A new time-domain decomposition for weakly stationary or trend stationary processes is introduced. The method is based on trigonometric polynomial modeling, and it is explicitly devised to disentangle medium to long-term and short-term fluctuations in macroeconomic and financial series. A multivariate extension involving sequential univariate decompositions and Principal Components Analysis is also provided. Based on this multivariate approach, new composite indexes of macro-financial conditions for the euro area are introduced. The indicators suggest that most of the GDP contraction during the current pandemic has been of short-term, cyclical nature. Moreover, the financial cycle might have currently achieved a peak area. Hence, the risk of further, deeper disruptions is high, particularly as a new sovereign/corporate debt crisis were not eventually avoided.
Morana, C. (2024). A new macro-financial condition index for the euro area. ECONOMETRICS AND STATISTICS, 29(January 2024), 64-87 [10.1016/j.ecosta.2021.09.005].
A new macro-financial condition index for the euro area
Morana C.
2024
Abstract
A new time-domain decomposition for weakly stationary or trend stationary processes is introduced. The method is based on trigonometric polynomial modeling, and it is explicitly devised to disentangle medium to long-term and short-term fluctuations in macroeconomic and financial series. A multivariate extension involving sequential univariate decompositions and Principal Components Analysis is also provided. Based on this multivariate approach, new composite indexes of macro-financial conditions for the euro area are introduced. The indicators suggest that most of the GDP contraction during the current pandemic has been of short-term, cyclical nature. Moreover, the financial cycle might have currently achieved a peak area. Hence, the risk of further, deeper disruptions is high, particularly as a new sovereign/corporate debt crisis were not eventually avoided.File | Dimensione | Formato | |
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