Opțiuni de căutare
Pagina inițială Media Materiale explicative Studii și publicații Statistici Politică monetară Euro Plăți și piețe Cariere
Sugestii
Sortează în funcție de
Nu este disponibil în limba română

Sophia Chen

20 April 2020
WORKING PAPER SERIES - No. 2395
Details
Abstract
This paper presents a new dataset on the dynamics of non-performing loans (NPLs) during 88 banking crises since 1990. The data show similarities across crises during NPL build-ups but less so during NPL resolutions. We find a close relationship between NPL problems—elevated and unresolved NPLs—and the severity of post-crisis recessions. A machine learning approach identifies a set of pre-crisis predictors of NPL problems related to weak macroeconomic, institutional, corporate, and banking sector conditions. Our findings suggest that reducing pre-crisis vulnerabilities and promptly addressing NPL problems during a crisis are important for post-crisis output recovery.
JEL Code
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
N10 : Economic History→Macroeconomics and Monetary Economics, Industrial Structure, Growth, Fluctuations→General, International, or Comparative
N20 : Economic History→Financial Markets and Institutions→General, International, or Comparative
Annexes
20 April 2020
ANNEX