Resources at the intersection of Data Science and Economics/ Social Science/ Policy
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Articles - Articles exploring the intersection of these two fields
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Academic Papers - Research papers by Economists/ Statisticians on ML and Economics
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Videos/ Lectures - Lectures given by Economists on ML/ Data Science
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Economists/Data Scientists - Economists working as Data Scientests in Industry and Academia
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Courses & Syllabus - Syllabus and courses which are at the intersection of Data Science and Economics
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Breaking the Spell That Grips Economics Noah Smith - Bloomberg
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Economics Struggles to Cope With Reality Noah Smith - Bloomberg
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All of a Sudden, Economists Are Getting Real Jobs Noah Smith - Bloomberg
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Data Geeks Are Taking Over Economics Noah Smith - Bloomberg
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Theory Versus Data? You Shouldn't Have to Choose Noah Smith - Bloomberg
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Goodbye, Ivory Tower. Hello, Silicon Valley Candy Store Steve Lohr - NYT
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How Economics Went From Theory to Data Justin Fox - Bloomberg
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Quora Session with Susan Athey Susan Athey- Stanford GSB Prof.
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Economics Gets Real Noah Smith - Bloomberg
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Susan Athey Interview: Applying Machine Learning to the Economy Stanford GSB
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Sexy and Social Data Scientists Forbes Article
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Computer Science Is Coming for Economics Vishal Wilde
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Micro stars, macro effects Economist Article
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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
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Are current trends in econ methodology just fads? Noah Smith
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Two Cousins Meet Avinash Tripathi
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Causal Inference and Machine Learning Guido Imbens
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Teconomics- Economists in Tech - Emily Glassberg Sands & Duncan Gilchrist
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Machine Learning for Decision Making - Emily Glassberg Sands & Duncan Gilchrist
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How to Use Machine Learning to Accelerate A/B Testing - Emily Glassberg Sands & Duncan Gilchrist
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Machine Learning Meets Instrumental Variables - Emily Glassberg Sands & Duncan Gilchrist
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Stanford is Using Machine Learning on Satellite Images to Predict Poverty- Analytics Vidhya
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Economic Predictions with Big Data: The Illusion of Sparsity - NY Federal Reserve
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Recent Ideas in Econometrics (Spring 2017)
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The State of Applied Econometrics: Causality and Policy Evaluation - Susan Athey & Guido W. Imbens
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Machine Learning: An Applied Econometric Approach - Sendhil Mullainathan & Jann Spiess
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The Use of Structural Models in Econometrics - Hamish Low & Costas Meghir
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Twenty Years of Time Series Econometrics in Ten Pictures - James H. Stock & Mark W. Watson
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Identification and Asymptotic Approximations: Three Examples of Progress in Econometric Theory - James L. Powell
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Big Data: New Tricks for Econometrics - Hal Varian
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High-Dimensional Methods and Inference on Structural and Treatment Effects - Alexandre Belloni, Victor Chernozhukov, Christian Hansen
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Political Campaigns and Big Data - David W. Nickerson & Todd Rogers
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Privacy and Data-Based Research - Ori Heffetz & Katrina Ligett
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Econometrics Tools (Fall 2011) - Various papers and authors
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Con out of Economics (Spring 2010)
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Taking the Dogma out of Econometrics: Structural Modeling and Credible Inference - Nevo and Whinston
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The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics - Angrist and Pischke
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A Structural Perspective on the Experimentalist School - M.P Keane
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- Beyond Big Data - Hal Varian
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Machine Learning: What's in it for Economics - Playlist Univ. of Chicago
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Machine Learning Meets Economics: Using Theory, Data, and Experiments to Design Markets
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Why Economics Needs Data Mining Cosma Shalizi(CMU)
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The Economics of Artificial Intelligence & Income Distribution Jeffrey Sachs
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Human Decisions and Machine Predictions Jon Kleinberg (Cornell)
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From Economist to Data Scientist: How our discipline can participate in the growth of analytics
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Matthew Harding : University of California - Irvine
- Check the Deep Data Lab
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David Broockman : Stanford University
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Andrew B. Hall : Stanford University
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Ariel Procaccia : Carnegie Mellon University
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Companies like Airbnb, Microsoft and Amazon have huge teams which is filled with Economists
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- Also check Economics @ Amazon
Economists | Company | Comments |
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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 |
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Machine Learning and Econometrics (Susan Athey, Guido Imbens) - Stanford University
- There are videos and course material available
- Course Material
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ECON 45: Using Big Data to Solve Economic and Social Problems - Raj Chetty @ Stanford University
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Data Science for Politics - Stanford University
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Machine Learning and Causal Inference - Susan Athey @ Stanford University
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Big Data - Daniel Bjorkegren @ Brown University
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Data Analysis for Social Scientists- Esther Duflo & Sara Fisher @ MITx
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Field Experiments - David Reiley @ UC Berkley
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Industrial Organization and Data Science - Justin Rao @ Microsoft
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Data Science for Game Theory and Pricing - Jacob @ Microsoft
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Designing the Digital Economy - Glen Weyl @ Yale
- Digitization is transforming a variety of markets from personal transportation services to advertising. This course explores the economic tools (market design, price theory, causal inference, etc.) and technical tools from computer science (machine learning, the analysis of algorithms, user interface design, etc.) students need to contribute meaningfully to this transformation.