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<!DOCTYPE html>
<html lang="en">
<head>
<!-- Global site tag (gtag.js) - Google Analytics -->
<script async src="https://www.googletagmanager.com/gtag/js?id=UA-176728098-1"></script>
<script>
window.dataLayer = window.dataLayer || [];
function gtag(){dataLayer.push(arguments);}
gtag('js', new Date());
gtag('config', 'UA-176728098-1');
</script>
<meta charset="utf-8">
<title>ML for Economic Policy - NeurIPS 2020</title>
<meta name="description" content="">
<meta name="author" content="">
<!-- Mobile Specific Metas -->
<meta name="viewport" content="width=device-width, initial-scale=1">
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<link href="https://fonts.googleapis.com/css?family=Alegreya+Sans:100,400,700|Alegreya+Sans+SC:300|Source+Code+Pro:300|Open+Sans:300&display=swap" rel="stylesheet">
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</script>
</head>
<body>
<div class="container">
<div class="row">
<div class="header text-center banner">
</div>
<div class="header text-center">
<h1>
ML FOR ECONOMIC POLICY
</h1>
<h5>
FRIDAY DECEMBER 11, NEURIPS 2020
</h5>
</div>
<div class="header text-center">
<a href="#talks">Talks</a> -
<a href="#papers">Papers</a> -
<a href="#organizers">Organizers</a>
</div>
</div>
<div class="row teaser">
<div class="twelve columns">
<ul class="nodecoration-list teaser-questions">
<li>
Can machine learning be used to help with the development of effective economic policy?
</li>
<li>
Can we understand economic behavior through granular, economic data sets?
</li>
<li>
Can we automate economic transactions for individuals?
</li>
<li>
How can we build rich and faithful simulations of economic systems with strategic agents?
</li>
</ul>
<p>
Machine learning offers enormous potential to transform our understanding of economics, economic decision making, and public policy. Yet its adoption by economists, social scientists, and policymakers remains nascent.
</p>
<p>
This workshop will highlight both the opportunities as well as the barriers to the adoption of ML in economics. In particular, we aim to accelerate the use of machine learning to rapidly develop, test, and deploy effective economic policies that are grounded in representative data.
</p>
<p>
This workshop will expose some of the critical socio-economic issues that stand to benefit from applying machine learning, expose underexplored economic datasets and simulations, and identify machine learning research directions that would have a significant positive socio-economic impact. This includes policies and mechanisms that target socio-economic issues such as diversity and fair representation in economic outcomes, economic equality, and improving economic opportunity.
</p>
</div>
</div>
<!-- <div class="row teaser extend-width" id="speakers">
<div class="six columns">
<h2>KEYNOTE SPEAKERS</h2>
<ul class="nodecoration-list">
<li>Micheal Kearns (UPenn)</li>
<li>Susan Athey (Stanford)</li>
<li>Sendhil Mullainathan (University of Chicago)</li>
<li>Doina Precup (Deepmind, McGill)</li>
</ul>
</div>
<div class="six columns">
<h2>PANELISTS</h2>
<ul class="nodecoration-list">
<li>Sharad Goel (Stanford)</li>
<li>Daniel Bjorkegren (Brown)</li>
<li>Eva Tardos (Cornell)</li>
<li>Rediet Abebe (Harvard)</li>
<li>Thore Graepel (Deepmind, UCL)</li>
<li>Doyne Farmer (Oxford)</li>
<li>Marietje Schaake (Stanford)</li>
<li>Emma Pierson (Cornell)</li>
</ul>
</div>
</div> -->
<div class="row extend-width" id="talks">
<div class="twelve columns">
<h2>
Introduction
</h2>
</div>
<div id="presentation-embed-00000000"></div>
</div>
<div class="row extend-width">
<div class="twelve columns">
<h2>
Michael Kearns
</h2>
</div>
<div id="presentation-embed-00000001"></div>
</div>
<div class="row extend-width">
<div class="twelve columns">
<h2>
Best Paper (Empirical)
</h2>
</div>
<div id="presentation-embed-00000002"></div>
</div>
<div class="row extend-width">
<div class="twelve columns">
<h2>
Doina Precup
</h2>
</div>
<div id="presentation-embed-00000003"></div>
</div>
<div class="row extend-width">
<div class="twelve columns">
<h2>
Panel Discussion: Algorithms & Methodology
</h2>
</div>
<div id="presentation-embed-00000004"></div>
</div>
<div class="row extend-width">
<div class="twelve columns">
<h2>
Susan Athey
</h2>
</div>
<div id="presentation-embed-00000005"></div>
</div>
<div class="row extend-width">
<div class="twelve columns">
<h2>
Best Paper (Methodology)
</h2>
</div>
<div id="presentation-embed-00000006"></div>
</div>
<div class="row extend-width">
<div class="twelve columns">
<h2>
Sendhil Mullainathan
</h2>
</div>
<div id="presentation-embed-00000007"></div>
</div>
<div class="row extend-width">
<div class="twelve columns">
<h2>
Panel Discussion: ML in Economics & Real-World Policy
</h2>
</div>
<div id="presentation-embed-00000008"></div>
</div>
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<div class="row" id="papers">
<div class="twelve columns">
<h2>
ACCEPTED PAPERS
</h2>
<p class="accepted_paper">
<span class="accepted_title">A Scalable Inference Method For Large Dynamic Economic Systems</span><br/>
<span class="accepted_authors">Pratha Khandelwal, Philip Nadler, Rossella Arcucci, William Knottenbelt and Yi-Ke Guo</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_16.pdf" target=_blank>PDF</a></span>
</p>
<p class="accepted_paper">
<span class="accepted_title">Kernel Methods for Policy Evaluation: Treatment Effects, Mediation Analysis, and Off-Policy Planning</span><br/>
<span class="accepted_authors">Rahul Singh, Liyuan Xu and Arthur Gretton</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_12.pdf" target=_blank>PDF</a></span>
<iframe width="560" height="315" src="https://www.youtube.com/embed/rttfjXZ1v4o" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</p>
<p class="accepted_paper">
<span class="accepted_title">Counterfactual Demand Predictions: Deep Learning with Microeconomic Theory</span><br/>
<span class="accepted_authors">Dong Soo Kim, Chul Kim, Mingyu Joo and Hai Che</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_2.pdf" target=_blank>PDF</a></span>
</p>
<p class="accepted_paper">
<span class="accepted_title">Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling</span><br/>
<span class="accepted_authors">Naveen Raman, Sanket Shah and John Dickerson</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_10.pdf" target=_blank>PDF</a></span>
</p>
<p class="accepted_paper">
<span class="accepted_title">Deep learning for understanding economic well-being in Africa from publicly available satellite imagery</span><br/>
<span class="accepted_authors">Christopher Yeh, Anthony Perez, Anne Driscoll, George Azzari, Zhongyi Tang, David Lobell, Stefano Ermon and Marshall Burke</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_30.pdf" target=_blank>PDF</a></span>
</p>
<p class="accepted_paper">
<span class="accepted_title">Where does the Stimulus go? Deep Learning for Commercial Banking Deposits</span><br/>
<span class="accepted_authors">Ni Zhan</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_21.pdf" target=_blank>PDF</a></span>
</p>
<p class="accepted_paper">
<span class="accepted_title">Regulating algorithmic filtering on social media</span><br/>
<span class="accepted_authors">Sarah Cen and Devavrat Shah</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_19.pdf" target=_blank>PDF</a></span>
</p>
<p class="accepted_paper">
<span class="accepted_title">Incentivizing Bandit Exploration: Recommendations as Instruments</span><br/>
<span class="accepted_authors">Daniel Ngo, Logan Stapleton, Vasilis Syrgkanis and Zhiwei Steven Wu</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_32.pdf" target=_blank>PDF</a></span>
</p>
<p class="accepted_paper">
<span class="accepted_title">Pandemic Response as Reinforcement Learning</span><br/>
<span class="accepted_authors">Blake Elias, Alex Siegenfeld and Yaneer Bar-Yam</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_29.pdf" target=_blank>PDF</a></span>
</p>
<p class="accepted_paper">
<span class="accepted_title">(Machine) Learning what Policymakers Value</span><br/>
<span class="accepted_authors">Daniel Bjorkegren, Joshua Blumenstock and Samsun Knight</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_7.pdf" target=_blank>PDF</a></span>
</p>
<p class="accepted_paper">
<span class="best_paper_tag">BEST EMPIRICAL PAPER AWARD</span><br/>
<span class="accepted_title">Estimating Policy Functions in Payment Systems using Reinforcement Learning</span><br/>
<span class="accepted_authors">Ajit Desai, Han Du, Francisco Rivadeneyra, Rodney Garratt and Pablo S Castro</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_15.pdf" target=_blank>PDF</a></span><br/>
<iframe width="560" height="315" src="https://www.youtube.com/embed/pTteVhSHlOU" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</p>
<p class="accepted_paper">
<span class="accepted_title">Mostly Harmless Machine Learning: Learning Optimal Instruments in Linear IV Models</span><br/>
<span class="accepted_authors">Jiafeng Chen, Daniel Chen and Greg Lewis</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_18.pdf" target=_blank>PDF</a></span><br/>
<iframe width="560" height="315" src="https://www.youtube.com/embed/tvkDVuXa3Dk" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</p>
<p class="accepted_paper">
<span class="accepted_title">Dynamic Pricing with Bayesian Updates from Online Reviews</span><br/>
<span class="accepted_authors">Andrew Xia, Jose Correa and Mathieu Mari</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_25.pdf" target=_blank>PDF</a></span>
</p>
<p class="accepted_paper">
<span class="accepted_title">A Multiagent Model of Efficient and Sustainable Financial Markets</span><br/>
<span class="accepted_authors">Betty Shea, Mark Schmidt and Maryam Kamgarpour</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_17.pdf" target=_blank>PDF</a></span>
</p>
<p class="accepted_paper">
<span class="accepted_title">Fairness Under Partial Compliance</span><br/>
<span class="accepted_authors">Jessica Dai, Sina Fazelpour and Zachary Lipton</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_20.pdf" target=_blank>PDF</a></span>
</p>
<p class="accepted_paper">
<span class="accepted_title">Learning and utility in multi-agent congestion control</span><br/>
<span class="accepted_authors">Pratiksha Thaker, Tatsunori Hashimoto and Matei Zaharia</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_34.pdf" target=_blank>PDF</a></span>
</p>
<p class="accepted_paper">
<span class="accepted_title">Reinforcement Learning of Simple Indirect Mechanisms</span><br/>
<span class="accepted_authors">Gianluca Brero, Alon Eden, Matthias Gerstgrasser, David C. Parkes and Duncan Rheingans-Yoo</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_27.pdf" target=_blank>PDF</a></span><br/>
<iframe width="560" height="315" src="https://www.youtube.com/embed/y_YkJ8mfqrc" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</p>
<p class="accepted_paper">
<span class="accepted_title">Bandit Data-driven Optimization: AI for Social Good and Beyond</span><br/>
<span class="accepted_authors">Zheyuan Ryan Shi, Zhiwei Steven Wu, Rayid Ghani and Fei Fang</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_6.pdf" target=_blank>PDF</a></span>
</p>
<p class="accepted_paper">
<span class="accepted_title">Right Decisions from Wrong Predictions: A Mechanism Design Alternative to Individual Calibration</span><br/>
<span class="accepted_authors">Shengjia Zhao and Stefano Ermon</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_36.pdf" target=_blank>PDF</a></span>
</p>
<p class="accepted_paper">
<span class="best_paper_tag">BEST METHODOLOGY PAPER AWARD</span><br/>
<span class="accepted_title">Empirical Welfare Maximization with Constraints</span><br/>
<span class="accepted_authors">Liyang Sun</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_14.pdf" target=_blank>PDF</a></span><br/>
<iframe width="560" height="315" src="https://www.youtube.com/embed/gqGOjph-4l0" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</p>
<p class="accepted_paper">
<span class="accepted_title">Certifying Strategyproof Auction Networks</span><br/>
<span class="accepted_authors">Michael Curry, Ping-Yeh Chiang, Tom Goldstein and John P. Dickerson</span><br/>
<span class="accepted_paper_files"><a href="papers/MLEconPolicy20_paper_4.pdf" target=_blank>PDF</a></span>
</p>
</div>
</div>
<div class="row" id="organizers">
<div class="twelve columns">
<h2>
ORGANIZATION
</h2>
</div>
<div class="twelve columns">
<div class="two columns organizer-tile">
<img src="images/nika.png" />
<p class="organizer-name">
Nika Haghtalab
</p>
<p class="organizer-affiliation">
Cornell
</p>
</div>
<div class="two columns organizer-tile">
<img src="images/annie.png" />
<p class="organizer-name">
Annie Liang
</p>
<p class="organizer-affiliation">
UPenn
</p>
</div>
<div class="two columns organizer-tile">
<img src="images/jamie.png" />
<p class="organizer-name">
Jamie Morgenstern
</p>
<p class="organizer-affiliation">
UW
</p>
</div>
<div class="two columns organizer-tile">
<img src="images/david.png" />
<p class="organizer-name">
David C. Parkes
</p>
<p class="organizer-affiliation">
Harvard
</p>
</div>
<div class="two columns organizer-tile">
<img src="images/alex.jpg" />
<p class="organizer-name">
Alex Trott
</p>
<p class="organizer-affiliation">
Salesforce
</p>
</div>
<div class="two columns organizer-tile">
<img src="images/stephan.jpg" />
<p class="organizer-name">
Stephan Zheng
</p>
<p class="organizer-affiliation">
Salesforce
</p>
</div>
</div>
</div>
<div class="row">
<div class="twelve columns">
<h2>
PROGRAM COMMITTEE
</h2>
<p><span class="reviewer_name">Alexander Trott</span>, <span class="reviewer_affiliation">Salesforce Research</span></p>
<p><span class="reviewer_name">Annie Liang</span>, <span class="reviewer_affiliation">University of Pennsylvania</span></p>
<p><span class="reviewer_name">Bhuvesh Kumar</span>, <span class="reviewer_affiliation">Georgia Institute of Technology</span></p>
<p><span class="reviewer_name">Bo Waggoner</span>, <span class="reviewer_affiliation">U. Colorado</span></p>
<p><span class="reviewer_name">Chara Podimata</span>, <span class="reviewer_affiliation">Harvard University</span></p>
<p><span class="reviewer_name">David Parkes</span>, <span class="reviewer_affiliation">Harvard University</span></p>
<p><span class="reviewer_name">Ellen Vitercik</span>, <span class="reviewer_affiliation">Carnegie Mellon University</span></p>
<p><span class="reviewer_name">Eric Sodomka</span>, <span class="reviewer_affiliation">Facebook</span></p>
<p><span class="reviewer_name">Gianluca Brero</span>, <span class="reviewer_affiliation">Harvard University</span></p>
<p><span class="reviewer_name">Hadi Elzayn</span>, <span class="reviewer_affiliation">University of Pennsylvania</span></p>
<p><span class="reviewer_name">James Wright</span>, <span class="reviewer_affiliation">University of Alberta</span></p>
<p><span class="reviewer_name">Jamie Morgenstern</span>, <span class="reviewer_affiliation">University of Washington</span></p>
<p><span class="reviewer_name">Jann Spiess</span>, <span class="reviewer_affiliation">Stanford Graduate School of Business</span></p>
<p><span class="reviewer_name">Kevin Lai</span>, <span class="reviewer_affiliation">Georgia Institute of Technology</span></p>
<p><span class="reviewer_name">Matthias Gerstgrasser</span>, <span class="reviewer_affiliation">University of Oxford</span></p>
<p><span class="reviewer_name">Nika Haghtalab</span>, <span class="reviewer_affiliation">Microsoft Research / Cornell</span></p>
<p><span class="reviewer_name">Nikhil Naik</span>, <span class="reviewer_affiliation">Salesforce</span></p>
<p><span class="reviewer_name">Stephan Zheng</span>, <span class="reviewer_affiliation">Salesforce</span></p>
<p><span class="reviewer_name">Sunil Srinivasa</span>, <span class="reviewer_affiliation">Salesforce Research</span></p>
<p><span class="reviewer_name">Zachary Schutzman</span>, <span class="reviewer_affiliation">University of Pennsylvania</span></p>
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