Learning Collider
@learncollider
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Building AI that Expands Human Opportunity Housing, Education, Workforce Nonprofit research lab founded by @peterbergman_ (@UTAustinEcon, @JPAL, @NBERpubs)
Joined April 2020
A practical guide to recent econometric advances with shift-share instruments, from @borusyak, @instrumenthull, and @Xjaravel
https://t.co/EZxtWXCyoG
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How can we improve access to quality education for all? Affordable Housing, @GreatSchools & J-PAL affiliate @PeterBergman_ highlight the impact of evidence on housing choices. Watch the full story🔽
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New working paper with @m_sendhil and Jens Ludwig on using LLM outputs in empirical research. Thread coming soon. Link to paper:
arxiv.org
Large language models (LLMs) are being used in economics research to form predictions, label text, simulate human responses, generate hypotheses, and even produce data for times and places where...
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📣A/B testing, common in tech, has massive potential to maximize impact in the social sector. Check out our new Insight Note @WWHGlobalEd @youthimpactorg: ➡️"A/B testing in education: rapid experimentation to optimise programme cost-effectiveness" https://t.co/cyHJHV25MD
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#EconTwitter I'm very excited to present our new working paper ( https://t.co/Gv6yOB9DPA) at @BrownUniversity tomorrow! Thanks for hosting me! A mid-sized 🧵 TL;DR: "Racial differences in income unable to explain a meaningful share of gaps in ambient air pollution exposure."
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Creating Moves to Opportunity: Experimental Evidence on Barriers to Neighborhood Choice @peterbergman_, Raj Chetty, Stefanie Deluca, @nhendren82, @lkatz42, Christopher Palmer Quotes: https://t.co/kCCDGxNq06 More:
learningcollider.org
Abstract: “The findings imply that most low-income families do not have a strong preference to stay in low-opportunity areas; instead, barriers in the housing search process are a central driver of...
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A common assumption is that families with Section 8 vouchers prefer to live in low-opportunity neighborhoods. What if that's not the case? Turns out, barriers to higher-opportunity neighborhoods play a major role in where low-income Americans end up living.
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Very excited that "Building Non-Discriminatory Algorithms in Selected Data" (with David Arnold & Will Dobbie) is now forthcoming at AER: Insights! This is the third (& final?) chapter of a series of AEA papers using IV methods to measure and reduce discrimination in high-stakes
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🎧#Listen to the latest podcast episode from @vox_dev featuring @WWHGlobalEd Academic Director @angrist_noam where he discusses the gap between policy and practice in education📚 based on an assessment of 50 countries during COVID-19. #VoxDevTalks
https://t.co/vlszib17YN
voxdev.org
There are large gaps between policy and practice in education. New systematic analysis shines a light on this 'policy-practice' gap in 50 countries during COVID-19 and motivates increased focus on...
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Alis paper develops new tools to measure discrimination in eviction filings, and uncovers a lot of it. I learned a ton in talking to her about this important work. Very well deserved!
Congratulations to Alison Lodermeier (PhD '24) for winning the 2024 APPAM PhD Dissertation Award for her dissertation "Essays on the Economics of Eviction." Amazing work Alison!
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Today at @TheLBJSchool -> @UTAustinEcon & Learning Collider's very own @peterbergman_ speaking on AI in Teaching & Learning. Go, Peter!
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At least one in six workers in management, business, and computer-related occupations is using generative AI at work every day. Also, 22% of blue collar workers use AI. From our new paper, "The Rapid Adoption of Generative AI": https://t.co/lCJwK5Xxia
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Looking forward to virtually tuning in. Fantastic line up, @WWHGlobalEd!
Excited to present our A/B testing work at the @WWHGlobalEd conference this week! Sharing insights from 10 rapid A/B tests on scaling and cost-effectiveness-boosting strategies in Ed. @youthimpactorg @angrist_noam @janica_magat
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Had a brilliant time at #AFE in London. Inspiring talks by @Econ_4_Everyone @Susan_Athey @orianabandiera @singhabhi @RDMetcalfe +more. A treat to join a panel moderated by @Econ_4_Everyone on the "science of using science" 👇a slide from my talk & link: https://t.co/ml76bTfhRX
We are excited for the Advances with Field Experiments (AFE) conference to start tomorrow. First of all, thank you to @LSEnews @LSEGeography for helping us put on the conference in a beautiful campus location in a fantastic city! #afe2024 @Econ_4_Everyone @Sefi_Roth_
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Please RT/spread the word about this online causal inference course! Starting September 9th -- I'm very excited for it!
I had a great time teaching a minicourse on design-based econometrics in Bergen last week. See attached for a snapshot of what we talked about! For those outside of Norway, I'll be teaching a version of the course online in two weeks. Sign up here! https://t.co/2UtusYvt5m
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Reasons I love this Yglesias-FAS collab: activates a nerdy readership towards policy action and entrepreneurship. More please!
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We're excited to share that our Founder and Director, @peterbergman_, is a proposed speaker for #SXSWEDU on the panel "Seeding Innovation: The Power of Breakthrough Funding." Help make this session happen by voting and commenting here. ⤵️
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Learn how transformative funding is empowering trailblazers and propelling innovation during the "Seeding Innovation: The Power of Breakthrough Funding" session at #SXSW 2025! Community voting is open til Aug 18! @WaltonFamilyFdn @RenPhil21 @learncollider
https://t.co/szzJmxbOpx
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Excited to see @ALeighMP cite our RCT on the effectiveness of a phone-based math program in the Philippines. @youthimpactorg is proud to collaborate w/ @poverty_action @DepEd_PH @unicefphils on this cost-effective initiative, now scaling & undergoing govt A/B tests! 📈📚✨#RCTs
"Evidence-Based Development”: my speech on randomised trials in development, delivered at an Asian Development Bank conference in honour of Peter McCawley https://t.co/Gp4mEXLfZw
#auspol @adb_hq @AusAmbPH #randomistas
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This was an extremely fun paper to be a part of! How can we evaluate whether a transformer has uncovered the right "world model"?
New paper: How can you tell if a transformer has the right world model? We trained a transformer to predict directions for NYC taxi rides. The model was good. It could find shortest paths between new points But had it built a map of NYC? We reconstructed its map and found this:
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