Hie Joo Ahn and Yunjong EoThis paper empirically investigates sources of hysteresis, focusing on downward nominal wage rigidity and the gender gap in the labor market, using U.S. state-level payroll employment data. Employing a Bayesian Markov-switching model of business cycles, we identify U-shaped and L-shaped recessions, which correspond to quick recoveries and hysteresis, respectively.
Ece Fisgin, Joaquin Garcia-Cabo, Alex Haag, and Mitch LottWe present a principal component analysis of euro area labor market conditions by combining information from 22 labor market indicators into two comprehensive series. These two novel indicators provide a systematic view of the current state and forward-looking direction of the euro-area labor market, respectively, and demonstrate superior forecasting performance compared to existing indicators.
The March 2023 banking turmoil has intensified discussions whether social media and the digitalisation of finance have become significant factors in driving severe deposit outflows. We introduce the concept of deposits-at-risk and utilize quantile regressions for disentangling determinants of stressed outflows at the lowest tail of the distribution.
Traditional exposure measures focus on direct exposures to evaluate the losses an institution is exposed to upon the default of a counterparty. Since the Global Financial Crisis of 2007-2008, the importance of indirect exposures via common asset holdings is increasingly recognized. Yet direct and indirect exposures do not to capture the losses that result from shock propagation and amplification following the counterparty's default. In this paper, we introduce the concept of \higher-order exposures" to refer to these spill-over losses and propose a way to formalize and quantify these.
Rehim KilicThis paper fills an important gap in the volatility forecasting literature by comparing a broad suite of machine learning (ML) methods with both linear and nonlinear econometric models using high-frequency realized volatility (RV) data for the S&P 500. We evaluate ARFIMA, HAR, regime-switching HAR models (THAR, STHAR, MSHAR), and ML methods including Extreme Gradient Boosting, deep feed-forward neural networks, and recurrent networks (BRNN, LSTM, LSTM-A, GRU).
The Bank of England’s Monetary Policy Committee is responsible for making decisions about Bank Rate.
Add full abstract text in one paragraph.This paper examines how the ECB’s 2022–2023 interest-rate hikes affected euro-area banks’ economic net worth and vulnerability to deposit runs. Drawing on granular, confidential data for 139 banks, we estimate each bank’s economic net worth and find that unrealised losses on loans and bonds averaged around 30 per cent of equity. By September 2023, however, roughly half of these losses had been offset by gains from the deposit franchise and interest-rate swaps.
How does environmental, social and governance regulation of banks affect capital provision to the sustainability transition? As ambitious sustainability targets face funding challenges, the financial sector is tasked with channeling more private capital into sustainable investments. However, scaling sustainable technologies often requires investment in non-ESG-compliant assets. The mobility transition to electric vehicles, for example, demands increased supply of battery raw materials like Lithium, Cobalt, Manganese, and Nickel.
The Bank's Court of Directors acts as a unitary board, setting the organisation's strategy and budget and taking key decisions on resourcing and appointments. Required to meet a minimum seven times per year, it has five executive members from the Bank and up to nine non-executive members.
Do climate stress tests affect bank credit supply to brown firms? Using a difference-in-differences approach and detailed data on individual bank loans in the euro area, this paper provides novel evidence on the effects of the ECB’s 2022 climate risk stress test. Despite no capital implications or public disclosures, participating banks significantly reduced credit to greenhouse gas-intensive industries relative to nonparticipants. Among affected firms, smaller borrowers were more negatively impacted.
