NEW CANDIDATES FOR THE EURO AREA? SIMILARITY OF SUPPLY AND DEMAND SHOCKS IN THE NON-EURO AREA COUNTRIES Stanislav Kappel 1 1 VSB-Technical Univesity of Ostrava, Faculty of Economics, Sokolská 33, 701 21 Ostrava Email:stanislav.kappel@vsb.cz Abstract: There are still countries of the European Union which are not in the Euro Area. There are nine countries in 2015. The purpose of this contribution is to find out, if there is any good candidate for a membership in the Euro Area. For this purpose we use structural vector autoregression model. We assume that supply shock has a permanent effect on output and demand shock has only a temporary effect on output. Moreover, both have a permanent effect of price level. The similarities of supply and demand shocks are compared in relation to the Euro Area as a whole and in relation to Germany. The analysed period is from the first quarter 1999 to the fourth quarter 2014. We find that according to the results we can claim that the best candidates are the United Kingdom, Croatia and Bulgaria for a membership in the Euro Area from analysed countries. Romania and Denmark have good results only either in the case of demand shocks (Romania) or in the case of supply shocks (Demark). The results in the rest analysed countries - in Poland, Hungary, the Czech Republic and Sweden are ambiguous. So we cannot say that these countries are appropriate for a membership in the Euro Area. Keywords: Economic Integration, Monetary Systems, Monetary Union, OCA Theory, Supply and Demand Shocks JEL classification: E32, E42, E52, F02 1. Introduction The Euro Area was created in 1999 and it has nineteen members now (in 2015). But the Euro Area has had many problems since the last economic crisis (there are especially still problems in Greece). On the contrary, the Euro Area accepts new members (Lithuania is the last, it entered to the Euro Area in 2015). On the other hand, the European Union consists of twenty eight member states (in 2015). It follows that all member states of the European Union are not part of the Euro Area. There are still nine countries which are not in the Euro Area. The question is: are there any appropriate candidates for a membership in the Euro Area? There are nine non-euro Area countries: Bulgaria, the Czech Republic, Denmark, Croatia, Hungary, Poland, Romania, Sweden and the United Kingdom. Only Denmark, Sweden and the United Kingdom were part of the European Union in 1999 when the Euro Area was created. From these countries Denmark and the United Kingdom have opt-out from the Euro Area (it is from the Maastricht Treaty). So they have not the duty to be part of the Euro Area. But Denmark is in a system of ERM II (European Exchange Rate Mechanism). On the other hand they can enter to the Euro Area if they will have this desire. All from the rest of the countries entered to the European Union after the creation of the Euro Area and they are obligated to enter to the Euro Area (including Sweden). So there is not the question if but when. The optimum currency area theory (OCA theory) is the most useful instrument for access if some country is or is not a good candidate for a membership in a monetary union. One of the substantial part of this theory is a question of symmetric and asymmetric shock. It follows that a similarity of supply and demand shocks is one of the crucial part of the optimum currency area (OCA) theory. The purpose of this contribution is to find out, according to the similarity of supply and demand shocks, whether there is any good candidate from non-euro area countries for a membership in the Euro Area. The similarities of supply and demand shocks are compared in relation to the Euro Area as a whole and in relation to Germany (as the strongest economy in the Euro Area). -266-
The remains of this contribution are as follows: The second part is literature review, methods and data are introduced in the third part. Results are in the fourth part, discussion in the fifth part. The last two sections are conclusion and literature. 2. Literature Review 2.1 Optimum Currency Area Theory A Canadian economist Robert Mundell is regarded as a father of the optimum currency area theory. Mundell (1961) is the first author, who researched the situation of asymmetric shocks in a monetary union. In his famous and pioneering article Theory of Optimum Currency Areas, he analyses a situation of an asymmetric shock and possibilities of an accommodation in two countries and in two regions. He claims that if shocks in two counties are asymmetric and there is no mobility of production factors (especially labour), it will be better to use a flexible exchange rate between these countries. He concludes that for some countries or regions it is more appropriate to retain their own currency because according to Mundell, the world is no an optimum currency area. Mongelli (2002) claims that if the incidence of demand and supply shock is similar across countries in a monetary union, then the benefit from a single currency is higher than the need for policy autonomy. In sixties, another two criteria have been added. The degree of economic openness (McKinnon, 1963) and the degree of diversification of consumption and production (Kenen, 1969). Except these three criteria, there are others: business cycle synchronization, price and wage flexibility, financial market integration, similarities of inflation rates, fiscal integration and political integration 1. 2.2 Supply and Demand Shocks As noted above, the similarity of supply and demand shocks is a crucial condition for creating a monetary union or for joining to a monetary union. Bayoumi and Eichengreen (1993) estimate similarity of supply and demand shocks. They follow up on Blanchard and Quah (1989). All authors use a vector autoregression model and two variables. Blanchard and Quah (1989) use GNP and unemployment while Bayoumi and Eichengreen use inflation instead of unemployment. This approach is used by most authors, also for non-euro Area countries, e.g. Frenkel, Nickel and Schmidt (1999) or Babetski, Boone and Maurel (2006). Frenkel, Nickel and Schmidt (1999) examine the Euro Area countries, non-euro Area countries, EFTA countries and Central and Eastern European countries (CEECs) from 1992q1 to 1998q2. They find the highest differences of supply and demand shocks in CEECs. Babetski, Boone and Maurel (2006) claim on quarterly data from 1990 to 2002 that demand shocks converge more than supply shocks in CEECs. Fidrmuc and Korhonen (2006) offer an interesting view in this area. They make a meta-analysis of thirty five publications which they analyse correlation of business cycle between the Euro Area and the Central and Eastern European countries (CEECs). They find a significance influence of methodology on correlation coefficients. Frankel and Rose (1996) stress the endogenity of the OCA criteria. They find a relationship between intraindustry trade and correlation of business cycles and the consequent symmetry of supply and demand shocks 2. The countries, which are longer in a monetary union, should have more synchronized business cycle. 1 For the development of the OCA theory, see Dellas and Tavlas (2009). 2 The European Commission has a similar view, EC (1990). In opposite, the different point of view has Krugman (1993) in his theory of specialization. -267-
3. Methods and Data We use two methods; correlation and structural vector autoregression model. The first method is correlation. We use a Pearson correlation coefficient. The Pearson correlation coefficient ( is formally expressed as: (1) Correlation between two variables is a measure how well the variables are related. We use the method of correlation to assess if the countries have or does not have similar supply and demand shocks. According to de Grauwe (2014) we could take as a measure of similarity (or symmetry) the correlation coefficient between two countries. If the correlation coefficient is 1, the measure of similarity (symmetry) is 1. On the contrary, if the correlation coefficient is -1, the measure of similarity (symmetry) is 0 (i.e. its minimum value). The second method is the structural vector autoregression model. Our research is based on Bayoumni and Eichengreen (1993). The join process of the variable GDP and price can be written as an infinite moving average representation of supply and demand shocks: when represents a vector of differences of logarithm of output and prices, is a lag operator, are matrices and is a vector of supply and demand shocks. We must introduce one condition: -268- (2). (3) It is assumed that demand shock has not an effect on output in the long run. It means that demand shock has only a temporary effect on output. On the contrary, supply shock has a permanent effect on output. Moreover, both have a permanent effect on a price level. The other assumptions are: orthogonality of supply and demand shocks and normalizing variances of shocks. Data (GDPs and prices (HICP)) are obtained from database of Eurostat (2015). The research period is based on quarter observations from the first quarter 1999 to the fourth quarter 2014. Data are available only from the third quarter 2002 for Poland and from the second quarter 2001 for Bulgaria and Croatia. The data are logarimized in the case of GDP and differentiated in both variables. Tests of stationarity of time series conducted using ADF (Augmented Dickey-Fuller test). In all cases stationarity of time series of variables are confirmed. The estimation of the number of VAR lags is made by sequential modified LR test statistic, Akaike information criterion, Schwarz information criterion and Hannan-Quinn information criterion. The lags of VAR models are four periods. The exceptions are Germany, Poland and the Euro Area as a whole (one period) and Sweden (five period). As mentioned above, the analysed states are the non-euro Area countries. There are: Bulgaria (BG), the Czech Republic (CZ), Denmark (DK), Croatia (HR), Hungary (HU), Poland (PL), Romania (RO), Sweden (SE) and the United Kingdom (UK). We analyse also Germany (DE) and the Euro Area as a whole (EA) for a comparison. 4. Results Empirical results are introduced in this part. In the first part of this chapter, the similarities of demand shocks are showed in Table 1, than there are similarities of supply shocks in the second part in Table
2 and a comparison is in the third part. The similarities are expressed according to correlation coefficients. The comparison is expressed in two figures in which are the correlation coefficients in relation to Germany and in relation to the Euro Area as a whole. The last part of this section deals with a table. In the Table 3, there are ranking of the Non-Euro Area countries in relation to the Euro Area as a whole and Germany. 4.1 Demand Shocks In following Table 1, there are results for correlation of demand shocks in selected countries. The order of the countries is in alphabetical order and the Euro Area as a whole and Germany are bold for better orientation. Table 1. Correlation of Demand Shocks of Non-Euro Area Countries BG CZ DE DK EA HR HU PL RO SE UK BG 1 CZ 0.02 1 DE 0.34 ** 0.03 1 DK 0.16 0.07 0.17 1 EA 0.40 *** 0.16 0.77 *** 0.10 1 HR 0.23 * 0.10 0.43 *** 0.22 0.33 ** 1 HU 0.10-0.02 0.21 0.00 0.28 ** 0.41 *** 1 PL 0.02 0.26 * -0.05 0.01 0.14-0.13 0.15 1 RO 0.22 0.03 0.48 *** 0.13 0.36 *** 0.32 ** 0.14-0.19 1 SE 0.27 ** 0.13 0.33 ** 0.34 *** 0.18 0.32 ** -0.01 0.01 0.45 *** 1 UK 0.21-0.01 0.42 *** 0.10 0.35 *** 0.46 *** 0.31 ** 0.05 0.14 0.23 * 1 Note: Data were available only from 2002q3 for Poland and from 2001q2 for Bulgaria and Croatia; *, **, *** is 10%, 5% resp. 1% statistical significance. Source: Eurostat (2015), author s calculations According to the Table 1 we can see that the highest similarity (the highest correlation coefficient) of demand shock has Germany. But, we assess the non-euro Area countries. Moreover, Germany is substantial part of the Euro Area (the biggest). It means that the result can be biased in the case of Germany. From the non-euro Area countries Bulgaria (0.40) has the highest correlation coefficient in relation to the Euro Area as a whole. In opposite, the lowest value is in the case of Denmark (0.10). It is interesting because Denmark is in ERM II and it is the country which has been already in the European Union in 1999 when the Euro Area was created. And Denmark entered the European Union in 1973. Also Sweden has low correlation coefficient (0.18) as an old country of the European Union. Sweden became a member of the European Union in 1995. On the contrary, the United Kingdom has high correlation coefficient (0.35) in comparison with analysed countries. High correlation have also Romania and Croatia (except Bulgaria) from the new EU countries. It is quite surprisingly because these countries entered the European Union as the last ones. Croatia became even the part of the European Union in 2013. Low correlations have Poland and the Czech Republic from the new EU countries. In relation to Germany, the results are similar. The highest correlation have Bulgaria (0.34), Romania (0.48), Croatia (0.43) and the United Kingdom (0.42), again. Moreover, Sweden (0.33) has high correlation (definitely in comparison with the Euro Area). In opposite, Poland, the Czech Republic and Denmark has the lowest correlations. Poland has the correlation coefficient close to zero (-0.05). -269-
The correlation coefficients between other countries are low with some exceptions (for example Denmark with Sweden, Croatia with the most of the countries). Next part deals with the results of similarity of supply shock. 4.2 Supply Shocks This subchapter deals with results in the case of supply shocks. Again, the order of the countries is in alphabetical order and the Euro Area as a whole and Germany are bold for better orientation. Table 2. Correlation of Supply Shocks of Non-Euro Area Countries BG CZ DE DK EA HR HU PL RO SE UK BG 1 CZ 0.41 *** 1 DE 0.45 *** 0.38 *** 1 DK 0.25 * 0.33 ** 0.39 *** 1 EA 0.46 *** 0.34 *** 0.82 *** 0.58 *** 1 HR 0.48 *** 0.29 ** 0.48 *** 0.47 *** 0.50 *** 1 HU 0.20 0.39 *** 0.14 0.21 0.20 0.29 ** 1 PL 0.00 0.19 0.11 0.09 0.13-0.01 0.25 1 RO 0.15 0.02 0.06 0.18 0.11 0.11 0.13-0.03 1 SE 0.24 * 0.28 ** 0.37 *** 0.44 *** 0.37 *** 0.25 * 0.16-0.05 0.19 1 UK 0.19 0.27 ** 0.45 *** 0.47 *** 0.51 *** 0.37 *** 0.28 0.07-0.14 0.37 *** 1 Note: Data were available only from 2002q3 for Poland and from 2001q2 for Bulgaria and Croatia; *, **, *** is 10%, 5% resp. 1% statistical significance. Source: Eurostat (2015), author s calculations In comparison with demand shocks we can see that the correlation coefficients are generally higher. Again, the highest similarity (the highest correlation coefficient) of demand shock has Germany in relation to the Euro Area as a whole. The highest correlations from the non-euro Area countries have Denmark (0.58), Croatia (0.50), Bulgaria (0.46) and the United Kingdom (0.51) in relation to the Euro Area as a whole. Sweden has correlation 0.37 as the old country of the European Union. In opposite, the lowest correlations have Romania (0.11), Poland (0.13) and Hungary (0.20). The remaining country the Czech Republic has correlation 0.34. The result are similar in relation to Germany, again. The exception is Denmark. Denmark has lower correlation (0.39). The correlation coefficients between other countries are generally lower than in relation to the Euro Area as a whole and in relation to Germany (with some exceptions). 4.3 Comparison This section shows two figures (Figure 1 and Figure 2) and a ranking (Table 3) of analysed countries in relation to the Euro Area as a whole and in relation to Germany. In Figure 1 there are similarities of demand shocks in relation to Germany and the Euro Area as a whole in graphical form. In Figure 2 there are similarities of supply shocks. Table 3 is a summary table of the results. -270-
Figure 1: Similarity of Demand Shocks in relation to Germany and the Euro Area EA 0,45 0,40 BG 0,35 UK RO 0,30 HU HR 0,25 0,20 0,15 PL CZ SE 0,10 DK 0,05 0,00-0,10 0,00 0,10 0,20 0,30 0,40 0,50 0,60 DE Source: Eurostat (2015), author s calculation We can see that the highest similarity have Romania, the United Kingdom, Croatia and Bulgaria in relation to the Euro Area as a whole and in relation to Germany. Sweden has one of the highest similarity in relation to Germany but lower in relation to the Euro Area as a whole. Hungary is in a reverse situation higher similarity in relation to the Euro Area as a whole and lower similarity in relation to Germany. On the opposite side of the figure there are Poland, the Czech Republic and Denmark. Poland is the only country which have the negative (but almost zero) similarity. It is with Germany. On the other hand, Denmark has the lowest correlation coefficient in relation to the Euro Area. In the next figure 2, there are introduced the same results but in the case of similarity of supply shocks. Figure 2: Similarity of Supply Shocks in relation to Germany and the Euro Area -271-
0,70 EA 0,60 0,50 0,40 0,30 RO CZ DK UK BG HR 0,20 0,10 RO PL HU 0,00 0,00 0,10 0,20 0,30 0,40 0,50 0,60 DE Source: Eurostat (2015), author s calculation There are two groups of countries in Figure 2. Romania, Poland and Hungary are on the left side of the figure. The similarity of supply shocks are low both in relation to the Euro Area and to Germany. On the right side of the Figure 2 (higher similarities), the lowest similarity have Sweden and the Czech Republic. The highest similarity have Croatia, the United Kingdom, Bulgaria and Denmark. On the other hand, Denmark has the highest similarity with the Euro Area but lower with Germany. The ranking of similarity of demand and supply shocks is introduced in Table 3. Table 3: Ranking of the Non-Euro Area Countries in Relation to the Euro Area and Germany Country Demand Shock Supply Shock Euro Area Germany Euro Area Germany Bulgaria 1. 4. 4. 2. - 3. Czech Republic 7. 8. 6. 5. Denmark 9. 7. 1. 4. Croatia 4. 2. 3. 1. Hungary 5. 6. 7. 7. Poland 8. 9. 8. 8. Romania 2. 1. 9. 9. Sweden 6. 5. 5. 6. United Kingdom 3. 3. 2. 2. - 3. Source: Eurostat (2015), author s calculation We can see that the ranking is similar both in the case of the Euro Area as a whole and in the case of Germany in demand shocks. Bulgaria has only greater differences in relation to the Euro Area as a whole and Germany (first and fourth). The best ranking have Bulgaria, Romania, Croatia and the United Kingdom, the worst have Denmark, Poland and the Czech Republic. The Spearman rank correlation coefficient is 0.82 (at 1% level of statistical significance) in the case of demand shocks. In means that the results are very similar in relation to the Euro Area as a whole and to Germany. The results are similar with some exceptions in the case of supply shocks. There are differences especially in Denmark and Romania unlike to demand shocks. Denmark has higher ranking (in relation to the Euro Area). In opposite, Romania has worse ranking. The best results have just Denmark, Croatia, the United Kingdom or Bulgaria. The worst results have just Romania, Poland or Hungary. The Spearman rank correlation coefficient is 0.85 (at 1% level of statistical significance). -272-
This high value indicates similar results in relation to the Euro Area as a whole and to Germany in the case of supply shocks. 5. Conclusion The purpose of this contribution was to find out, according to the similarity of supply and demand shocks, if there is any good candidate for a membership in the Euro Area. According to the results we can claim that the best candidates are the United Kingdom, Croatia and Bulgaria for the membership in the Euro Area. But there are some political reasons, in the case of the United Kingdom, why this country is not a part of the Euro Area. The United Kingdom has an opt-out from the membership in the Euro Area. The British people do not want to be a part of the Euro Area and the United Kingdom has also a negative experience with fixed exchange rates from the early of nineties when the United Kingdom was in European Exchange rate mechanism. The reason why Bulgaria has so high correlations can be caused that Bulgaria has a currency board and their currency is fixed to euro. Croatia has a central bank but its currency is also fixed to euro. Also these countries are willing to join to the Euro Area. Romania and Denmark have good results only either in the case demand shocks or in the case of supply shocks. Romania has the second highest similarity of demand shocks with the Euro Area but the lowest in the case of supply shocks from the analysed countries. The situation of Denmark is reversed. Denmark has the highest similarity with the Euro Area in the case of supply shocks and the worse in the case of demand shocks. The results in the rest of the analysed countries - in Poland, Hungary and the Czech Republic and Sweden are ambiguous. So we cannot claim that these countries are appropriate for a membership in the Euro Area. This paper was financially supported within the VŠB - Technical University SGS grant project No. SP2015/115 Institutional and Monetary Context of Economic Integration of European Countries Today. References [1] Babetskii, I., Boone, L., Maurel, M., 2004. Exchange Rate Regimes and Shocks Asymmetry: The Case of the Accession Countries. Journal of Comparative Economics, vol. 32, issue 2, pp. 212-229. [2] Bayoumi, T., Eichengreen, B., 1993. Shocking Aspects of European Monetary Integration. In: Adjustment and Growth in the European Monetary Union. Cambridge: Cambridge University Press, pp. 241 261. [3] Blanchard, O. J., Quah, D., 1989. The Dynamics Effects of Aggregate Demand and Supply Disturbance. American Economic Review, vol. 79, issue 4, pp. 655 673. [4] Dědek, O., 2008. Historie evropské měnové integrace. Od národních měn k euru. Praha: C. H. Beck. [5] Dellas, H., Tavlas, G., 2009. An Optimum-Currency-Area Odyssey. Journal of International Money and Finance, vol. 28, issue 7, pp. 1117-1137. -273-
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