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Using Credit Variables to Date Business Cycle and to Estimate the Probabilities of Recession in Real Time
Author(s) -
Aprigliano Valentina,
Liberati Danilo
Publication year - 2021
Publication title -
the manchester school
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.361
H-Index - 42
eISSN - 1467-9957
pISSN - 1463-6786
DOI - 10.1111/manc.12292
Subject(s) - business cycle , recession , economics , econometrics , financial crisis , credit cycle , dynamic factor , economic indicator , great recession , markov chain , macroeconomics , keynesian economics , statistics , mathematics
Following the debate on the relationship between business and financial cycle rekindled in the last decade since the global financial crisis, we assess the ability of some financial indicators to track the Italian business cycle. We mostly use credit variables to detect the turning points and to estimate the probability of recession in real time. A dynamic factor model with Markov‐switching regimes is used to handle a large data set and to cope with the nonlinear evolution of the business cycle. The in‐sample results strongly support the capacity of credit variables to estimate the probability of recessions and the implied coincident indicator proves their ability to fit the business cycle. Also in real time the contribution of credit is not negligible compared to that of the industrial production, currently used for the conjunctural analysis.