The role of global financial conditions for credit supply in EMU periphery countries

ABSTRACT

The article analyses the role of global financial conditions for credit supply and growth performance in individual member states of the European Monetary Union (EMU). In line with the risk-taking channel of monetary policy, we find that in the short run, the Fed and European Central Bank (ECB) interest rate policy compensate for changes in global risk assessment thereby supporting net private credit flows to the European periphery. However, in later periods, a worsened risk sentiment weighs on credit flows to these countries. In contrast, EMU core countries are generally less affected by global financial shocks. This asymmetric influence of global conditions on EMU member states are smoothed by the uniform access of commercial banks to the Eurosystem’s open market operations in conjunction with the redistribution of liquidity via the TARGET mechanism.

KEYWORDS:

• European monetary union
• credit flows
• global financial cycle
• risk-taking channel

JEL CLASSIFICATION:

• F32
• F36
• F45

Acknowledgment

We thank Georg Stadtmann, Ulrich Grosch and Annalee McWilliams for valuable comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ In addition to changes in TARGET balances with the ECB, this item also includes capital inflows from official assistance. Both variables are measured relative to domestic GDP.

² We use nonseasonally adjusted time series to prevent estimated coefficients from potential biases. However, results remain qualitatively the same when applying seasonally adjusted time series.

³ The spill-over estimates are very similar using alternative orderings. See Bruno and Shin (2015) for a detailed discussion on this.

⁴ We use the panel unit root test outlined by Im, Pesaran, and Shin (2003) and the Fisher PP and ADF tests described by Maddala and Wu (1999).

⁵ The 66% confidence intervals correspond approximately to ±1 SD, which is a standard choice in VAR analyses; see Sims and Zha (1999) and Stock and Watson (2001).

⁶ The corresponding F-statistics are F_28,440(npr) = 2.16; F_28,440(targ) = 2.06; F_28,440(cred) = 0.27; F_28,440(gdp) = 1.59.