Podcasts about Econometrics

Ever wonder how Walmart, Kroger, Home Depot, and Instacart are different from a guy in a trench coat? They ask for consent before exposure! Join Simon and Jim as they dive into the often misunderstood world of retail media networks with Sky Frontier, EVP at Incremental.Discover why retail media is the Wild West of advertising, how it's moving up the funnel, and the unique challenges it poses. Learn about Sky's journey from philosophy to advertising, and why your branded search strategy might need a rethink. Plus, we tackle Amazon's recent Google Shopping mystery – did they just pull off the greatest experiment of all time?Links from the show:Skye Frontier on LinkedInIncrementalShow Notes:00:00 Welcome Back and Summer Catch-Up00:34 AI Measurement Solutions and Future Prospects01:10 Retail Media Networks: An Introduction02:21 Guest Introduction: Sky Frontier04:15 Defining Retail Media Networks06:46 Challenges in Retail Media Measurement14:12 Incrementality in Retail Media18:42 Operational Challenges and Clean Rooms22:55 Challenges in Retail Media Experimentation23:41 Econometrics and Granularity in Retail Media25:18 Synthetic Experimentation and Difference-in-Differences Analysis28:30 Future Trends in Retail Media32:28 Amazon's Strategic Shift in Advertising41:55 Concluding Thoughts on Retail Media Measurement

Spriha Tucker is the Field CTO at Buildkite, where she plays a pivotal role in bridging the gap between Buildkite's engineering teams and its clients. A two-time Y-Combinator founder, Spriha previously co-founded Aviator, a developer productivity platform, which served customers like Slack, Figma, Doordash, Bosch, and others. Her prior experience includes Product Management at Google on developer tools, data, infrastructure and search ads, and at Microsoft, on platform tooling. Spriha also taught as an instructor at General Assembly and spent time as a Quantitative Trader at Morgan Stanley, focusing on developing trading models and trade execution algorithms for equities. She holds a Bachelor's degree in Econometrics and a Master's in Computer Science from the University of Pennsylvania.You can find Spriha on the following sites:LinkedInXGitHubHere are some links provided by Spriha:BuildkitePLEASE SUBSCRIBE TO THE PODCASTSpotifyApple PodcastsYouTube MusicAmazon MusicRSS FeedYou can check out more episodes of Coffee and Open Source on https://www.coffeeandopensource.comCoffee and Open Source is hosted by Isaac Levin

Rita is a visionary member of Project Kamp, a Portugal-based research community dedicated to prototyping a sustainable way of living in harmony with the planet. As a key collaborator in this innovative experiment, Rita has helped transform a 9-hectare plot of abandoned land and kick start a research place for sustainable practices, from upcycling plastic waste with Precious Plastic to building communal spaces with recycled materials. Her work embodies a bold reimagination of how humans can live, eat, and connect within nature. In this inspiring episode, Rita shares the journey of Project Kamp and her insights on sustainable living, including: The spark behind Project Kamp and its mission to rethink modern living The challenges and triumphs of transforming raw land into a sustainable community How Project Kamp's connection to Precious Plastic drives innovative plastic recycling Lessons on sustainable food systems, community cooperation, and living closer to nature A vision for a future where humanity thrives in balance with the environment This conversation is a must-listen for anyone curious about sustainable living, community-driven innovation, and the power of collective action to reshape our world.

Which research methods are better, quantitative or qualitative? What is more important, getting a richer picture of what goes on in organizations, or seeking generalizable insights about causality? This debate has raged at the very least since Glaser and Strauss popularized the grounded theory method in the mid twentieth century. In 2025, we want to put this debate to rest. We asked one of the best econometric scholars we know () and one of the best qualitative scholars we know () to fight this debate on air and come up with their very own end-of-all arguments. The result? It may surprise you: We all ought to get mad.   Episode reading list Chang, H. (2008). Inventing Temperature: Measurement and Scientific Progress. Oxford University Press. Burtch, G., Carnahan, S., & Greenwood, B. N. (2018). Can You Gig It? An Empirical Examination of the Gig Economy and Entrepreneurial Activity. Management Science, 64(12), 5497-5520. Greenwood, B. N., Kobayashi, B. H., & Starr, E. P. (2025). Can You Keep a Secret? Banning Noncompetes Does Not Increase Trade Secret Litigation. SSRN, . Kraemer, K. L., Dickhoven, S., Tierney, S. F., & King, J. L. (1987). Datawars: The Politics of Modeling in Federal Policymaking. Columbia University Press. Roth, J., Sant'Anna, P. H. C., Bilinski, A., & Poe, J. (2023). What's Trending in Difference-in-Differences? A Synthesis of the Recent Econometrics Literature. Journal of Econometrics, 235(2), 2218-2244. Matherly, T., & Greenwood, B. N. (2024). No News is Bad News: The Internet, Corruption, and the Decline of the Fourth Estate. MIS Quarterly, 48(2), 699-714. Levitt, S. D., & Dubner, S. J. (2005). Freakonomics: A Rogue Economist Explores the Hidden Side of Everything. William Morrow. Greenwood, B. N., & Wattal, S. (2017). Show Me the Way to Go Home: An Empirical Investigation of Ride-Sharing and Alcohol Related Motor Vehicle Fatalities. MIS Quarterly, 41(1), 163-187. King, A. A. (2025). Does Corporate Social Responsibility Increase Access to Finance? A Commentary on Cheng, Ioannou, and Serafeim (2014). Strategic Management Journal, forthcoming. . Seidel, S., Frick, C. J., & vom Brocke, J. (2025). Regulating Emerging Technologies: Prospective Sensemaking through Abstraction and Elaboration. MIS Quarterly, 49(1), 179-204. Pentland, B. T. (1999). Building Process Theory with Narrative: From Description to Explanation. Academy of Management Review, 24(4), 711-725. Lee, J., & Berente, N. (2013). The Era of Incremental Change in the Technology Innovation Life Cycle: An Analysis of the Automotive Emission Control Industry. Research Policy, 42(8), 1469-1481. Anderson, P., & Tushman, M. L. (1998). Technological Discontinuities and Dominant Designs: A Cyclical Model of Technological Change. Administrative Science Quarterly, 35(4), 604-633. Brynjolfsson, E., & Hitt, L. M. (1996). Paradox Lost? Firm-Level Evidence on the Returns to Information Systems Spending. Management Science, 42(4), 541-558. Noe, R. (2025). Moral Incoherence During Category Emergence: The Contentious Case of Connected Toys. Harvard Business School Working Paper, 24-071, . 

With conflict escalating in the Middle East, could we see a repeat of 2022’s global inflation wave as the oil price rises?See omnystudio.com/listener for privacy information.

Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Intro to Bayes Course (first 2 lessons free)Advanced Regression Course (first 2 lessons free)Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work!Visit our Patreon page to unlock exclusive Bayesian swag ;)Takeaways:Setting appropriate priors is crucial to avoid overfitting in models.R-squared can be used effectively in Bayesian frameworks for model evaluation.Dynamic regression can incorporate time-varying coefficients to capture changing relationships.Predictively consistent priors enhance model interpretability and performance.Identifiability is a challenge in time series models.State space models provide structure compared to Gaussian processes.Priors influence the model's ability to explain variance.Starting with simple models can reveal interesting dynamics.Understanding the relationship between states and variance is key.State-space models allow for dynamic analysis of time series data.AI can enhance the process of prior elicitation in statistical models.Chapters:10:09 Understanding State Space Models14:53 Predictively Consistent Priors20:02 Dynamic Regression and AR Models25:08 Inflation Forecasting50:49 Understanding Time Series Data and Economic Analysis57:04 Exploring Dynamic Regression Models01:05:52 The Role of Priors01:15:36 Future Trends in Probabilistic Programming01:20:05 Innovations in Bayesian Model SelectionThank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki...

Episode #24 of Impact in the 21st Century features the legendary author, editor, and bibliophile Alberto Manguel. Alberto Manguel is the acclaimed author of A History of Reading, The Library at Night, and dozens of other works exploring literature, memory, and the profound human need for stories. A lifetime reader and former Director of the National Library of Argentina, Manguel has lived a life shaped by books—reading to Jorge Luis Borges as a teenager, curating libraries across continents, and writing deeply about the roles books play in our personal and collective lives. In this episode, Manguel offers a masterclass on the power of reading in shaping empathy, identity, and civilization itself. We explore: What it means to read deeply in a distracted age How libraries function as the “memory of humanity” Why stories hold the key to understanding ourselves and our societies His reflections on the current state—and future—of reading This is a timeless conversation for lovers of language, ideas, and the written word.  

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

Episode #23 of Impact in the 21st Century features the dynamic Hylton Kallner. Hylton is the CEO of Discovery Bank, a trailblazer in digital banking and behavioral economics. With a background in actuarial science and a deep passion for innovation, Hylton has helped shape Discovery's vision of a shared-value ecosystem—one that rewards people for living healthier and more financially responsible lives. In this episode, Hylton shares the journey of building Discovery Bank from the ground up, the power of incentives to change behavior at scale, and how technology, when aligned with purpose, can redefine financial services. From tackling inequality to enabling better money habits through gamified banking, Hylton's insights are both practical and inspiring. We also dive into his personal motivations, the future of finance, and why South Africa is uniquely positioned to pioneer inclusive banking solutions that make a real difference.

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

Following Minister of Finance Enoch Godongwana's belated budget speech, the biggest headline is a VAT increase to 15.5%, with a further rise to 16% next financial year. Questions remain about whether the minister had other options, whether the VAT-exempt product basket has been expanded, and how this hike will impact the cost of living for ordinary South Africans. Dr Ntokozo Nzimande, Senior Lecturer in the Department of Economics and Econometrics at UJ explains Webpage

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

Welcome to episode 15 of season 4's The Mixtape with Scott! I am of, you guessed it, Scott. And this is my podcast which is a podcast where I interview economists and ask them about their personal story. If you were dying to know the games that economists played when they were kids, or what books they read in high school, then man are you ever in luck because that's literally what we talk about on here!This week's guest is Dmitry Arkhangelsky, an associate professor at CEMFI in Madrid, Spain. Dmitry is known to many people because of his 2021 American Economic Review article with an Avengers like team of econometricians and statisticians — Susan Athey, Guido Imbens, David Hirshberg and Stefan Wager — entitled “Synthetic Difference-in-Differences”. Synth diff-in-diff is a well known contribution to the pantheon of new causal panel methods and is quite versatile and flexible. Dmitry is currently on leave from CEMFI and had just arrived to Harvard for a research sabbatical when we did this interview. Dmitry is an econometrician and machine learning, and as he's connected to this new diff-in-diff and synth literature that has been exploding and evolving over the last few years, his work on those topics are well known. But I think as he's not on social media, he's not someone people may know as much about. So I hope you that this is an interesting interview for those of you wanting to learn about his life growing up in the bustling city of Moscow, Russia. It's a bit of a rags to riches story in some way as unlike many Russian economists who are dialed into the best schools as a young person, where they are exposed to intensive training in mathematics early on, Dmitry's journey was different, and I don't want to spoil it. But I think it's one that many of us may identify with. Thank you again for all your support of the podcast. It's a labor of love to get to have a chance to just pause, look at another person, and listen. I continue to believe that it's in the moments when we can look at a person that we know ourselves. And so I enjoy doing it and appreciate your support and hope it is the same for you on some level. And thank you to Dmitry for being generous with his time to share a little about his life. Consider becoming a paying subscriber where you get full access to all kinds of weird posts ranging from econometrics, practical opinions about work, discussion of my classes, and taking care of my ailing dad, as well as a fairly regular reflection on the economic implications of new technologies. 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

The secret to success in data driven marketing is relationships - according to Chris Love, Head of Marketing Performance & Econometrics at Virgin Media O2. On the latest podcast episode, Chris explains why getting the marketing team out of its silo and knowing how to contribute to other teams' success, while letting them help yours with their insights, has stood him in good stead throughout his marketing career. He also shares his views on the importance of "sweating the small stuff" and why, ultimately, all we do is sales.

If you've been in leadership development for a long time, you're in for a treat with this episode. Our guest, Howard Leong, is the youngest person to appear on the podcast! Don't let his youth fool you. He is wise beyond his years in his understanding of leadership and personal growth. Howard has been mentored by Asheesh Advani, CEO of Junior Achievement or JA Worldwide, and you'll see that he's absorbed key lessons from this extraordinary leader. Howard is featured in a new book that Asheesh co-authored with Marshall Goldsmith, Modern Achievement: A New Approach to Timeless Lessons for Aspiring Leaders. In this conversation, we explore the experiences and lessons learned that Howard shares in the book. Howard is the Research Strategist at JA Worldwide and is currently building The JA Institute. He's a college senior specializing in Econometrics and Machine Learning with four years of experience in software product management and international economic development.  Howard was awarded the Global Student Prize in 2021 from JA for building an online marketplace, JA Malaysia Mall, for high school entrepreneurs. In just two months, it fulfilled over 1,000 orders. He also built an investment app that received The Webby Award Honoree 2024. Howard has consulted the City of Calgary on economics, AI, and electricity rates. You'll discover: The messages Howard got from his family growing up in Malaysia and changes he felt compelled to make after leaving homeWhat the phrase, Modern Achievement, means to Asheesh and what it means to HowardWays Howard learned to advocate for himself—and the payoffs he got from doing soWhat employers need to know about working with young adultsTips for young employees who want to have a positive impactCheck out all the episodesLeave a review on Apple PodcastsConnect with Meredith on LinkedInFollow Meredith on TwitterDownload the free ebook Listen Like a Pro

Alexander Rinnooy Kan (1949) grew up in The Hague. He graduated in Mathematics from the University of Leiden in 1972. In the same year, he acquired a Candidate's degree in Econometrics at the University of Amsterdam. From 1973 to 1977 he taught mathematics and statistics at Delft University of Technology. During that period, in 1976, he obtained his PhD in Mathematics at the University of Amsterdam. Between 1977 and 1991 Rinnooy Kan held senior academic positions at Erasmus University Rotterdam and other European and American universities. He was rector magnificus of Erasmus University from 1986 to 1989, has published widely in professional journals and holds a number of honorary degrees. As Chairman of the Confederation of Netherlands Industry and Employers (VNO-NCW), a post he held from 1991 to 1996, Rinnooy Kan was one of the main representatives of Dutch business. He was member of the ING Group Executive Board from 1996 to 2006. Rinnooy Kan has been Chairman of the Netherlands Social and Economic Council from 2006 to 2012. In 2012, he was appointed as Distinguished University Professor at the University of Amsterdam. In June 2015, he was elected to the Dutch Senate. He sits on a variety of boards and has advised the Dutch government on numerous occasions.

We talk with Gautam Dhingra about his journey from a young boy in New Delhi, to managing over $1 billion as the founder of High Pointe Capital, to his diagnosis with terminal cancer. We discuss how he thinks about investment valuation, his decision to become an entrepreneur, and his thinking on life. Gautam is the founder of High Pointe Capital. He has served as the President of Chicago's CFA Society, and was honored by the CFA Society of Chicago with a Lifetime Achievement Award. Gautam holds a Ph.D. in Finance and Econometrics, has been a lecturer with Northwestern University's School of Management, and holds his CFA charter.   What Gautam is Reading Right Now: Becoming by Michelle Obama  Gautam's Music Recommendation: “Satnam Sri Wahe Guru” by Jagjit Singh Read More from Gautam: Gautam's Website, LinkedIn   ____ Get updated when new episodes release by joining our list: https://bit.ly/4dwwTgD Connect with CFA Society Dallas/Fort Worth: LinkedIn | Instagram| www.cfasociety.org/dallasfortworth

In this episode of the Oxford Policy Podcast, MPP student and Australian Rhodes Scholar Tahlia Smith sits down with John Roome, who recently retired after a distinguished 35-year career at the World Bank. A fellow Oxford alum, John reflects on how his time at Oxford and the Rhodes Scholarship shaped his path to international public service and leadership within the World Bank, one of the world's most influential development organisations.Tahlia and John discuss the evolving role of the World Bank in addressing complex global challenges such as climate change and development, and how international organisations can balance large-scale initiatives with local needs. John shares his experiences building coalitions to tackle climate change amidst political polarisation, his leadership of diverse teams across continents and cultures, and making tough decisions under pressure in high-stakes environments.With insights on leadership, the role of public service, and navigating the challenges of global governance, this episode provides a unique look into the career of someone who has played a key role in shaping international development policy. Tune in to hear John's reflections on maintaining resilience in the face of global crises and his advice for the next generation of international public servants.***John Roome recently concluded his role as Regional Director, South Asia Sustainable Development at the World Bank. Before that he was Senior Director for Climate Change. He joined the World Bank in 1989, working initially in Africa, and has since held various positions including Operations and Strategy Director for Global Practices and Cross Cutting Solutions, Director for Sustainable Development in the Bank's East Asia and the Pacific Region, Operations and Strategy Director in the Bank's South Asia region and as Operational Quality Director in the Bank's Africa region. His experience spans water, urban, transport, energy, rural, agriculture, environment, and social sectors, as well as disaster risk management and climate change. Before joining the World Bank, John worked in Europe for Monitor Company, a leading corporate strategy consulting firm, and at Old Mutual, a South African Life Assurance Company. He was educated at Oxford University, where he obtained Masters Degrees in Econometrics and in Management Studies, and the University of Cape Town where he obtained a Bachelor's degree in Economics, Statistics and Actuarial Science.

Here are the key takeaways from the podcast:* Effectiveness in marketing: It's about ensuring that marketing efforts, particularly advertising, achieve their intended goals, whether that's awareness, behavior change, or sales.* Econometrics simplified: Econometrics uses data to determine if a marketing campaign worked by analyzing both the campaign's direct impact and other factors (e.g. a competitor campaign) that could influence the outcome.* When to use econometrics: It's most useful for businesses with multiple marketing channels and more complex budgets but might not be necessary for very small businesses with straightforward marketing efforts.* Creativity matters: In a world with fragmented attention, compelling creative content is essential. Strong branding and creative consistency across platforms amplify marketing effectiveness.* The rise of digital: While traditional media like TV is losing its dominance, the advent of digital tools allows for more targeted, cost-effective, and immediate marketing responses, making brand-building and performance marketing work hand-in-hand.Links* Grace Kite & Magic Numbers* Grace on LinkedIn This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit letstalkbranding.substack.com

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 studying the effect of terrorism on economic growth that introduced the synthetic control estimator. My guest is Javier Gardeazabal, a professor at the University of the Basque Country. Javier Gardeazabal is a professor at the University of the Basque Country whose body of work has covered topics in macroeconomics, time series econometrics, labor economics, cultural economics, and political economy. He did his PhD at the University of Pennsylvania in May 1991, an experience that he will share about in the interview. He is from the Basque Country and returned to the Basque Country after graduation where he has been ever since. It is therefore inspiring to me that his home became the topic of a paper that he is perhaps most widely known for — a seminal contribution to both causal inference and measuring the economic costs of terrorism, coauthored with Alberto Abadie, in the 2003 American Economic Review paper, “The Economic Cost of Conflict: A Case Study of the Basque Country.” This groundbreaking study made a major contribution to causal inference by introducing the synthetic control estimator, but also assessing the economic impact of terrorism on economic growth in the Basque Country. It was a major contribution to the field possessing all the elements of great articles in economics — an important question answered extraordinarily well with clarity and rigor. This influential paper not only cast a massive shadow over the evolution of causal inference and econometrics; it also accelerated Javier's own research to include not only macroeconomics, but also the economics of terrorism and conflict. His career is evidence of an economist who followed his curiosity and intellectual interests to include understanding the economic costs of terrorism, introducing methods for measuring the aggregate cost of conflict, and the impact of political violence on economic well-being, but also exchange rate dynamics, time series econometrics, cultural policies, optimal test scoring methods, gender wage discrimination and more. Javier's versatility is evident in his ability to adapt to and excel in a variety of economic topics and methodologies, continually evolving to address new and relevant economic issues.Thank you again everyone for supporting the podcast and the substack. I hope that this interview speaks to you wherever you are, whenever you are. Scott's 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 Substack at causalinf.substack.com/subscribe

Jeffrey Lacker is a senior affiliated scholar at the Mercatus Center, but has also previously worked at the Federal Reserve Bank of Richmond from 1989 to 2017, serving as its president from 2004 to 2017. Jeff is also a returning guest to podcast, and he rejoins Macro Musings to talk about Fed governance issues and the lessons learned from the recent inflation surge. Specifically, David and Jeffrey also discuss the issue of maximum employment, how the Fed could reform its governance structure, what the central bank should address during the next framework review, and more.   Transcript for this week's episode.   Jeffrey's Mercatus profile Jeffrey's website Jeffrey's Richmond Fed archive   David Beckworth's Twitter: @DavidBeckworth Follow us on Twitter: @Macro_Musings   Check out our new AI chatbot: the Macro Musebot! Join the new Macro Musings Discord server!   Join the Macro Musings mailing list! Check out our Macro Musings merch!   Related Links:   *Governance and Diversity at the Federal Reserve* by Jeffrey Lacker   *What Lessons Should the Federal Reserve Learn from the Recent Inflation Surge?* Presentation by Jeffrey Lacker at the 2024 UC San Diego Economics Roundtable Lecture Series   *Central Bank Undersight: Assessing the Fed's Accountability to Congress* by Andrew Levin and Christina Parajon Skinner   *Reform the Federal Reserve's Governance to Deliver Better Monetary Outcomes* by Dan Katz and Stephen Miran   *Don't Audit the Fed, Restructure It* by Michael Belongia and Peter Ireland   *Restoring the Promise of Federal Reserve Governance* by Peter Conti-Brown   *Jim Hamilton on Econometrics, Energy Markets, and Low Interest Rates* by Macro Musings   Timestamps:   (00:00:00) – Intro   (00:04:35) – Jeffrey's View on “Monetary Federalism”   (00:10:01) – Reducing the Number of Regional Fed Banks   (00:13:11) – Addressing Peter Conti-Brown's Proposals for Fed Governance Reform   (00:18:23) – Addressing Andy Levin and Christina Skinner's Proposals for Fed Governance Reform   (00:23:07) – Altering the Fed's Responsibilities as a Bank Regulator   (00:29:21) – What Lessons Should the Federal Reserve Learn from the Recent Inflation Surge?   (00:36:14) – The Issue of Maximum Employment   (00:46:38) – Evaluating the Fed's Response to the Recent Inflation Episode   (00:50:45) – What Should the Fed Be Addressing During the Next Framework Review?   (00:55:01) – Outro

Lars Christensen is a founding member of the market monetarist tradition, an entrepreneur in the AI space, and is also a returning guest to Macro Musings. Lars rejoins the podcast to talk about AI and its implications for the economy and for monetary policy. David and Lars also discuss the basics and implications of dynamic pricing, AI's growing use within econometric analysis, how AI will impact the Fed and its policymaking, and much more.   Transcript for this week's episode.   Lars's Twitter: @MaMoMVPY Lars's blog   David Beckworth's Twitter: @DavidBeckworth Follow us on Twitter: @Macro_Musings   Check out our new AI chatbot: the Macro Musebot! Join the new Macro Musings Discord server!   Join the Macro Musings mailing list! Check out our Macro Musings merch!   Related Links:   *From Merchants to Quants: The Digital Revolution in Retail* by Lars Christensen   *Less Than Zero: The Case for a Falling Price Level in a Growing Economy* by George Selgin   Timestamps:   (00:00:00) – Intro   (00:01:16) – Lars's Move from Macro to AI   (00:08:02) – The Basics and Implications of Dynamic Pricing   (00:16:17) – Using AI for Econometric Analysis   (00:23:54) – The Implications of AI for the Economics Field   (00:35:45) – How Will AI Impact the Federal Reserve and its Policymaking   (00:38:55) – Deflation as a Response to an AI Driven Productivity Shock   (00:52:08) – Outro   Photo Credit: Nordnet Bank

About the author of "DEALS DANGER DESTINY"So, if you thought a Renaissance Man was a thing of the past, think again. That opening quote was made by Dr. John LaCasse, who has ricocheted through life with ups and downs - ultimate highs and dismal lows. This high ridge walker from Montana became a wizard of wealth in Seattle as a successful yacht broker for 25 years. It brought him into relationships with business magnates such as Boeing, and Weyerhaeuser, political figures such as Secretary of State George Shultz, actor Gene Hackman, Prince Rainier III of Monaco, oceanographer Jacques Cousteau, Adriana Salinas de Gortari, and organized crime bosses Meyer Lansky and Johnny Carbone.Fast and Furious with Penthouse style, fast cars, and outlaw bikers…Being handed checks in the millions, drinking and smoking to excess—it was all real until one day it hit him: “Why am I living this life? Why am I letting this happen?”Even though marriage and fatherhood provided new sources of happiness and responsibility, the loss of two sons brought unimaginable grief. The piles of money meant nothing. Curiosity and education meant everything. John returned to school in middle age, but his attitude got him kicked out of three universities as he became reacquainted with "Who has the power." John ultimately prevailed with three terminal degrees including a Ph.D., in Education eLearning.Fearless John has waded into more than one situation with some interesting results. On a large transaction involving a meeting with the Chairman of Native Northwest Tribes, he realized he had no experience with Native Americans. When he showed up for the meeting, the tribal chairman motioned for John to take his seat across from him. John sat. The Chairman sat. They stared at each other. John raised his right hand and said, “How.” The Chairman leaned in and in a soft voice replied, “I have a master's degree, and I'm writing my Ph.D. dissertation on Biomass at the University of Washington, and I speak English.” That became a friendship that lasts to this day, and John carries a Chief Honor Blanket from The Confederated Tribes of the Colville Reservation. ******************John LaCasse is the founding principal of Silvertip Research. A team organization connected through companion disciplines in Factor Analysis for Statistics, Economics, Econometrics, eLearning, and Education. He is a private pilot on land and sea. CAPT United States Merchant Marines. --- Send in a voice message: https://podcasters.spotify.com/pod/show/charles-perry/message

As an entrepreneur, investor, and Army veteran, Craig is a true Austinite super connector immersed in the city's vibrant tech community. He is the Special Advisor for Military and Veteran Affairs for Capital Factory and serves on the Advisory Boards of VetsInTech, Texas Venture Labs at UT McCombs School of Business, and DivInc. After 17 years of military service that earned him a Bronze Star, he co-founded the transportation platform RideScout, which was acquired by Mercedes-Benz.In 2014, Craig co-founded Moonshots Capital alongside Kelly Perdew to invest in extraordinary leadership in the military veteran community and beyond. Craig holds a B.S. in Political Science from West Point, where he was their first Truman Scholar and later served as Assistant Professor of Political Science.He also holds a Ph.D. in Political Science and Econometrics from Columbia University, is a member of the 2016 class of Henry Crown Fellows with the Aspen Institute and was recently named a Future Texas Legend Veteran by the Texas Business Hall of Fame. He is married to Lawton Posey Cummings and has two children, Addison (21), and Cooper (18).Find out more at:https://www.moonshotscapital.com/https://medium.com/leadership-prevailshttps://www.linkedin.com/in/unleashcraig/

Part 2 of 3. My guest for this week's episode is Grant Aarons, Co-Founder and CEO of FabricNano, a London-based biotech whose mission is to transform industrial chemical processes using cell-free biomanufacturing. FabricNano empowers users with the world's most advanced, flexible, and easily scalable biocatalyst platform, providing highly stable and performant biocatalysts to enable profitable production of sustainable and biobased chemicals. Their approach starts with novel immobilization engineering for enzyme stabilization, followed by budget-conscious protein engineering and process engineering to reach their clients' targets for commercialization of their new biochemical production process.

Show Summary Dr. Sundas Ali, a former Lecturer at the University of Oxford and now an admissions consultant at Accepted, discusses the differences between graduate school admissions in the UK and the US. She explains that while there are some similarities in the application process, such as the importance of personal statements in both countries,there are also several differences. Dr. Ali emphasizes the importance of tailoring personal statements and resumes to each program and university, as well as the significance of strong recommendations from professors. She also advises applicants to start early, do thorough research on the programs they are interested in, and proofread their application materials carefully to avoid common mistakes. Dr. Ali shares her own experience of overcoming challenges and pursuing her dream of studying at Oxford University. Show Notes Welcome to the 574th episode of Admissions Straight Talk. Thanks for joining me. The challenge at the heart of admissions is showing that you both fit in at your target schools and stand out in the applicant pool. Accepted's free download, "Fitting In and Standing Out: The Paradox at the Heart of Admissions", will show you how to do both. Master this paradox and you're well on your way to acceptance. You can download this free guide at accepted.com/fiso. It is my pleasure to welcome Dr. Sundas Ali to Admissions Straight Talk. Originally from Pakistan, Sundas received both a BS in Economics and Econometrics and an MSc in International Relations from the University of Bristol in the UK and then a PhD in Sociology from the University of Oxford. She worked for several years at the UK Civil Service and, since 2013, served as a Lecturer at the University of Oxford. While at Oxford, she was involved in Oxford's prestigious PPE (Philosophy, Politics, and Economics) admission process. She has also been involved in teaching high school and college students in rural areas of Pakistan through online platforms as well as guiding them through the college admissions process. At Accepted, Sundas will be working primarily with college and graduate school applicants. The show today will focus on graduate school admissions as always.  Sundas, welcome to Admissions Straight Talk and Accepted. [2:12] Thank you, Linda. It's a pleasure to be on this podcast today, and I'm absolutely delighted to be a part of the team at Accepted. I'm delighted to have you both as a part of the team and on the podcast. At Oxford, you worked with students both at Oxford and outside of it who wanted to attend UK graduate programs. Is there some quality or element of the admissions process that is unique to UK universities or to Oxford? Something that non-UK applicants need to adjust to? [2:23] Yes. Having worked with students for over 15 years at Oxford and those outside wanting to apply to the UK, US, and the rest of the world, I think what's distinct about the UK is quite similar to other countries when it comes to graduate applications. If we were looking at college, that's quite a difference between the US and the UK. But I find that actually for graduate programs, there's quite a lot of similarity. For example, the personal statement, the academic statement of personal statement, which is very important when applying for graduate study in the UK. And it's similarly very important when you're applying to the US. So there are a lot of similarities across the board when it comes to graduate study. The degree programs vary. So we have different degree structures in the UK, so you have an MRes, for example, which is a research degree and different types of degrees to the US perhaps, which maybe there are two different types of graduate programs when it comes to masters. But specifically thinking about Oxford and Cambridge, what's quite different is that when you're applying to Oxford and Cambridge, you are applying to not just a department, but also a college.

Shwetank Verma is the co-founder of Leo Capital, a venture capital fund investing in companies inIndiaand South East Asia. Recent investments include CoLearn (edtech), WayForward (mental health), CoverGenius (Insurtech) and IndiaGold (Digital Gold). Leo Capital is backed by institutional investorsfrom Singapore and Silicon Valley. Prior to Leo Capital, he led Open Innovation for MetLife Asia and was a part of the senior management team of LumenLab, MetLife's innovation consultancy. At LumenLab, he advised MetLife country CEOs andsenior leaders on growth, startup collaboration, culture change and new product development. Prior to joining MetLife, he was a serial entrepreneur in healthcare and education in India. He serves asInnovation Adviser to the Institute of Innovation and Entrepreneurship at the Singapore Management University. He is also a fellow of the Institute of Chartered Accountants England and Wales and holds a Bachelor of Science in Economics and Econometrics from the University of Nottingham (UK), where he was a Foreignand Commonwealth Office scholar. . . . Episode Notes: State of the industry in 2024  How does Shwetank define a good investor? Takeaways from working with portfolio founders Vision for India the next 5 years Examples of building from India for the world from a category-creation play Best investor persona: Operator vs Pure investor? How did Leo build its internal thesis? Why did Shwetank become an investor? What does Shwetank like and dislike about investing? How has Shwetank evolved as an investor? Insights from working with Leo's porticos Advice Shwetank would give his younger self . . . Social Links: Follow Shwetank on Twitter Follow ⁠Shwetank on LinkedIn⁠ Follow ⁠The Desi VC on LinkedIn⁠ Follow ⁠Akash Bhat on Twitter⁠ Follow Akash Bhat on LinkedIn

Episode 149: Using Data to Create a Better Employee ExperienceHow can organizations use data to enhance the employee experience and drive positive cultural change within their workplace?On this episode of Practice Disrupted, Dr. Serena Huang, a data analytics executive in Fintech, joins us to discuss how organizations can optimize the employee experience by leveraging data and communication strategies in the workplace. As a data analytics executive, Dr. Huang is passionate about leading change, building high-performance teams, and helping business leaders see data as an asset in large organizations. First, Dr. Huang defines the employee experience as various aspects of work, from physical environments to manager interactions and digital work capabilities. She emphasizes the importance of measuring employee experience beyond physical space and attendance and suggests surveys and feedback tools to gauge workplace culture and gather recommendations. Then, we explore the challenges and apprehensions that can arise when introducing survey data to the workplace, including concerns about legal action and the fear of uncovering uncomfortable truths. For architects, we address the common fear about not being able to afford an immediate solution for desires such as taking time off. Dr. Huang shares advice for effectively communicating with architecture leaders who are reluctant to engage in surveys due to these fears, yet recognize their need for growth. She believes leadership needs timely action, collaborative problem-solving, and transparency to drive change.It comes down to communication. Fundamentally, as humans, we all need to be heard, whether at home, in a relationship, or at work. For employees to feel heard, instead of ignoring the elephant in the room, why don't we ask about it and then come up with some solutions? It may not be the perfect solution, but I think the leadership team should come from a place of genuine care, communicate that back to the employees and say, "We heard you." - Dr. Serena HuangTo wrap up the conversation, Dr. Huang shares her perspective on employees and leaders navigating their career alongside their mental health management. She advocates for leadership therapy and coaching sessions to enhance self-awareness and emotional well-being.Tune in next week for an episode about women defining AI for architects.Guest:Dr. Serena HuangDr. Serena Huang is an accomplished thought leader and professional keynote speaker with 150+ speaking engagements covering topics including people analytics, AI, future of work, personal branding, and data storytelling. She regularly guest-lectures at top MBA programs including Kellogg, Wharton, and Haas. Dr. Huang's unique ability to speak to audiences of different cultures and backgrounds, along with her experience in both F100 and startups make her an in-demand speaker. Her 2024 focus is helping organizations realize the full potential of AI through creating a new workforce strategy and improving internal talent mobility.Prior to founding Data With Serena, Dr. Huang led sizable analytics teams at prominent organizations including PayPal, Kraft Heinz, GE, and Koch Industries. She pioneered the applications of machine learning algorithms to predict absenteeism and turnover and led corporate councils for Ethical AI in these global organizations. Dr. Huang holds a Ph.D. in Economics with specializations in Econometrics and Labor Economics.

This week on the Tech Policy Grind, we're sharing two conversations from State of the Net 2024, the premier internet policy conference that took place in February in Washington, D.C, to discuss the impact of AI on cybersecurity policy and the future of work.  Foundry Fellow Sasa Jovanovic and I spoke with Heather West and Charley Snyder on the impact of AI on cybersecurity policy. We discussed the nexus between Artificial Intelligence and cybersecurity, revealing how AI’s advancements carry both protective potential and novel vulnerabilities.  We also chatted with Dr. Athina Kanioura, Chief Strategy and Transformation Officer at PepsiCo, about navigating the policy challenges around the deployment of AI in the workplace, while making sure that AI promotes societal values and labor equity.  DISCLAIMER: Daniela, Evan, Sasa, Athina, Heather and Charley engaged with this episode by the Internet Law & Policy Foundry voluntarily and in their personal capacity. The views and opinions expressed on this show do not reflect the organizations and institutions they are affiliated with. Bios Athina Kanioura is Executive Vice President, Chief Strategy and Transformation Officer at PepsiCo. An accomplished innovator and transformation leader, Kanioura oversees PepsiCo's end-to-end strategy to win both as a total company and in key markets, including our digitalization strategy. She also leads company-wide transformation—ensuring that our scale is leveraged as we focus on accelerating profitable growth and identifying areas of cost efficiency and optimization—in addition to overseeing Data Products, Platforms, and Talent. Prior to joining PepsiCo, Kanioura was the Chief Analytics Officer and Global Head of Applied Intelligence at Accenture, where she specialized in applying AI and analytics to drive business value. During her 15 years at Accenture, Kanioura grew the Applied Intelligence function from a subspecialty to a global group at the forefront of scale business transformation. Kanioura is a member of the Royal Statistical and Economics Society, where she contributes to shaping government policy around how data is used by bodies like the IMF. She also sits on the board of the Institute of Marketing Sciences and is a keen educator who has held lectureships at UMIST (UK), Imperial College London (UK), and the University of Sheffield (UK), where she also earned her PhD in Econometrics and Quantitative Economics.  Charley Snyder serves as Head of Security Policy at Google. In this role, Charley leads efforts to organize Google’s security expertise and technology to help solve the world’s pressing challenges related to safety and security online. Charley has security technology and policy experience in the public and private sectors. Before joining Google, he was a senior vice president at Goldman Sachs Group, where he was Global Head of Vulnerability Management and later led the Engineering Division's zero-trust security strategy. Previously, Charley served in the United States government, including multiple roles in the Department of Defense. He served as Deputy Director of Strategic Cyber Defense and Capabilities in the Office of the Secretary of Defense, and as a Senior Cyber Policy Advisor. Earlier in his career, Charley was a professional staff member for the U.S. House of Representatives Committee on Homeland Security, where he led the committee's oversight of Federal cybersecurity and intelligence issues.  Heather West is a policy and tech translator, product consultant, and long-term digital strategist guiding the intersection of emerging technologies, culture, governments, and policy. Equipped with degrees in both computer and cognitive science, Heather focuses on data governance, data security, artificial intelligence (AI), and privacy in the digital age. She is a subject matter authority who has written extensively about AI and other data driven topics for over a decade. She is also a member of the Washington Post’s The Network, “a group of high-level digital security experts” selected to weigh in on pressing cybersecurity issues.

Joining the Native Angelino Podcast from Kyoto, Japan, Professor Linus Yamane speaks eloquently about the lessons the United States can learn from the Japanese economy. Heavy government debt levels restrain the ability of policymakers to correct problems even in light of obvious trends. An aging population, a declining population, increasing wealth disparity and education inequality pressure the social security system. What policy prescriptions are available to ensure the proper functioning and availability of the system for future generations? Bio: Professor Yamane is a Professor of Economics at Pitzer College in Claremont, California. He joined the Pitzer faculty in 1988, and is currently on sabbatical (2023-2024). His research interests include the Japanese Economy, Labor Economics, Econometrics and Macroeconomics. He attended Yale University (MA, MPhil, PhD)and the Massachusetts Institute of Technology (BS).About The Author And Podcast Host Tom LevineTom Levine is a Native Angelino and graduate of USC Marshall School of Business, the Claremont Colleges, and spent a term at the London School of Economics.Following a 25 year career in capital markets, Tom Levine founded Zero Hour Group in 2014. The Los Angeles, California-based firm provides consulting, strategic analysis, valuation and real estate services. Serving individuals, family offices, institutions and professional investors.Native Angelino Real Estate, established 2017, for residential, commercial and investment related transactions. Additionally, he is a consultant, broker and certified Short Sale and Forclosure specialist under the National Association of Realtors. (CADRE #2052698)The Native Angelino Podcast is underwritten and produced in conjunction with the Zero Hour Group.“From a vantage point within sight of the Hollywood Sign, seated beneath a palm tree, Tom Levine takes you on a twisted, exploratory tour of popular thought, the upside-down theories of classical economics, politics, and other strange things.Tom talks all things Los Angeles, bright new ideas, and complex topics of interest to creative thinkers and discerning skeptics.L.A. locals state with pride, "You can surf in the morning and ski in the afternoon." Well, if you get a really early start, it's true. Sometimes.Los Angeles is the City of the Angels, and Tom Levine is a Native Angelino. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.1929.live/subscribe

Get ready for another captivating episode of Talk Money To Me as Candice and Felicity return with Part 2 of their limited Fixed Income series!Join Candice and Felicity as they delve into the historical returns of bonds and uncover insightful reasons to hold, buy more, or sell bonds, tailored to where the economic cycle stands.But wait, there's more! This episode features another expert in the fixed income space. Dr. Christopher Baylis, PhD in Econometrics and Founder/CIO at Fortlake Asset Management, shares his invaluable thoughts on the asset class and offers a glimpse into the potential outlook ahead.Listeners won't want to miss out on this enriching discussion packed with actionable advice and expert perspectives. If you want to know more about Fixed Income as an asset class you won't want to miss this episode!If you missed it, check out last week's Part 1 of the Fixed Income series to hear about the basic mechanics of bonds, the different types of bonds and important factors which impact the pricing or interest returns on offer for asset class. Follow Talk Money To Me on Instagram, or send Candice and Felicity an email with all your thoughts here. Felicity Thomas and Candice Bourke are Senior Advisers at Shaw and Partners, and you can find out more here. *****In the spirit of reconciliation, Equity Mates Media and the hosts of Talk Money To Me acknowledge the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respects to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander people today. *****Talk Money To Me is a product of Equity Mates Media. This podcast is intended for education and entertainment purposes. Any advice is general advice only, and has not taken into account your personal financial circumstances, needs or objectives. Before acting on general advice, you should consider if it is relevant to your needs and read the relevant Product Disclosure Statement. And if you are unsure, please speak to a financial professional. Equity Mates Media operates under Australian Financial Services Licence 540697.Talk Money To Me is part of the Acast Creator Network. Hosted on Acast. See acast.com/privacy for more information.

Jan has a boy crush on IS Econ researchers while Nick thinks they reduce all phenomena to regressions. Time to put both myths – and a few others – to rest. We brought on the inimitable and wonderful and to talk about everything you ever wanted to know about economics, econometrics, difference-in-difference designs, mechanism identifications, analytical modeling, and forbidden comparisons. At the end of it all, Jan's boy crush has subsided a little bit – which is probably good – and Nick's theory that every study is just a case study is, well, still a theory. But Gordon and Brad share a wealth of insights and tricks about how to do good econometric research in IS and how to get it published. As usual, the references to readings we mention are listed on . Also, just to be clear – the 2024 SIG DITE paper development workshop keynote speakers are not yet confirmed, but it will definitely be worthwhile to attend. In case you are interested, follow .

Econtalk There's often a gap between the textbook treatment of statistics and the cookbook treatment--how to cook up the numbers when you're in the kitchen of the real world. Jeremy Weber of the University of Pittsburgh and the author of Statistics for Public Policy hopes his book can close that gap. He talks to EconTalk host Russ Roberts about how to use numbers thoughtfully and honestly.

Econtalk There's often a gap between the textbook treatment of statistics and the cookbook treatment--how to cook up the numbers when you're in the kitchen of the real world. Jeremy Weber of the University of Pittsburgh and the author of Statistics for Public Policy hopes his book can close that gap. He talks to EconTalk host Russ Roberts about how to use numbers thoughtfully and honestly.

There's often a gap between the textbook treatment of statistics and the cookbook treatment--how to cook up the numbers when you're in the kitchen of the real world. Jeremy Weber of the University of Pittsburgh and the author of Statistics for Public Policy hopes his book can close that gap. He talks to EconTalk host Russ Roberts about how to use numbers thoughtfully and honestly.

In this episode of The Brand Called You, Trent Eddy, a private equity investor in frontier ASEAN markets, discusses opportunities there. He explores unique options in Frontier ASEAN. Trent emphasizes the growing blend of impact investing and commercial returns. He provides examples of exit strategies, including sales to various buyers. Trent advocates visiting frontier markets to see investability and dispel misperceptions. Overall, he shares insights on ASEAN frontier private equity. About Trent Eddy Trent is the Co-Founder and Director at frontier-ASEAN private equity fund manager, Emerging Markets Investment Advisers. Before this Trent worked at companies like Bain & Company and Myanmar Private Equity & Venture Capital Association (MPEVCA). He completed his MSc, Econometrics & Mathematical Economics from the London School of Economics and Political Science (LSE). --- Support this podcast: https://podcasters.spotify.com/pod/show/tbcy/support

Bronwyn Williams & Germinal G. Van | The Small Print In this episode, Bronwyn speaks to entrepreneur and political scientist, Germinal G. Van. They discuss the relationship between capitalism and wealth inequality, inequality vs unfairness, the effect of monetary policy on inflation, the virtues of a commodity-backed economy, the entrepreneurial culture of Anglo-Saxon countries, and more. Bronwyn Williams is a futurist, economist, trend analyst and host of The Small Print. Her day job as a partner at Flux Trends involves helping business leaders to use foresight to design the future they want to live and work in. You may have seen her talking about Transhumanism or Tikok on Carte Blanche, or heard her talking about trends on 702 or CNBC Africa where she is a regular expert commentator. When she's not talking to brands and businesses about the future, you will probably find her curled up somewhere with a (preferably paperback) book. She tweets at @bronwynwilliams. Twitter Flux Trends Website Germinal G. Van is an award-winning author, economist, political scientist, and scholar. He is a member of the National Association of Business Economics and the Economic History Association. He was born in Abidjan, Cote d'Ivoire. He immigrated to the United States in 2010. He obtained a bachelor's degree in political science from the Catholic University of America in 2014, earned a master's degree in political management from George Washington University in 2017, and acquired a non-degree certificate in Mathematical Statistics from Duke University. His works mainly focus on Public Choice Theory, Economic History, Econometrics, Statistics, and Mathematical Economics. GGV Publishing Company, LLC The Lake Street Review, Inc. Instagram Twitter LinkedIn Subscribe to our Substack.   Follow us on Social Media: YouTube LinkedIn Facebook Twitter Instagram   Subscribe to the Discourse ZA Podcast: iTunes Stitcher Spotify RSS feed  

In this episode, The Random Sample switches things up a bit. The people who usually ask the questions on this podcast, our hosts, are actually our guests.We explore why these researchers wanted to also become podcasters and what they've learnt along the way by hosting this podcast. Our hosts turned guests for this episode are: Rose Crocker is an applied mathematician with the Australian Institute of Marine Science; Cynthia Huang is a PhD Candidate in the Department of Econometrics and Business Statistics at Monash University; Dr James Nichols is a mathematician and lecturer at the Australian National University; Dr Sevvandi Kandanaarachchi is a Senior Research Scientist at CSIRO.  Our host for this episode is Peter Taylor, a Redmond Barry Distinguished Professor of Mathematics at The University of Melbourne.See omnystudio.com/listener for privacy information.

Athina Kanioura, PepsiCo's EVP and Chief Strategy Officer, oversees global strategy for iconic brands, contributing to an $86 billion revenue in 2022. Formerly with Accenture, she led AI initiatives, specializing in business transformation across industries. With a PhD in Econometrics, Athina shapes data policy at the Royal Statistical Society and educates at UK universities. On The Menu: 1. Integrated Digital Transformation: Spanning the organization's value chain. 2. Tech Application: AI, web3, robotics, blockchain in manufacturing, logistics, product development. 3. Streamlined Innovation: Focused on direct consumer engagement and mass personalization. 4. Theory-Practice Integration: Balancing academic rigor with real-time problem-solving. 5. Digital Hubs' Functions: Co-creating AI solutions, fostering career growth, diverse tech skills. 6. Pepsi's Tech Training: Digital Academy upskilling employees in varied roles.

In today's podcast, we're delving deeper into the follow-up to the groundbreaking book, "Predictions: Society's Telltale Signature Reveals the Past and Forecasts the Future." This sequel takes us on an exciting journey, offering a fresh perspective on understanding society and ourselves by employing scientific principles to forecast social phenomena. But that's not all; we're also tackling the daring task of revisiting the predictions made two decades ago and comparing them to real-world data—a step forecasters typically shy away from. And to sweeten the deal, this book introduces many new, relevant topics that have emerged recently. Stay tuned for an enlightening exploration of these intriguing insights! Find Theodore here: 00:00:00.355 Introduction and Recap of Part One 00:02:00.301 Growth Potential in China and India 00:10:23.649 Synthetic Rubber: Exceptional Growth During the War 00:12:32.440 Anticipating New Product Introductions and Disease Trajectories 00:15:45.440 Cardiovascular vs. Cancer: Competing Diseases 00:17:49.360 Competing Travel Means: Cars, Trains, and Planes 00:20:01.429 Competition for Energy: Fuel and Share Growth 00:22:13.924 The Fuel Conundrum: Fluctuations and Fracking 00:25:08.739 The Succession of S-curves in Energy Consumption 00:27:17.544 Subjective vs Concrete Variables in Econometrics 00:28:49.043 The Breakdown of Data Agreement in Electricity Production

From the frontlines in Afghanistan to the center of the Texas startup ecosystem, Craig Cummings has built an incredible career developing technology that solves real-world problems. He's now General Partner at Moonshots Capital, a venture capital firm in Austin that invests in technology startups, with a special focus on those founded by military veteran entrepreneurs.  Join us as we delve into Craig's inspiring journey, his insights into technology investments, and the unique perspective he brings to the entrepreneurial world. In this episode, Craig shares with Michael his experience: Crafting an elevator pitch that advances your career Building a strong local entrepreneurship community in Austin Helping other talented veteran entrepreneurs succeed Before he became an entrepreneur, Craig spent 17 years in the Army, most of that time as an Intelligence Officer serving in support of the National Security Agency (NSA). Craig deployed to Afghanistan with the Joint Special Operations Command where he was awarded the Bronze Star.  Craig holds a B.S. in Political Science from the U.S. Military Academy at West Point, where he was recognized as their first Truman Scholar. He also has a Ph.D. in Political Science with a minor in Econometrics from Columbia University. Thank you to ACG Denver for being a sponsor of CXO Conversations Podcast. Association for Corporate Growth in its role as the hub of the middle market business community for quality networking, education and events. Connections are made, deals are formed and thought leadership is exchanged.   Enjoy the show? Leave us a review on iTunes - thanks!  Thank you Jalan Crossland for lending your award-winning banjo skills to CXO Conversations.

PJ Glandon is an associate professor of economics at Kenyon College, where he also serves as chair of the economics department. PJ joins David on Macro Musings to talk about his recent co-authored article, *Macroeconomics Research: Present and Past.* David and PJ also more broadly discuss the state of macroeconomics as a discipline, both in terms of research and pedagogy.   Transcript for this week's episode.   PJ's Twitter: @pjglandon PJ's Kenyon profile   David Beckworth's Twitter: @DavidBeckworth Follow us on Twitter: @Macro_Musings   Join the Macro Musings mailing list! Check out our new Macro Musings merch!   Related Links:   *Macroeconomics Research, Present and Past* by PJ Glandon, Ken Kuttner, Sandeep Mazumder, and Caleb Stroup   *Let's Close the Gap: Updating the Textbook Treatment of Monetary Policy* by Jane Ihrig and Scott Wolla

When it comes to machine learning and artificial intelligence being deployed for marketing mix modeling, we might want to pump the brakes a bit, at least that's what some industry leaders are saying. To explore this topic in a little more depth, we wanted to bring on an expert, someone who's been in this field for nearly 2 decades, and has built a highly successful company around marketing mix modeling over the past 10 years. Dr. Ramla Jarrar has a Master of Science in Quantitative methods in Marketing and Optimization, a Ph.D in Econometrics and Quantitative Economics. She's a Professor at the Mediterranean School of Business, and is the Co-Founder and President of MASS Analytics, a software solution and service provider with a focus on marketing effectiveness measurement. And, you may recognize her from one of the many YouTube videos on the MASS Analytics channel where she provides free marketing mix modeling master classes. We discuss the warnings about AI-driven MMM, and provide guidance on how AI can help. ▶️ Watch on YouTube Links from the show: Dr. Ramla Jarrar on LinkedIn MASS Analytics  MMM Master Classes (YouTube) --- Send in a voice message: https://podcasters.spotify.com/pod/show/measure-up/message

This episode is proudly supported by Monash University, promoting the Masters of Indigenous Business Leadership program, delivered by Monash Business School & The William Cooper Institute. The Master of Indigenous Business Leadership, is a cross-disciplinary program with leading units delivered by Monash Business School, complemented by a tailored offering in design thinking, together with a mastery unit from Law. The partnership series features interviews with Aboriginal and Torres Strait Islander past and current students, staff and guest speakers from the program. In this episode I yarn with Monash University staff members, Amale Scally & Robert Brooks. Robert Brooks is a professor in the Department of Econometrics and Business Statistics and Deputy Dean, Education in the Faculty of Business and Economics. Amale Scally is a Lecturer/Deputy Director of Education, Department of Banking and Finance. Together, we yarn all about the MOIBL program. An excellent insight from a staff perspective, especially if you are considering looking further into the program. If you are interested, listen to this episode! If you'd like to apply, please see the links below. Recommendations throughout this episode:  https://www.monash.edu/study/courses/find-a-course/indigenous-business-leadership-b6024? Website: www.blackmagicwoman.com.au Follow us on Instagram - @blackmagicwomanpodcast The Black Magic Woman Podcast is hosted by Mundanara Bayles and is an uplifting conversational style program featuring mainly Aboriginal guests and explores issues of importance to Aboriginal people and communities.  Mundanara is guided by Aboriginal Terms of Reference and focusses more on who people are rather than on what they do. If you enjoyed this episode, please ‘Subscribe' on Apple Podcasts or ‘Follow' on your Spotify app and tell your friends and family about us! If you'd like to contact us, please email, info@blackmagicwoman.com.auSee omnystudio.com/listener for privacy information.

Gaya Herrington is Vice President Sustainability Research at Schneider Electric (voted most sustainable corporation in the world in 2021). She studies how environmental, social, behavioral and economic trends interact and what systems changes are needed for achieving true global sustainability. Gaya is best known for her research on the Limits to Growth (LtG), and how it informs us about a more human and ecocentric economic system, one fit for the 21st century: wellbeing economics.   Gaya has given keynote speeches and guest lectures around the world, and is an Advisor to the Club of Rome, an international 100-member club of scientists, economists, and other thinkers. She has a Master's degree in Econometrics from the Liberal Amsterdam University and another Master's in Sustainability from Harvard University. She lives in Washington D.C.   Recent interview with Gaya about her work: https://www.wired.com/story/gaya-herrington-avoiding-global-collapse/ Peer-reviewed journal article on Gaya's LtG research: https://onlinelibrary.wiley.com/doi/abs/10.1111/jiec.13084 Gaya's book (free for download): https://www.mdpi.com/books/mono/6206   Social media: Gaya's Facebook and Schneider Electric's: Twitter, Facebook and Instagram.   The songs picked by all our guests can be found via  our playlist #walktalklisten here.    Please let me/us know via our email innovationhub@cwsglobal.org what you think about this new series. We would love to hear from you.   Please like/follow our Walk Talk Listen podcast and follow mauricebloem on twitter and instagram.  Or check us out on our website 100mile.org.  We also encourage you to check out the special WTL series Enough for All about an organization called CWS. 

What does it take to avoid global collapse?  Is there still time?  And if so, what are the societal, social, cultural and goal-oriented changes that we need to make to get there? This week's guest is one of the new generation of super-thinkers who have the capacity, individually and collectively, to bring into being that better future our hearts know is possible. Gaya Herrington received her first master's degree in Econometrics from the Liberal University of Amsterdam and her second master's in Sustainability from Harvard University. In between she worked for KPMG, for the Dutch Government as a regulator and then back to KPMG in the US, where she now lives. She is a member of the Transformational Economics Commission of the Club of Rome, a recurring guest lecturer at the Victoria University of Wellington, New Zealand, and works at Schneider Electric as Vice-President of ESG Research. She wrote her thesis for her second Masters on the seminal Limits To Growth work that first came out in 1972. The paper she wrote as a result of this went viral - and she expanded it into a book called Five Insights for Avoiding Global Collapse. She has made this freely available by download and I have put a link in the show notes - because this is absolutely essential reading for anyone on this path. The take home message though, as you'll hear, is that if we all work together, there is still time. Which should be a fairly familiar idea to those of you who have listened to other guests. But this time, we'll really unpick the data and concepts behind it in the company of someone who has worked hard at the coal face of the old system and has seen how to change it. Gaya's book https://mdpi-res.com/bookfiles/mono/6206/Five_Insights_for_Avoiding_Global_Collapse.pdf?v1682069789Gaya's paper at KPMG https://advisory.kpmg.us/articles/2021/limits-to-growth.htmlManfred Max-Neef https://gaiafoundation.org/the-barefoot-economist-manfred-max-neef/Club of Rome: Earth for All https://www.clubofrome.org/publication/earth4all-book/

BIO: Laurens Swinkels is an Associate Professor of Finance at Erasmus University in Rotterdam and Executive Director and Head of Quant Strategy at Robeco's Sustainable Multi-Asset Strategies team.STORY: Lauren bought a house in Rotterdam. Just five years later, he had to move to Norway. Laurens managed to sell the house in the Netherlands many years later at a loss.LEARNING: Liquidity is very important even when investing long-term. Remove emotions from your decision-making. “Even though you're a long-term investor and you think you're really long-term, there may be things that cross your path that require liquidity.”Laurens Swinkels Guest profileLaurens Swinkels is an Associate Professor of Finance at Erasmus University in Rotterdam and Executive Director and Head of Quant Strategy at Robeco's Sustainable Multi-Asset Strategies team. His areas of expertise include allocation research and empirical asset pricing. He teaches Finance courses and has published his academic work in peer-reviewed journals such as the Journal of Financial Economics. Laurens holds a Ph.D. in Finance and a Master's in Econometrics from Tilburg University in the Netherlands.Worst investment everWhen Laurens started his masters in Tilburg, Netherlands, he decided to move out of his parent's home. He was torn between buying an apartment and renting one because the real estate prices were quite favorable for buyers then. He decided to rent since he would only be in school for a few years.After completing his master's, Laurens decided to do a Ph.D. and stayed another five years in Tilburg. He was still renting his apartment. After graduating, Laurens moved to Amsterdam, where the house prices were unimaginably high. Hoping that the prices would go down, he rented an apartment. But the prices just kept going up. Laurens had to commute daily from Amsterdam to Rotterdam. After getting tired of the commute, Laurens decided to buy a house in Rotterdam, where the prices were lower than in Amsterdam.Laurens didn't foresee that he would have to move to Norway five years after that decision. At this point, the house he'd bought was 25% underwater. The investment in this house made a large part of his wealth, so taking a 25% loss was tough for Laurens. He managed to sell the house only two years ago.Lessons learnedThe liquidity that allows you to sell and buy a house in another location whenever you want is very valuable.Even when you're investing long-term, liquidity is still essential.Remove emotions from your decision-making.Andrew's takeawaysBuying a house is a trap because you may lack liquidity.Home buying comes with the risk of not realizing the final capital gain that you thought you would.Actionable adviceIf you're not yet ready to buy a home or don't know where to buy, you can first get exposure to real estate through listed markets.Lauren's recommendationsLaurens recommends his data page on the university website, where you can download datasets if you want to do number crunching when investing. You can also check out Google Scholar or SSRN, where people post their latest thoughts. You can set alerts and get notified when papers on topics you're interested in are published. If you don't have the time for that, there are several people, like

Hello everyone, and welcome to Ideas Untrapped podcast. My guest for this episode is Decision Scientist, Oliver Beige - who is returning to the podcast for the third time. Oliver is not just a multidisciplinary expert, he is one of my favourite people in the world. In this episode, we talk about scientific expertise, the norms of academia, peer review, and how it all relates to academic claims about finding the truth. Oliver emphasized the importance of understanding the imperfections in academia, and how moral panics can be used to silence skeptics. I began the conversation with a confession about my arrogance about the belief in science - and closed with my gripe about ‘‘lockdown triumphalism''. I thoroughly enjoyed this conversation, and I am grateful to Oliver for doing it with me. I hope you all find it useful as well. Thank you for always listening. The full transcript is available below.TranscriptTobi;I mean, it's good to talk to you again, Oliver. Oliver; Tobi, again.Tobi;This conversation is going to be a little bit different from our previous… well, not so much different, but I guess this time around I have a few things I want to get off my chest as well. And where I would start is with a brief story. So about, I dunno, I've forgotten precisely when the book came out, that was Thinking Fast and Slow by the Nobel Laureate Daniel Kahneman. So I had this brief exchange with my partner. She was quite sceptical in her reading of some of the studies that were cited in that book. And I recall that the attitude was, “I mean, how can a lot of this be possibly true?” And I recall, not like I ever tell her this anyway…but I recall the sort of assured arrogance with which I dismissed some of her arguments and concerns at the time by saying that, oh yeah, these are peer-reviewed academic studies and they are most likely right than you are. So before you question them, you need to come up with something more than this doesn't feel right or it doesn't sound right. And, what do you know? A few years, like two or three years after that particular experience, almost that entire subfield imploded in what is now the reproducibility or the replication crisis, where a lot of these studies didn't replicate, a lot of them were done with very shoddy analysis and methodologies, and Daniel Kahneman himself had to come out to retract parts of the book based on that particular crisis. So I'm sort of using this to set the background of how I have approached knowledge over my adult life. So as someone who has put a lot of faith naively, I would say, in science, in academia and its norms as something that is optimized for finding the truth. So to my surprise and even sometimes shock - over different stages of my life and recently in my interrogation of the field of development economics, people who work in global development - [at] the amount of politics, partisanship, bias, and even sometimes sheer status games that academics play and how it affects the production of knowledge, it's something that gave me a kind of deep personal crisis. So that's the background to which I'm approaching this conversation with you. So where I'll start is, from the perspective of simply truth finding, and I know that a lot of people, not just me, think of academia in this way. They are people who are paid to think and research and tell us the truth about the world and about how things work, right? And they are properly incentivized to do that either by the norms in the institutional arrangements that birthed their workflows and, you know, so many other things we have known academia and educational institutions to be. What is wrong with that view - simply academia as a discipline dedicated to truth finding? What is wrong with that view? Oliver;There's many things. Starting point is that it was not only Daniel Kahneman, behavioral economics has multiple crises also with Falsified work. Not only with wrong predictions, wrong predictions are bad but acceptable. This is part of doing science, part of knowledge production. But Falsification is, of course, a bigger problem now and they had quite a few scandals in that. The way I approach it always is sort of like a metaphor from baseball. Basically there's something called the Mendoza Line in baseball which is a hitter that has a 200 hitting average. This is like the lowest end of baseball. If you go below 200, then you're usually dropped off the baseball teams. And on the upper end you have really good hitters that hit an average of like 300 or something. If you have a constant 300 average you usually get like million dollar contracts, right? We can translate this to science in a lot of ways. Of course, there is a lot of effort involved in going from a 200 average to a 300 average to a 20% average of being right to 30% a average of being right. But still if you're at a 300 level, you're still wrong 70% of the time. And so the conversations I observe, they're people that are not specialists in a field [and] we're trying to figure out who is right in a certain conversation. Talking about conversations in a scientific field we basically try to use simple pointers, right? One of the pointers is of course a paper that has gone through peer review. You see these conversations of like, okay, this paper has not been peer reviewed, this paper has been peer reviewed. But peer review does not create truth. It sort of reduces the likely likelihood of being wrong somewhat but it doesn't give us any indicator of this is true. The underlying mechanism of peer review usually cannot find outright fraud. Cannot detect outright fraud. This happened quite a few times. And also peer review is usually how close is the submitted paper to what the reviewers want to read. There is a quality aspect to it, but ultimately it changes the direction of the paper much more than it changes quality. So academia overall is a very imperfect truth finding mechanism. The goal has to be [that] the money we spend on academic research has to allow us to get a better grasp of so far undiscovered things, undiscovered related relationships, correlations, causal mechanisms, and ultimately, it has to give us a better grasp of future and it has to give us a better grasp of what we should do in order to create better futures. And this all basically comes down to, like, predicting the future or things that were in the past but yet are to be discovered. Evolution tends to be a science that is focused on the past, looking at things in the past. But there's still things we have to discover, connections we still have to discover. And this is what academia is about. And the money, the social investment we put into academia has to create a social return in the way that we are better off doing the things we need to do to create a better future for everyone. And its [academia] track record in that regard has been quite mixed. That's true.Tobi;So let's talk a little bit about incentives here. Someone who has also written quite a lot, who talked so much about some of the issues - I think he's more focused on methods. He's andrew Gelman, the statistician. I read his blog quite a lot, and there's something he consistently allude to and I just want to check with you how much you think that influenced a lot of the things that we see in academia that are not so good, which is the popularity contest - the number of Twitter followers you have; whether you are blue checked or not; bestselling books; Ted Talks that then lead to people making simplistic claims. There's the issue of scientific fraud, right, some of which you alluded to also in behavioral economics, behavioral science generally. There was recently the case of Dan Ariely, who also wrote a very popular book, Predictably Irrational, but who was recently found to have used falsified data. And I recall that you also persistently criticized a lot of people during the pandemic, even till date - a lot of people who made outright wrong predictions with terrible real life consequences because policymakers and politicians were acting under the influence of the “expert” advice of some of these people who will never come out to admit they are wrong and are less likely to even correct their mistakes. So how is the incentive misaligned? Oliver; Okay, many questions at once. How does academia work? And like I always like to say that academic truth finding or whatever you want to call it is not too far away from how gossip networks work. The underlying thing is, of course, any kind of communication network is basically sending signals. In this case, snippets of information, claims, hypotheses and the receiver has to make a decision on how credible this information is. You have the two extreme versions, which is basically saying, yeah, I just read this paper and I think this paper makes a good claim and is methodologically sound or I just read this paper and this paper is crap as everything about it is wrong. So you basically start with a factual claim and an evaluation. This happens in science Twitter in the same way a gossip network communicates typically good or bad news about the community. Also, a gossip network communicate hazards within the community, sending warnings, which is what academics have been doing quite a bit over the last two and a half years. And they also have this tendency to, a) exaggerate claims, reduce claims, and [they] also have this tendency to create opposing camps. Because very few middling signals are being retransmitted. I've been watching the funeral of the Queen, I have no strong opinion about British royalty in either direction so if I post something on Twitter about it, nobody will retweet. And, of course, the two extreme ends will be retweeted. This is how Twitter works, but it's also how science usually works. You'll see that strong claims in either direction are being transmitted much more frequently than middling moderate claims. So the bifurcation of opinions is inherent in both of them. This element of credibility, that you build credibility, based on how someone else reflects your own beliefs. Your own prior beliefs, really. This is the core mechanism [that if] I read something that confirms my prior beliefs, I'm much more likely to retransmit it with a positive note that "I really like this and I think it's methodologically sound." And if it's something that contradicts my prior beliefs, I'm very much more inclined to question its methodology. And I think we've seen this to an extreme over the two and a half years because we had situations where the discussion was very polarized. And the really bad thing to observe in a scientific discourse in general, but also the amplified scientific discourse on Twitter, is like the absolute lack of quality control when something confirms one's own prior beliefs. So this is usually what a scientist has to do. Like, if I get something that confirms my beliefs, I still have to do a minimum quality control [to check] if it's actually methodologically sound. And this clearly did not happen. People were just passing on anything that confirmed their beliefs and basically expected someone else to do the quality control. The first job any academic has is basically to subject everything, even that confirms your beliefs, and this is also [what] you think is true, you still have to subject it to quality control. And clearly this rarely ever happens. This is why academia is supposed to run on confrontation that, basically, the other camp does it. But if you bring academia together with Twitter, which is [an] amplification network that runs on social engagements, likes and retweets, then you have a very toxic mix. And this is the situation we had over the last two and a half years, how scientific communities can coalesce around things that are just not empirically sustainable.Tobi;Now pardon my language, there's a way that academics, whether they are scientists or social scientists (I know economists are particularly notorious in this arena), they completely f**k with your mind when you're a skeptic. So I'll give you an example. Two days ago…I opened with the replication crisis in psychology, so two days ago, I read a SubStack by someone who is presumably a psychologist, who was then basically complaining that, “oh, yeah, after the replication crisis, a lot of them in academia who were doing PhDs, were also having their own crisis of confidence, because then you have to confront a public who thinks they know everything.” So, like, you describe your study or you say you found something and someone says, "oh, but the field didn't replicate." The whole thing just sounded like some weak apologia that just didn't make any sense. I recall that sometimes a little bit after the financial crisis [of] '07-'08, if I recall correctly, Paul Krugman was dismissing something Talib, Nicholas Nassim Talib, wrote by saying that, oh, if you think you found something that a whole community of academic experts… I'm not quoting him verbatim, I'm paraphrasing… If you think you found anything that a whole academic community of experts missed, then you are most likely to be wrong.So, it brings me to the question of skepticism and how to approach it, because at the other extreme end of this is to say… and certainly there are people like that in the world today who think that no scientific knowledge is true, who question even proven medicine, and there are also conspiracy theorists who say outrightly false things for their own motives, no doubt. So, like, how does one deal with skepticism? Especially if you have conspiracy theorists and outrightly ignorant people on one side, and on the other side you have academic confusion or experts who out of their own biases or some of these institutional and social problems that you have described can also not really come out and admit that, oh, we botched this and this and this is what we are doing to correct our errors. How do you handle skepticism in such a milieu?Oliver; The first thing is and it's also the reason why I like the baseball metaphor is if you are [an] academic, you're an expert in a field, you spend far more time studying this field than others, you're communicating with other experts in the field, so you can get this feeling, and probably justified feeling that because you put more effort into it you should get more reward in the form of more recognition and more credibility. But you should also come up with a realization or understanding that any field you're in and that includes economics and all other fields, there are so many things that are still undiscovered, so many things that are undiscoverable that we have to build axiomatic constructs around in order to actually help us move forward. And if you're able as an academic to move from 20% right over many years to 30% right, you're still 70% wrong. So these are not empirical numbers, but I think they get the point across. And if you don't get that, then you're doing something wrong in academics in general, right? And we've seen this arrogance that was not supported by imperial superiority, like, quite a bit over the last years. Especially Paul Cook when he got some of the things very wrong just recently when he came out, when he admitted that most macroeconomists have been dead wrong about inflation for over a year. And then he claimed that nobody could have foreseen that. This is doubly wrong. You can be arrogant or you can be incompetent, but you cannot be both at the same time. Basically, academia is also a competition for attention. This is an attention industry and exaggerated claims get more attention than moderate claims. So this is not a problem. The problem is, and I see in the discussion is the complete absence of understanding of what the scientific method entails. And that clearly, a lot of academics become specialists in a particular subsection of the scientific method but don't have an understanding of how the whole thing works. Which is interesting, especially in economics, because economics has this very strong claim that it underwent An Empirical Revolution over the last 20 years, which is certainly true. Econometrics have got a much bigger role over the last 20 years, but they also claimed that because they underwent an empirical revolution, they also underwent a credibility revolution, that their results are much more credible and this is a much bigger claim. And this is not a claim that recent events have validated or recent economic performance has not been up to par to support it. But the key thing [is that] the scientific method is basically starting out from a theory which does not have to be a formal way of expressing, but you have to have an overarching idea of how things are connected, how some things cause other things. And from this, you have to be able to create predictions. Basically, foresee future discoveries. And you do this in a number of steps. The first step is usually formalization. You try to come up with a formal model. There are lots of discussions about like, okay, how formal does a model have to be? Usually, formalization is a self-discipline device. It means that you don't come up with ad hoc predictions, but the predictions are based on a clear mechanism that should be working under a variety of conditions. And then once you have a formal model, which we've seen a lot of people trying to build formal models over the last few years, and a lot of them have gotten more attention than they deserved or that they expected, and then you come up with a hypothesis. Hypothesis usually means are you comparing your own view of the world to competing views of the world. You try to find the positions where they diverge the most or where it becomes visible. And then you do empirical test experiments. Or in economics, you try to do a natural experiment or control trials in order to show that your overarching theory, your model, is closer to the truth than the competition. But the key is also and this is remarkably what a lot of people have just simply missed out on, this is the replicability and the role of moving away from a subjective view of the world to an objective view of the world so this can be refuted or replicated by others.And this also means that people who are opposed to your viewpoint have to admit that your view of the world was better than others. And this has almost completely broken down. Because in the two scenarios, economics (macroeconomics) in particular has been dead wrong, especially about inflation which is really one of the core predictive elements of macroeconomics and they have been dead wrong for an extended period of time for the very simple reason because they did not want to acknowledge it. And this is a problem, right? So then we start obfuscating about where you went wrong and you're trying to play political games that being wrong was not just unexpected change in economic environment or social environments or something but being dead wrong was basically caused by your model being fundamentally wrong. Very clearly economics should be in a crisis. The crisis should be clear within the field and the less the field itself owns up to this crisis, the more the outside world [should] pressure the field itself to come clear with its wrong predictions because the cost of getting these things wrong are staggering Tobi;True. So I have three questions but I'll ask them differently. You mentioned towards the end of your answer you talked about political games which is something that also gets me really angry and sometimes confused. And a related issue about that I found also is in development economics. But that will take us into the second question. So let's talk about the politics here. For example, take a field like economics which is highly partisan. You have some people that are called neoliberal economists. Some people are socialists, some people are heterodox, some people are capitalists. I know within the field of macroeconomics itself, they have all these other labels - new Keynesian monetarist, you know, whatever. But what I'm getting at is the role of partisanship, because you always have rival camps accusing themselves of partisanship. One story I related to, which I'm sure you also must have come across is - I saw a story on Twitter a couple of weeks ago before the Chilean constitutional referendum that Mariana Mazukato, Gabriel Zukman and Thomas Piketty, who are all economists, who are all leftists, who mix their research with political preferences and policy advocacy, plan to travel to Chile to celebrate the new draft constitution because it's a win for justice, it's a win for this or that. It's the final rejection of the Pinochet dictatorship and the neoliberal imposition that is. I did not encounter in that particular discourse chain anybody asking what is good for Chile, and Chileans, and even more relevantly how Chileans feel about this. And, I mean, what do you know? The referendum happened and 60% of the voters rejected the new draft. And I know that partisanship and political games, like you said, play not just in economics, it happens in other fields as well. So I'm curious - is this okay? And how exactly did should I say, scholars, particularly in social science, people that have been able to make extraordinary contributions to our body of knowledge and what we know, how have they managed to keep their politics, their personal politics away from their work? Or is it just that everything just used to be easier before we had Twitter? Oliver;Politics and economics have been intermixed long before Twitter. So this is not particularly new, and the mechanism itself is also not new. But your starting point is basically, as I said, like, very simplified that the role of academia is to predict the future and to design strategies to reach good futures. So in that situation, it's not surprising that academics take political positions. The problem comes in, of course, that if the ideological mix in academia and the ideological mix in the overall population and the ideological mix in sort of the ruling elites don't line up. This is a tricky situation, but being close enough to the highest echelons of power for long enough to observe what happens. If you have a change in the administration in Washington DC, then usually the new administration brings in economic experts from favourite schools. And then if the administration loses to the other party, then the other party brings in their favourite economists. So in that regard, if you have this semiconstant exchange of viewpoint, an economic viewpoint gets discredited, it gets replaced via the political process with other people, this is usually how you get closer to the view - I used to call it the drunk unicyclist. You're not really moving forward in a straight path, but you're moving around left and right, and you just try to avoid falling into a ditch. And this is what we observe. No political process is perfect. And as long as the political interests of the academics and the political interests of the elite are aligned with population ones, this is as good as we can get it. I generally have a problem with ideology in economics, but it's inevitable. And my quality is that I be able to read and appreciate writers from the left end of the spectrum, on the right end of the spectrum. I usually deduct points over ideological bent. But good thinkers can make good points even if they are driven by ideology. The problem also comes in when there is essentially no penalty for being wrong in academia. So basically being wrong and being catastrophically wrong externalizes the damage to others. So the worst scenario you do if you're tenured faculty, sort of what I call the endowed chair blue check, like a tenured faculty with a wide reach in social media, you can be dead wrong,you can be persistently wrong, completely unwilling to own up being wrong, and there's no real penalty to it. This is the major problem we're facing right now.Tobi;So that then brings me to the question of niches or what I'll call cottage industries in academic research generally. I know recently I did ask you about what you think about the EA movement. I'm not talking about them, but for descriptive purposes we see the behavior of that group, the adherents, the critics and how much commitment, particularly adherents display to their tribe. I see a lot of that too in academic research. One group I am very familiar with is in economic development (development economics) where everything now is about field experiments and randomized control trials. And one of the fundamental ways it biases research in my opinion and also have negative real life consequences is, if you do a field experiment, a randomized control trial on cash transfer, say in a Kenyan village over a period of time and you measure your results and they are positive and say oh yeah, well, cash transfer works. But the real question that policymakers, whether local governments or central governments or regional governments really deal with every day are sometimes bigger than that. So, like, for example, if you want to choose between building a power station for that particular village at $1 million versus scaling up your cash transfer program, what you'll find is that development economists in the current paradigm would most likely go for the cash transfer plan. Let's scale it up. We have tested this. It works. Essentially they are biased to what they can measure - like, we don't know the spillover benefits of electrification, it would be difficult to design a study, there are so many externalities. So basically they reduce real-life situations into the parameters of their methods and its limitations. And such behaviour is very, very similar to what you see with other social groups. Whether it is the Effective Altruism movement… I was briefly involved also with the Charter City people where for every problem that they can see, the solution is to build a charter city.That movement was actually inspired by your dear friend, Paul Romer. So there is this almost blind commitment and loyalty to their method, to their cottage industry. And sometimes I see it as just drumming up support for their tribe, as opposed to a commitment to the truth and finding what works. So, again, pardon my big question, what's going on here?Oliver; Okay, two things on the starting point about tribes within academia is…like, one of my favourite sayings is that tribalism is the shared belief in counterfactuals, counterfactual being everything that is unknown. And the less we know, the more unknowns there are, the more we tend to flock with our own tribes. So this is something you see everywhere in academia. That's what we call thought collectives. Ludwig Fleck, one of the guys who influenced Thomas Kuhn, came up with this term, thought collectives, to describe this idea that people that share the same idea of causal mechanisms tend to come together and confirm each other and create this thought collective. And this is, of course, what we see here, especially in academia. Economics has additional problem. I think it's not nearly as strong in development economics as other fields, but it's also visible there. This is very much the way economists are recruited. Economics, especially US and UK-centric economics, is extremely mathematicized. So, like, mathematical skills are basically number one, two, and three and the priority. And so you have basically a situation where real-world understanding has almost no role in getting accepted into PhD programs or getting promoted within the system. It used to be theory knowledge, formal theory knowledge. Now it's econometrics knowledge that gets you promoted. And this is very far away from qualification to solve real-world problems. And of course, people are impressed by mathematical skills. So this is something that you can play as a trump card. And this is what happens in the field. And the field is closing itself off from all kinds of outside knowledge because of that, especially in the social sciences. And in my world, I use people with mathematical skills, but only for very, very clearly defined tasks. I have my own mathematical skill set, but I also understand what the limitations are, and I think that's a major problem. And basically, if everyone around you came up in this system that promotes mathematical skills over real-world skills, then you believe that this is the only thing you need. And it's been very clear that basically every ten years, economics has a major crisis about being completely wrong in their predictions. And this intellectual monopoly is a major problem with that.Tobi;My third question in that line then pertains to the philosophy of science. Oliver;Yes. Tobi;So there are people who argue that a lot of these problems are also because modern science or the methodology of science today is divorced from some kind of philosophical foundation. I'm familiar relatively mildly with three philosophical approaches to science and let's just say truth finding. Thomas Kuhn basically puts everything down to competing paradigms. Like my last question, you know, competing tribes. And it's the tribe that wins at the moment that sort of has the monopoly of truth, not strictly, but socially. Then there's Karl Popper, which is also quite popular, that for anything to be valid as truth, it has to be falsifiable. And we've seen this play out so much in particle physics with things like string theory and things like many-worlds interpretation and so many things where their critics are saying, you guys are basically making claims that are not falsifiable, that cannot be tested and what you are doing is not science. And that has been going on now more or less for about three decades, right? And, of course, there's the Lakatos approach, which sort of fits into your own view, correct me if I'm wrong, which is that science has to make novel claims and it has to be predictive, it has to make predictions about the world. So my question then is academia, science, the truth-finding industry, so to speak, or the knowledge production industry, is it having a philosophical crisis?Oliver;I think it has more of a structural crisis. I'm not that deep in the philosophy of science I'm much more interested in the process itself. But one of the things that I think matters to me is Milton Friedman's claim that there are no wrong assumptions but whatever assumptions you make about the world has to generate correct predictions. A theory is being evaluated by its ability to produce non-falsifiable predictions, right? Predictions that turn out to be true even if others don't believe them. This is something you see in the arts as well, you see actually in religion as well, this mechanism of belief propagation that starts with one person believing and over time and over time, can be many decades, of something being accepted as true by everyone. So everyone starts believing in it. Basically, social contagion mechanism. I've always been interested in this. One scenario where this happens or should be happening is science. Right. This is, of course, a process. A process happens via this academic mechanism of peer-reviewed publications, getting tenure based on publication records and so on. And these are all very very imperfect mechanisms. The two extreme versions of that [are] the American system, which is extremely stratified, and the German version is the opposite, it's non-stratified, [and] we produce a massive amount of mediocrity. So, like, neither of them are optimal mechanisms to create truth. And we've seen that over the last two and a half years that political posturing took precedence over truth finding. Is it in a crisis? I think, yes, very clearly. We have two and a half years where very wrong, easily debunkable claims were propagated and were not retracted, even after they've been proven to be wrong. And ultimately, we're in a situation where an economic crisis is very clearly caused by misjudgment from people which we support and pay for being less wrong than the overall population. And that just simply did not work.Tobi;One last thing I'll like to get off my chest and then I'll pass them out to you is, I mean, specifically, if we follow from our last two podcast episodes, I'm a bit frustrated that there is a bit of lockdown triumphalism that the people who vigorously and vehemently used their academic or expert pedigree…Oliver;Credentials. Tobi;Yeah…to advocate for lockdowns are also taking a sort of victory lap. So the pandemic is over. Everything is back to normal. We did the right thing, even though the whole world was against us. That frustrates me a little. I was still watching a clip on YouTube recently because you get even more sensible take from everyday people, people who are experiencing these things than people who are building models and tweeting. One person somewhere here in southwest Nigeria complaining during the pandemic that the government has decided that it is better for us to die at home of hunger than not die from the pandemic. Because this pandemic, we don't know what it is, we don't know how it spreads, but without giving us any information, you basically confined us to our homes with no means of livelihood and nothing to depend on. That makes me sad because in Nigeria here and in many parts of Africa today, a lot of what we are seeing as, and are calling the food crisis, cost of living crisis, whatever it is you want to call it, did not necessarily start, but were aggravated or exacerbated by that approach to the pandemic. And it makes me sad that the people that are culpable, we can have a situation where they can take a victory lap. So that's me. Over to you. What would you like to get off your chest about everything that we have disclosed today?Oliver; Number one is epidemiological modelling was clearly an empirical debacle. The predicted epidemic wave that would take five to six months, that would wipe all large parts of the population never happened. And we have, I don't know, how many thousand waves in our database now, they all go for eight weeks. They start declining, acceleration starts declining very early on. And now we had enough scenarios where simple no measures were taken at any time during the wave. The key moment in that case was, I think, Paul Krugman complained that Denmark was removing all restrictions at the height of the epidemic wave and basically the very next day, the Danish wave dropped. Not a lot of people saw it, but it was extremely embarrassing for him. I've been in very much the same situation because I was living in the United States in the early 2000s and I was very clear from the very beginning of the Iraq war that Saddam Hussein did not have bioweapons. And so the whole invasion was built on Untruth. And the United States and the UK back then also knew that. Back then there was a strong moral panic, especially in the United States, against anyone who was basically speaking against the rationale for going to war. Now, 20 years later, almost nobody is willing to admit that they were speaking up in favour of the invasion back then. This is like a one-generation thing. And we'll see the same thing about the epidemic. This is very clear. The young people who had to carry most of the restrictions…up till now in Germany they're still forced to wear masks at school. They will have a very different view about what happened than the politicians in power. These are the things that'll evolve over many, many years. So I expect the same thing to happen. The interesting thing is really sort of back then it was more on the right end of the spectrum that drove this moral panic. Now it's moved over to the left end of the political spectrum. This is something that we're still to be investigated, why these moral panics unfolded onto the ideological spectrum as we know it. But it might be an interesting topic for the next call.Tobi;True. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.ideasuntrapped.com/subscribe

Summary The ecosystem for data professionals has matured to the point that there are a large and growing number of distinct roles. With the scope and importance of data steadily increasing it is important for organizations to ensure that everyone is aligned and operating in a positive environment. To help facilitate the nascent conversation about what constitutes an effective and productive data culture, the team at Data Council have dedicated an entire conference track to the subject. In this episode Pete Soderling and Maggie Hays join the show to explore this topic and their experience preparing for the upcoming conference. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Hey there podcast listener, are you tired of dealing with the headache that is the 'Modern Data Stack'? We feel your pain. It's supposed to make building smarter, faster, and more flexible data infrastructures a breeze. It ends up being anything but that. Setting it up, integrating it, maintaining it—it's all kind of a nightmare. And let's not even get started on all the extra tools you have to buy to get it to do its thing. But don't worry, there is a better way. TimeXtender takes a holistic approach to data integration that focuses on agility rather than fragmentation. By bringing all the layers of the data stack together, TimeXtender helps you build data solutions up to 10 times faster and saves you 70-80% on costs. If you're fed up with the 'Modern Data Stack', give TimeXtender a try. Head over to dataengineeringpodcast.com/timextender (https://www.dataengineeringpodcast.com/timextender) where you can do two things: watch us build a data estate in 15 minutes and start for free today. Your host is Tobias Macey and today I'm interviewing Pete Soderling and Maggie Hays about the growing importance of establishing and investing in an organization's data culture and their experience forming an entire conference track around this topic Interview Introduction How did you get involved in the area of data management? Can you describe what your working definition of "Data Culture" is? In what ways is a data culture distinct from an organization's corporate culture? How are they interdependent? What are the elements that are most impactful in forming the data culture of an organization? What are some of the motivations that teams/companies might have in fighting against the creation and support of an explicit data culture? Are there any strategies that you have found helpful in counteracting those tendencies? In terms of the conference, what are the factors that you consider when deciding how to group the different presentations into tracks or themes? What are the experiences that you have had personally and in community interactions that led you to elevate data culture to be it's own track? What are the broad challenges that practitioners are facing as they develop their own understanding of what constitutes a healthy and productive data culture? What are some of the risks that you considered when forming this track and evaluating proposals? What are your criteria for determining whether this track is successful? What are the most interesting, innovative, or unexpected aspects of data culture that you have encountered through developing this track? What are the most interesting, unexpected, or challenging lessons that you have learned while working on selecting presentations for this year's event? What do you have planned for the future of this topic at Data Council events? Contact Info Pete @petesoder (https://twitter.com/petesoder) on Twitter LinkedIn (https://www.linkedin.com/in/petesoder) Maggie LinkedIn (https://www.linkedin.com/in/maggie-hays) Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ (https://www.pythonpodcast.com) covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast (https://www.themachinelearningpodcast.com) helps you go from idea to production with machine learning. Visit the site (https://www.dataengineeringpodcast.com) to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com (mailto:hosts@dataengineeringpodcast.com)) with your story. To help other people find the show please leave a review on Apple Podcasts (https://podcasts.apple.com/us/podcast/data-engineering-podcast/id1193040557) and tell your friends and co-workers Links Data Council (datacouncil.ai/austin) Podcast Episode (https://www.dataengineeringpodcast.com/data-council-data-professional-community-episode-96) Data Community Fund (https://www.datacommunity.fund) DataHub (https://datahubproject.io/) Podcast Episode (https://www.dataengineeringpodcast.com/acryl-data-datahub-metadata-graph-episode-230/) Database Design For Mere Mortals (https://amzn.to/3ZFV6dU) by Michael J. Hernandez (affiliate link) SOAP (https://en.wikipedia.org/wiki/SOAP) REST (https://en.wikipedia.org/wiki/Representational_state_transfer) Econometrics (https://en.wikipedia.org/wiki/Econometrics) DBA == Database Administrator (https://www.careerexplorer.com/careers/database-administrator/) Conway's Law (https://en.wikipedia.org/wiki/Conway%27s_law) dbt (https://www.getdbt.com/) Podcast Episode (https://www.dataengineeringpodcast.com/dbt-data-analytics-episode-81/) The intro and outro music is from The Hug (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/Love_death_and_a_drunken_monkey/04_-_The_Hug) by The Freak Fandango Orchestra (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/) / CC BY-SA (http://creativecommons.org/licenses/by-sa/3.0/)

Lucy D'Agostino McGowan and Ellie Murray chat with Maria Glymour, Professor of Epidemiology & Biostatstics at UCSF and incoming chair of the Department of Epidemiology at Boston University. Maria successfully convinces Ellie and Lucy that instrumental variables can be very useful in epidemiology.  Follow up: ✍️ Andrew Heiss's blog post on marginal and conditional effects for GLMMs Follow along on Twitter: Maria Glymour: @MariaGlymour The American Journal of Epidemiology: @AmJEpi Ellie: @EpiEllie Lucy: @LucyStats