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A data-driven approach to measuring financial soundness throughout the world

Alessandro Bitetto (), Paola Cerchiello () and Charilaos Mertzanis ()
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Alessandro Bitetto: University of Pavia
Paola Cerchiello: University of Pavia
Charilaos Mertzanis: University of Pavia

No 199, DEM Working Papers Series from University of Pavia, Department of Economics and Management

Abstract: We use a fully data-driven approach and information provided by the IMF’s financial soundness indicators to measure the soundness of a country’s financial system around the world. Given the nature of the measurement problem, we apply principal component analysis (PCA) to deal with the presence of strong cross-sectional dependence in the data due to unobserved common factors. Using this comprehensive sample and various statistical methods, we produce a data-driven measure of financial soundness that provides policy makers and financial institutions with a tool that is easy to implement and update.

Keywords: Financial soundness; Data-driven; Cross-country; Policy framework; Principal Component Analysis; Random Forest (search for similar items in EconPapers)
JEL-codes: E02 E32 E42 E61 F02 (search for similar items in EconPapers)
Pages: 29
Date: 2021-02
New Economics Papers: this item is included in nep-cwa, nep-fdg and nep-mac
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