Dealing with dimension reduction in financial panel data

Abstract

In this paper, we present a fully data-driven statistical approach to building a syn thetic 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 con tribute 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 to gether 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 Inter national Monetary Fund ranging from 2006 to 2017 for 140 countries that span the globe, including both strong and developing economies.

Keywords: Financial stability, Financing constraints, Data-driven, Dynamic Factor Model, State-space model, dimension reduction.