Best Causal Inference Podcasts (2024)

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S4E1: Janet Currie, Health and Children, Princeton 1:35:36

1d ago1:35:36

1:35:36

Welcome the Mixtape with Scott! This is a podcast with a simple objective: listen to the personal stories of living economists who are the primary guests I have on the show. The secondary goal is to follow a thread of people around topics I care about and allow a patchwork story of the profession to form based on, from and through those personal na…

1
Free Will, LLMs & Intelligence | Judea Pearl Ep 21 | CausalBanditsPodcast.com 55:34

17d ago55:34

55:34

Send us a Text Message. Meet The Godfather of Modern Causal Inference His work has pretty literally changed the course of my life and I am honored and incredibly grateful we could meet for this great conversation in his home in Los Angeles To anybody who knows something about modern causal inference, he needs no introduction. He loves history, phil…

1
Conditional Power: How Likely Is Trial Success? 16:28

20d ago16:28

16:28

Benjamin R. Saville, PhD, Department of Biostatistics, Vanderbilt University Medical Center, discusses Conditional Power: How Likely Is Trial Success? with JAMA Statistical Editor Roger J. Lewis, MD, PhD. Related Content: Conditional Power

1
S3E26: Javier Gardeazabal, Political Economy and Econometrics, University of the Basque Country 1:29:48

1M ago1:29:48

1:29:48

Welcome to this week’s episode of the Mixtape with Scott, a podcast devoted to listening to the personal stories of living economists and creating an oral history of the profession. This episode is partly inspired by my visit to San Sebastián, Spain, with my daughter right now and partly inspired by a 2003 article co-authored with Alberto Abadie st…

1
Causal AI & Individual Treatment Effects | Scott Mueller Ep. 20 | CausalBanditsPodcast.com 54:07

1M ago54:07

54:07

Send us a Text Message. Can we say something about YOUR personal treatment effect? The estimation of individual treatment effects is the Holy Grail of personalized medicine. It's also extremely difficult. Yet, Scott is not discouraged from studying this topic. In fact, he quit a pretty successful business to study it. In a series of papers, Scott d…

1
S3E25: Avinash K. Dixit, Microeconomics, Princeton University 1:05:38

1M ago1:05:38

1:05:38

Welcome to this week’s episode of “The Mixtape with Scott”! My podcast tries to capture the personal stories of living economists and create an oral history of the profession from the narratives. And this week, I’m thrilled to welcome Dr. Avinash K. Dixit, a distinguished economist whose life’s work has influenced many fields within economics. But …

1
Starting the Conversation on Models with Alyssa Bilinski | Season 5 Episode 11 48:12

1M ago48:12

48:12

Alyssa Bilinski, Peterson Family Assistant Professor of Health Policy, and Assistant Professor of Biostatistics, at Brown University School of Public Health. Her research focuses on developing novel methods for policy evaluation and applying these to identify interventions that most efficiently improve population health and well-being. Episode note…

1
S3E24: David Autor, Labor Economist, MIT 1:00:51

1M ago1:00:51

1:00:51

Welcome to this week’s episode of "The Mixtape with Scott”! This podcast is dedicated to capturing the personal stories of living economists and creating an oral history of the profession through these narratives. This week, I’m excited to welcome David Autor, an esteemed labor economist from MIT, where he serves as the Daniel (1972) and Gail Rubin…

1
Bayesian Hierarchical Models With Dr McGlothlin 15:07

1M ago15:07

15:07

Anna E. McGlothlin, PhD, Berry Consultants, LLC, discusses Bayesian Hierarchical Models with JAMA Statistical Editor Roger J. Lewis, MD, PhD. Related Content: Bayesian Hierarchical Models

1
S3E23: Adriana Lleras-Muney, Labor Economist, UCLA 1:29:19

1M ago1:29:19

1:29:19

Welcome to another exciting episode of the Mixtape with Scott! Today, I get to have on the show someone who has become something of a friend the last few years, an expert in health economics and social policy, Adriana Lleras-Muney at UCLA, a Professor of Economics at UCLA. Dr. Lleras-Muney's journey in economics is super impressive and even involve…

1
Causal AI in Personalization | Dima Goldenberg Ep 19 | CausalBanditsPodcast.com 1:08:07

2M ago1:08:07

1:08:07

Send us a Text Message. Video version of this episode is available here Causal personalization? Dima did not love computers enough to forget about his passion for understanding people. His work at Booking.com focuses on recommender systems and personalization, and their intersection with AB testing, constrained optimization and causal inference. Di…

1
Flexible methods with Edward Kennedy | Season 5 Episode 10 38:57

2M ago38:57

38:57

Edward Kennedy Associate Professor, Department of Statistics & Data Science, Carnegie Mellon. ehkennedy.com Evaluating a Targeted Minimum Loss-Based Estimator for Capture-Recapture Analysis: An Application to HIV Surveillance in San Francisco, California: https://academic.oup.com/aje/article/193/4/673/7425624 Doubly Robust Capture-Recapture Methods…

1
S3E22: Manisha Shah, Development Economist, UC Berkeley (episode 100!) 1:26:15

2M ago1:26:15

1:26:15

We have officially passed 100 episodes with today’s guest, and it’s wonderful to get to do it with my good friend, Manisha Shah. Manisha is the Chancelor’s Professor of Public Policy at University of California Berkeley. Manisha is an applied microeconomist who has historically specialized in topics related to health, education, gender and labor, w…

1
(Repeat): S2:E1 Interview with Jeff Wooldridge, Economist and Econometrician 1:09:38

3M ago1:09:38

1:09:38

My producer is on vacation this week, and so I am unable to post my latest episode, so I thought I’d post an oldie but a goodie — my season 2 opening interview with Jeff Wooldridge, a much beloved econometrician and economist at Michigan State. So enjoy! Apologies and I’ll see you all next week with a new guest! Thanks again for all your support. C…

1
Causal Inference for Drug Repurposing & CausalLib | Ehud Karavani Ep 18 | CausalBanditsPodcast.com 54:59

3M ago54:59

54:59

Send us a Text Message. Was Deep Learning Revolution Bad For Causal Inference? Did deep learning revolution slowed down the progress in causal research? Can causality help in finding drug repurposing candidates? What are the main challenges in using causal inference at scale? Ehud Karavani, the author of the CausalLib Python library and Researcher …

1
What Sports and Feminism can tell us about Causal Inference with Sheree Bekker & Stephen Mumford | Season 5 Episode 9 49:43

2M ago49:43

49:43

Sheree Bekker & Stephen Mumford are Co-directors of the Feminist Sport Lab and have a book coming soon: “Open Play: the case for feminist sport”, coming Spring 2025. Reaktion Books (UK), University of Chicago Press (US). Sheree Bekker: Associate Professor, University of Bath, Department for Health, Centre for Qualitative Research Centre for Health …

1
S3E21: Ashesh Rambachan, Predictive Algorithms and Causal Inference, MIT 1:16:44

3M ago1:16:44

1:16:44

Greetings listeners! It is a pleasure to introduce this week’s guest on the podcast, Ashesh Rambachan, an assistant professor of economics at MIT. I wanted to talk to Ashesh for two main reasons. First, because I wanted to, and second, because I was aware of some of his recent work in econometrics. His recent article on evaluating the fragility of …

1
Sequential, Multiple Assignment, Randomized Trial Designs With Dr Kidwell 13:27

2M ago13:27

13:27

Kelley Kidwell, PhD, professor of biostatistics, University of Michigan, discusses Sequential, Multiple Assignment, Randomized Trial Designs with JAMA Statistical Editor Roger J. Lewis, MD, PhD. Related Content: Sequential, Multiple Assignment, Randomized Trial Designs

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S3E20: Henry Farber, Labor Economist, Princeton 1:18:17

3M ago1:18:17

1:18:17

This week’s guest on the Mixtape with Scott is esteemed labor economist, Henry Farber, the Hughes-Rogers Professor of Economics at Princeton University. Dr. Farber’s accolades are numerous: a Fellow of the Econometric Society, the Society of Labor Economists, and the Labor and Employment Relations Association, past President of the Society of Labor…

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From Physics to Causal AI & Back | Bernhard Schölkopf Ep 17 | CausalBanditsPodcast.com 35:10

3M ago35:10

35:10

Send us a Text Message. Causal AI: The Melting Pot. Can Physics, Math & Biology Help Us? What is the relationship between physics and causal models? What can science of non-human animal behavior teach causal AI researchers? Bernhard Schölkopf's rich background and experience allow him to combine perspectives from computation, physics, mathematics, …

1
Observational Causal Analyses with Erick Scott | Season 5 Episode 8 51:43

3M ago51:43

51:43

Erick Scott is founder of cStructure, a causal science startup. Erick has expertise in medicine, public health, and computational biology. info@cStructure.io “A causal roadmap for generating high-quality real-world evidence” https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10603361/ Follow along on Twitter: The American Journal of Epidemiology: @AmJEpi…

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S3E19: Sarah Miller, Health Economist, Michigan 1:10:19

3M ago1:10:19

1:10:19

This week's episode of "The Mixtape with Scott" features a conversation with Sarah Miller, a health economist at the University of Michigan. Sarah has made significant contributions to the field of economics, particularly in understanding gender dynamics and reproductive health. Her research has been influential in shaping public policy, and her gr…

1
S3E18: E. Glen Weyl, Economist and Author, Microsoft 1:17:26

4M ago1:17:26

1:17:26

This week's episode of "The Mixtape with Scott" features an insightful conversation with E. Glen Weyl, a distinguished economist whose career has spanned academia and industry. Glen earned his PhD from Princeton, spent three years at the Harvard Society of Fellows, and served as an assistant professor at the University of Chicago, where he made sig…

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Open Source Causal AI & The Generative Revolution | Emre Kıcıman Ep 16 | CausalBanditsPodcast.com 43:47

4M ago43:47

43:47

Send us a Text Message. What makes two tech giants collaborate on an open source causal AI package? Emre's adventure with causal inference and causal AI has started before it was trendy. He's one of the original core developers of DoWhy - one of the most popular and powerful Python libraries for causal inference - and a researcher focused on the in…

1
Friends Let Friends Do Mediation Analysis with Nima Hejazi | Season 5 Episode 7 59:07

4M ago59:07

59:07

Nima Hejazi is an assistant professor in biostatistics at Harvard University. His methodological work often draws upon tools and ideas from semi- and non-parametric inference, high-dimensional and large-scale inference, targeted or debiased machine learning (e.g., targeted minimum loss estimation, method of sieves), and computational statistics. Su…

1
S3E17: Matthew Jackson, Economics of Networks, Stanford 1:09:23

4M ago1:09:23

1:09:23

This week on the podcast, Matthew Jackson from Stanford University is the guest and it was such a delight for me to talk to him and get to know his story a little better. I’d met him before, but only briefly, but I’d read a lot of his work because I once developed and taught a class on networks for our masters of economics students. His textbook on…

1
S3E16: Bruce Sacerdote, Labor Economist, Dartmouth 1:11:05

4M ago1:11:05

1:11:05

Welcome to this week’s episode of the Mixtape with Scott where I get to interview Bruce Sacerdote, the Richard S. Braddock 1963 Professor in Economics at Dartmouth. Bruce is a prolific labor economist whose work spans the range of crime, education and peer effects. Some of his papers have been some of my favorite, even. His early work on crime with…

1
Why Hinton Was Wrong, Causal AI & Science | Thanos Vlontzos Ep 15 | CausalBanditsPodcast.com 1:06:56

4M ago1:06:56

1:06:56

Send us a Text Message. Recorded on Jan 17, 2024 in London, UK. Video version available here What makes so many predictions about the future of AI wrong? And what's possible with the current paradigm? From medical imaging to song recommendations, the association-based paradigm of learning can be helpful, but is not sufficient to answer our most int…

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Target Trial Emulation for Causal Inference From Observational Data With Dr Hernán 27:25

4M ago27:25

27:25

Miguel A. Hernán, MD, DrPH, professor of epidemiology, Harvard T.H. Chan School of Public Health, discusses Target Trial Emulation: A Framework for Causal Inference From Observational Data with JAMA Statistical Editor Roger J. Lewis, MD, PhD. Related Content: Target Trial Emulation

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Fun and Game(s) Theory with Aaditya Ramdas | Season 5 Episode 6 48:23

4M ago48:23

48:23

Aaditya Ramdas is an assistant professor at Carnegie Mellon University, in the Departments of Statistics and Machine Learning. His research interests include game-theoretic statistics and sequential anytime-valid inference, multiple testing and post-selection inference, and uncertainty quantification for machine learning (conformal prediction, cali…

1
S3E15: Peter Boettke, Austrian Economics, George Mason University 1:41:14

4M ago1:41:14

1:41:14

This week’s guest on the Mixtape with Scott is someone I’ve admired for a very long time, even before I entered graduate school in 2002. Peter J. Boettke is the Distinguished University Professor of Economics and Philosophy, the Director of the F. A. Hayek Program for Advanced Study in Philosophy, Politics and Economics and the BB&T Professor for t…

1
S3E14: Jesse Rothstein, Labor Economist, UC Berkeley 1:13:08

4M ago1:13:08

1:13:08

This week’s guest on the Mixtape with Scott is Jesse Rothstein, the Carmel P. Friesen Chair in Public Policy at UC-Berkeley and the Faculty Director of the California Policy Lab. Jesse has a long list of things to which he’s made meaningful contributions, ranging from labor economics, to discrimination, to education, to causal inference and more. H…

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Cookies, Causal Inference, and Careers with Ingrid Giesinger #Epicookiechallenge | Season 5 Episode 5 46:49

5M ago46:49

46:49

Ingrid is a doctoral student in Epidemiology at the Dalla Lana School of Public Health at the University of Toronto. Winning cookie recipe Follow along on Twitter: The American Journal of Epidemiology: @AmJEpi Ellie: @EpiEllie Lucy: @LucyStats 🎶 Our intro/outro music is courtesy of Joseph McDadeEdited by Cameron Bopp…

1
S3E13: Martin Gaynor, Health Economist, Carnegie Mellon/DOJ 1:37:29

5M ago1:37:29

1:37:29

Welcome to the Mixtape with Scott! We are getting closer to the hundredth episode! This is our 91st interview if I include Adam Smith (played by ChatGPT-4), which I absolutely will be counting. And the guest is someone I have admired for a long time — Martin Gaynor, or “Marty”. Marty is the J. Barone University Professor of Economics and Public Pol…

1
Causal Inference & Financial Modeling with Alexander Denev Ep 14 | CausalBanditsPodcast.com 1:05:36

5M ago1:05:36

1:05:36

Send us a Text Message. Video version available here Are markets efficient, and if not, can causal models help us leverage the inefficiencies? Do we really need to understand what we're modeling? What's the role of symmetry in modeling financial markets? What are the main challenges in applying causal models in finance? Ready to dive in? About The …

1
S3E12: Daniel Chen, Political Economy, Toulouse 1:14:02

5M ago1:14:02

1:14:02

Welcome to the 12th episode of the third season of the Mixtape with Scott, a podcast devoted to listening to the stories of living economists. This week's guest is Daniel Chen, an economist at the Toulouse School of Economics. I had a chance to meet Daniel when he came to Baylor and presented to use a tour de force of his body of scholarship, and I…

1
On Deep Learning for Medical Image Analysis With Dr Carin 22:54

5M ago22:54

22:54

JAMA Statistical Editor Roger J. Lewis, MD, PhD, discusses On Deep Learning for Medical Image Analysis with Lawrence Carin, PhD. Related Content: On Deep Learning for Medical Image Analysis

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Analyzing the Analysts: Reproducibility with Nick Huntington-Klein | Season 5 Episode 4 45:44

5M ago45:44

45:44

Nick Huntington-Klein is an Assistant Professor, Department of Economics, Albers School of Business and Economics, Seattle University. His research focus is econometrics, causal inference, and higher education policy. He’s also the author of an introductory causal inference textbook called The Effect and the creator of a number of Stata packages fo…

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S3E11: Peter Klein, Entrepreneurship, Baylor 1:27:49

5M ago1:27:49

1:27:49

Welcome to the Mixtape with Scott! To set up this week’s guest, let me just share real quick a personal anecdote. When I graduated college, I got a job as a qualitative research analyst doing focus groups and in-depth interviews. I had majored in literature, so this was my first exposure to anything related to the social sciences. I loved the freed…

1
Causal Inference & Reinforcement Learning with Andrew Lampinen Ep 13 | CausalBanditsPodcast.com 56:51

5M ago56:51

56:51

Send us a Text Message. Love Causal Bandits Podcast? Help us bring more quality content: Support the show Video version of this episode is available here Causal Inference with LLMs and Reinforcement Learning Agents? Do LLMs have a world model? Can they reason causally? What's the connection between LLMs, reinforcement learning, and causality? Andre…

1
S3E10: Richard Blundell, Labor Economist, University of College London 1:04:02

5M ago1:04:02

1:04:02

This week’s guest on the Mixtape with Scott is famed labor economist, Richard Blundell, the David Ricardo Professor of Political Economy at the University of College at London. Dr. Blundell’s accolades are extensive: a Fellow of the Econometric Association, Fell of the American Academy of Arts and Science, former President of SOLE, of the Royal eco…

1
Immortal Time Bias | Season 5 Episode 3 34:37

6M ago34:37

34:37

Lucy and Ellie chat about immortal time bias, discussing a new paper Ellie co-authored on clone-censor-weights. The Clone-Censor-Weight Method in Pharmacoepidemiologic Research: Foundations and Methodological Implementation: https://link.springer.com/article/10.1007/s40471-024-00346-2 Immortal time in pregnancy: https://pubmed.ncbi.nlm.nih.gov/3680…

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