj Chetty
Industrial Organization and Data Science	Course	Microsoft	Justin Rao
Data Science for Game Theory and Pricing	Course	Microsoft	Jacob
Machine Learning and Econometrics	Course	Stanford/Berkley	Susan Athey, Guido Imbens
Enviornmental Economics and Data Science	Course	University of Oregon	Grant McDermott
Designing the Digital Economy	Course	Yale	Glen Weyl		Machine Learning for Economics	Course Notes	University of Zurich	Matteo Courthoud/ Damian Kozbur