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 [email protected].

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 [email protected]. 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 [email protected].

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 [email protected].

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 [email protected].

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 [email protected], 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 [email protected].

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 [email protected].

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 [email protected].

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