Prior to unification, some suggested that sacrificing monetary autonomy would prevent adjustment to country-specific shocks (Bayoumi and Eichengreen 1992), as a unique monetary policy would be unable to address idiosyncratic economic fluctuations. Others questioned just how independent the ECB would be from political institutions (Alesina and Grilli 1991). This debate furthered during the financial and sovereign debt crises, which impacted member states differently, highlighting the possible benefit of specific policy responses. In addition, a discussion concerning the transparency of the decision-making process within the euro area has come to the fore (Caporale and Cipollini 2002), with rising Euroscepticism and a sharp decline in trust in the ECB placing further pressure on European institutions (Bergbauer et al. 2019, Roth and Jonung 2019).

The persistence of potential asymmetries in the euro area and the need for transparency in the decision-making process of policy enactment gain prominence in light of the recent discussions concerning the need for a centralised fiscal capacity in the Economic and Monetary Union (EMU). Hence, steps toward assessing just how the differing interests of euro area countries are considered and further examining the nature of policy decisions can promote transparency and institutional development.

In our recent paper (Pereira and Tavares 2019), we provide evidence to this debate by extracting the implicit country-specific weights in the ECB’s conventional monetary policy conduct over the period 1999-2016. Country-specific weights are computed using a measure based on the difference between the ECB’s reference interest rate and an estimated counterfactual interest rate for each of the EMU11. To obtain the counterfactual interest rates in each quarter, we model national central banks’ reaction functions to estimate how they would have likely responded to post-euro macroeconomic fundamentals had their behaviour mimicked their pre-euro response functions. Departing from the seminal contribution on monetary policy rules by Clarida et al. (1998), we consider five different Taylor rule specifications. 

Counterfactual interest rates: One policy, many stories

The first result is summarised in Figure 1, where the actual and the five distinct counterfactual interest rate paths are presented. The sample of countries can be approximately divided into two groups: countries where counterfactual estimates track actual interest rates closely, and countries where the opposite holds. The first group comprises Germany, the Netherlands, Austria, Belgium, France, and Spain. Other countries, including Finland, Ireland, Italy, Portugal, and, most significantly, Greece, see a marked decoupling between estimated counterfactual interest rates and the actual rate. The magnitude and frequency of deviations between the two rates is reflected in the country-specific weights.

Figure 1 Actual and counterfactual interest rate paths (%)

Source: Pereira and Tavares (2019). 
Notes: The counterfactual interest rate paths correspond to the estimated series using each of the five different reaction functions based on different types of Taylor rules. 

Implicit country weights

Using the counterfactual interest rate paths, we compute country-specific weights for the pre-crisis (1999-2009) and the post-crisis period (2010-2016). Figure 2 shows the average pre-crisis and post-crisis weight for each country, the maximum-minimum range of weight estimates and population, GDP, and equal size lines which represent the weight each member state would receive according to those indicators. Analysing the results across different estimation procedures, Germany, closely followed by the Netherlands, Belgium, and Spain, are attributed the largest policy weights in the ECB’s interest rate setting, whereas Greece, Ireland, Portugal, and Italy systematically secure smaller weights. After the financial crisis, most countries lose weight to the benefit of Spain, Belgium, and the Netherlands. Noticeably, Germany’s centrality to policymaking wanes somewhat during the crisis. Our results can stem from the severity of the crisis for Southern European countries, which, with the exception of Spain, diverge from the path of Germany and other countries.

Figure 2 Average weight and maximum-minimum range of weight estimates (%)

Source: Pereira and Tavares (2019). 
Notes: The average weight estimate consists of the average of the five different implicit weight estimates, whereas the maximum-minimum range corresponds to the maximum and minimum weights of those estimated. The population and GDP series presented consist of the country-specific averages from 2010 to 2016. 

Adding economic integration

A much-debated feature of monetary unification is the potential feedback loop between the sharing of a common currency and the synchronisation of underlying economic shocks. Hence, we examine the extent to which country-specific weights may reflect the degree of real integration with Germany, the euro area’s largest economy and the country perceived as the anchor for the ECB’s decision-making (Beyer et al. 2008). Figure 3 compares the average country weights with two measures of economic integration: the synchronisation of member states’ and Germany’s output gaps and supply shocks. 

For the entire period, we observe that implicit weights are positively associated with greater correlation of output gaps and supply shocks between member states and Germany. In the period of 1999-2009, output gaps across the euro area became considerably more correlated with Germany’s, with the exception of Greece. This pattern partially reverts in the period of 2010-2016, i.e. after the crisis, more noticeably for Greece, Ireland, Portugal, and Spain, precisely the countries with smaller weights. Analysing aggregate disturbances, supply shocks become asymmetric for Greece and Ireland after the crisis, and integration with Germany experiences a slight decrease for all of the other countries. 

Figure 3 Average country weights and output gap (top) and supply shocks’ (bottom) synchronisation with Germany (%)

Notes: Output gaps were obtained using a Hodrick-Prescott filter (λ = 1600) on quarterly GDP and supply shocks using a Blanchard and Quah (1989) decomposition, as adapted by Bayoumi and Eichengreen (1992).
Source: Pereira and Tavares (2019). 

Towards risk-sharing and further integration

In summary, our findings are threefold: 

• First, countries’ implicit weights are not strongly correlated with a member state’s economic or population size. Germany and France receive large weights that are considerably below their shares of output and population in the euro area. 
• Second, across different specifications, countries receiving greater weights are Germany, Belgium, and the Netherlands, with Greece and Ireland, closely followed by Portugal and Italy, securing the smallest. 
• Third, countries receiving smaller weights are those whose output gaps and supply shocks reveal a lower correlation vis-à-vis Germany’s.

The euro area is arguably the most important monetary policy experience ever, and the ECB’s policymaking suffers frequent criticism regarding the perceived imbalances insofar as countries’ economic fundamentals are taken into account differently. Our estimates suggest that such concerns over asymmetry do not follow from the obtained weights when compared to countries’ economic and population sizes as a share of the EMU11. In sum, our results suggest that the different implicit country weights obtained from the ECB’s behaviour do not differ to a degree that constitutes a serious political liability to the future of European institutions. However, special consideration of smaller countries’ idiosyncratic circumstances, such as those arising in the wake of the sovereign debt crisis, are strongly advised. Given the beheld disparities, policies can be implemented either to increase the symmetry between countries through long-term approaches, or to smooth the response of asymmetric shocks through short-term and medium-term procedures. Regarding the former, a much-debated response are structural reforms, which can increase countries’ resilience to shocks (Draghi 2017) and have the potential of boosting integration. Concerning the latter, risk-sharing and fiscal insurance mechanisms at the euro area level have been proposed to promote income stabilisation when certain members face asymmetric disturbances. 

References

Alesina, A and V Grilli (1991), “The European Central Bank: Reshaping Monetary Politics in Europe”, Technical report, National Bureau of Economic Research.

Bayoumi, T and B Eichengreen (1992), “Shocking Aspects of European Monetary Unification”, Technical report, National Bureau of Economic Research.

Bergbauer, S, J-F Jamet, E Persson and N Hernborg (2019), “The Reputation of the Euro and the ECB: Interlinked or Disconnected?“, Paper presented at the EUSA conference. 

Blanchard, O J and D Quah (1989), “The Dynamic Effects of Aggregate Demand and Supply Disturbances”, American Economic Review 79(4): 655–673.

Beyer, A, V Gaspar, C Gerberding and O Issing (2008), “Opting out of the Great Inflation: German monetary policy after the break down of Bretton Woods”, Technical report, National Bureau of Economic Research.

Caporale, G M and A Cipollini (2002), “The euro and monetary policy transparency”, Eastern Economic Journal 28(1): 59–70.

Clarida, R, J Galí and M Gertler (1998), “Monetary Policy Rules in Practice: Some International Evidence”, European Economic Review 42: 1033–1067.

Draghi, M (2017), “Structural reforms in the euro area”, ECB Conference, Frankfurt am Main.

Pereira, M and J Tavares (2019), “Extracting Implicit Country Weights from ECB’s Monetary Policy”, CEPR Discussion Paper No. DP14090.

Roth, F and L Jonung (2019), “Public support for the euro and trust in the ECB: The first two decades”, VoxEU.org, 13 December.