Greetings everyone. I’m still in moving mode, packing up life in Texas and getting ready for a year in Boston. I hit the road on Friday of this week for a three day road trip and am still behind on everything. That means the podcast is still on reruns for now, but I should have a new episode for you next time. This week’s rerun is one I really liked, though—my conversation from two years ago with Steven Berry.

Steven is the Sterling Professor of Economics at Yale and the inaugural Faculty Director of the Tobin Center. His work in industrial organization has shaped how economists think about markets in equilibrium, and his research spans industries from autos to airlines to media. He’s also a winner of the Frisch Medal, a member of the National Academy of Sciences, and one of the field’s most respected voices.

We talked about his path into economics—from the Midwest, to Wisconsin, to a career that’s helped define modern empirical IO. Naturally, we dug into the BLP model, the landmark framework he developed with James Levinsohn and Ariel Pakes that changed how we estimate demand in differentiated product markets. It’s one of those ideas that’s both deeply technical and hugely practical in policy and business.

If you missed it the first time, I think you’ll enjoy hearing Steven reflect on his career, his collaborators, and where the field is headed. Here’s my rerun conversation with Steven Berry.

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I’m still going through some older reruns for the summer due to my travel schedule. This one is an interview with Rocío Titiunik, a quantitative methods political scientist and professor in the department of politics at Princeton University, as well as a researcher that has been at the frontier of work on regression discontinuity designs.

Her name is synonymous with cutting-edge work on regression discontinuity design, developed in close collaboration with scholars like Sebastián Calonico, Matías Cattaneo, and Max Farrell. Together, they’ve shaped the modern landscape of causal inference, not only through groundbreaking theory but also through widely used software tools in R, Stata, and Python. In addition to her contributions to quantitative methodology, Rocío’s applied research — from electoral behavior to democratic institutions — has become a major voice in political science. She also holds a formidable editorial footprint: associate editor for Science Advances, Political Analysis, and the American Journal of Political Science, and APSR. It’s no exaggeration to say she helps steer the field as much as she contributes to it.

In this older interview, Rocío shared how her journey into economics began not with data, but with theory, literature, and the big questions that led her to the discipline. Her path into Berkeley’s PhD program in agricultural and resource economics was anything but linear, and even once there, she wasn’t sure how all the parts of herself — the scholar, the immigrant, the thinker — would fit together. During our conversation, she opened up about moments of uncertainty, of feeling lost in the sheer vastness of academic economics. Her honesty was disarming. It reminded me that no matter how decorated someone’s résumé may be, we’re all just trying to find our way — and sometimes, the most important breakthroughs happen when we admit we haven’t arrived yet.

Thanks again for tuning in! I hope you like listening to this older podcast interview.

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Greetings from San Sebastián Spain where I am on holiday with my daughter for another couple of weeks. I have still not done any new podcasts as I realized only after I left that I did not pack my microphone. And, I didn’t want to buy a new one, and I wasn’t really 100% positive if using my Apple AirPods would work well. All of that is to say — excuses.

So, this week we are going back down memory lane to an interview I did 1-2 years ago with one of my favorite young up and coming econometricians, Tymon Słoczyńsi from Brandeis University. Tymon is the author of a wonderful 2022 article on OLS models with, I’ll call it, “additive and separable” covariates under unconfoundedness. Autocorrect wanted that to be “addictive” instead of “additive”, which would’ve been a really clever Freudian slip.

Tymon’s interview was one of my favorites. I know I say that about every interview, but they all feel like that, but let’s just this one really really feels that way. And I think you’ll feel the same way.

One of the things I love about Tymon’s articles is how excellent the writing is. His paragraphs oftentimes feel like the kind of paragraphs that you can tell he wrote, and rewrote, and rewrote, and rewrote like a hundred times. It amazes me that English is not his first language and he writes this well. I don’t even mean this clear — I mean it’s beautiful writing. Here’s a paragraph I think is outstanding, for instance:

“To aid intuition for this surprising result, recall that an important motivation for using the model in equation (1) and OLS is that the linear projection of y on d and X provides the best linear predictor of y given d and X (Angrist & Pischke, 2009). However, if our goal is to conduct causal inference, then this is not, in fact, a good reason to use this method. Ordinary least squares is “best” in predicting actual outcomes, but causal inference is about predicting missing outcomes, defined as ym = y(1) × (1− d ) + y(0) × d. In other words, the OLS weights are optimal for predicting “what is.” Instead, we are interested in predicting “what would be” if treatment were assigned differently.”

A lot of his sentences are sentences that are so precise, so insightful, that I wish I could have written it. It’s superb, he’s superb, and if you haven’t listened to this, I hope you do, and if you already have listened to it, then I hope you listen to it again.

Thanks again for all your support. Wish me luck as I wrap up my summer in Europe, start making my plans to move to Boston, teach new students, meet new colleagues, and make new friends. And get some new clothes to replace the ones the gentleman who stole my luggage on the train in Switzerland is now in possession of.

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Welcome to the Mixtape with Scott — an interview-based podcast where I, Scott Cunningham, talk to living economists about their personal lives. I continue my travels in Europe without a good microphone, which has caused me to delay my newest interviews a little bit longer. Therefore this week’s episode is an oldie but a goodie — Jon Roth, a young econometrician at Brown University. Jon has had many high profile publications to his name already in a short period of time, many of which center around difference-in-differences. Several have focused on the event study (e.g., here, here and here) , whereas others have focused on the logarithm both within diff-in-diff but also outside of it. I think it is fair to say that Jon’s econometric contributions have been unusually practical to applied researchers while also scientifically robust and accurate. I remember enjoying this conversation with Jon a great deal, and if you haven’t listened to it, it’s a great time to do so now, and if you have listened to it, it’s a great time to listen to it again! Thank you again for all your support!

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This week’s episode of the Mixtape with Scott is a rerun of an earlier interview I did with Muhammad Akbarpour, an economic theorist at Stanford University. Muhammad tells his life story of growing up in Tehan, Iran and his long and windy road into economics and Stanford University, where he both went to grad school and is now an assistant professor. If you haven’t had a chance to listen to it or watch it, I highly recommend it again. Mohammad is one of my favorite young economists, particularly theorists, working today and I find talking to him to be really inspiring. This was one of my favorite, top 5 even, interviews I’ve had on the show so far too.

Thank you again for your support.

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Welcome back to The Mixtape with Scott, a podcast about the lives and stories of living economists. This show often unfolds in themed mini-series, and lately I’ve been exploring one that I’ve been curious about for a while: the economists who navigated and participated in the heterodox tradition in economics.

Today’s guest is Amitava Krishna Dutt, a development economist, now emeritus at the University of Notre Dame. His work sits at the intersection of structuralist macroeconomics, post-Keynesian theory, and development, with deep engagement in political economy. He’s long been committed to questions of global inequality, the dynamics of capitalist growth, and the limitations of orthodoxy in addressing the needs of the Global South.

So thank you for tuning in. I hope this is as interesting to you as it was to me.

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Welcome to this week’s episode of The Mixtape with Scott. Today’s podcast guest is our 127th guest on the show—Vitor Possebom, Assistant Professor in the Department of Economics at the Fundação Getulio Vargas. Vitor’s research sits at the intersection of two areas — econometrics and causal inference, and policy evaluation in Latin America, particularly Brazil.

His contributions revolve around refining and extending tools for estimating causal effects in observational data, especially under common data imperfections like selection bias, measurement error, and treatment effect heterogeneity.

* Sample selection and marginal treatment effects (e.g., “Identifying Marginal Treatment Effects in the Presence of Sample Selection” (Journal of Econometrics), “Crime and Mismeasured Punishment” (Review of Economics and Statistics))

* Misclassification and measurement error (e.g., “Potato Potahto in the FAO-GAEZ Productivity Measures?”)

* Inference and sensitivity in synthetic control methods (e.g., “Cherry Picking with Synthetic Controls”, “Synthetic Control Method: Inference, Sensitivity Analysis and Confidence Sets”)

* Probability of causation in non-experimental settings (e.g., “Probability of Causation with Sample Selection”)

I invited Vitor onto the podcast because of his creative contributions to causal inference, as he fits into a larger informal series I’ve been for the last several years on causal inference in general. In today’s conversation, we talk about Vitor’s path from Brazil to Yale University and then back. Vitor, thank you so much for joining us.

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Welcome to The Mixtape with Scott, a podcast dedicated to exploring the personal stories of living economists. I'm your host, Scott Cunningham, Professor of Economics at Baylor University.

Today, I'm delighted to introduce Jessica Brown, Assistant Professor of Economics at the Darla Moore School of Business at the University of South Carolina. Jessica is also a Research Fellow at IZA and a Faculty Affiliate at the Wilson-Sheehan Lab for Economic Opportunities.

I invited Jessica onto the podcast because of her deep connections to the credibility revolution, causal inference, and the esteemed tradition of labor economics nurtured at Princeton University’s Industrial Relations Section, where she completed her PhD in 2019.

Jessica is also joining us as part of a special series I've been hosting, loosely titled "The Students Of..." Within this series, she specifically contributes to our "Students of Alan Krueger" mini-series. Alan Krueger, a pioneering economist whose work profoundly shaped labor economics, tragically passed away in 2019. Jessica was one of Alan's last doctoral students, and his death came shortly before her dissertation defense.

In our conversation today, we'll explore Jessica's journey as an economist, her experiences studying under Alan Krueger, and the influence he had on her professional and personal development.

Jessica, thank you so much for joining us.

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