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69 Results

Interconnected Banks and Systemically Important Exposures

How do banks' interconnections in the euro area contribute to the vulnerability of the banking system? We study both the direct interconnections (banks lend to each other) and the indirect interconnections (banks are exposed to similar sectors of the economy). These complex linkages make the banking system more vulnerable to contagion risks.

Understanding the Systemic Implications of Climate Transition Risk: Applying a Framework Using Canadian Financial System Data

Our study aims to gain insight on financial stability and climate transition risk. We develop a methodological framework that captures the direct effects of a stressful climate transition shock as well as the indirect—or systemic—implications of these direct effects. We apply this framework using data from the Canadian financial system.

Learning, Equilibrium Trend, Cycle, and Spread in Bond Yields

Staff working paper 2020-14 Guihai Zhao
This equilibrium model explains the trend in long-term yields and business-cycle movements in short-term yields and yield spreads. The less-frequent inverted yield curves (and less-frequent recessions) after the 1990s are due to recent secular stagnation and procyclical inflation expectations.

The (Mis)Allocation of Corporate News

Staff working paper 2024-47 Xing Guo, Alistair Macaulay, Wenting Song
We study how the distribution of information supply by the news media affects the macroeconomy. We find that media coverage focuses particularly on the largest firms, and that firms’ equity financing and investment increase after media coverage. But these equity and investment responses are largest among small, rarely covered firms. Our quantitative studies highlight that the aggregate effects of media coverage depend crucially on how that coverage is allocated.

Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects

Staff working paper 2019-16 Kerem Tuzcuoglu
Modeling and estimating persistent discrete data can be challenging. In this paper, we use an autoregressive panel probit model where the autocorrelation in the discrete variable is driven by the autocorrelation in the latent variable. In such a non-linear model, the autocorrelation in an unobserved variable results in an intractable likelihood containing high-dimensional integrals.
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