Financial Conditions Index and Identification of Credit Supply Shocks for the Euro Area

• Published date: 01 December 2014
• Author: Diego Nicolas Moccero,Laurent Maurin,Matthieu Darracq Pariès
• DOI: http://doi.org/10.1111/infi.12056
• Date: 01 December 2014

Financial Conditions Index and

Identification of Credit Supply

Shocks for the Euro Area

Diego Nicolas Moccero

y

,MatthieuDarracqPariès

z

and Laurent Maurin

z

y

European Central Bank, Macro‐Financial Linkages Division, Frankfurt am

Main, Germany, and

z

European Central Bank, Monetary Analysis Division,

Frankfurt am Main, Germany

Abstract

The international financial crisis and the euro‐area sover eign debt crisi s

brought to the fore the importance of financial condit ions to the macro‐

economy. The complexity of the financial sector means that a wide range

of financial variables is needed to fully characterize its functioning in

real time. In this paper we construct a financial conditions index (FCI)

for the euro area following the studies by Hatzius et al. and Brave and

Butters. Our FCI successfully tracks both worldwide and euro‐area‐

specificfinancial events. We then incorporate the FCI into a VAR model

comprising outp ut, inflation, the monetar y policy rate, bank loa ns and

bank lending spreads to identify credit supply shocks with sign restric-

tions. These shocks are estimated to have caused around one‐fifth of the

declineineuro‐area manufact uring product ion at the trough of the

financial crisis and a rise in bank lending spreads of around 30 basis

points.

International Finance 17:3, 2014: pp. 297–321

DOI: 10.1111/infi.12056

© 2014 John Wiley & Sons, Ltd.

I. Introduction

The international financial crisis of 2008–09 and the euro‐area sovereign

debt crisis have underscored the importance of financial conditions to the

macroeconomy. Financial conditions characterize the functioning of finan-

cial markets and acce ss to credit by non‐financial agents. To be operational

for policy‐makers, they are often synthesized into either one or a handful of

indicators, computed either as a weighted average of several standardized

variables or as latent variables contributing to the explanation of the

dynamics of observable variables.

Financial market frictions impair, through different channels, the normal

flow of lending to consumers and corporations, depressing economic activity

and inflation. Increasing borrowing costs and falling asset prices depress

consumption through both wealth and inter‐temporal substitution effects.

Higher bank lending rate spreads are associated with higher borrowing costs,

which reduce dema nd for new physica l capital. Consu mption and invest-

ment are also impaired by changes in risk perceptions and risk tolerance that

alter market risk premia, and by imperfections in credit supply (such as

information asymmetries between lenders and borrowers). Changes in the

exchange rate also have a burden on activity through their impact on net

exports.

The complexity of the financial sector means that a wide range of financial

variables is needed to characterize the extent of its functioning in real time.

Although individual financial indicators can be useful as predictors of

economic activity and inflation at specific points in time, their relevance is

likely to change ove r time. As shown by St ock and Watson (2002a), the us e

of large information sets produces more robust signals. In the case of the

United States, where a large part of the economy is financed through bond

markets, Gilchrist and Zakrajcek (2011) show that a large number of

corporate spreads provide a good measure of financial conditions. In the

euro‐area, where the external financing of non‐financial corporations oper-

ates primarily via banks, information related to the corporate debt market is

likely to be insuf ficient. Indeed, other financial prices , related mainly to bank

lending (such as short‐and long‐term bank lending rates to households and

non‐financial corporations), are needed to capture financial conditions

adequately for the euro area. Furthermore, when conditions are tight,

information conveye d by financial quantities such as bank lending volumes

and equity issuance can also provide additional signals to identify shifts in

the supply of credit to the economy.

1

Combining these variables into a

1

Matheson (2012) and An gelopoulou et al. (2013) also highl ight the importance of quantities

in computing FCIs for the euro area.

298 Diego Moccero et al.

© 2014 John Wiley & Sons, Ltd.