Advertise on podcast: The Mixtape with Scott

Welcome back to The Mixtape with Scott. I’m currently in the process of putting together a new slate of interviews, and while it’s not quite ready yet, I didn’t want to leave you hanging. So in the meantime, I’m re-sharing some conversations from earlier seasons — episodes that I think are worth revisiting or perhaps discovering for the first time. Today’s rerun is from Season Two, and it’s one of my favorite interviews from that time: my conversation with Ariel Pakes, the Thomas Professor of Economics at Harvard University. This was such a fun and rich interview. People either know Dr. Pakes very well or only by the letter “P”. He’s a towering figure in industrial organization and structural econometrics, with landmark contributions both theoretical and applied. Among many things, he’s the “P” in the Berry-Levinsohn-Pakes model — BLP — which remains one of the most influential tools for estimating demand in differentiated product markets. That paper — Automobile Prices in Market Equilibrium — published in Econometrica in 1995, has had a ripple effect not just in economics, but well beyond it. But this interview wasn’t just about methods and models. Dr. Pakes and I talked about basketball, about growing up in a radical socialist youth group, about his early love of philosophy, and his own path through Harvard as a young man trying to straddle economics and philosophy before finding his place. He spoke softly, with depth and reflection, and he offered a glimpse into how he works — by getting himself in way over his head and then slowly, patiently, working his way out. It’s a way of thinking that hasn’t just shaped his own work but has helped shape the rest of ours too. I hope you enjoy this one as much as I did. Get full access to Scott's Mixtape Substack at causalinf.substack.com/subscribe

Greetings from Cambridge! I’m still mid-move and not fully settled—classes kick off next week and I’m wrapping the last bits of admin—so I’m sharing one more rerun before we close out Season 4. Today’s guest is a Cambridge neighbor just down the Charles at MIT: Dr. Amy Finkelstein, John Bates Clark Award–winning economist. If you’re new to her work: Amy is a leading health economist at MIT and coauthor of We’ve Got You Covered (with Liran Einav), a timely book from a couple of years ago. In it, they argue for universal basic coverage that guarantees financial protection from major medical costs, while leaving room for supplemental private insurance—simple, fair, and focused on what insurance is actually for. In our conversation we cover the Oregon Medicaid Experiment and the ideas that shaped it, plus the arc of her career. I loved this one. Hope you enjoy the rerun. Scott's Mixtape Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Mixtape Substack at causalinf.substack.com/subscribe

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. Scott's Mixtape Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Mixtape Substack at causalinf.substack.com/subscribe

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. Scott's Mixtape Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Mixtape Substack at causalinf.substack.com/subscribe

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. Scott's Mixtape Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Mixtape Substack at causalinf.substack.com/subscribe

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! Scott's Mixtape Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Mixtape Substack at causalinf.substack.com/subscribe

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. Scott's Mixtape Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Mixtape Substack at causalinf.substack.com/subscribe

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. Scott's Mixtape Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Mixtape Substack at causalinf.substack.com/subscribe

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. Scott's Mixtape Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Mixtape Substack at causalinf.substack.com/subscribe

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. Scott's Mixtape Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Mixtape Substack at causalinf.substack.com/subscribe

Welcome to this week's episode of The Mixed Tape with Scott. I'm your host, Scott Cunningham. This podcast is devoted to the personal stories of living economists, diving into their lives, careers, and the fascinating paths they've walked. This week's guest is Michael Anderson, an economist from the University of California Berkeley's Department of Agricultural Resource Economics. Michael earned his PhD at MIT in 2006 under the mentorship of Josh Angrist, making him part of a broader narrative I've been exploring—the Princeton Industrial Relations Section and the influential lineage of scholars who shaped the modern credibility revolution in economics. In our conversation, we touch on Michael's rich and varied research. We discuss his insights into the returns to college athletic success, delve into his foundational work on the Perry Preschool program and the challenge of multiple inference, and explore the real-world impacts outlined in his American Economic Review paper on subway strikes and slowdowns. As always, though, this episode is much more than just research highlights—it's about Michael's journey through economics, his stories, and the experiences that have defined his path. I hope you enjoy the show! Scott's Mixtape Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Mixtape Substack at causalinf.substack.com/subscribe

I’m thrilled to announce that our next guest on The Mixtape with Scott is Professor Philip Oreopoulos—one of the most impactful economists working today in education and labor. A PhD student advisee of David Card, Phil is part of the distinguished lineage that helped shape the credibility revolution in applied microeconomics. Now a Professor of Economics and Public Policy at the University of Toronto, Phil has spent his career studying how education policies and interventions affect outcomes for students and workers. His work blends rigorous causal inference with real-world relevance to uncover how both the very large interventions we employ to help society, as well as the seemingly surgically narrow ones, shape the lives of workers and students. He’s also a Research Associate at the National Bureau of Economic Research and a Research Fellow at the Canadian Institute for Advanced Research. His CV is full of important papers, but it’s the heart behind the work that really stands out—his curiosity about the world and his desire to make a difference. In this episode, we go beyond the papers. We talk about his journey, what it was like working with David Card, and how he found his calling. It’s a thoughtful, warm conversation with a scholar who represents the very best of what economics can be. Scott's Mixtape Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Mixtape Substack at causalinf.substack.com/subscribe

I'm excited to announce the newest episode to the podcast features a brilliant mind in econometrics and applied microeconomics: Dr. Liyang "Sophie" Sun from University College London. While Liyang has technically been a guest before, our previous conversation had been narrowly focused on econometric techniques. This time, we're shifting gears to align with the core purpose of the podcast—exploring the personal stories and journeys of living economists. Many of you know Liyang by reputation or have cited her groundbreaking work. Her 2021 paper with Sarah Abraham in the Journal of Econometrics on difference-in-differences estimated using two-way fixed effects with leads and lags was recognized as one of the recipients of the Aigner award for 2022 —a remarkable achievement. That paper in particular helped clarify exactly what we were—and weren't—measuring in difference-in-differences event studies. Beyond diagnosing issues in existing approaches, they introduced a new and more accurate estimator, known formally as the interaction-weighted estimator, but which most of us now fondly call simply “SA” (Sun and Abraham). I love that paper; it has taught me a great deal. Her research portfolio extends well beyond this, spanning instrumental variables, synthetic control methods, and other innovative approaches that have reshaped how we think about causal inference in economics. In this episode, we'll dive into Liyang’s personal journey through growing up in China, coming to the United States as a high school student, and then through college, grad school and a career as a professional economist and econometrician. She generously shares the experiences, people and discoveries that have shaped her career and research directions. It was a genuine pleasure to hear more of her story, and I believe you'll find it both enlightening and inspiring. Thank you again for all your support! Scott's Mixtape Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Mixtape Substack at causalinf.substack.com/subscribe

Welcome to the Mixtape with Scott! This week’s guest is Nathan Nunn, professor in the Vancouver School of Economics at University of British Columbia. Nathan is a development economist and economic historian whose work on the development of the African continent has been viewed as pioneering, seminal even. Two of his major works focused on the African slave trade and its impact on trust (here in this AER) and the continent’s longterm development (here). The body of work is so massive that I can only point you to his webpage and vita. He’s currently an editor at Quarterly Journal of Economics, a member of NBER and a research fellow at BREAD. And here is his google scholar page. And for giggles, here are the people at NotebookLM explaining his vita! Here’s that NotebookLM link for people looking on YouTube or podcast platforms like Apple Music or Spotify. url: https://notebooklm.google.com/notebook/ac825f4e-3e35-4359-b154-bc82ef808a79/audio Thanks again everyone and I hope you enjoy this great interview! Scott's Mixtape Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Mixtape Substack at causalinf.substack.com/subscribe

Welcome welcome one and all! This is the newest episode of the The Mixtape with Scott where we talk to living economists, ask them what they wanted to be when they were little, learn what and how they did become, are becoming, what they became as an adult, and this week too, the road less traveled. This week’s guest is named Jérémy L’Hour. I first learned about Jeremy because of a JASA on synthetic control he wrote with Alberto Abadie a few years ago entitled “A Penalized Synthetic Control Estimator for Disaggregated Data”. I then learned that Jérémy had studied with Xavier D’Haultfoueuille, the econometrician and coauthor to the famed difference-in-differences estimator in the AER that helped launch a thousand ships on difference-in-differences with differential timing. I reached out to see if we might talk as Jérémy has a story that I have not had a chance to hear about. Jérémy is the author of Machine Learning for Econometrics with Christophe Galliac which is forthcoming at Oxford University Press. And of course he is the author of the JASA on synthetic control with Abadie. But interestingly, he is not an academic. Rather, he works for a hedge fund called Capital Fund Management. Which was another reason I wanted to talk to him. The last many years, we’ve seen more and more talented economists go into industry rather than academia, but mostly I interview economists in tech. I haven’t interviewed anyone who is at a hedge fund before, and I thought that that might be an interesting guest. There’s always a lot of uncertainty in the job market, but maybe now more than ever, and hearing about more options in the private sector would be useful to people all over the world. So thank you again everyone for supporting the substack and the podcast. I appreciate it immensely as it helps me to do what I love which is listening to people’s stories. I hope you enjoy this interview as much as I did. Scott's Mixtape Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Mixtape Substack at causalinf.substack.com/subscribe