Does Bulgaria exhibit signs of contagion coming from the Eurozone?

This paper examines factors that lead to financial contagion and what makes a country with a fixed exchange rate or a currency peg even more vulnerable to contagious effects. More specifically, this paper tests whether Bulgaria, a small open East European economy, a member of the European Union (EU), with a fixed exchange rate to the euro, exhibits signs of contagion coming from the Eurozone. The empirical approach uses the Bulgarian stock market index and the EUROSTOXX50 index to proxy the Eurozone financial markets. In a vector error-correction model and a GARCH framework, it is shown that the Bulgarian stock market was contagious during the Global Financial Crisis as well as during the following European Sovereign Debt Crisis. Some further evidence of contagion is shown in terms of trade and foreign direct investment. The result can be attributed to the strong financial linkages the country has with the EU and the Eurozone, and the repercussions of the country’s inability of macroeconomic adjustment through its exchange rate.

1. Introduction

There are undoubtedly many benefits for a country to become a member of the European Union (EU) and the European Monetary Union (EMU), but there are costs to it as well, especially during an economic crisis. The higher integration and interdependence within a currency union leads to strong financial linkages between countries, which in turn makes these countries highly susceptible to potential negative shocks coming from the rest of the currency area. In addition, the lack of sovereign monetary policy, an independent central bank, and control over exchange rate policy makes countries that are members of a currency union even more prone to contagion effects. These linkages affect financial markets and might diminish the portfolio diversification benefits for international investors. These effects apply as well to countries with a fixed exchange rate. In order to maintain the peg, the monetary authority has to follow the interest rate set by the country to which the currency is pegged. One such country is Bulgaria, which has maintained a currency board and has its currency, the lev, fixed to the euro.

As more emerging countries in East Europe similar to Bulgaria make efforts to join the EU and potentially the EMU, integration between those countries and the financial markets in the EMU is growing. This dynamic has been of interest to scholars. Several studies have examined financial contagion effects in emerging markets in Europe and worldwide during the Global Financial Crisis (GFC) and the following European Sovereign Debt Crisis (ESDC). A limited number of papers have studied the transmissions of shocks and financial market contagion from West Europe and the EMU to East Europe. These papers, however, have not focused specifically on Bulgaria, but rather have examined the region in general and how its financial markets were affected during various periods between 2008 and 2015. These papers have not focused on contagion in countries with fixed exchange rates. Moreover, there has not been a consensus in their evaluation of the transmissions of shocks from the Eurozone to East Europe, and more precisely, to Bulgaria.

Bulgaria provides an interesting case for financial contagion in terms of its monetary regime and a unique status as a member of the European Union. Even though the country has not introduced the euro, it is very closely integrated with the EU and the EMU because Bulgaria has had a fixed exchange rate – first to the German mark and then to the euro – since 1997. Thus, the country has developed strong economic linkages to the EU and the Eurozone in terms of trade, banking, foreign direct investment, and financial markets. In fact, the country was ready to join the currency area in 2012, and had met all necessary criteria, but it has since halted its efforts to do so.

The objective of this paper is to examine the correlation between the Eurozone and the Bulgarian stock markets and to determine whether the Bulgarian financial market, as well as the Bulgarian economy, were contagious during the most recent financial turbulences. This paper will contribute to the literature on emerging markets and financial contagion by focusing solely on Bulgaria’s financial market before, during, and after the Global Financial crisis and the European Sovereign Debt crisis. The paper will also examine the macroeconomic factors that might be contributing to contagion in the Bulgarian financial markets, and try to draw implications for whether joining of a monetary union, proxied by a fixed exchange rate to the euro, exacerbates or mitigates financial contagion during crises. This paper will use the definition of contagion that it is the transmission of shocks from one country, market, or institution to another, or a group thereof, but that is not related to fundamentals (Pritsker, 2000).

To develop a strong analysis of the dynamics of the Eurozone market, proxied by the EUROSTOXX50 index and the Bulgarian stock market and economy, the paper estimates a vector error-correction model and a GARCH model, and shows the dynamic conditional correlations (DCCs) between the EMU and the Bulgarian stock markets. The paper tests the statistical significance of the dynamics between the two markets during the GFC and the ESDC using appropriate dummy variables and constructs interaction terms. A significant increase in the stock market correlations during the two crisis periods would indicate contagion effects through changes in investors’ risk aversion. The results of the empirical tests do show contagion effects in the Bulgarian markets. The paper presents further evidence of the propagation of shocks to the Bulgarian economy through trade and the country’s foreign assets and liabilities.

The remainder of this paper is organized in the following way: Section 2 highlights the importance of the topic and expands on the subject of financial contagion. Section 3 presents some of the most recent and relevant literature on the topic. Section 4 and Section 5 present the data, methodology, and empirical results, and section 6 provides some further data to support the research question.

2. The Importance of Financial Contagion

Studying and understanding financial contagion is important for several reasons. This topic of research has implications for economic activity, financial integration and financial markets, and policy.

The EMU is very large. It is comprised of 28 member countries, with more preparing to join the European Union and subsequently join the currency area. Additionally, all member states not part of the currency area are expected to join the area, with the special opt-out cases for the UK and Denmark. A spread of a crisis or a shock within such a large area could have global repercussions because of the huge role the EMU plays in the world economy. For instance, in 2011, the Eurozone accounted for about one fifth of the global output. Its share of world trade is large, and it has one of the world’s largest financial sectors – with the euro being one of the world’s most important reserve currencies. The Eurozone is closely linked to the rest of the world, especially through some of the channels of contagion described such as trade, banking, and financial markets. Thus, a crisis within the currency area would not only affect its member countries, but it would have a global scope. All of this might have repercussions for international investors holding emerging markets assets as well.

Financial contagion impacts financial markets and is crucial for investors and portfolio diversification. The extent to which such markets are affected by economic downturns can provide useful information for optimal asset allocation and efficiency. In the case of the Eurozone, there are several emerging markets that are members of the European Union, some of which have adopted the common currency, some of which are expected to adopt the euro, and some emerging economies that are non-members applying for membership into the union and potentially the Eurozone. The more integrated these emerging economies’ financial markets become with the currency area, the higher the risks for portfolio diversification by both domestic and international investors.

Understanding financial contagion has important implications for policy as the Eurozone is expanding. Whether considering policy on a local level or on a shared institutional level, policy makers need to be aware of how prone their member countries are to contagion. This will help design policies to alleviate potential risks or mitigate contagion when it has already occurred.

Financial contagion and the propagation of shocks happens through channels such as trade, the banking sector, reevaluation of risks (as in the case of potential bailouts), and the financial markets through investors’ portfolio choices (Forbes, 2012). Other than these channels, what is unique for a currency union is that there is the lack of sovereign monetary policy and an independent central bank. Not having independent monetary policy reduces the ability of a country to utilize it to stabilize the economy in case of a crisis or a boom. What a country is left with instead is fiscal policy. However, fiscal policy might not work either, because of the fiscal discipline rules that a country should adhere to as a member of the Eurozone. Such a country loses the central bank as a lender of last resort to provide liquidity in case of bank runs, and it could lose competitiveness in its external sector as it gives up exchange rate policy. The same considerations apply to countries with fixed exchange rates. For smaller countries and emerging economies, joining a currency union can seem like a panacea for many economic issues. These countries see a lot of benefits to becoming part of the EU and the Eurozone such as gains from trade, foreign direct investment, remittances, and aid flows. However, governments should be wary, because in economic downturns the negative effects of crisis propagation might outweigh the benefits of a monetary union membership. Governments should adopt policies that shield their economies from negative shocks and even design policies that could prevent the spread of a shock at the inception of a crisis in another country.

Moreover, there is the increased integration of financial market returns due to no exchange rate risk. Joining a monetary union or a fixed exchange rate could benefit financial markets, but it could also have negative consequences on market participants’ behavior and investment in an investor’s home country. There are two effects discussed in the literature on the financial markets because of currency union participation. On one hand, having a common currency removes the so-called exchange rate risk. Since the exchange rate is very important for determining portfolio composition and allocation, fluctuations in the exchange rate create risk for an agent who wants to invest abroad and could increase transaction costs. In a currency union and in the case of a pegged exchange rate, there is no currency exchange. Thus, a fixed rate reduces the volatility of assets. This serves to increase the mean-variance efficiency of investors’ portfolios. On the other hand, however, joining a currency union leads to more integrated financial markets of the member countries. Higher co-movements of the financial markets with the markets in the Eurozone means higher correlation of portfolio returns in the domestic country and the EMU market. The smaller the amount of assets an investor can choose from, the smaller the diversification benefits of a portfolio.

3. Literature Review

Some channels thorough which shocks are transmitted include the banking sector and trade linkages between countries. Bonin (2010) looks at the question of whether a foreign-owned bank benefits the host country during a crisis period and the potential for financial contagion via bank lending. The study examines the so-called European countries in transition such as Poland, Czech Republic, Hungary, Slovakia, Slovenia, Bulgaria, Croatia, Romania, Serbia, and Russia. In the early 1990s, after the change of the Communist regimes in these countries, foreign banks took part in government efforts to privatize the state-owned banks. These foreign banks have a dominant part in the banking sector in the countries. The author evaluates the likely contagion through bank-lending as a result of the response of foreign-owned banks to the financial crisis in 2008. In five of the countries the top five banks are foreign-owned, while in another three countries the top four banks are foreign-owned. The paper finds evidence for a credit squeeze in corporate lending in 2008 of about half of the banks’ lending in 2007 as well as a dramatic decrease in household lending in 2008 compared to 2007. Despite this decline in lending, parent banks seemed to have maintained their commitment to lending. The author finds that the banks were not the major determinant of the contracted economies in the countries in transition.

Authors have also studied the factors affecting the transmission of shocks and factors facilitating recovery from such shocks in East European countries with fixed versus floating exchange rates. A paper by Petrevski, Bogoev, and Tevdovski (2014) explores the transmission of shocks from the Eurozone to three South European Economies – Croatia, Macedonia, and Bulgaria. They explore the effects of fiscal and monetary policy changes in the foreign countries on these economies, primarily because they are small open economies with very rigid exchange rates. The study uses a recursive vector autoregressive (VAR) methodology to examine how foreign shocks translate into the economies of the three countries. The paper finds that foreign shocks are transmitted quickly. The more integrated they are with the EU, the stronger the effects of foreign policy changes on the three countries, especially in terms of trade. The authors find that financial integration plays a crucial role as domestic banks are highly dependent on foreign financing, as the large majority of the banks in the three countries are foreign-owned by Eurozone banks. Thus, when the parent banks are facing difficulties, this quickly exacerbates the transmission of foreign shocks into the local economies. A major finding is that once under a fixed-exchange rate regime, monetary policy is highly ineffective in accommodating foreign shocks, and fiscal policy also becomes ineffective (unlike the Mundell-Fleming model would predict). One last important implication is a comparison between the shock transmissions in the South Eastern European countries and Central European countries, which shows that the effects are smaller and less persistent in countries with inflation targeting such as Poland, Hungary, and the Czech Republic.

Thus, the role of monetary policy or the lack the thereof is a major contributor to financial vulnerability. A study by Lama and Rabanal (IMF, 2014) compares the trade benefits of the United Kingdom joining the Eurozone to the cost of giving up monetary policy and exchange rate policy as tools for macroeconomic stabilization during a crisis. They measure the impact of different policies under several scenarios. They find that during non-crisis times there are significant gains from being in the Eurozone, but during an economic turbulence similar to what the area periphery countries experienced during the GFC and the ESDC, the volatility of the risk premium increases by 20 percent, exacerbating macroeconomic volatility. There was also a welfare loss of 2.2 percent of life-time consumption.

Another way that shocks are transmitted to other countries in a currency union is through bailout of member states or even a potential exit of a union (as in the case of Greece). Bizuneh and Valev (2014) present survey data from Bulgaria that investigates the perception of bailouts on the decision to join the EMU. The authors find that the Eurozone membership was associated with negative consequences on the economy as well as on the personal budget. After all, the country decided to halt its accession to the EMU because of the potential of suffering a crisis and austerity measures if obligated to help bailout other countries.

Contagion effects between developed and emerging markets is an important topic in finance. It is particularly vital for investors who want to diversify their portfolios. Studies have examined financial contagion in emerging markets as a result of the GFC and the ESDC. The contagion effects of the GFC and the following ESDC on emerging markets were explored by Gencer and Demiralay (2016). They focus on different financial channels of contagion such as aggregate stock market contagion, financial sector contagion, real economy sector contagion from the financial system of the crisis-originating country, and idiosyncratic effects of the real economy spreading in the financial sector of the emerging markets. The authors use a time-series regression within a GARCH framework model using stock market indices from Morgan Stanley Capital Investment indices. The authors analyzed a wide array of emerging markets worldwide such as Brazil, Chile, China, Egypt, Greece, Russia, Qatar, Turkey, and others. The study finds that the emerging markets are not strongly affected by the GFC, especially with regards to contagion from the US. However, significant contagion effects were discovered with regards to the ESDC.

The study that is most closely related this paper was conducted by Alexakis and Kenourgios (2015). The authors examined the relationship between the developed and emerging stock market contagion, most specifically between the Eurozone and the three Baltic countries – Latvia, Lithuania, and Estonia, during the GFC and ESDC. Although similar in their macroeconomic characteristics, the three countries exhibited differences in their contagion patterns. While Estonia was not affected by the GFC but was affected by the ESDC, Latvia and Lithuania were contagions during the former and not contagious during the latter. The authors provide reasons for this such as the macroeconomic and financial environment and the introduction of the euro in Estonia. More specifically, they cite factors such as foreign direct investment (FDI), market capitalization, and the value of stocks as a percentage of GDP. The authors estimate asymmetric dynamic conditional correlations into an FIAPARCH framework, and then test these during the two crises. The data used was the daily aggregate closing prices for the three countries’ stock prices and EURO STOXX50.

In addition to the emerging market contagion literature, papers have examined Eastern and Central European countries in aggregate and how their financial markets were affected during the 2008-2014 crises. One such study by Harkmann (2014) looks at possible contagion effects between Western and Eastern European countries during the 2008-2012 crisis in Europe, triggered by the US subprime mortgage crisis and the following ESDC. The paper studies the co-movements between stock market indices of 6 countries (Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, and Romania) and the Euro zone EURO STOXX50 index, using a DCC-GARCH model. The paper finds evidence for contagion and shows that the dynamic conditional correlations (DCCs) between the 6 countries and STOXX50 index increased steadily. It also shows that the ESDC contributed to increased correlations.

A study of the capital markets in several East European Countries (Romania, Czech Republic, Hungary, Bulgaria, and Poland) by Chirila, Turturean, Chirila (2015) examines the volatility spillovers between these countries and the countries of the Eurozone in the period 2014 – 2015. It uses a GARCH model to explore the relationships between the markets’ volatility. The paper uses the stock market indices in the five countries and the Eurozone index EURO STOXX50. The results show that the East European markets are more strongly affected by local shocks than by shocks in the Eurozone stock market. Moreover, the paper shows that shocks from the Eurozone market were transmitted into the East European countries, but that the opposite is not observed.

Another group of literature focuses on contagion in the Central and East European countries in general as well as factors that could affect negative spillovers. For example, Kutasi (2015) focuses on banking contagion and hypothesizes that different foreign exchange regimes and policies had different results in terms of contagion intensity in the Central East European countries. He assumes that the types of the foreign exchange (FX) regime determine the ratio of the non-performing loans in these countries. This depends on the FX regime and the number of foreign loans during the GFC, as the FX assets of banks depended on the volatility of the exchange rate. The author uses a linear regression to test his hypothesis. The findings show that countries with a pegged exchange rate and thus, zero volatility of the FX, have no significant impact on debtors’ solvency. The currency of the loan financing was shown to have a strong effect on credit defaults during the crisis.

Furthermore, according to Oanea (2015) highly integrated financial markets provide the easiest way of spreading negative effects of crises within those markets. He examines whether there are any major interactions between the stock markets from Central and Eastern Europe. Using market indices for Romania, Hungary, Czech Republic, Slovakia, Bulgaria, and Poland, the author uses a co-integration test and a vector error correction model for the period 2005-2014. The study finds that the Bulgarian, Hungarian, and Slovakian capital markets were most strongly impacted by the financial crisis, and that the Polish market was the most profitable. In addition, it is shown that the strongest influence on the market indices is determined by the market indices of the neighboring countries.

In order to achieve a more precise analysis of the contagion effects of the most recent financial crises on Bulgaria’s economy and financial market, an estimation of the effects could be performed separately for Bulgaria. Comparing the periods before, after, and during the crises could indicate whether such effects took place, what factors might be attributed to this, and the implications for policy makers and investors.

4. Data Description and Preliminary Analysis

The data sample contains information on the stock market indices of the Eurozone and Bulgaria, EUROSTOXX50 and SOFIX respectively. The indices were extracted from the Thomson Reuters IKON database. The data are daily historical indices for the period of January 2002 to December 2014 (3205 observations) denominated in euro. The return on each index is estimated as . In the data, the period of the Global Financial Crisis is defined as being from August 2007 to March 2009, and the European Soveregn Debt Crisis is defined as being from May 2009 to October 2013.

Fig. 1 presents the price evolution of the indices over time. The figure shows significant changes in the levels of the indices, especially during the GFC period. The dynamics of SOFIX broadly resembles that of EUROSTOXX50. However, the Bulgarian index has not increased significantly over its lowest levels after the crises. Fig.2 illustrates the return of the two stock markets over the sample period. Increased volatility in returns is present during both the GFC and the ESDC in both markets. However, the Bulgarian market seems to exhibit more volatility during the GFC than during the ESDC.

Table 1 displays the descriptive statistics for the returns in both markets during the full sample period as well as during both periods of turmoil. The kurtosis of both indices during the full sample period as well as during the two crises is positive and larger than 3, which suggests the presense of leptokurtosis. This indicates possible abnormal distribution of both market returns. A test for normality of the returns on both indices rejects the null hypothesis of normal distribution.

Table 2 presents the correlation between the price indices as well as the correlation between the returns on EUROSTOXX50 and SOFIX. There is a higher correlation between the price indices than between the returns, which might be indicating cointegration between the two market indices.

Further, the natural logarithms of the two price indices are tested for unit root using the Augmented Dickey-Fuller test. The test shows that the two series at levels are non-stationary. Additionally, the stock market returns are found to be stationary, and thus suitable for tests. The results from the Augmented Dickey-Fuller test are shown in Table 3.

5. Empirical Results

Since the price indices are non-stationary, the Johansen test for cointegration is applied using the non-stationary data to check if there is any long-term relationship between the two markets. The optimal lag is estimated based on the Schwarz Criterion. Table 4 displays the test results. Based on both the trace and eigenvalue max statistics, the null hypothesis is rejected at the 1% significance level. The test indicates one cointegration equation at the 1% significance level. Thus, the two series exhibit a long-run association, moving together in the long run.

Because the indices are cointegrated, a vector error-correction model is estimated. The results are presented in Table 5. The results show that the long-run coefficient is negative and significant, pointing toward a long-run causality running from the Eurozone stock market to the Bulgarian stock market. The opposite is not indicated by the test. A test for short-run cointegration is also run. It tests whether the lags of the EUROSTOXX50 index are jointly zero, or if they cannot joinly explain SOFIX. The null hypothesis that there is no short-run cointegration running from the Eurozone to Bulgaria is rejected. The tests show that there is no presence of autocorrelaton of the residuals and that they are normally distributed.

Table 6 presents the variance decomposition, which shows that a shock to the Eurozone stock market has a stronger effect on the Bulgarian market than the opposite. We can see that a shock to EUROSTOXX50 has an average impact of about 3.39% on SOFIX during the first 8 days after the shock, while a shock to SOFIX explains only about 0.33% on average of the variation in EUROSTOXX50.

Fig. 5 shows the impulse response functions for the two indices. Cholesky decomposition is used with ordering of EUROSTOXX50 and then SOFIX at the 99% confidence level.

The presence of “fat tails” described earlier suggests the use of a GARCH approach. It will test for contagion effects during the GFC and the ESDC. A linear model is estimated with a mean equation of the following form:

, (1)

where is the SOFIX return at time

is the EUROSTOXX50 return at time

is an interaction term that with a dummy variable, which is equal to 1 during the GFC period and 0 otherwise

is an interaction term that with a dummy variable, which is equal to 1 during the GFC period and 0 otherwise

is a disturbance term

After running the mean GARCH equation and predicting the residuals, a plot of them shows the presence of clustering volatility. After checking for the presence of ARCH effects, the null hypothesis that there are no ARCH effects is rejected. Thus, the GARCH (1,1) model is applied to the data. The estimated GARCH equation has the following form:


By estimating this equation, an analysis of whether the two crisis periods significantly changed the dynamics between the two indices can be conducted. If the coefficients of the dummy interaction terms are significant, this would indicate any structural changes in the mean of the correlation coefficients because of the crises’ shocks. Thus, positive and statistically significant coefficients will show that the mean correlation coefficients during the crisis periods are statistically different from the previous period. This would indicate the presence of contagion. Table 7 presents the estimates of the GARCH model.

We can see from the results that the coefficients of the lagged squared error and lagged conditional variance are highly statistically significant. Moreover, the sum of the coefficients of the lagged squared error and lagged conditional variance is equal to 0.997, therefore very close to 1. This implies that the shocks to the conditional variance will be highly persistent. Most importantly, the estimated and coefficients are positive and statistically significant, indicating that the correlation between the two markets during the specific crisis periods is significantly different than in the previous period. This shows evidence of contagion effects from the Eurozone market to the Bulgarian market during both the GFC and the ESDC. The magnitude of the effect seems to be higher during the GFC than the ESDC.

Lastly, to look at the conditional correlation dynamics between SOFIX and EUROSTOXX50, a Dynamic Conditional Correlation (DCC-MGARCH) model is applied. The following equation is estimated in the model as presented by Engel (2002):


All estimates in the model are highly statistically significant and the graph of the dynamic conditional correlation is shown in Fig. 6, Fig. 7, and Fig. 8.

6. Other Evidence of Contagion Effects in Bulgaria

Forbes (2012) empirically shows that a country is more susceptible to contagion if it has a more leveraged banking system, large international portfolio investment liabilities, higher trade exposure, and weaker macroeconomic fundamentals. Whether during a crisis or in peaceful times, the more interdependent a country is with another country or area, the more difficult it would be to stop contagion. This part of the paper will look at Bulgaria’s trade, external financial position, and banking system, and analyze the behavior of some macroeconomic indicators for the sample period.

As previously discussed, trade is one of the channels of contagion. A crisis in one country causes a decrease in demand for imports and this can significantly reduce exports to it by other countries. According to Forbes (2012), contagion through trade happens with two effects – bilateral trade and third markets competition. According to government trade data, Bulgaria’s largest trading partners in terms of exports of goods are Russia, Germany, Romania, Italy, Turkey, Greece, Belgium, and France. Most of these countries are Eurozone members. Figure 9 shows the value of Bulgaria’s exports and imports for the sample period. It can be observed from the graph that during the GFC there was a strong negative impact on the country’s value of imports and exports of goods. Both levels of the value of imports and exports are consistently increasing until the middle of the GFC. The figure shows a sharper increase in both indicators between the start of 2007 until the middle of the GFC period. This is consistent with the start of the country’s membership in the EU. This is not unexpected, as one of the key objectives of the EU is to increase integration between its members and reduce the barriers to trade. The levels of these indicators dramatically drop in 2008 to near-2006 levels. It is observed from the data that toward the end of the sample period in 2014 the levels of imports and exports of goods have barely reached their pre-crisis levels. Figure 10 and Figure 11 show the percent changes in imports and exports. Increased volatility is seen during both the GFC and the ESDC. Furthermore, Figure 12 shows Bulgaria’s import and export indices for the sample period. The graph follows a similar trend as the levels of the value of both imports and exports. Both indices are steadily rising until 2008 when they plummet and the effect persists until they start to slowly rise again in 2011. In 2014, the volume indices of imports and exports have not reached their pre-GFC values. Based on these figures on trade, there seems to be evidence that Bulgaria’s trade in terms of goods was strongly impacted during the two crises. Given the fact that the country’s largest trade partners are EU and Eurozone members, it appears that Bulgaria’s trade exhibits contagion effects during both crises. This is not surprising, as the high interdependence between the Eurozone and Bulgaria – especially in terms of trade – would suggest this result.

Further evidence of contagion could be seen from Figure 13. The Graph shows the percentage of non-performing loans to the total gross amount of loans in Bulgaria. A sharp increase in the non-performing loans is observed starting in 2009. In that year, it rose to about 6 percent from 2 percent in 2008. The following year, it reached about 12 percent, and it finally reached almost 17 percent in 2014.

Figure 14 shows Bulgaria’s direct investment from its Balance of Payments financial account. The graph shows the net acquisition of assets and liabilities during the sample period, and Figure 15 presents Bulgaria’s FDI and Portfolio investment for the same period. FDI is the difference between the net acquisition of foreign liabilities and the net acquisition of foreign assets, and it follows the same trend as the net acquisition of liabilities. We can observe from these graphs the positive trend in FDI in the beginning of the period and the sharp rise starting in 2007. These effects seem logical as Bulgaria’s macroeconomic environment has been stable since the introduction of the currency board in 1997. Its fixed exchange rate to the euro has fostered higher integration with the EU and stability of the price level. In addition to these factors, Bulgaria has had a very favorable foreign investment environment, with very low and flat corporate taxes and cheap labor. Thus, the country has attracted very high amounts of foreign capital. This is seen in the data. What is observed is the large amount of capital inflows until the third quarter of 2007 due to the positive impact of the EU membership and the fixed exchange rate the country has with the euro. There is, however, a drop in FDI during the GFC and FDI remains persistently low during the ESDC and afterwards. This trend is supported by Forbes (2012) which argues that contagion is exacerbated when a country has more foreign liabilities than assets, referring to the structure of a country’s external sector financial integration, rather than the level of it.

Table 8 shows some additional financial indicators in the country for the sample period as percent of GDP. It shows the sharp decrease in market capitalization of the companies traded in the Bulgarian Stock Exchange after 2007. The total value of the stocks traded decreased abruptly that year from 15.2 percent of GDP in 2007 to 2.4 percent in 2008. FDI also declines from 28.8 percent in 2007 to 16.8 percent in 2008.

The data presented in this section shows that Bulgaria was very strongly impacted during the GFC and the ESDC. Given the large degree of economic interdependence with the EU and the Eurozone as well as the high external position exposure to foreign capital, Bulgaria was most likely contagious during the two crises. What is more, the country was unable to make any macroeconomic adjustments through monetary policy or the exchange rate because it had to keep its commitment to the currency peg to the euro. It is no wonder, then, that Bulgaria has barely recovered in terms of trade, non-performing loans, and the external financial position at the end of the sample period in 2014.

7. Conclusion

This paper analyzed the factors and channels leading to financial contagion and focused on the contagious effects in Bulgaria during the GFC and the ESDC. Bulgaria presented a unique way to analyze contagion because of its strong financial linkages with the EU and the Eurozone and its macroeconomic specificities in terms of its currency board. In a GARCH framework, it was shown that the country was contagious during both crises. The paper used the Bulgarian stock market index SOFIX and the Eurozone’s EUROSTOXX50 to examine the co-movements between the two markets during the most recent financial crises. It was found that the Bulgarian stock market exhibited long-term cointegration with the Eurozone market and was found to be contagious during the financial crises. Through a DCC model, it was also shown that the dynamic conditional correlations of the two indices increased steadily during the GFC and were relatively high during the ESDC. Some further evidence of contagion was presented in terms of trade, nonperforming loans, and the external financial position of Bulgaria. It was shown that Bulgaria had a large amount of foreign liabilities and that might have been a factor in exacerbating contagion in the country. All evidence pointed toward strong contagion effects in the country’s economy during the GFC, while the country seemed to be not as strongly affected during the following sovereign debt crisis. Although still impacted during the ESDC, Bulgaria has been slowly recovering, even though it had not reached pre-crisis levels in the end of the sample period. What seemed to be exacerbating the shocks transmitted from the EU and the Eurozone was the country’s inability to use its monetary policy, central bank, or exchange rate to stabilize the economy during both crises.

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