Building a financial conditions index for the euro area and selected euro area countries: What does it tell us about the crisis?

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. The refereeing process of this paper has been coordinated by a team composed of Gerhard Rünstler, Kalin Nikolov and Bernd Schwaab (all ECB). Terms of use: Documents in EconStor mayThe paper is released in order to make the research of MaRs generally available, in preliminary form, to encourage comments and suggestions prior to final publication. The views expressed in the paper are the ones of the author(s) and do not necessarily reflect those of the ECB or of the ESCB. AcknowledgementsWe would like to thank Dafni Giannikou for excellent research assistance. Additionally, thanks are due to Stephen Hall with whom we discussed issues related to the interpretation of the principal components and to Daphne Papadopoulou for discussions on monetary policy implementation. Non-technical summaryThe systemic financial crisis which engulfed the global economy from 2008, along with the subsequent sovereign debt crisis in the euro area, has led to the need to reassess the relationship between financial conditions and real economic activity. Within the context of the Macroprudential Research Network (MaRs), organized by the ESCB, one of the three workstreams is devoted to examining this relationship and the channels through which it operates.A prior question which arises is how exactly financial conditions should be depicted within models. Traditionally, macroeconometric models include only an interest rate. However, during periods of financial stress, changes in interest rates alone may not suffice to capture all the interactions between the financial system and the real economy. Variables such as credit aggregates, survey data reflecting the supply of loans and their terms and conditions, volatility in financial markets and spreads between various assets in different risk classes can all convey additional information on financial conditions and, in turn, influence economic activity through their effect on consumption, savings, investment and exports.In this paper, we seek to construct indices of financial conditions for the euro area and for selected individual euro area countries, which can be used to explore further macro-financial linkages in the economy at large. We construct indices which both exclude and include

The impact of financial liberalization on economic growth in sub-Saharan Africa

“…The paper argues that FCI can be used as a good indicator to ascertain inflation targets and to monitor development in the Turkish economy. Angelopoulou et al (2014) also constructed a FCI; and they found that for countries, like Greece and Portugal, their financial condition deteriorated after the sovereign crisis and the global financial crisis, when compared with countries like Germany that enjoyed a strong financial condition. Therefore, the effect of financial liberalization can be heterogeneous across the globe.…”

“…These include studies, such as Matheson (2012), Koop and Korobilis (2014), Angelopoulou, Balfoussia, and Gibson (2014), and Bulut (2017), amongst others. These papers usually construct a financial conditions index to measure the real state of economic and financial activities, instead of using the traditional interest rate variable.…”

Measuring the Instability of China’s Financial System: Indices Construction and an Early Warning System

“…Hence, an FCI should cover all the contents about the future state of the economy contained in these current financial variables. Using similar methodology as in constructing an FSI, Angelopoulou et al (2013) summarizes several ways from which the weights of FCIs are generally derived: (1) structural models as in Goodhart et al (2002); (2) reduced form models likely in Mayes and Viren (2001); (3) Principal Components Analysis in Forss et al (2011); (4) impulse responses of a VAR or Kalman filter. FCIs have been developed for a number of countries (US, Canada, Finland, Sweden, Germany, UK, Euro area etc.).…”

A financially stressed euro area

“…2 Notable exceptions are Angelopoulou et al (2014) and Hatzius et al (2010), where a higher number of factors is explicitly addressed. Their focus, however, is somewhat different as they aim at improving the forecast ability and end up with one aggregate index or do not assess the dimension of underlying shocks, for instance.…”

“…This is probably the most prominent index, besides numerous different indices presented in the recent literature. For instance, Davig and Hakkio (2010) and Hakkio and Keeton (2009) construct the Kansas City Financial Stress Index (KCFSI), as well as Angelopoulou et al (2014) build a financial stress index by using principal components analysis (PCA) to capture the co-movement of the underlying series. Dynamic factor econometrics methods are used by Brave and Butters (2011) and Butters (2012), van Roye (2013) and Matheson (2012).…”