Articles/ Journals and Videos related to Economics:chart_with_upwards_trend: and Data Science :bar_chart:
Resources at the intersection of Economics and Data Science
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:page_facing_up: Articles - exploring the intersection of these two fields | :clipboard:Academic Papers - Research papers by Economists/ Statisticians on ML and Economics | :tv: Videos/ Lectures - Lectures given by Economists on ML/ Data Science |
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:woman: :man: Economists/Data Scientists - Economists working as Data Scientists in Industry and Academia | :mortar_board: Courses & Syllabus - Syllabus and courses which are at the intersection of Data Science and Economics |
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
Are current trends in econ methodology just fads? Noah Smith
Two Cousins Meet Avinash Tripathi
Causal Inference and Machine Learning Guido Imbens
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
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: 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
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
Machine Learning: What's in it for Economics - Playlist Univ. of Chicago
Machine Learning Meets Economics: Using Theory, Data, and Experiments to Design Markets
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
Matthew Harding : University of California - Irvine
David Broockman : Stanford University
Andrew B. Hall : Stanford University
Ariel Procaccia : Carnegie Mellon University
Dario Sansone : Phd Candidate Georgetown University
Soubhik Barari : Harvard University
Companies like Airbnb, Microsoft and Amazon have huge teams which is filled with Economists
Economist | Company | Comment |
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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 |
MIT has started a new Major for Undergraduates. The Program aims to impart students skills from Data Science and Economics
Machine Learning and Econometrics (Susan Athey, Guido Imbens) - Stanford University
ECON 45: Using Big Data to Solve Economic and Social Problems - Raj Chetty @ Stanford University
Data Science for Politics - Stanford University
Machine Learning and Data Science in Politics - In Song Kim @ MIT
Machine Learning and Causal Inference - Susan Athey @ Stanford University
Big Data - Daniel Bjorkegren @ Brown University
Data Analysis for Social Scientists- Esther Duflo & Sara Fisher @ MITx
R-Based High Performance Computing for Social Science- Soubhik Barari @ MIT
Field Experiments - David Reiley @ UC Berkley
Industrial Organization and Data Science - Justin Rao @ Microsoft
Data Science for Game Theory and Pricing - Jacob @ Microsoft
Designing the Digital Economy - Glen Weyl @ Yale
Enviornmental Economics and Data Science - Grant McDermott @ University of Oregon
Data for Sustainable Development - Marshall Burke, Stefano Ermon, David Lobell @ Stanford University