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7 Results

Measuring Systemic Risk Across Financial Market Infrastructures

Staff working paper 2016-10 Fuchun Li, Héctor Pérez Saiz
We measure systemic risk in the network of financial market infrastructures (FMIs) as the probability that two or more FMIs have a large credit risk exposure to the same FMI participant.

Vertical Specialization and Gains from Trade

Staff working paper 2017-17 Patrick Alexander
Multi-stage production is widely recognized as an important feature of the modern global economy. This feature has been incorporated into many state-of-the-art quantitative trade models, and has been shown to deliver significant additional gains from international trade.

Producer Heterogeneity, Value-Added, and International Trade

Staff working paper 2016-54 Patrick Alexander
Standard new trade models depict producers as heterogeneous in total factor productivity. In this paper, I adapt the Eaton and Kortum (2002) model of international trade to incorporate tradable intermediate goods and producer heterogeneity in value-added productivity.

News-Driven International Credit Cycles

Staff working paper 2021-66 Galip Kemal Ozhan
This paper examines the implications of positive news about future asset values that turn out to be incorrect at a later date in an open economy model with banking. The model captures the patterns of bank credit and current account dynamics in Spain between 2000 and 2010. The model finds that the use of unconventional policies leads to a milder bust.

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.

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.