AI Economics Research Podcast

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 land...

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 cu...

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 impli...

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 d...

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 stud...

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 pape...

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...

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...

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 underestima...

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 sec...

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 under...

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...

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 th...

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 vita...

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 impli...

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...

This episode breaks down a Bank of England research paper that significantly improves economic forecasting methods. It explains how economists use advanced statistical models, factor augmentation, and account for asymmetric loss and volatility to create more accurate predictions. Tune in to understand how these sophisticated adjustments enhance forecast performance across a range of economic varia...

This episode breaks down a Bank of England Staff Working Paper, explaining how economists use advanced statistical models called Bayesian Vector Autoregressions (VARs). Discover how these powerful tools help central bankers and researchers forecast key economic and financial variables and understand the impact of policies like interest rate changes. This episode explains a real academic paper in p...

This episode dives into a Bank of England Staff Working Paper exploring how machine learning techniques can enhance macroeconomic forecasting. We break down the paper's findings on using diverse data sources, from traditional surveys to text-based indicators from news articles, to predict economic activity. Discover which models and data combinations yield the most accurate predictions and why the...

This episode unpacks a recent Bank of England research paper on the often-overlooked 'fragility' of deep learning models in finance. We explore how subtle changes can cause AI to give vastly different *explanations* for its decisions, even when predictions are identical. Discover the significant implications this has for financial stability, risk management, and regulatory practices. This episode...

This episode breaks down a Bank of England research paper on using interpretable machine learning for economic forecasting. Discover how advanced AI models can outperform traditional methods by uncovering complex, time-varying relationships in data, specifically demonstrated through forecasting US unemployment. We explain how a new workflow makes these powerful predictions transparent and actionab...

This podcast episode explains groundbreaking Bank of England research uncovering the financial mechanics behind Britain's 1833 slavery abolition compensation. Delve into newly analyzed archival data to understand who truly benefited from the £20 million payout to slave-owners, revealing the crucial role of London's financial institutions and intermediaries in quickly monetizing these government as...

This episode explores a Federal Reserve Bank of New York research paper on the economic effects of legalizing mobile sports betting. We unpack how betting and consumer credit distress can spill across state borders, impacting credit scores and delinquency rates, especially for younger individuals. Understand the fiscal asymmetry created for states that haven't legalized, bearing costs without the...

This episode dives into how ordinary households form their views on inflation, revealing a surprising truth: changes in food prices matter most. Discover why the cost of your groceries profoundly influences collective inflation expectations across all demographics, more so than even energy prices. This research offers crucial insights for central banks in understanding and predicting persistent in...

New research reveals that rising global temperatures are significantly increasing the costs of international trade, a factor largely overlooked in climate impact assessments. This study combines historical trade and weather data to show how climate change, particularly through its effects on sea ports, makes shipping goods more expensive. Discover how ignoring this trade cost channel leads to a su...