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Markus' Academy

MarkusAcademy

Princeton University's Markus Brunnermeier hosts conversations with leading academics and policymakers on the global economy, global politics, and artificial intelligence.

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Yesterday · 1 hr
Experimentally Validated Digital Twins with Raj Chetty & Jamie Fogel | Ep. 168
Follow the link for the full summary: https://markusacademy.substack.com/p/experimentally-validated-digital Link to sign up for the webinar series: https://markusacademy.substack.com/ Watch on Youtube: https://youtu.be/UlJGLmLoVLI Paper: https://opportunityinsights.org/paper/digital-twins/ Raj Chetty and Jamie Fogel joined Markus' Academy to present their new paper, "Experimentally Validated Digital Twins: Evaluating Workforce Training Programs in the Age of Big Data". Chetty is a Professor of Economics at Harvard University and the Director of Opportunity Insights, where Fogel is a Research Scientist. A summary in three bullets: ● The US has more than 5,000 workforce training programs. Fewer than 1% have been evaluated in a randomized controlled trial (RCT) because trials are expensive ● Chetty et al. (2026) provides a toolbox to do policy evaluation based on observational data using machine learning ● In the age of big data, RCTs may be most valuable for validating observational models rather than for identifying treatment effects themselves Timestamps: [00:00] Big data and workforce training programs [12:21] Validation against 37 randomized trials [27:11] What changed since LaLonde (1986) [33:52] How results can differ across cities and years [45:51] What's next for applied economics and AI?
September 23 · 32 min
Canaries in the Treasury Coal Mine with Bill Dudley & Jonathan Payne | Markus Academy | 167-2
Follow the link for the full summary: https://markusacademy.substack.com/p/us-treasury-yields Link to sign up for the webinar series: https://markusacademy.substack.com/ Watch on Youtube: https://youtu.be/ZseTYM_A-60 Listen to part 1: https://open.spotify.com/episode/6HXuoDrSOO0dEmCxDyj0qf?si=49aaf2a925d346f0 Bill Dudley and Jonathan Payne joined Markus’ Academy for a two-part conversation on US Treasury yields. This is part 2. Dudley is a Senior Advisor to Princeton’s Griswold Center and a former President of the Federal Reserve Bank of New York. Payne is an Assistant Professor at Princeton. A summary in three bullets: ● The expectations hypothesis holds in general throughout US history except in the period of 1965-1990, so that the risk premium on government debt was time-varying only then. ● The fact that Microsoft’s yields have widened with respect to other AAA corporates or sovereigns suggests growing default risks around AI, not that the government may be crowding out AI investment ● R* has drifted up, from zero after the financial crisis to 1.2% today (as projected by the Fed) Timestamps: [0:00] R* has moved up, and we only learn it through its works [8:15] The expectations hypothesis and the stock-bond correlation [23:12] Is the government crowding out AI investment? [27:25] Hope is not a strategy The views expressed by Jonathan's coauthors in the papers discussed are those of the authors and do not necessarily reflect the views of the Board of Governors of the Federal Reserve System.
September 23 · 50 min
The Government Funding Advantage is No Free Lunch with Bill Dudley & Jonathan Payne | Ep. 167-1
Follow the link for the full summary: https://markusacademy.substack.com/p/us-treasury-yields Link to sign up for the webinar series: https://markusacademy.substack.com/ Watch on Youtube: https://youtu.be/SAUrOFLlK-kLink to LIsten to part 2: https://open.spotify.com/episode/4aexS87sDsu6x2Fj8diXuM?si=kqTUF8zDQ-CzuTdOyCfyhw Bill Dudley and Jonathan Payne joined Markus’ Academy for a two-part conversation on US Treasury yields. This part covered the history of American debt starting in minute 21:09. Before then it started with a refresher on basic concepts to study yield curves. Dudley is a Senior Advisor to Princeton’s Griswold Center and a former President of the Federal Reserve Bank of New York. Payne is an Assistant Professor at Princeton. A summary in three bullets: ● There is no Phillips-style curve between debt-to-GDP ratios (safe asset scarcity) and the government funding advantage. The simple relationship disappears when adjusting our prior measures of the funding advantage for the tax treatment of the government’s long-term debt during the Great Inflation ● The US government’s funding advantage was largest in the 19th century during the national banking era, not after WWII or Bretton Woods. ● Governments face financing trilemma, having to pick two among: (1) a large funding advantage, (2) a solvent banking sector, (3) a regime that inflates the debt away. The funding advantage is a reward for prudence Timestamps: [00:00] Today’s yields are not high by historical standards [11:52] Fiscal-monetary interactions [22:38] The history of America’s debt [34:30] The national banking era was a stablecoin regime [41:15] The funding advantage is a reward for prudence The views expressed by Jonathan's coauthors in the papers discussed are those of the authors and do not necessarily reflect the views of the Board of Governors of the Federal Reserve System.
August 28 · 29 min
A Mini-Series on AI for Economic Theorists & Mathematicians, Part 4: Promtps and Agent Swarms | Markus' Academy | Ep. 166-4
Follow the link for the full summary: https://markusacademy.substack.com/p/ai-for-economic-theorists-and-mathematicians Link to sign up for the webinar series: https://markusacademy.substack.com/ Pietro Ortoleva and Fedor Sandomirskiy joined Markus' Academy for a mini-series on AI for economic theorists and mathematicians. This is episode 4. Both are economic theorists at Princeton University.The value has shifted from prompt engineering to context engineering: specify the task. Write a lazy two-line prompt, ask the same model that will do the work to expand it. Never let one session grade its own work, but run a separate verifier and, if the two disagree, a third instance as a judge. Fedor dissected the prompt OpenAI published for the cycle double cover proof - 64 agents, running at least eight hours, a supervisor eliminating agents that converge on the same route. And in his work adds tricks of his own.Timestamps:[0:00] Is prompt engineering still a thing?[3:40] Prompt expansion: let the model write the prompt[9:45] Prover versus verifier, LaTeX not PDF, and when to restart[16:43] Agent swarms, and AI proofreading
August 28 · 12 min
A Mini-Series on AI for Economic Theorists & Mathematicians, Part 3: Which Model to Use | Markus' Academy | Ep. 166-3
Follow the link for the full summary: https://markusacademy.substack.com/p/ai-for-economic-theorists-and-mathematicians Link to sign up for the webinar series: https://markusacademy.substack.com/ Pietro Ortoleva and Fedor Sandomirskiy joined Markus' Academy for a mini-series on AI for economic theorists and mathematicians. This is episode 3. Both are economic theorists at Princeton University.An AI's intelligence and stamina are substitutes. A slightly shallower model that grinds all day often gets further than a deeper one you can only afford to run for twenty minutes. Pietro compared the models available today: their preference, narrowly, is GPT-5.6, since it has more stamina than Fable. Pietro also argues that agents are fundamental in empirical work, but that for theory the browser is still enough for brainstorming.Timestamps:[0:00] The frontier since June: Fable 5, GPT-5.6, Opus 5[4:13] Intelligence and stamina are substitutes[8:53] The verdict, and what to run on a Pro, $20, or free budget[11:10] Browser or agents?
August 28 · 15 min
A Mini-Series on AI for Economic Theorists & Mathematicians, Part 2: Can AI Be Creative? | Markus' Academy | Ep. 166-2
Follow the link for the full summary: https://markusacademy.substack.com/p/ai-for-economic-theorists-and-mathematicians Link to sign up for the webinar series: https://markusacademy.substack.com/ Pietro Ortoleva and Fedor Sandomirskiy joined Markus' Academy for a mini-series on AI for economic theorists and mathematicians. This is episode 2. Both are economic theorists at Princeton University.In this video, Fedor asks whether models can actually generate new ideas. In economic theory this is hard to settle because a model's quality is subjective, while in math a proof either holds or it does not. AI is poor at attribution, but superb at aggregation of knowledge.Timestamps:[0:00] Can models be creative, and why the evidence comes from math[2:20] The ten Erdős problems episode, and Terence Tao's ledger[5:19] The unit distance conjecture falls[8:44] Jacobian, cycle double cover, and what it means for theory
August 28 · 18 min
A Mini-Series on AI for Economic Theorists & Mathematicians, Part 1: Core Uses of AI for Economic Theory | Markus' Academy | Ep. 166-1
Follow the link for the full summary: https://markusacademy.substack.com/p/ai-for-economic-theorists-and-mathematicians Link to sign up for the webinar series: https://markusacademy.substack.com/ Pietro Ortoleva and Fedor Sandomirskiy joined Markus' Academy for a mini-series on AI for economic theorists and mathematicians. This is episode 1. Both are economic theorists at Princeton University.In this first video, Pietro sets out where AI fits into theory research. Unlike mathematics, a theory paper does not set out to prove a stated conjecture; it searches for a fixed point between defensible assumptions, interesting statements, and proofs that certify them. AI changes the cost of each loop of that search. Pietro lists seven use cases for AI in theory, and argues that sketching is the most underused of them. On proofs, frontier models can now generate reliable proofs of the kind of model economists typically write. The higher-value uses are attack (a hostile referee hunting for weak steps), repair (which assumption rescues a false statement) and inspiration: even a wrong proof can point to the right route.Timestamps:[0:00] Introduction, and economic theory as a fixed point[5:12] Seven use cases, and why sketching is the most underused[8:46] Proofs: attack, repair, and inspiration[15:12] Extensions, microfoundations, simplifications
August 28 · 44 min
The Second China Shock, Part 2: Why Europe is the Front Line | Markus' Academy | Ep. 165-2
Follow the link for the full summary: https://markusacademy.substack.com/p/the-second-china-shock-implications Link to sign up for the webinar series: https://markusacademy.substack.com/ For our latest episode, Brad Setser joined Markus’ Academy for a two-part conversation on the second China shock and the second coming of global imbalances. This video is the second part. Setser is a Senior Fellow at the Council on Foreign Relations and a former official at the US Treasury and the Office of the US Trade Representative.Timestamps:[0:00] Europe sandwiched, Germany in the crosshairs[17:52] China’s imbalance will not fix itself[22:20] How Europe should act[39:00] Implications for the rest of Asia
August 28 · 1 hr 6 min
The Second China Shock, Part 1: How This Time Is Different with Brad Setser | Markus Academy | Ep. 165-1
Follow the link for the full summary: https://markusacademy.substack.com/p/the-second-china-shock-how-this-time Link to sign up for the webinar series: https://markusacademy.substack.com/ For our latest episode, Brad Setser joined Markus’ Academy for a two-part conversation on the second China shock and the second coming of global imbalances. This video is the first part. Setser is a Senior Fellow at the Council on Foreign Relations and a former official at the US Treasury and the Office of the US Trade Representative. Timestamps:[00:00] Markus’ Introduction[05:17] China’s unprecedented surpluses[21:00] An export boom bolted to a stalled economy[35:11] This time the surpluses are not recycled[50:11] China’s statistical puzzles and the undervalued yuan
August 28 · 1 hr 12 min
AI and Messy Jobs with Luis Garicano | Markus' Academy | Ep. 164
Follow the link for the full summary: https://markusacademy.substack.com/p/ai-and-messy-jobs Link to sign up for the webinar series: https://markusacademy.substack.com/ For our latest episode, Luis Garicano joined Markus’ Academy to discuss his new book with Jin Li and Yanhui Wu, Messy Jobs. Garicano is a Professor at the London School of Economics and a former Member of the European Parliament.Timestamps:[02:43] Tasks are not jobs: the autonomy threshold[12:48] Three tiers of jobs, three kinds of AI impact[30:06] Hierarchies and which jobs will survive[46:33] The value of organization[1:00:57] Three tiers, three economies
August 28 · 1 hr
Neglected Risks in Private Markets with Martin Schmalz | Markus' Academy | Ep. 163
Follow the link for the full summary: https://markusacademy.substack.com/p/neglected-risks-in-private-equity Link to sign up for the webinar series: https://markusacademy.substack.com/ For our latest episode, Martin Schmalz joined us for a conversation on the neglected risks in private markets. Schmalz is a Professor of Finance, Economics, and Real Estate at Oxford's Saïd Business School.Timestamps:[05:24] Returns aren't what they used to be[15:25] Reported vs. realized returns[26:47] Diversification myths and concentration risk[37:00] Opaque fee structures[46:45] Liquidity, systemic, and agency risks
August 28 · 1 hr 5 min
A Mini Series on Claude Code for Applied Economists, Part 8: Integration and Collaboration | Markus' Academy | Ep. 162-8
Follow the link for the full summary: https://markusacademy.substack.com/p/claude-code-for-applied-economists Link to sign up for the webinar series: https://markusacademy.substack.com/ Paul Goldsmith-Pinkham joined Markus’ Academy for a mini-series on Claude Code for Applied Economists. This is the last episode of the 8 part series. Goldsmith-Pinkham is an Associate Professor of Finance at the Yale School of Management and a Faculty Research Fellow at NBER. Through a replication of Jay Ritter’s results on post-IPO stock performance, Paul shared some best practices for verifying Claude Code’s work. Integrating with GitHub let him track the project as a chain of committed steps rather than one final output, and review Claude’s work one change at a time.Finally, Paul connected the project’s repository to Overleaf via GitHub (Dropbox works too), so that Claude can update figures and tables directly in one’s paper. The core principle: every number in a draft should come from the code, not from an AI’s memory.Timestamps:[0:00] Verification is the new bottleneck[6:30] Using GitHub to verify Claude’s output[38:35] How to give feedback[52:27] Integration with Overleaf for Collaboration
August 28 · 47 min
A Mini Series on Claude Code for Applied Economists, Part 7: Permissions and OpenClaw | Markus' Academy | Ep. 162-7
Follow the link for the full summary: https://markusacademy.substack.com/p/claude-code-for-applied-economists Link to sign up for the webinar series: https://markusacademy.substack.com/ Paul Goldsmith-Pinkham joined Markus’ Academy for a mini-series on Claude Code for Applied Economists. This is episode 7 of 8. Goldsmith-Pinkham is an Associate Professor of Finance at the Yale School of Management and a Faculty Research Fellow at NBER. In this episode, Paul explained how to think about autonomy, and risk when using Claude Code and other agentic AI tools, for example covering different types of permissions. Paul showed how containers and sandboxes, including Docker-based workflows and tools like Safe House, can give AI agents more autonomy while limiting potential damage. Paul also discussed OpenClaw-style bots, and introduced us to his own “Duncan Idaho” research assistant agent. Timestamps: [0:00] Permission types and an overview of agentic tools[11:37] Sandboxing with containers and Docker[35:43] OpenClaw and autonomous research agents
August 28 · 31 min
A Mini-Series on Claude Code for Applied Economists, Part 6: Claude Skills | Markus' Academy | 162-6
Follow the link for the full summary: https://markusacademy.substack.com/p/claude-code-for-applied-economists Link to sign up for the webinar series: https://markusacademy.substack.com/ Paul Goldsmith-Pinkham joined Markus’ Academy for a mini-series on Claude Code for Applied Economists. This is episode 6 of 8. Goldsmith-Pinkham is an Associate Professor of Finance at the Yale School of Management and a Faculty Research Fellow at NBER. In this episode, Paul explained Claude Skills: reusable instruction bundles that help Claude perform recurring tasks in a standardized way. He showed where Skills are stored, how global and project-level Skills differ, and then built a paper-summary Skill for seminar preparation. Paul also introduced community Skill packs such as “superpowers.”Timestamps:[0:00] What are Claude Skills?[7:33] Building a paper-summary Skill[21:50] Skill packs, “superpowers,” and cautions about overusing Skills
August 28 · 46 min
A Mini-Series on Claude Code for Applied Economists, Part 5: Writing & Thinking | Markus' Academy | 162-5
Follow the link for the full summary: https://markusacademy.substack.com/p/claude-code-for-applied-economists Link to sign up for the webinar series: https://markusacademy.substack.com/ Paul Goldsmith-Pinkham joined Markus’ Academy for a mini-series on Claude Code for Applied Economists. This is episode 5 of 8. Goldsmith-Pinkham is an Associate Professor of Finance at the Yale School of Management and a Faculty Research Fellow at NBER.In three different parts, Paul showed how Claude can support the writing side of research: 1. First, he showed how to create a personal style guide from your own papers. 2. Second, he showed how Skills can be used to develop a revision plan after receiving a referee report. He especially recommended Jukka Sihvonen’s Skill for Strategic Revisions. 3. Third, he shared some advice on how to use LLMs as editors and thinking partners rather than judgment outsourcers.Timestamps:[1:27] Developing a Style Guide[18:12] Using Skills for Referee Reports[35:37] Claude for Brainstorming and Editing[43:42] Summary
August 28 · 55 min
A Mini-Series on Claude Code for Applied Economists, Part 4: Large Datasets | Markus' Academy | Ep. 162-4
Follow the link for the full summary: https://markusacademy.substack.com/p/claude-code-for-applied-economists Link to sign up for the webinar series: https://markusacademy.substack.com/ Paul Goldsmith-Pinkham joined Markus’ Academy for a mini-series on Claude Code for Applied Economists. This is episode 4 of 8. Goldsmith-Pinkham is an Associate Professor of Finance at the Yale School of Management and a Faculty Research Fellow at NBER.Timestamps:[00:00] Intro[02:59] Building a mortgage panel from the Home Mortgage Disclosure Act Data[07:52] DuckDB + Parquet for large-scale data work[11:47] Claude Code's planning mode and agent workflow[27:55] Harmonizing 18 years of mortgage data[42:01] Fintech lender classification and market-share trends
August 28 · 27 min
A Mini-Series on Claude Code for Applied Economists, Part 3: Web Scraping | Markus' Academy | Ep. 162-3
Follow the link for the full summary: https://markusacademy.substack.com/p/claude-code-for-applied-economists Link to sign up for the webinar series: https://markusacademy.substack.com/ Paul Goldsmith-Pinkham joined Markus’ Academy for a mini-series on Claude Code for Applied Economists. This is episode 3 of 8. Goldsmith-Pinkham is an Associate Professor of Finance at the Yale School of Management and a Faculty Research Fellow at NBER.Paul used Claude Code to scrape SEC EDGAR filings. Claude Code extracted the risk-factors mentioned in firms’ 10-K reports and built a structured DuckDB database to show how tariff-related risk disclosure became more frequent and more specific in recent years.Overall, this episode highlighted how to best work with Claude Code by planning and iterating on results. Paul turned messy filings into usable research data in just a few minutes.Timestamps:[1:26] Developing a plan to scrape 10K filings[12:40] Modifying the plan[18:05] Running the scraper and debugging[24:03] Which sectors mention tariffs the most?[26:32] Recap
August 28 · 37 min
A Mini-Series on Claude Code for Applied Economists, Part 2: Data Analysis | Markus' Academy | Ep. 162-2
Follow the link for the full summary: https://markusacademy.substack.com/p/claude-code-for-applied-economists Link to sign up for the webinar series: https://markusacademy.substack.com/ Paul Goldsmith-Pinkham joined Markus’ Academy for a mini-series on Claude Code for Applied Economists. This is episode 2 of 8. Goldsmith-Pinkham is an Associate Professor of Finance at the Yale School of Management and a Faculty Research Fellow at NBER.Paul showed how Claude Code dramatically shrinks the gap between a vague research idea and initial results. As an example, he used Claude Code to obtain and plot data on home ownership in the US. Claude Code found the relevant data from the Census, handled scraping issues, cleaned spreadsheets, generated the required scripts.Timestamps:[1:33] Starting from nothing[6:16] Agent spawning[13:20] Scraping tips[22:24] Plotting graphs[30:04] Results[35:20] Summing up
August 28 · 36 min
A Mini-Series on Claude Code for Applied Economists, Part 1: Getting Started | Markus' Academy | Ep. 162-1
Follow the link for the full summary: https://markusacademy.substack.com/p/claude-code-for-applied-economists Link to sign up for the webinar series: https://markusacademy.substack.com/ Paul Goldsmith-Pinkham joined Markus’ Academy for a mini-series on Claude Code for Applied Economists. This is episode 1 of 8. Goldsmith-Pinkham is an Associate Professor of Finance at the Yale School of Management and a Faculty Research Fellow at NBER.Paul introduced Claude Code as a terminal-based AI coding assistant that can read files, write and run code locally, and accelerate research workflows. He explained his key principles for using these tools optimally, for example the importance of the context window and compaction.He contrasted Claude Code with the more sandboxed Cowork environment, and discussed other complementary tools like Ghostty, Zellij, and Oh My Zsh.Timestamps:[1:43] Series Overview[6:52] What is Claude Code / Cowork?[22:10] Installation and pricing[23:54] The context window[29:31] Privacy[31:18] Tips for getting started
August 27 · 1 hr 11 min
Data Centers: Financing the AI Buildout | Markus' Academy | Ep. 161
Follow the link for the full summary: https://markusacademy.substack.com/p/data-centers-financing-the-ai-buildout Link to sign up for the webinar series: https://markusacademy.substack.com/ For the latest episode of Markus’ Academy Stijn Van Nieuwerburgh presented his recent paper: Financing the AI Buildout: https://business.columbia.edu/sites/default/files-efs/imce-uploads/svannieuwerburgh/papers/FinancingAIBuildout_03192026.pdfVan Nieuwerburgh is the Earle W. Kazis and Benjamin Schore Professor of Real Estate and Professor of Finance at Columbia University's Graduate School of Business.Timestamps:[04:32] Why AI changed the Economics of Data Centers[22:25] The changing ownership and financing of the AI buildout[38:20] The New Finance Architecture of the AI Buildout Transfers Risk and Increases Opacity[50:26] What could go wrong?

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