On the interaction between market and credit risk: a factor-augmented vector autoregressive (FAVAR) approach
AbstractThe aim of the paper is to understand the interaction between market and credit risk. Using a comprehensive set of Italian data, we apply a factor model to identify the common sources of risk driving fluctuations in the real and financial sectors. The common latent factors are then inserted in a VAR framework via a Factor Augmented Vector Autoregressive (FAVAR) approach to analyse the role of risk interactions with monetary policy shocks. We find that the impact of a restrictive monetary policy shock on credit risk is amplified when considering the feedback effect deriving from macroeconomic and equity market risk. Thus, neglecting dynamic interactions among risks may lead to biased estimates of the overall risk measure. The approach provides a framework for modelling macro and financial feedback dynamics, shedding some light on the complex interdependence between the financial sector and the real economy.
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Bibliographic InfoPaper provided by Bank of Italy, Economic Research and International Relations Area in its series Temi di discussione (Economic working papers) with number 779.
Date of creation: Oct 2010
Date of revision:
FAVAR approach; credit risk; market risk; factor model;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
- G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-11-20 (All new papers)
- NEP-BAN-2010-11-20 (Banking)
- NEP-MIC-2010-11-20 (Microeconomics)
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