FUTURE EURO AREA MEMBERSHIP OF BULGARIA IN TERMS OF THE BUSINESS CYCLE Head Assist. Prof. Ivan K. Todorov1, PhD Aleksandar D. Aleksandrov2, PhD Student Kalina L. Durova3, PhD Student Faculty of Economics, South-West University ‘N. Rilski’ – Blagoevgrad, Department of Finance and Accounting Abstract: In the present paper, vector autoregression (VAR) is used to assess the extent to which Bulgaria’s economic cycle is synchronized with the one of the euro area (EA). The main fiscal and monetary factors affecting the coordination of the business cycles of Bulgaria and the EA are identified. Recommendations for macroeconomic policies are formulated to support the synchronization of Bulgaria’s economic cycle with the one of the EA and to prepare our country for the adoption of the euro. Keywords: Bulgaria, membership, euro area, business cycles, synch- ronization. JEL: E32, E42, E50. * * * Introduction hirteen new Member States (NMS) joined the European Union (EU) during the last three enlargements in 2004, 2007, and 2013 – Poland, T the Czech Republic, Hungary, Slovakia, Slovenia, Lithuania, Latvia, Estonia, Malta, Cyprus, Bulgaria, Romania, and Croatia. Seven of the coun- tries were already members of the euro area (EA) – Slovenia, Malta, Cyprus, Slovakia, Estonia, Latvia, and Lithuania. The other six countries – Poland, the Czech Republic, Hungary, Romania, Bulgaria, and Croatia, in compliance 1 E-mail: [email protected] 2 E-mail: [email protected] 3 E-mail: [email protected] Economic Archive 4/2018 3 with the EU accession agreements signed by them, had to accept the single European currency after meeting certain requirements (the Maastricht conve- rgence criteria). Therefore, the question is not whether, rather when these six countries will become members of the EA. When assessing a country’s readiness for EA membership, it is advisable to use not only the Maastricht convergence criteria but also the criteria of the optimum currency area theory. Simultaneous use of the two sets of criteria helps to combine their strengths, avoid their weaknesses and get the most complete and credible assessment of the candidate countries’ prepa- redness for Economic and Monetary Union (EMU) membership. One of the most important criteria for the optimum currency area is the similarity between the economic cycles of participating countries. If these cycles are not synchronized, it is possible for the monetary union to be affected by asymmetric shocks. The presence of asymmetric shocks makes the common monetary policy ineffective as it has a pro-cyclical effect in coun- tries whose cycle is not converged with the overall currency area cycle. During an upswing, the common monetary policy creates inflationary ‘bub- bles’ and the danger of economy ‘overheating’, while in a period of downturn further exacerbates recession in countries with divergent economic cycles. It is not advisable for countries whose individual business cycles are not sufficiently correlated with the overall currency area cycle to join a monetary union. One of the reasons for the debt crisis in the EA is the insufficient synchronization of the economic cycles of peripheral countries with the over- all monetary union cycle. The present study aims to assess Bulgaria’s readiness for EA member- ship in terms of convergence of the Bulgarian business cycle with the aggre- gate EA cycle. To achieve this goal, the study will be structured as follows: • Empirical assessment of the degree of convergence of Bulgaria’s economic cycle with the overall EA cycle (section 1); • Identifying fiscal and monetary factors affecting the convergence of the Bulgarian cycle with the one of the EA (section 2); • Formulating recommendations for macroeconomic policies to support the synchronization of Bulgaria’s economic cycle with the one of the EA and to prepare our country for the adoption of the euro. (conclusion). In the present study, vector autoregression (VAR) methods and the Hodrick-Prescott filter are applied, and advisable macroeconomic policy options to stimulate the convergence of Bulgaria’ business cycle with the one of the EA are formulated. Quarterly seasonally adjusted Eurostat data are used for the period from the first quarter of 2000 to the fourth quarter of 2017. All indicators are calculated as a percentage of real Gross Domestic Product (GDP) except for the disruption in manufacturing, which is calculated as a 4 Economic Archive 4/2018 percentage of potential GDP. Potential output is estimated by using the Hod- rick-Prescott filter. Economic cycles of Bulgaria and the EA are dated and their phases (downturns and upswings) and positions (inflationary and defla- tionary shocks) are identified. The empirical assessment of the degree of convergence of the eco- nomic cycles of Bulgaria and the EA is carried out by the following four indicators: • Difference between disruption of GDP in Bulgaria and the disruption of the EA GDP; • Correlation coefficient between disruption of GDP in Bulgaria and the disruption of the EA GDP; • Percentage of convergent phases of Bulgaria’s business cycle and the one of the EA; • Percentage of convergent cyclical positions of Bulgaria and the EA. All variables are tested for stationarity. When it is found out that they are integrated of order one, tests are made for the optimal number of lags and for Johansen co-integration. The optimal number of lags is used in the Johansen test and later when creating vector autoregression. If the Johannes test demonstrates a co-integration relationship between the variables, a restric- ted vector autoregression, also known as Vector Error Correction (VEC), is applied. Otherwise unrestricted vector autoregression is used. Short-term cause-and-effect relationships between variables are ana- lyzed by Pairwise Granger Causality Tests, while long-term by Granger Causality/Block Exogeneity Wald Tests. Impulse Response graphs are drawn showing how the target variable (the difference between disruption in manu- facturing in Bulgaria and the EA) responds to fiscal and monetary shocks. Recommendations for macroeconomic policies are formulated to support the synchronization of Bulgaria’s business cycles with the ones of the EA and to prepare our country for the adoption of the euro. When selecting explanatory fiscal and monetary variables involved in vector autoregression, macroeconomic policy specifics under conditions of a currency board and a monetary union are taken into account. 1. Empirical assessment of the degree of convergence of Bulgaria’s economic cycle with the overall EA cycle Figure 1 shows the dynamics of the difference between disruption in manufacturing in Bulgaria and the EA, calculated as a percentage of potential GDP. The Hodrick-Prescott filter is used to determine the potential GDP of Bulgaria and the EA. Disruption in manufacturing is calculated by the following formula: Economic Archive 4/2018 5 (1) Disruption = (Real GDP – Potential GDP) *100 / Potential GDP 6 5 4 3 2 1 0 -1 2000Q1 2000Q4 2001Q3 2002Q2 2003Q1 2003Q4 2004Q3 2005Q2 2006Q1 2006Q4 2007Q3 2008Q2 2009Q1 2009Q4 2010Q3 2011Q2 2012Q1 2012Q4 2013Q3 2014Q2 2015Q1 2015Q4 2016Q3 2017Q2 -2 -3 Source: Calculations by the authors based on Eurostat data Figure 1. Dynamics of the difference between disruption in manufacturing in Bulgaria and the EA In the 2000-2009 period, there were serious differences between disruption in manufacturing in Bulgaria and the EA, exceeding 5% in the last quarter of 2008. In the 2010-2017 interval, these differences were reduced and rarely exceeded 1%, which implies a significant increase in the synchro- nization of Bulgaria’s business cycle with the one of the EA. The same conclusion can be drawn from the correlation coefficient between disruption in manufacturing in Bulgaria and in the EA. For the 2000- 2009 period, the coefficient was 0.60, increasing to 0.86 for the 2010-2017 period. Analysis of the dynamics of the disruption of GDP and the EA (see Figure 2) helps to determine the turning points (tops and bottoms), phases (upswings and downturns), and positions (inflationary and deflationary dis- ruptions) in their economic cycles. When determining the turning points, a rule is observed that there must be at least three and at most eight years between two tops (two bottoms). Phases between a top and a bottom are called downturns, while between a bottom and a top are called upswings. Positive disruptions in manufacturing are inflationary, while negative – deflationary. 6 Economic Archive 4/2018 6.00 5.00 4.00 3.00 2.00 1.00 0.00 -1.00 -2.00 2000Q1 2000Q4 2001Q3 2002Q2 2003Q1 2003Q4 2004Q3 2005Q2 2006Q1 2006Q4 2007Q3 2008Q2 2009Q1 2009Q4 2010Q3 2011Q2 2012Q1 2012Q4 2013Q3 2014Q2 2015Q1 2015Q4 2016Q3 2017Q2 -3.00 -4.00 Разрив_БгDisruption Bulgaria Разрив_ЕЗDisruption EA Source: Calculations by the authors based on Eurostat data Figure 2. Dynamics of disruptions in manufacturing in Bulgaria and the EA The turning points in the economic cycles of Bulgaria and the EA are shown in Tables 1 and 2. In the 2000-2009 period, the share of converging phases and positions in Bulgarian and the EA cycles was 62.5% and 67.5% respectively. In the 2010-2017 period, the share increased to 84.38% and 87.5% respectively, a fact confirming the strong convergence of the Bulgarian cycle with the one of the EA. Table 1 Turning points in Bulgaria’s business cycle Tops 2000 – 2008 – 2011 – 2017 – quarter 1 quarter 3 quarter 2 quarter 4 Bottoms 2003 – 2009 – 2014 – quarter 3 quarter 4 quarter 1 Source: Calculations by the authors based on