AI Economics Research Podcast

This episode breaks down a recent paper from the FEDERAL RESERVE BANK OF ST. LOUIS that reveals how job switching—known as employer-to-employer (EE) transitions—significantly influences inflation and impacts optimal monetary policy decisions. We explore why central banks need to consider job mobility alongside unemployment rates to accurately forecast price changes and set interest rates, with examples from the Great Recession and the Great Resignation. Dive deeper into the research at https://fedinprint.org/item/fedlwp/94640/102106 and share your thoughts with us at feedback@econpod.org. This episode explains a real academic paper in plain English for a general audience. Source paper: FEDERAL RESERVE BANK OF ST. LOUIS Labor Market Shocks and Monetary Policy - FEDERAL RESERVE BANK OF ST. LOUIS https://doi.org/10.20955/wp.2022.016 Keywords: Inflation, Monetary Policy, Job Mobility, Labor Markets, Central Banking, Interest Rates

This episode explores a fascinating research paper from the Federal Reserve Bank of New York, diving into the critical difference between programmable payments and programmable money. As central banks worldwide explore digital currencies, understanding this distinction is vital to ensure new monetary systems don't compromise the fundamental qualities of "good" money like uniformity and fungibility. Discover how a new framework clarifies this debate, and share your thoughts at feedback@econpod.org. Read the full paper at https://www.newyorkfed.org/research/staff_reports/sr1180.html. This episode explains a real academic paper in plain English for a general audience. Source paper: Michael Junho Lee | Antoine Martin Programming Money Without Programmable Money - Federal Reserve Bank of New York Staff Reports https://doi.org/10.59576/sr.1180 Keywords: Programmable Money, Digital Payments, Central Banking, Digital Currency, Monetary Systems, Financial Stability

This episode unpacks a Bank of England staff working paper by Jamie Lenney and Biagio Rosso, exploring how economic models can better reflect real-world human behavior. We dive into a new flexible approach that moves beyond traditional rational expectations, allowing for agents to overreact or underreact to economic conditions and news. Learn how incorporating these 'behavioural expectations' significantly improves the empirical fit of macroeconomic models, especially when forecasting inflation. We welcome your thoughts at feedback@econpod.org, and you can find the full paper at https://www.bankofengland.co.uk/-/media/boe/files/working-paper/2026/a-flexible-deviation-from-fire-in-the-sequence-space.pdf. This episode explains a real academic paper in plain English for a general audience. Source paper: A flexible deviation from FIRE in the Jamie Lenney and Biagio Rosso - Bank of England Keywords: Macroeconomics, Behavioural economics, Inflation, Monetary policy, Economic forecasting, Rational expectations

This episode dives into a Bank of England research paper by Eric Tong and Rennae Cherry, titled "Central bank communications that reach the public." We explore how central bank messages, as encountered through news media, actually shape households' inflation expectations, challenging the traditional view that central bank communication rarely reaches the public. Learn why measuring communication as the public experiences it is crucial for understanding its impact on financial stability and macroeconomics, and share your thoughts at feedback@econpod.org. Find the full paper at https://www.bankofengland.co.uk/-/media/boe/files/working-paper/2026/central-bank-communications-that-reach-the-public.pdf This episode explains a real academic paper in plain English for a general audience. Source paper: Central bank communications that Eric Tong and Rennae Cherry - Bank of England Keywords: central banking, inflation expectations, macroeconomics, financial stability, monetary policy, public communication, textual analysis, economic forecasting, media influence

This episode breaks down a new Bank of England research paper that explores how rapid innovation in digital payments and new private digital monies challenge the idea that all money should trade at par—a concept known as "monetary singleness." Discover when small deviations from par are efficient and why central bank reserves and cash are crucial for financial stability in an evolving digital landscape. Read the full paper at https://www.bankofengland.co.uk/-/media/boe/files/working-paper/2026/a-model-of-monetary-singleness.pdf, and share your thoughts at feedback@econpod.org. This episode explains a real academic paper in plain English for a general audience. Source paper: A model of monetary singleness - Bank of England Keywords: Monetary Singleness, Digital Money, Central Banking, Financial Stability, Payment Systems, Cash

This episode dives into a Federal Reserve Bank of New York Staff Report that uses big data from foot traffic to uncover hidden demand shocks affecting businesses in New York City. We explore how retail, service, and health establishments experience highly varied and unpredictable changes in customer demand, challenging traditional economic assumptions. Hear the plain English explanation of this cutting-edge research and share your thoughts at feedback@econpod.org. This episode explains a real academic paper in plain English for a general audience. Source paper: NO. 1191 Shocks from Foot Traffic Marina Azzimonti | David Wiczer | Yang Xuan - Federal Reserve Bank of New York Staff Reports https://www.newyorkfed.org/medialibrary/media/research/staff_reports/sr1191.pdf?sc_lang=en Keywords: Foot Traffic, Demand Shocks, Retail Economics, Service Sector, Big Data, Economic Forecasting

This episode dives into a new Bank of England research paper exploring whether Large Language Models like GPT-3.5 Turbo can form inflation perceptions and expectations similar to human households. Using a clever quasi-experimental design, the study compares LLM outputs to survey data, revealing how AI responds to economic signals and its surprising sensitivity to food inflation. Discover the implications for economic forecasting and social science research, and share your thoughts at feedback@econpod.org. Find the full paper here: https://www.bankofengland.co.uk/-/media/boe/files/working-paper/2026/inflation-attitudes-of-large-language-models.pdf This episode explains a real academic paper in plain English for a general audience. Source paper: Inflation attitudes of large Nikoleta Anesti, Edward Hill and Andreas Joseph - Bank of England Keywords: inflation, large language models, AI, economic forecasting, central banking, macroeconomics

This episode breaks down a recent Federal Reserve Bank of St. Louis research paper, offering a strategic economic analysis of narcoterrorism in plain English. We explore how terrorist groups extort drug farmers for funding, how developed nations use crop destruction as a counterterrorism tool, and the complex interplay of drug markets, terror financing, and international policy. For questions or discussion, email feedback@econpod.org. This episode explains a real academic paper in plain English for a general audience. Source paper: FEDERAL RESERVE BANK OF ST. LOUIS A Strategic Analysis of Narcoterrorism: Counterterrorism, Terrorist - FEDERAL RESERVE BANK OF ST. LOUIS https://s3.amazonaws.com/real.stlouisfed.org/wp/2025/2025-032.pdf Keywords: Narcoterrorism, Counterterrorism, Drug Trafficking, Terrorist Financing, International Economics, Security Policy

This episode breaks down a research paper from the Federal Reserve Bank of St. Louis, exploring whether different measures of the money supply are useful for forecasting US inflation. Using advanced non-linear techniques, the authors find limited support for monetary aggregates as reliable inflation predictors in the early to mid-2000s. Dive into the specifics of this intriguing macroeconomic study at https://fedinprint.org/item/fedlwp/10440/original and share your thoughts at feedback@econpod.org. This episode explains a real academic paper in plain English for a general audience. Source paper: FEDERAL RESERVE BANK OF ST. LOUIS Does Money Matter in Inflation Forecasting? - FEDERAL RESERVE BANK OF ST. LOUIS https://doi.org/10.20955/wp.2009.030 Keywords: inflation, money supply, forecasting, monetary policy, central banking, macroeconomics

This episode dives into a Federal Reserve Bank of St. Louis research paper asking a crucial question: Do monetary aggregates actually help forecast inflation? We break down the paper's novel approach using neural networks and kernel regression to evaluate money's predictive power for US inflation in the early 2000s, explaining the findings in plain English. For more details, find the original paper at https://fedinprint.org/item/fedlwp/10440/original, and we welcome your feedback and discussion at feedback@econpod.org. This episode explains a real academic paper in plain English for a general audience. Source paper: FEDERAL RESERVE BANK OF ST. LOUIS Does Money Matter in Inflation Forecasting? - FEDERAL RESERVE BANK OF ST. LOUIS https://doi.org/10.20955/wp.2009.030 Keywords: Inflation, Money Supply, Forecasting, Macroeconomics, Central Banking, Neural Networks

This episode dives into a Federal Reserve Bank of St. Louis research paper that examines how to make economic forecasts more accurate, particularly in an environment of structural change. We break down how combining "recursive" (using all available data) and "rolling" (using only recent data) forecasting methods can significantly improve prediction quality. Learn about this innovative strategy and share your feedback at feedback@econpod.org, or read the full paper at https://fedinprint.org/item/fedlwp/9611/original. This episode explains a real academic paper in plain English for a general audience. Source paper: FEDERAL RESERVE BANK OF ST. LOUIS Improving Forecast Accuracy by Combining Recursive and Rolling - FEDERAL RESERVE BANK OF ST. LOUIS https://doi.org/10.20955/wp.2008.028 Keywords: forecasting, macroeconomics, structural change, central banking, model averaging, forecast accuracy

This episode delves into an OECD research paper that challenges conventional wisdom on forecasting recessions. We explore how a "wisdom of crowds" approach, averaging predictions from multiple simple models, can be as effective as advanced machine learning techniques like Random Forests for predicting economic downturns in OECD countries. Do you have thoughts on the best forecasting methods? Share them with us at feedback@econpod.org. This episode explains a real academic paper in plain English for a general audience. Source paper: Harnessing the wisdom - Organisation for Economic Co-operation and Development https://www.oecd.org/content/dam/oecd/en/publications/reports/2025/12/harnessing-the-wisdom-of-crowds-to-assess-recession-risks-in-oecd-countries_d197200d/46880adc-en.pdf Keywords: Recession, Economic Forecasting, Macroeconomics, Machine Learning, Wisdom of Crowds, OECD

This episode explains a Bank of England Staff Working Paper, "Non-standard errors," by Albert J Menkveld et al., exploring how variations in researcher choices introduce significant "non-standard errors" into scientific findings. We break down their study of 164 teams testing hypotheses on the same data, revealing these errors are substantial, decrease with peer feedback, and are often underestimated by participants. Have thoughts or questions on how researcher bias impacts economic insights? Send them to feedback@econpod.org. This episode explains a real academic paper in plain English for a general audience. Source paper: Keywords: non-standard errors, research methodology, scientific uncertainty, economics research, central banking, data analysis

This episode dives into a Federal Reserve Bank of New York Staff Report that explores a critical challenge in information disclosure: how to ensure a sender, like a bank regulator, can truly commit to a disclosure rule without manipulating signals after the fact. We'll break down how the paper introduces 'Receiver-Private Certified Bayesian Persuasion,' revealing why cryptography, specifically secure two-party computation, is not just a tool but a necessary condition to prevent ex-post information suppression in economic settings like bank stress tests. This episode explains a real academic paper in plain English for a general audience. Source paper: MAY 2026 and Cryptography Bayesian Persuasion and Cryptography - Federal Reserve Bank of New York Staff Reports https://doi.org/10.59576/sr.1194 Keywords: central banking, financial stability, information disclosure, stress testing, cryptography, economic commitment

This episode breaks down a new Bank of England research paper that explores how economic cycles, like recessions, impact the stability of earnings for UK households. It reveals that during downturns, negative income shocks become more frequent, even if the overall spread of income changes remains similar, and introduces a new model to track these crucial dynamics for policymakers. Tune in to understand why this matters for financial stability and macroeconomic policy, and share your thoughts with us at feedback@econpod.org. This episode explains a real academic paper in plain English for a general audience. Source paper: Modelling income risk dynamics in - Bank of England https://www.bankofengland.co.uk/-/media/boe/files/working-paper/2025/modelling-income-risk-dynamics-in-the-uk-a-parametric-approach.pdf Keywords: Income Risk, UK Economy, Macroeconomics, Financial Stability, Central Banking, Earnings Dynamics

This episode breaks down a recent Bank of England working paper, exploring the best econometric methods for accurately estimating structural parameters in complex economic models. We demystify Local Projections (LP) versus Vector Autoregressions (VAR), and compare Impulse Response Function (IRF) matching with Indirect Inference. Discover why Indirect Inference is often the more robust and reliable approach for central banks and researchers. This episode explains a real academic paper in plain English for a general audience. Source paper: Local Projections vs. VARs for - Bank of England https://www.bankofengland.co.uk/-/media/boe/files/working-paper/2025/local-projections-vs-vars-for-structural-parameter-estimation.pdf Keywords: DSGE models, Econometrics, Macroeconomics, Indirect Inference, VAR models, Local Projections

This episode delves into a groundbreaking research paper from the Bank for International Settlements, exploring how artificial intelligence is being harnessed to monitor and predict financial market stress. We break down a novel approach that combines recurrent neural networks (RNNs) to forecast market dysfunction with large language models (LLMs) to explain the underlying drivers. Discover how this dual AI system can identify "canaries in the coal mine" like deviations in currency arbitrage, offering early warnings for financial stability. This episode explains a real academic paper in plain English for a general audience. Source paper: Harnessing artificial - Bank for International Settlements https://www.bis.org/publ/work1291.pdf Keywords: Financial Stability, Forecasting, Artificial Intelligence, Machine Learning, Central Banking, Market Stress

This episode delves into a Bank of England research paper exploring how machine learning is being applied in central banking and policy analysis. We break down complex AI concepts into plain English, showing how tools like neural networks are used for economic forecasting, financial regulation, and understanding market trends. Discover the future of data-driven decision-making at institutions vital to financial stability. This episode explains a real academic paper in plain English for a general audience. Source paper: https://www.bankofengland.co.uk/-/media/boe/files/working-paper/2017/machine-learning-at-central-banks.pdf Keywords: Machine Learning, Central Banking, Economic Forecasting, Financial Stability, Inflation, Macroeconomics

This episode dives into a new Bank for International Settlements (BIS) research paper investigating Artificial Intelligence (AI) adoption across European firms. Learn how AI boosts labor productivity by 4% without displacing jobs in the short term, primarily through 'capital deepening.' We explore the uneven distribution of these gains, the role of complementary investments, and the critical implications for economic policy. This episode explains a real academic paper in plain English for a general audience. Source paper: AI adoption, productivity - Bank for International Settlements Keywords: Artificial Intelligence, Productivity, Employment, Europe, Macroeconomics, Digital Transformation

This episode delves into a new research paper from the Bank for International Settlements, exploring how the lightning speed of high-frequency trading (HFT) influences the cost of capital for companies. We uncover how HFT can paradoxically raise capital costs for some stocks by amplifying systematic risk, while simultaneously reducing it for others through improved liquidity. Discover the crucial implications of these complex findings for financial market regulation and real economic outcomes. This episode explains a real academic paper in plain English for a general audience. Source paper: high-frequency trading - Bank for International Settlements https://www.bis.org/publ/work1290.pdf Keywords: high-frequency trading, cost of capital, financial markets, market regulation, systematic risk, financial stability