I am hiring PhD students and/or Postdocs, to work on the theory of explainable machine learning. Please apply through Ellis or IMPRS, deadlines end october/mid november. In particular: Women, where are you? Our community needs you!!! imprs.is.mpg.de/application ellis.eu/news/ellis-p...

🚨Job alert🚨 Premium tenure-track (ass to full prof) in "𝐌𝐋 𝐌𝐞𝐭𝐡𝐨𝐝𝐬 𝐢𝐧 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐚𝐧𝐝 𝐄𝐜𝐨𝐧𝐨𝐦𝐢𝐜𝐬" @unituebingen.bsky.social made possible by @ml4science.bsky.social Spread the word and feel free to reach out if you have any questions about the position or the environment. Link: shorturl.at/QHZ5G

The OutcomeWeights #RStats package now has a logo and a new vignette illustrating how Double ML improves covariate balance over "Single ML" RA or IPW. Check it out: mcknaus.github.io/OutcomeWeigh... #causalSky #causalML

Wir suchen jemanden, der im WS 25/26 unseren vakanten Lehrstuhl für Statistik und Quantitative Methoden in den Wirtschaftswissenschaften vertritt. Auch die Dauerstelle wird bald ausgeschrieben. Wir freuen uns über nette, engagierte Kollegen! Gerne teilen... Link im nächsten Post.

Our cluster Machine Learning for Science is up for 7 years more funding!

Excellent news! The "Machine Learning for Science" cluster is an incredible public good for researchers @unituebingen.bsky.social interested in ML in all its facets. Great job by @philipp.hertie.ai, @ulrikeluxburg.bsky.social and the cluster team.

We're super happy: Our Cluster of Excellence will continue to receive funding from the German Research Foundation @dfg.de ! Here’s to 7 more years of exciting research at the intersection of #machinelearning and science! Find out more: uni-tuebingen.de/en/research/... #ExcellenceStrategy

Junior Professorship (W1) with tenure track (W3) in Statistics and Empirical Economics #Econsky

🧵New survey paper: "Inference with Few Treated Units" Luis Alvarez, Bruno Ferman and Kaspar Wüthrich Tired of referees saying your standard errors are wrong? This survey will help you understand if you really have a problem — and, if so, how to fix it!

One of my favorite parts is running OLS within the DoubleML package of @philippbach.bsky.social and colleagues. Of course this is unnecessarily complicated, but instructive.

How can we design algorithms that maximize social welfare, rather than profits? This paper merges multi-armed bandits and adversarial learning with optimal tax theory and welfare economics. @maxkasy @NicoloCB @Rcolomboni buff.ly/pxPY8nj

One year ago I gave a #CausalML Workshop for Ukraine 🇺🇦 We hand-coded DoubleML and causal forest in very few lines of code to exactly replicate their package outputs. If you better understand theory through coding like me, check it out. You find the R notebook now online: shorturl.at/uM82n #RStats

🤖 Interested in machine learning, economics, and the state of AI?🤖 In September, I will teach a 1-week intensive version of my course on foundations of ML (maxkasy.github.io/home/ML_Oxfo...) in our summer school. Apply here: ouess.web.ox.ac.uk/september-su... Spread the word!

#EctJ published a SI celebrating the seminal contributions of Philip G. Wright to causal inference in economics. Both our editorial & reproduction of Wright (1928) are free to read. @resmedia.bsky.social @p-hunermund.com @borusyak.bsky.social @instrumenthull.bsky.social res.org.uk/celebrating-...

Interesting new paper: arxiv.org/pdf/2503.09907 improves on both rdrobust and rdhonest! Quite compelling... 1/n

It’s finally out! People, I’ve been hearing about this paper for so many years, but I am grateful it is out. Andrew Baker, Brantly Callaway, Scott Cunningham, Andrew Goodman-Bacon, Pedro H. C. Sant’Anna www.linkedin.com/posts/andrew... arxiv.org/abs/2503.13323

Just uploaded the first block of my lecture notes on econometrics with unobserved heterogeneity! 📊 Introduction and a block on average effects in linear models with heterogeneous coefficients — why standard estimators fail and a robust approach. Link below. #econsky

Our dept/faculty @[email protected] is looking for a senior scientist - to coordinate a new master program - to teach statistics & data science in that master (and beyond) German skills needed. Further details & online application at: lfuonline.uibk.ac.at/public/karri...

Among the many good things about support for 🇺🇦: Doing it together This coordination of donations is open until tomorrow 10am CET 👇 and support via any other channel is equally good, too.

we are looking for an Associate Professor (tenure track) in applied Economics, pls share: www.timeshighereducation.com/unijobs/list...

📣Now hiring: Predoc in Economics and Data Science We are hiring a predoc -- work at ETH Zurich on exciting projects in applied econ (political econ, education, etc.), using AI, NLP, and causal inference. Apply here: econjobmarket.org/positions/11505

🚀 Call for Papers: CREST-IFAU Workshop on Labor Market Policy Evaluation 📊 🗓 June 12-13, 2025 – Paris (Palaiseau) 🎤 Keynote: Stéphane Bonhomme (University of Chicago) 📅 Submit by: March 10, 2025 📩 Send papers (PDF) to: [email protected] @ifau.bsky.social

🚀 We’re hiring! Join Bernhard Schölkopf & me at @ellisinsttue.bsky.social to push the frontier of #AI in education! We’re building cutting-edge, open-source AI tutoring models for high-quality, adaptive learning for all pupils with support from the Hector Foundation. 👉 forms.gle/sxvXbJhZSccr...

Adding fixed effects is supposed to reduce bias — but under realistic parameter heterogeneity, it can make bias worse I wrote a post explaining how and why this can happen, with simulations and what you can do about it (Video: results summary) Links to post and Python code in replies #EconSky

We’re looking for a motivated researcher to apply for a Marie Skłodowska-Curie postdoc with our Econometrics & Data Science group at SDU! Focus: Causal Inference, Machine Learning, Big Data Full support for promising projects More info & apply: www.sdu.dk/en/om-sdu/in...

To continue the public good streak, here are some cool materials that our @emoryeconomics.bsky.social student, Marcelo Ortiz-Villavicencio, prepared for his independent studies. marcelortiz.com/ECON697R/ I am biased, but the slides are clear and relevant to many econometrics topics.

Some good strategies on how to deal with larger-than-memory data are covered in this book „Big Data Analytics“ by Ulrich Matter #rstats #EconSky #EcinBsky umatter.github.io/BigData/

Excited to share a new paper on ML-assisted randomization tests for detecting various treatment effects!

Are you estimating a first-difference (FD) regression, assuming that treatment changes randomly assigned? Happy to share new paper with two simple pieces of advice. papers.ssrn.com/sol3/papers.... Advice 1: start by regressing treatment change Delta D on baseline treatment D1.

A while coming, but happy to say that `parttree` is finally on CRAN. #rstats #dataviz Visualize simple decision tree partitions on the scale of the data. Useful for getting an intuitive sense of how your model has carved up the feature space. Works for both classification & regression tasks. 1/2

We use a new machine learning technique to identify the most cost-effective policies to boost immunization demand in India. We evaluated 75 combos of reminders, incentives, and local community ambassadors. The most effective increased immunization by 44%. https://buff.ly/4j0v3IF

I've gotten a flurry of requests to access my slides on "Models, Measurement, and Language in Economics" (presumably thanks to the great new year's reading list from @rohitlamba.bsky.social). The file is publicly available via my web page, but here is the link: www.dropbox.com/scl/fi/ntgkb...

🆕 New year, new working paper: Adventures in Demand Analysis using AI 🆕 Our question: How can we advance demand analysis using recent tools from AI (Deep Learning, LLMs etc)? Our idea: Use information from text & images in digital marketplaces like Amazon Paper: arxiv.org/abs/2501.00382 #EconSky

My 2024 “highlights” (or what consumed my work year): 1. Double cross-fitting (arxiv.org/abs/2403.15175) 2. Calibrated sensitivity models (arxiv.org/abs/2405.08738) 3. Fair comparisons (arxiv.org/abs/2410.13522) For #3, bsky.app/profile/alec.... Below: gory details for 1 and 2 (new to bsky) 1/9

Here are the first five sets of slides: 01 Introduction: psantanna.com/DiD/01_Intro... 02 Classical 2x2 setup: psantanna.com/DiD/02_two_b... 03 Clustering issues: psantanna.com/DiD/03_Clust... 04 Functional form: psantanna.com/DiD/04_Funct... 05 Covariates: psantanna.com/DiD/05_Covar...

Deadline on Sunday for a tenure track (W1 to W3) position in Economic History and Empirical Macroeconomics. Still time to apply!

Causal Christmas 🎄 Challenge: mcknaus.github.io/assets/cctc/... My Causal ML students draw sth using 2 potential outcome functions and see how causal forest approximates the resulting CATE fct as bonus assignment. Wanna join the challenge? Share your art in the replies #rstats #CausalSky #EconSky

The next issue of #EctJ celebrates the seminal contributions of Philip G. Wright to causal inference in economics and puts them in a modern perspective. At its core is a reproduction of Appendix B in his 1928 book "The Tariff on Animal and Vegetable Oils" #EconSky academic.oup.com/ectj/advance...

😀 Excited to teach an online course on Causal Machine Learning at the Africa Training Workshop in Econometrics 2024 of @econometric.bsky.social, Dec 3–6: editorialexpress.com/conference/A... #EconSky

We are looking for a full professor in economics with Focus on Big Data and Large Language Models in Social Data Science. Deadline: February 17, 2025 fa-eosd-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/Candid...

Program evaluation evaluation

3 - Double Machine Learning (DML) has become hugely popular for estimating structural parameters using ML. We highlight the risk of employing ill-suited machine learners and show the benefits of pairing DML with model averaging. With R & Stata software. Accepted @ JAE: arxiv.org/pdf/2401.01645

1 - How can we encourage eligible immigrants to naturalize? We design and field a policy tree for a letter-based information campaign. The policy tree optimally selects between alternative encouragement letters. Forthcoming JAE: doi.org/10.1002/jae....

New paper! arxiv.org/pdf/2411.14285 Led by amazing postdoc Alex Levis: www.awlevis.com/about/ We show causal effects of new "soft" interventions are less sensitive to unmeasured confounding & study which effects are *least* sensitive to confounding -> makes new connections to optimal transport

The European Causal Inference Meeting 2025 is coming to Ghent! ✨ Share your work with experts across the globe – abstract submission for oral & poster presentations is now open! eurocim.org/abstracts.html

A very interesting new working paper by the greats Ashesh Rambachan, Rahul Singh, and @vivianodavide.bsky.social: arxiv.org/pdf/2411.10959 It seems that this is another area where the empirical common practice was "too fast,'' and econometrics is catching up! Cool and empirically relevant stuff!

I’m hiring- info in the link below, or get in touch if interested 📣 JOB OPPORTUNITY!  💻 Research Fellow in causal inference and machine learning, Statistical Science Department, UCL 🔗 www.ucl.ac.uk/work-at-ucl/... 📅 Deadline 5th December #causality #stats

Part 2: Why do boosted trees outperform deep learning on tabular data?? @alanjeffares.bsky.social & I suspected that answers to this are obfuscated by the 2 being considered very different algs🤔 Instead we show they are more similar than you’d think — making their diffs smaller but predictive!🧵1/n

From double descent to grokking, deep learning sometimes works in unpredictable ways.. or does it? For NeurIPS(my final PhD paper!), @alanjeffares.bsky.social & I explored if&how smart linearisation can help us better understand&predict numerous odd deep learning phenomena — and learned a lot..🧵1/n

New WP 🚨 1. Recipe to write estimators as weighted outcomes 2. Double ML and causal forests as weighting estimators 3. Plug&play classic covariate balancing checks 4. Explains why Causal ML fails to find an effect of 1 with noiseless outcome Y = 1 + D 5. More fun facts arxiv.org/abs/2411.11559