Towards a New Model for Early Warning Signals for Systemic Financial Fragility and Near Crises: An Application to OECD Countries

38 Pages Posted: 6 Feb 2012 Last revised: 30 Jan 2013

See all articles by Nashwa Saleh

Nashwa Saleh

City University London - The Business School

Barbara Casu

City University London - The Business School

Andrew Clare

City, University of London - Bayes Business School

Date Written: November 27, 2012

Abstract

Despite the exorbitant cost of financial crises had highlighted the importance of early warning systems for financial fragility, existing models failed to signal warnings for the 2007-2010 crisis. Using a signal extraction framework and looking at OECD countries over a 27 year period, this paper attempts to identify a number of variables significant in predicting near-crises as a pre-cursor to full-fledged crises. These include growth in pension assets as an indicator for the development of liquidity bubbles, equity market dividend yields as a proxy for corporate balance sheet health, banking sector assets growth and relative size to GDP. We also study the development of asset price bubbles through an equity markets indicator and a house price indicator. Finally we also look at a banking sector funding stability indicator and liquidity indicator on a micro-level. Simultaneously, a dynamic research design improves on previous static set-ups and enhances the model predictive power and applicability to different time periods. Our results indicate that as early as 2004, clear signals were being given that vulnerabilities were building up for a number of countries. EWS design has significant implications for financial stability and financial regulation.

Keywords: financial crises, financial fragility, liquidity bubbles, early warning signals, financial stability, financial regulation

Suggested Citation

Saleh, Nashwa and Casu, Barbara and Clare, Andrew D., Towards a New Model for Early Warning Signals for Systemic Financial Fragility and Near Crises: An Application to OECD Countries (November 27, 2012). Available at SSRN: https://ssrn.com/abstract=2000141 or http://dx.doi.org/10.2139/ssrn.2000141

Nashwa Saleh (Contact Author)

City University London - The Business School ( email )

106 Bunhill Row
London, EC1Y 8TZ
United Kingdom

Barbara Casu

City University London - The Business School ( email )

106 Bunhill Row
London, EC1Y 8TZ
United Kingdom

Andrew D. Clare

City, University of London - Bayes Business School ( email )

106, Bunhill Row
London, EC1Y 8TZ
United Kingdom

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