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Dealing with dimension reduction in financial panel data

Author

Listed:
  • Alessandro Bitetto

    (University of Pavia)

  • Paola Cerchiello

    (University of Pavia)

  • Charilaos Mertzanis

    (Abu Dhabi University)

Abstract

In this paper, we present a fully data-driven statistical approach to building a synthetic index based on intrinsic information of the considered ecosystem, namely the financial one. Among the several methods made available in the literature, we propose the employment of a Dynamic Factor Model approach which allows us to fully and correctly compare observations at hand in space and time. We contribute to the research field by offering a statistically sound methodology which goes beyond state of the art techniques on dimension reduction, mainly based on Principal Component Analysis. We adopt a country by country fitting strategy to elicit the inner country specific characteristics and then we combine results together by means of a Vector Autoregressive and Kalman filter approach. To this aim, we analyze a set of 17 Financial Soundness Indicators provided by the International Monetary Fund ranging from 2006 to 2017 for 140 countries that span the globe, including both strong and developing economies.

Suggested Citation

  • Alessandro Bitetto & Paola Cerchiello & Charilaos Mertzanis, 2022. "Dealing with dimension reduction in financial panel data," DEM Working Papers Series 207, University of Pavia, Department of Economics and Management.
    • Handle: RePEc:pav:demwpp:demwp0207
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    File URL: http://dem-web.unipv.it/web/docs/dipeco/quad/ps/RePEc/pav/demwpp/DEMWP0207.pdf
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    Keywords

    Financial stability; Financing constraints; Data-driven; Dynamic Factor Model; State-space model; dimension reduction;
    All these keywords.

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