The FMI Annual Report sets out how the Bank has exercised its responsibilities in respect of supervising financial market infrastructures since the last report.
This study involves tasking ChatGPT with classifying an “activity sentiment score” based on PMI news releases. It explores the predictive power of this score for euro area GDP nowcasting. We find that the PMI text scores enhance GDP nowcasts beyond what is embedded in ECB/Eurosystem Staff projections and Eurostat’s first GDP estimate. The ChatGPT-derived activity score retains its significance in regressions that also include the composite output PMI diffusion index.
This study involves tasking ChatGPT with classifying an “activity sentiment score” based on PMI news releases. It explores the predictive power of this score for euro area GDP nowcasting. We find that the PMI text scores enhance GDP nowcasts beyond what is embedded in ECB/Eurosystem Staff projections and Eurostat’s first GDP estimate. The ChatGPT-derived activity score retains its significance in regressions that also include the composite output PMI diffusion index.
David Glancy, Robert J. Kurtzman, and Lara LoewensteinWe use microdata on the phases of commercial construction projects to document three facts regarding the sector's time-to-plan lags: (1) plan times are long and highly variable, (2) nearly half of projects in planning are abandoned, and (3) property price appreciation reduces the likelihood of abandonment.
R. Matthew Darst, Ehraz Refayet, and Alexandros VardoulakisWe examine how macroprudential capital requirements interact with competition between banks and non-banks to shape lending standards. Banks have private information and benefit from deposit insurance, while non-banks lack such advantages but are less regulated.
Leland D. Crane, Akhil Karra, and Paul E. SotoWe evaluate the ability of large language models (LLMs) to estimate historical macroeconomic variables and data release dates. We find that LLMs have precise knowledge of some recent statistics, but performance degrades as we go farther back in history.
This article looks into residential real estate (RRE) lending standards, focusing on their key determinants and assessing the implications of loose lending standards for financial stability and the real economy. Two key insights emerge. First, lending standards tend to be procyclical – i.e., they become looser during economic upturns and tighter during downturns. Second, loose lending standards amplify the effects of negative housing market shocks on the real economy and heighten financial stability risks via an increase in the probability of default of households.
Borrower-based measures (BBMs) are critical tools in the banking union’s macroprudential policy frameworks. They are designed to promote sustainable lending practices and strengthen the resilience of borrowers, lenders and the broader economy. Over the past decade, the adoption of BBMs has significantly increased across countries in the banking union, likely reflecting their effectiveness.
The Bank of England (the Bank), the Financial Conduct Authority (FCA), the Prudential Regulation Authority (PRA), and the Payment Systems Regulator (PSR) (the Authorities) have a Memorandum of Understanding (MoU) which sets out the high-level framework that we use to cooperate with one another in relation to payments in the UK.
Our paper uses a general equilibrium framework to examine the effects of temperature on firm-level demand, productivity and input allocative efficiency. Using data from Italian firms and detailed climate data, it uncovers a sizeable negative effect of extreme temperatures on firm-level productivity. Based on these estimates, the model generates aggregate productivity losses from local temperature fluctuations that are higher than previously thought, ranging from 0.60% to 6.82% depending on the scenario and the extent of adaptation.
