Martin Huber
@causalhuber.bsky.social
Professor of Applied Econometrics and Policy Evaluation at the University of Fribourg/Freiburg (Switzerland) - causal analysis, statistics, econometrics, machine learning...and telemarking
Pinned
Martin Huber
@causalhuber.bsky.social
· Sep 1
🚀 Registration is open for the #Fribourg #WinterSchool in #DataAnalytics & #MachineLearning, Feb 2–13 2026.
📍Hybrid: at Fribourg University or online
🔍Topics: data analytics, predictive/causal machine learning, deep learning
💻 Software: Python, R, Julia, Knime
👉 Sign up: www.unifr.ch/appecon/en/w...
📍Hybrid: at Fribourg University or online
🔍Topics: data analytics, predictive/causal machine learning, deep learning
💻 Software: Python, R, Julia, Knime
👉 Sign up: www.unifr.ch/appecon/en/w...
📢 Registration is open for the 2026 Symposium of Causal Inference in the Health Sciences, hosted at Fribourg University on March 18. This year’s focus is on AI/machine learning in causal inference for health sciences/economics - register here: projects.unifr.ch/pophealthlab... #CausalAI
January 27, 2026 at 10:23 AM
📢 Registration is open for the 2026 Symposium of Causal Inference in the Health Sciences, hosted at Fribourg University on March 18. This year’s focus is on AI/machine learning in causal inference for health sciences/economics - register here: projects.unifr.ch/pophealthlab... #CausalAI
📢 Last call! Register for the #Fribourg #WinterSchool in #DataAnalytics & #MachineLearning (📅 Feb 2–13, 2026) until Jan 25. Join us on site in Fribourg or online for data analytics, predictive/causal machine learning, and deep learning, using Python, R, Julia, & KNIME: www.unifr.ch/appecon/en/w...
Further education | Chair of Applied Econometrics and Policy Evaluation | University of Fribourg
www.unifr.ch
January 22, 2026 at 7:23 AM
📢 Last call! Register for the #Fribourg #WinterSchool in #DataAnalytics & #MachineLearning (📅 Feb 2–13, 2026) until Jan 25. Join us on site in Fribourg or online for data analytics, predictive/causal machine learning, and deep learning, using Python, R, Julia, & KNIME: www.unifr.ch/appecon/en/w...
📢 Update of our #DiD paper on continuous treatments with machine learning-based covariate adjustment, joint with M Haddad, J Medina-Reyes, and L Zhang. Now includes an evaluation of the impact of second-dose COVID-19 vaccination rates on mortality in Brazil:
arxiv.org/abs/2410.21105
arxiv.org/abs/2410.21105
Difference-in-Differences with Time-varying Continuous Treatments using Double/Debiased Machine Learning
We propose a difference-in-differences (DiD) framework designed for time-varying continuous treatments across multiple periods. Specifically, we estimate the average treatment effect on the treated (A...
arxiv.org
January 16, 2026 at 8:40 AM
📢 Update of our #DiD paper on continuous treatments with machine learning-based covariate adjustment, joint with M Haddad, J Medina-Reyes, and L Zhang. Now includes an evaluation of the impact of second-dose COVID-19 vaccination rates on mortality in Brazil:
arxiv.org/abs/2410.21105
arxiv.org/abs/2410.21105
The new year starts with a great conference: the Labor Seminar in #Laax 🏔️ Inspiring talks with applications of causal inference methods in empirical labor economics and related fields. Thanks to Pia Schilling and Christina Felfe for putting together a fantastic program!
January 13, 2026 at 1:18 PM
The new year starts with a great conference: the Labor Seminar in #Laax 🏔️ Inspiring talks with applications of causal inference methods in empirical labor economics and related fields. Thanks to Pia Schilling and Christina Felfe for putting together a fantastic program!
📄 New paper (joint with J Kueck & M Mattes):
arxiv.org/abs/2601.05728
When outcomes depend on others’ actions in a social network, causal evaluation becomes difficult. We use causal AI to learn network interference from data and to test whether common ways of modelling interference are valid.
arxiv.org/abs/2601.05728
When outcomes depend on others’ actions in a social network, causal evaluation becomes difficult. We use causal AI to learn network interference from data and to test whether common ways of modelling interference are valid.
Learning and Testing Exposure Mappings of Interference using Graph Convolutional Autoencoder
Interference or spillover effects arise when an individual's outcome (e.g., health) is influenced not only by their own treatment (e.g., vaccination) but also by the treatment of others, creating chal...
arxiv.org
January 12, 2026 at 4:42 PM
📄 New paper (joint with J Kueck & M Mattes):
arxiv.org/abs/2601.05728
When outcomes depend on others’ actions in a social network, causal evaluation becomes difficult. We use causal AI to learn network interference from data and to test whether common ways of modelling interference are valid.
arxiv.org/abs/2601.05728
When outcomes depend on others’ actions in a social network, causal evaluation becomes difficult. We use causal AI to learn network interference from data and to test whether common ways of modelling interference are valid.
📢The #Fribourg #WinterSchool in #DataAnalytics & #MachineLearning is coming up Feb 2-13. Join us on site at @ses_unifr or online for a two-week program on data analytics, predictive/causal machine learning & deep learning using Python, R, Julia & KNIME:
www.unifr.ch/appecon/en/w...
www.unifr.ch/appecon/en/w...
January 9, 2026 at 7:25 AM
📢The #Fribourg #WinterSchool in #DataAnalytics & #MachineLearning is coming up Feb 2-13. Join us on site at @ses_unifr or online for a two-week program on data analytics, predictive/causal machine learning & deep learning using Python, R, Julia & KNIME:
www.unifr.ch/appecon/en/w...
www.unifr.ch/appecon/en/w...
Happy holidays from the #Venet in #Tirol, #Austria ❄️⛷️ - the perfect crowd-free ski retreat, recharging energy for fresh #CausalAnalysis and #ImpactEvaluation in the new year 😉 www.venet.at
December 27, 2025 at 9:58 AM
Happy holidays from the #Venet in #Tirol, #Austria ❄️⛷️ - the perfect crowd-free ski retreat, recharging energy for fresh #CausalAnalysis and #ImpactEvaluation in the new year 😉 www.venet.at
⏳ Our #Fribourg #WinterSchool in Data Analytics & Machine Learning is only a few weeks away (Feb 2–13, 2026). Strengthen your skills in predictive and causal machine learning, deep learning using Python, R, Julia & Knime.
Register here to join us in person or online: www.unifr.ch/appecon/en/w...
Register here to join us in person or online: www.unifr.ch/appecon/en/w...
December 12, 2025 at 2:29 PM
⏳ Our #Fribourg #WinterSchool in Data Analytics & Machine Learning is only a few weeks away (Feb 2–13, 2026). Strengthen your skills in predictive and causal machine learning, deep learning using Python, R, Julia & Knime.
Register here to join us in person or online: www.unifr.ch/appecon/en/w...
Register here to join us in person or online: www.unifr.ch/appecon/en/w...
Very honored to be recognized as a Distinguished Author of the Journal of Applied Econometrics in 2025 (for the equivalent of three single-authored publications). I’m very grateful to my coauthors - most of my work in this journal has been collaborative! 😊 onlinelibrary.wiley.com/page/journal...
Journal of Applied Econometrics DISTINGUISHED AUTHORS ANNOUNCEMENT
The Journal of Applied Econometrics is a statistical and mathematical economics journal for the application of econometric techniques to economic problems.
onlinelibrary.wiley.com
December 9, 2025 at 1:47 PM
Very honored to be recognized as a Distinguished Author of the Journal of Applied Econometrics in 2025 (for the equivalent of three single-authored publications). I’m very grateful to my coauthors - most of my work in this journal has been collaborative! 😊 onlinelibrary.wiley.com/page/journal...
🚀 A new version of our causalweight package for the statistical software R is online, containing some of the latest causal machine learning methods for the estimation of treatment effects: www.rdocumentation.org/packages/cau...
#CausalInference #CausalAnalysis #MachineLearning
#CausalInference #CausalAnalysis #MachineLearning
causalweight package - RDocumentation
Various estimators of causal effects based on inverse probability weighting, doubly robust estimation, and double machine learning. Specifically, the package includes methods for estimating average tr...
www.rdocumentation.org
December 5, 2025 at 7:10 AM
🚀 A new version of our causalweight package for the statistical software R is online, containing some of the latest causal machine learning methods for the estimation of treatment effects: www.rdocumentation.org/packages/cau...
#CausalInference #CausalAnalysis #MachineLearning
#CausalInference #CausalAnalysis #MachineLearning
Had the great pleasure of teaching a short course on #CausalAnalysis (based on my book of the same name) and methods in policy evaluation this week at the European Central Bank in Frankfurt. A big thank you to David Marques-Ibanez and all participants for hosting me and for the engaging discussions!
November 27, 2025 at 5:07 PM
Had the great pleasure of teaching a short course on #CausalAnalysis (based on my book of the same name) and methods in policy evaluation this week at the European Central Bank in Frankfurt. A big thank you to David Marques-Ibanez and all participants for hosting me and for the engaging discussions!
Reposted by Martin Huber
With @jeromevalette.bsky.social & Jesús Fernández-Huertas Moraga, we are happy to announce the CfPapers for the
4th edition of the Junior Workshop on the Economics of Migration
on May 26-27, 2026 @uc3meconomics.bsky.social, Spain.
Submit until February 1, 2026 on economig2026.sciencesconf.org
With @jeromevalette.bsky.social & Jesús Fernández-Huertas Moraga, we are happy to announce the CfPapers for the
4th edition of the Junior Workshop on the Economics of Migration
on May 26-27, 2026 @uc3meconomics.bsky.social, Spain.
Submit until February 1, 2026 on economig2026.sciencesconf.org
November 24, 2025 at 9:27 AM
With @jeromevalette.bsky.social & Jesús Fernández-Huertas Moraga, we are happy to announce the CfPapers for the
4th edition of the Junior Workshop on the Economics of Migration
on May 26-27, 2026 @uc3meconomics.bsky.social, Spain.
Submit until February 1, 2026 on economig2026.sciencesconf.org
With @jeromevalette.bsky.social & Jesús Fernández-Huertas Moraga, we are happy to announce the CfPapers for the
4th edition of the Junior Workshop on the Economics of Migration
on May 26-27, 2026 @uc3meconomics.bsky.social, Spain.
Submit until February 1, 2026 on economig2026.sciencesconf.org
The #CDSM2025 is coming up tomorrow: www.causalscience.org. Mara Mattes will present our joint work with Jannis Kueck on learning and testing the structure of interference effects in social networks - how the treatment of others affects one’s own outcomes - using graph convolutional autoencoders.
Causal Data Science Meeting - Home
Fostering a dialogue between industry and academia on causal data science.
www.causalscience.org
November 11, 2025 at 12:00 PM
The #CDSM2025 is coming up tomorrow: www.causalscience.org. Mara Mattes will present our joint work with Jannis Kueck on learning and testing the structure of interference effects in social networks - how the treatment of others affects one’s own outcomes - using graph convolutional autoencoders.
📢The #Fribourg #WinterSchool in #DataAnalytics & #MachineLearning is coming up (Feb 2–13, 2026)! On site at @unifr.bsky.social or online - covering data analytics, predictive & causal machine learning, and deep learning using Python, R, Julia & Knime. Register now: www.unifr.ch/appecon/en/w...
November 5, 2025 at 4:28 PM
📢The #Fribourg #WinterSchool in #DataAnalytics & #MachineLearning is coming up (Feb 2–13, 2026)! On site at @unifr.bsky.social or online - covering data analytics, predictive & causal machine learning, and deep learning using Python, R, Julia & Knime. Register now: www.unifr.ch/appecon/en/w...
Very happy to attend the Young Researcher Workshop of the Universities of Tübingen and #Hohenheim (as an invitee, even if I’m not that young anymore 😉) - lots of great presentations and lively discussions, including on causal machine learning! Many thanks to B. Jung, M. Biewen & the organising team!
September 25, 2025 at 9:26 AM
Very happy to attend the Young Researcher Workshop of the Universities of Tübingen and #Hohenheim (as an invitee, even if I’m not that young anymore 😉) - lots of great presentations and lively discussions, including on causal machine learning! Many thanks to B. Jung, M. Biewen & the organising team!
📚 In summer 2023, my book Causal Analysis was published with @mitpress.bsky.social. Just two years later😉 I’m very happy to share that the lecture slides are now freely available in both PDF and LaTeX (as zip files), along with the datasets and R/Python code:
👉 www.unifr.ch/appecon/en/r...
👉 www.unifr.ch/appecon/en/r...
September 9, 2025 at 2:14 PM
📚 In summer 2023, my book Causal Analysis was published with @mitpress.bsky.social. Just two years later😉 I’m very happy to share that the lecture slides are now freely available in both PDF and LaTeX (as zip files), along with the datasets and R/Python code:
👉 www.unifr.ch/appecon/en/r...
👉 www.unifr.ch/appecon/en/r...
Reposted by Martin Huber
📣 Last Call!
Don't miss the chance to 🤿 dive into IV and RDD in R with @causalhuber.bsky.social!
Register Now!
➡️ t1p.de/caus-inf-2025
Don't miss the chance to 🤿 dive into IV and RDD in R with @causalhuber.bsky.social!
Register Now!
➡️ t1p.de/caus-inf-2025
Struggling to identify causal effects when experiments aren’t feasible? Learn how Instrumental Variables and Regression Discontinuity Designs can help!
Join @causalhuber.bsky.social to dive deep into IV and RDD in R —from core concepts to advanced topics like machine learning: t1p.de/caus-inf-2025
Join @causalhuber.bsky.social to dive deep into IV and RDD in R —from core concepts to advanced topics like machine learning: t1p.de/caus-inf-2025
September 3, 2025 at 9:39 AM
📣 Last Call!
Don't miss the chance to 🤿 dive into IV and RDD in R with @causalhuber.bsky.social!
Register Now!
➡️ t1p.de/caus-inf-2025
Don't miss the chance to 🤿 dive into IV and RDD in R with @causalhuber.bsky.social!
Register Now!
➡️ t1p.de/caus-inf-2025
🚀 Registration is open for the #Fribourg #WinterSchool in #DataAnalytics & #MachineLearning, Feb 2–13 2026.
📍Hybrid: at Fribourg University or online
🔍Topics: data analytics, predictive/causal machine learning, deep learning
💻 Software: Python, R, Julia, Knime
👉 Sign up: www.unifr.ch/appecon/en/w...
📍Hybrid: at Fribourg University or online
🔍Topics: data analytics, predictive/causal machine learning, deep learning
💻 Software: Python, R, Julia, Knime
👉 Sign up: www.unifr.ch/appecon/en/w...
September 1, 2025 at 10:44 AM
🚀 Registration is open for the #Fribourg #WinterSchool in #DataAnalytics & #MachineLearning, Feb 2–13 2026.
📍Hybrid: at Fribourg University or online
🔍Topics: data analytics, predictive/causal machine learning, deep learning
💻 Software: Python, R, Julia, Knime
👉 Sign up: www.unifr.ch/appecon/en/w...
📍Hybrid: at Fribourg University or online
🔍Topics: data analytics, predictive/causal machine learning, deep learning
💻 Software: Python, R, Julia, Knime
👉 Sign up: www.unifr.ch/appecon/en/w...
Thanks @p-hunermund.com!
I just ordered a copy of @causalhuber.bsky.social's brand new book, and I'm excited to have a look at it! mitpress.mit.edu/978026255292...
August 21, 2025 at 11:20 PM
Thanks @p-hunermund.com!
😀 Attending the World Congress of the Econometric Society in the stunning city of Seoul, and thrilled to present joint work with N Apfel, J Hatamyar, & J Kueck on machine learning–based testing of conditions sufficient for identifying treatment effects: virtual.oxfordabstracts.com/event/73643/...
August 21, 2025 at 8:15 AM
😀 Attending the World Congress of the Econometric Society in the stunning city of Seoul, and thrilled to present joint work with N Apfel, J Hatamyar, & J Kueck on machine learning–based testing of conditions sufficient for identifying treatment effects: virtual.oxfordabstracts.com/event/73643/...
Excited to share our working paper “Machine Learning for Detecting Collusion and Capacity Withholding in Wholesale Electricity Markets”, joint with Jeremy Proz. We propose a machine learning–based approach for detecting cartels among suppliers in electricity markets:
👉 arxiv.org/abs/2508.09885
👉 arxiv.org/abs/2508.09885
Machine Learning for Detecting Collusion and Capacity Withholding in Wholesale Electricity Markets
Collusion and capacity withholding in electricity wholesale markets are important mechanisms of market manipulation. This study applies a refined machine learning-based cartel detection algorithm to t...
arxiv.org
August 19, 2025 at 6:21 AM
Excited to share our working paper “Machine Learning for Detecting Collusion and Capacity Withholding in Wholesale Electricity Markets”, joint with Jeremy Proz. We propose a machine learning–based approach for detecting cartels among suppliers in electricity markets:
👉 arxiv.org/abs/2508.09885
👉 arxiv.org/abs/2508.09885
Very happy to be teaching a @gesistraining.bsky.social workshop on causal inference with instrumental variables and regression discontinuity designs on October 9–10, 2025. Registration is still open: training.gesis.org?site=pDetail...
August 11, 2025 at 1:07 PM
Very happy to be teaching a @gesistraining.bsky.social workshop on causal inference with instrumental variables and regression discontinuity designs on October 9–10, 2025. Registration is still open: training.gesis.org?site=pDetail...
🎉 Seems like the release of "Impact Evaluation in Firms and Organizations" is off to a great start! Huge thanks to everyone who's been reading, sharing, and supporting my book!
mitpress.mit.edu/978026255292...
mitpress.mit.edu/978026255292...
August 7, 2025 at 3:27 PM
🎉 Seems like the release of "Impact Evaluation in Firms and Organizations" is off to a great start! Huge thanks to everyone who's been reading, sharing, and supporting my book!
mitpress.mit.edu/978026255292...
mitpress.mit.edu/978026255292...
📘 My book Impact Evaluation in Firms and Organizations is officially out today with @mitpress.bsky.social! An accessible, non-technical introduction to impact evaluation (& causal machine learning) designed for practitioners & students, with use cases in R & Python: mitpress.mit.edu/978026255292...
August 5, 2025 at 6:01 AM
📘 My book Impact Evaluation in Firms and Organizations is officially out today with @mitpress.bsky.social! An accessible, non-technical introduction to impact evaluation (& causal machine learning) designed for practitioners & students, with use cases in R & Python: mitpress.mit.edu/978026255292...
Delighted that our working paper “Catching Bid-rigging Cartels with Graph Attention Neural Networks”, joint work with D. Imhof and E. Viklund, is out! We propose a novel #DeepLearning algorithm based on GATs to detect collusive behavior in markets/tenders: arxiv.org/abs/2507.12369 #MachineLearning
Catching Bid-rigging Cartels with Graph Attention Neural Networks
We propose a novel application of graph attention networks (GATs), a type of graph neural network enhanced with attention mechanisms, to develop a deep learning algorithm for detecting collusive behav...
arxiv.org
July 23, 2025 at 3:45 PM
Delighted that our working paper “Catching Bid-rigging Cartels with Graph Attention Neural Networks”, joint work with D. Imhof and E. Viklund, is out! We propose a novel #DeepLearning algorithm based on GATs to detect collusive behavior in markets/tenders: arxiv.org/abs/2507.12369 #MachineLearning