Financial integration and growth -Is emerging Europe different?

Christian Friedrich, Isabel Schnabel and Jeromin Zettelmeyer

SummaryUsing industry-level data, this paper shows that the European transition region benefited much more strongly fromfinancial integration in terms of economic growth than other developing countries in the years preceding the currentcrisis. We analyse several factors that may explain this finding: financial development, institutional quality, tradeintegration, political integration, and financial integration itself. The explanation that stands out is politicalintegration. Within the group of transition countries, the effect of financial integration is strongest for countries thatare politically closest to the European Union. This suggests that political and financial integration arecomplementary and that political integration can considerably increase the benefits of financial integration.

Keywords: Financial integration; political integration; economic growth; multinational banking; Europeantransition economies.

JEL Classification: F32, F36, O16, G21.

Contact details: Jeromin Zettelmeyer, One Exchange Square, London EC2A 2JN, United Kingdom.Phone: +44-207-338 6178; Fax: +44-207-338 6178; email: zettelmj@ebrd.com.

Christian Friedrich is a PhD candidate at the Graduate Institute for International and Development Studies, Geneva;Isabel Schnabel is a Professor of Economics at the Johannes Gutenberg University, Mainz; Jeromin Zettelmeyer isDeputy Chief Economist of the European Bank for Reconstruction and Development.

We thank Erik Berglof, Nauro Campos, Ralph de Haas, Stephanie Hofmann, Ayhan Kose, Cedric Tille, and participants of the ECB-JIEConference on “What Future for Financial Globalisation?” for valuable comments and suggestions. We also benefited from comments byseminar participants at the European Bank for Reconstruction and Development, the Universities of Bayreuth, Mainz, Osnabruck, Tubingen, andthe Graduate Institute Geneva. An early draft of this paper was prepared as a background study for the 2009 EBRD Transition Report.

The working paper series has been produced to stimulate debate on the economic transformation of central andeastern Europe and the CIS. Views presented are those of the authors and not necessarily of the EBRD.

Working Paper No. 123 Prepared in December 2010

1 Introduction

Political, trade and financial integration have been the three defining pillars of the “developmentmodel” of the European transition countries in the past two decades. Until recently, this modelwas considered a spectacular success. Since the mid-1990s, the transition region had experiencedan externally financed growth spurt, which does not have many parallels in economic history.However, the disastrous impact of the financial crisis on the transition region has cast somedoubt on this model. Several countries suffered double-digit percentage decreases in GDP in2009. Nevertheless, the benefits of political and trade integration - which are closely linked -have not seriously been questioned. A reversion of the political integration process is barelyconceivable, and the benefits of trade integration are now widely accepted, both by politiciansand by academics (see, for example, Edwards, 1998).

The criticism focuses instead on financial integration. The financial crisis was transmitted mainlythrough financial channels. In addition, financial integration seems to have fuelled the creditboom preceding the financial crisis. This credit boom and the related stocks of private foreigndebt are widely believed to have made the transition region so vulnerable to the financial crisis,and are in fact strongly correlated with extent to which output declined in the region during thecrisis (see Berglof, Korniyenko, Plekhanov, and Zettelmeyer, 2009). The academic literatureis also far less conclusive regarding the benefits of financial integration than it is with respectto trade integration. In an influential paper, Prasad, Rajan, and Subramanian (2007) show in asample of 65 developing, non-transition countries that current account surpluses had a positiveimpact on growth between 1970 and 2004, implying that countries relying on foreign financinggrew more slowly than countries relying on domestic savings, which contradicts the neoclassi-cal view. Gourinchas and Jeanne (2007) refer to the negative correlation of capital flows andeconomic growth in developing countries as the allocation puzzle.

Studies using more disaggregated data tend to draw a somewhat more positive picture of financialintegration than country-level studies (see Kose, Prasad, Rogoff, and Wei, 2009b, for an excellentoverview of the literature). When using industry-level data, Prasad et al. (2007) find evidence ofthreshold effects: financial integration appears to have positive growth effects once the financialsystem is sufficiently developed. Moreover, several studies (starting with Bekaert, Harvey, andLundblad, 2005) have found evidence of a beneficial effect of financial integration through equitymarket liberalisation.1 Overall, the picture is still mixed at best, with scant or no evidence tosuggest that financial integration supports economic growth in developing countries.

However, as already noted by Prasad et al. (2007), the experience of the European transition re-gion does not seem to conform to this rather sceptical view of the relationship between financialintegration and growth. The combination of large current account deficits and high growth ratesin the years preceding the crisis prima facie suggests that capital inflows may have been benefi-cial for economic growth in these countries. Guiso, Jappelli, Padula, and Pagano (2004) applythe Rajan and Zingales (1998) methodology to test for the effect of financial development oneconomic growth using industry-level data (61 countries over the period 1981-1995, excludingtransition countries) and firm-level data (firms from 26 countries, among them 11 transition coun-

1See also De Nicolo and Juvenal (2010).

1

tries, between 1996 and 2001). Their results indicate that financial development has a “growthdividend” in Europe, and they speculate that this will also translate into positive growth effects offinancial integration. This view is supported by a recent study by Abiad, Leigh, and Mody (2009)who show in a country-level panel regression framework that financial integration as measuredby current account deficits had a positive growth effect between 1975 and 2004 in Europe, butnot in the rest of the world.2 Thresholds in institutional quality and financial integration itselfcan explain only part of the differences between Europe and the rest of the world. Abiad et al.(2009) argue that the remaining difference may be explained by the reduction in frictions betweenintra-EU borders and compare European capital flows to interstate flows within the United States.

Our paper makes two main contributions to this literature. First, we show, using industry-leveldata, that financial integration has indeed caused higher growth in European transition economiesin the years preceding the current crisis whereas the same is not true for other developing coun-tries. In contrast to many other papers, our study relies on a sample of developing countriesonly and does not include industrialised countries (as in Prasad et al., 2007; Abiad et al., 2009).A homogeneous sample is preferable because we are interested in explaining the differences inthe growth performance of different developing countries rather than those between developingand developed countries. Second, we carefully examine the potential reasons for why financialintegration was so successful over this time period in the European transition countries. We firsttest empirically for threshold effects, which have figured prominently in the academic literature(for example, Kose, Prasad, and Taylor, 2009c). As threshold variables, we consider financialdevelopment, institutional quality, trade integration and financial integration itself. The use of ahomogenous sample is critical here: in analyses including both groups of countries, such effectsmay be driven by differences between the two country groups rather than by differences withinthe group of developing countries. Since threshold effects are not able to explain the observeddifferences between emerging Europe and other countries, we finally analyse the role of politicalintegration, which so far has hardly been considered in the literature. Political integration withadvanced economies is one of the distinguishing features of European transition countries. Weconstruct a broad index of political integration on the basis of information on regional integrationagreements, taking into account four dimensions of political integration: institutions, policy coor-dination, attitudes, and political stability. We then test whether the effect of financial integrationis affected by the degree of political integration.

Our analysis suggests that political integration can explain why financial integration had suchstrong growth effects in European transition economies, but not in other developing countries.When including political integration in the regression, there is no longer a discernible differ-ence between emerging Europe and other developing countries. Moreover, within the group oftransition countries, the effect of financial integration is strongest for the countries that are moststrongly politically integrated with the EU. This suggests that political and financial integrationare complementary and that political integration can considerably increase the benefits of finan-cial integration. The reason may be that political integration affects investors’ expectations aboutfuture institutions and policies, which may influence the way foreign investors employ their cap-ital in the region in a growth-enhancing way. Hence, financial integration may be beneficial foreconomic growth even if the current institutional framework is still relatively weak. There arealso some indications that the presence of foreign banks contributed positively to the growth ef-

2Note that the number of observations from transition economies in their sample is rather small.

2

fect of financial integration. Indeed, the emergence of multinational banking may itself be seenas a consequence of political integration. Hence, emerging Europe may be different from otherdeveloping countries because financial integration was accompanied by corresponding advancesin political integration.

The paper proceeds as follows. Section 2 elaborates on the stylised fact that emerging Europeis different. Section 3 puts the recent growth episode of transition economies into perspectiveby searching comparable episodes in economic history and discusses the theoretical channelsthrough which financial integration may affect economic growth. Section 4 presents industry-level evidence showing that emerging Europe was indeed different from other developing coun-tries in the considered time period. Sections 5 and 6 analyse different candidates that may explainthese differences. Section 5 presents threshold specifications regarding financial development, in-stitutional quality, trade integration, and financial integration itself. Section 6 then focuses on therole of political integration. Section 7 concludes.

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2 The stylised fact

According to standard economic theory, capital flows to developing countries contribute to eco-nomic growth. Neoclassical theory predicts that capital flows from rich countries with highcapital-labour ratios to poor countries with low capital-labour ratios (and hence a higher marginalproduct of capital), increasing capital in the latter countries and thereby contributing to conver-gence and economic growth. By and large, empirical evidence has not confirmed these predic-tions (see, for example, Lucas, 1990; Gourinchas and Jeanne, 2007, and the papers cited in theintroduction). However, basic Stylized facts regarding capital flows to developing countries sincethe mid 1990s suggest that there may be differences in the relationship between capital flows andgrowth across developing country regions, which are well worth exploring.

Chart 1: Current account balances in emerging market regions, 1994 - 2008

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Chart 1 displays the current account balance as a percentage of GDP for the three main emergingmarket regions between 1994 and 2008. All three regions exhibited growth spells during thisperiod: in the case of European transition countries, since about 1995; in the case of emergingAsia, since 1999, following the end of the Asian crisis; and in the case of Latin America, since2003. However, the degree to which the three regions relied on external savings in financing thesegrowth spells is startlingly different. In Asia, the current account adjustment that was promptedby the crisis (from moderate deficits to a large surplus) failed to revert after the crisis was over;instead, the region saw a period of rapid growth accompanied by large current account surpluses,that is, capital exports. Latin America saw a rather similar pattern: a narrowing of the currentaccount deficit in the crisis period is followed not by a return to deficits during the recovery,but instead by a further narrowing and a move toward surpluses. Only emerging Europe showsa completely different pattern: already entering the transition period with substantial current

4

Chart 2: Savings and investment in European transition countries, 1994-2008

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account deficits, emerging Europe experienced a surge in net private capital flows from 2000onwards, which resulted in persistent and, on average, growing current account deficits. Duringthe (2006-2008) peak of the boom, these reached double-digit percentage of GDP ratios in severalcountries (such as the three Baltic countries, and some countries in south-eastern Europe).3

Hence, while the idea that capital inflows are at best neutral and possibly harmful for growthresonates well with the experience of Latin America and particularly emerging Asia during theirmost recent growth spells, this does not seem to be true for the European transition countries.Consistent with this impression, Chart 2 reveals that the surge of current account deficits in thetransition countries was not driven by a reduction in savings, but rather by a surge in investment toGDP over the last decade.4 This gives rise to the presumption that foreign capital may have had apositive effect on the growth performance in European transition countries. The observed combi-nation of rising investment, high growth performance and a widening current account deficit wasnot shared by other regions in this time period (except for a brief widening of the current accountdeficit in Latin America just before the crisis, see also Fabrizio, Leigh, and Mody, 2009).5

Lastly, it can be shown that there is indeed a significant negative cross-country correlation be-tween current account balances and real GDP per capita growth rates in emerging Europe. In

3In the following, emerging Europe includes the transition countries in central, eastern and south-easternEurope. It does not include states that used to be part of the Soviet Union. In the following, the terms “emergingEurope” and “European transition countries” are used interchangeably.

4Due to missing country-level data on savings and investment, this chart is based on the regional definition of“central and eastern Europe” in the IMF’s World Economic Outlook database.

5In Section 3, we show, however, that there were comparable episodes in economic history.

5

Chart 3: Current account balances and growth in developing countries, 1994-2008

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contrast, this correlation is positive in the overall sample of low- and middle income countriesexcluding European transition countries (see charts 3 and 4). Although correlation does not im-ply causation and a more sophisticated analysis will be needed to verify this conjecture, theseobservations raise the question whether emerging Europe is different with respect to the impactof financial integration on economic growth.6

6Note that the same relationship is obtained for the 1998-2005 period, which is used in the regressions.Moreover, the same stylised fact is also visible in a scatter plot of industry-level growth rates (as used in theempirical analysis) and financial integration. See charts 5 and 6 in the Appendix.

7

3 Historical parallels

The facts presented in the previous section indicate that the combination of high sustained growthand large current account deficits is unusual in the developing country experience since the mid1990s. But is it also unusual in a broad historical perspective? To answer this question, purchas-ing power-adjusted GDP per capita and current account data were collected for a broad group ofcountries from the Americas, the Asia-Pacific region, and Europe from 1850 to 2008. A two-stage selection was then made: in the first stage, all episodes with an average annual growth rateabove 2.5 per cent over a time span between 10 and 20 years - comparable to the recent growthphase in the European transition region - were identified. This led to 321 episodes. In the secondstage, all episodes from that group where average current account deficits exceeded 4.2 per centof GDP (the average value for emerging Europe between 1995 and 2008, based on the regionaldefinition of “central and eastern Europe” in the IMF’s World Economic Outlook database) wereselected. The resulting set contains 10 growth episodes with high current account deficits foremerging Europe after 1990 (with an average growth rate of 5.6 per cent and an average currentaccount deficit of 7.6 per cent) against 39 episodes from other regions (see Table 1). Therefore,growth episodes accompanied by large capital inflows do indeed seem much less frequent, inrelative terms, in the broad non-transition sample.

There are, however, a small number of growth episodes in history that indeed show a similarpattern: Canada and Finland in the pre-World War I episode, Norway, Portugal, and Spain duringthe 1920s, the post-World War II catch-up in western Europe, Latin America from the 1960s untilthe 1980s’ debt crisis, and some countries from emerging Asia between the 1970s until the mid1990s. When analysing what these episodes have in common with the current transition expe-rience, one observes that most of these episodes involved some policy or regime change priorto the episode (for example, post-war reorganisation, introduction of democracy, or renouncingimport substitution growth strategies). A possible interpretation of the observed association be-tween high capital inflows and growth is that these changes increased the distance between theactual and the steady state capital stocks either by making existing capital obsolete or by increas-ing expected total factor productivity (TFP), and hence desired levels of per capita capital. Insuch a situation, the growth benefits of financial integration are particularly strong because thetransition between actual and desired capital stocks can be significantly accelerated by capitalinflows (Hoxha, Kalemli-Ozcan, and Vollrath, 2009).

In emerging Europe, financial integration was preceded by some degree of capital obsolescenceand accompanied by strong advances in political integration - especially with the EuropeanUnion. This suggests a possible explanation of the stylised fact presented in Section 2. Onceit became clear that European transition countries would become part of the European Union ora European Union-dominated Europe, there was a reasonable expectation that their institutions -and, hence, TFP levels - would eventually converge to the European average, raising the expectedsteady state. This may have created incentives for foreign investors and banks, particularly fromwestern Europe, to pursue long-term investment strategies in the region (even ahead of actualinstitutional improvements). These would include the build-up of branches and subsidiaries witha better knowledge of the financial needs of local businesses and thus better opportunities to fi-nance growth-generating investments. In this way, financial integration may have speeded up the

8

Table 1: Sustained growth spells associated with large capital inflows

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transition process from the current to the expected steady state, which would have taken a muchlonger time period if it had had to be financed by domestic savings. On top of this, the “collateralbenefits” of financial integration (see Kose et al., 2009b; Kose, Prasad, Rogoff, and Wei, 2010)may even have led to higher steady state growth rates, for example by accelerating financial deep-ening. One goal of our empirical analysis is to check whether there is any empirical support forthe proposed explanation of the stylised fact.7

7Given our short sample period of seven years, we cannot distinguish between the transition to a higher steadystate and higher steady state growth rates in our empirical analysis.

10

4 Is emerging Europe different? Baseline specification

4.1 Empirical model

Our analysis is based on industry-level data, applying the methodology developed in the seminalpaper by Rajan and Zingales (1998) to the context of financial integration. The approach relies onthe following theoretical presumption: some industries depend on external finance - as opposedto internal finance, such as retained earnings - more than others (for example, because they haveto make large investments that generate cash flows only after several years). If financial integra-tion “works” in the sense that it facilitates access to financing and thereby ultimately influencesinvestment and growth, it should have a larger effect on industries that depend strongly on ex-ternal financing. This implication can be tested by estimating an econometric model in whichthe growth effect of financial integration is allowed to vary according to the external financialdependence of an industry.

The estimation equation underlying the baseline specification is as follows:

Growth j,k = αk +β j + γ · industryshare j,k

+δ0 · (ext.dependence j · f in.integrationk)

+δ1 · (ext.dependence j · f in.integrationk) ·Emerg.Europe dummyk + ε j,k,

(1)

where j denotes the industry and k the country. One major advantage of this methodology isthat is controls for country (αk) and industry (β j) fixed effects, which mitigates the endogeneityproblem. Furthermore, the industry share is included in order to account for the fact that youngindustries on average grow faster than mature industry; hence, we expect γ to be negative. The twointeraction terms capture the effect of financial integration on industry-level growth, dependingon external dependence of an industry. External dependence measures the degree to which firmsof industry j are dependent on external finance. In the first interaction term, external dependenceis interacted with various measures of financial integration at the country level. The secondinteraction term is additionally interacted with an indicator variable that takes on the value of 1when a country is part of emerging Europe. This term captures differences between Europeantransition economies and other developing countries regarding the effect of financial integrationon industry-level growth.8

Hence, the main coefficients of interest are δ0 and δ1. δ0 captures the impact of financial integra-tion, depending on external dependence, in countries outside of emerging Europe. If industriesthat rely strongly on external financing benefit more from financial integration in this group ofcountries, this coefficient should be positive. δ1 captures the differential effect of financial inte-gration in emerging Europe. A significant coefficient implies that the growth effects of financial

8The original Rajan-Zingales paper studied the interaction effect between external dependence and financialdevelopment rather than financial integration. We do not control for financial development in this regression(except to the extent that it is absorbed by the country dummy) because we are interested in the impact of financialintegration on growth through all channels, including through financial development.

11

integration are different in European transition countries. The sum of δ0 and δ1 captures the to-tal effect of financial integration (again depending on external dependence) in emerging Europe.Note that the overall effect of financial integration cannot be identified because the level effect isabsorbed by the country fixed effects; only the slope effect measuring the dependence on externaldependence is identified.

4.2 Data

Industry growth We use industry data from the Industrial Statistics Database provided by theUnited Nations Industrial Development Organization (UNIDO). Since our focus is on the Euro-pean transition region, we are using the UNIDO (Revision 3) dataset, which is the only versioncovering transition economies to a large extent. This comes at the cost that other regions havea lower coverage (see Appendix A.2 for details). We restrict our analysis to developing coun-tries because we are interested in explaining the differences in the growth performance withinthe group of developing countries rather than those between developing and industrialised coun-tries. Starting from the maximum sample of developing countries for which industry data isavailable, we follow Prasad et al. (2007) in eliminating a number of countries according to somepre-defined criteria to avoid a distortion of results. Specifically, we drop small island economies,countries relying strongly on oil exports, and countries with substantial inflows of developmentalaid (see Appendix A.1 for details). This selection procedure leads us to a sample of 25 middle-and low-income countries, twelve of which are from emerging Europe.

As a measure of industry growth, we calculate average growth rates of real output over the pe-riod 1998 to 2005.9 This time period reflects the trade-off between choosing a long time span tocapture medium-term effects of financial integration and smooth out business cycle effects, andmaintaining a reasonably large cross-section of countries, including a broad set of transition coun-tries.10 Moreover, we exclude the boom in transition economies preceding the subprime crisis toavoid biasing our results towards finding positive growth effects in these countries. Therefore, ourresults should be considered a lower bound to the actual growth effects of financial integration.11

Table 2 shows the composition of the sample and some descriptive statistics at the country level.12

The sample used in most of our regressions contains 992 observations. Note that the sample ishighly unbalanced as many countries do not provide any information on some sectors.

Industry share The industry share of an industry j in country k is computed as the ratio of thesize of this industry and the size of the entire manufacturing sector of the respective country in1998.

9Note that the growth variable has been winsorised at the 1st and 99th percentiles.10Long-run effects, especially those from FDI, are unlikely to materialise in such a short time period.11It would be desirable to also explore the effect of financial integration on TFP growth (as in Bonfiglioli, 2008;

Kose, Prasad, and Terrones, 2009a). Due to a lack of sufficient data on investment in the given data set, such ananalysis in not feasible here.

12For overall descriptive statistics, see Table A.3 in the Appendix.

12

Table 2: Country-level descriptive statistics

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External dependence The external dependence ratios of industries are taken from Rajan andZingales (1998) and are defined as the ratio of capital expenditures minus cash flow from opera-tions, divided by capital expenditures. Hence, they measure the share of capital expenditures thatcannot be financed internally in a given industry. Since observed external dependence ratios indeveloping countries are distorted by financial frictions, Rajan and Zingales suggested to use thecorresponding ratios of US industries, arguing that the US capital market comes closest to theideal of a frictionless market. The fact that these ratios were computed on the basis of data fromthe 1980s comes in handy here, since the US industry structure at that time should better reflecttoday’s industry structure in developing countries than a corresponding up-to-date ratio. It shouldbe noted that we had to adjust the industry definitions in our dataset to those used by Rajan andZingales (1998) (see Appendix A.2 for details).

Financial integration Regarding financial integration, Kose et al. (2009b) argue in favour ofquantity-based, de facto measures. The early literature had used mostly de jure measures, suchas those based on the IMF’s Annual Report on Exchange Arrangements and Exchange Restric-tions (AREAER). However, such measures do not fully capture the degree of enforcement andeffectiveness of capital controls as well as regulations in other fields that affect capital flows.Regarding the choice between quantity- and price based measures, Kose et al. point out that ob-

13

served price differences may be due to risk and liquidity premia rather than being an indication oflow financial integration. In addition, domestic financial markets might not be liquid enough toefficiently diminish price differentials, so that price-based measures may underestimate the truedegree of financial integration. Therefore, quantity-based measures are also used in this study.

We use nine de facto, quantity-based measures of financial integration. To ensure comparabilitywith Prasad et al. (2007) and Abiad et al. (2009), we use the current account deficit in per centof GDP - taken from the IMF’s World Economic Outlook database - as our first variable (CA, seeTable 2 for the values of financial integration measures of all included countries). Moreover, wecompute six measures from the External Wealth of Nations Mark II Database, which was con-structed and updated by Lane and Milesi-Ferretti (2007). We use both stock and flow variables.13

First, we use the standard measure of gross financial integration, defined as the sum of total for-eign assets and total foreign liabilities in per cent of GDP (GFI). Gross measures of financialintegration have the advantage that they also capture risk-sharing benefits of financial integration.Then we consider various measures taking into account only foreign liabilities (capturing onlythe financing side of financial integration), distinguishing different types of foreign liabilities:foreign direct investment (FDI) and foreign debt (D), both expressed in per cent of GDP.14 Inaddition, we consider the changes of these variables between 1998 and 2005: the change in FDIliabilities (∆FDI) and the change in foreign debt (∆D). Further, we consider the change in net for-eign assets (defined as the difference between foreign assets and foreign liabilities) between 1998and 2005 in per cent of GDP (∆NFA), which serves as a valuation-change adjusted equivalent tothe current account. Lastly, we use two measures capturing the presence of foreign banks, whichis one distinguishing feature of financial integration in the European transition region. First, weuse the share of assets held by foreign banks in total assets of the respective banking system(Foreign bank asset share); second, we use the share of the number of foreign banks in all banks(Foreign bank number share). Both variables are taken from Claessens, Van Horen, Gurcanlar,and Sapiain (2008).15

It should be noted that the variable choice reflects our intention to mainly capture the benefitsof financial integration running through the financing side, for example, the loosening of capitalconstraints of local firms and the transfer of managerial skills from parent firms to local firmsthrough FDI transactions. To capture benefits from risk-sharing, other variables may be moreappropriate. However, the financing side is likely to be the most relevant transmission channelin the European transition region. Nevertheless, the estimated values should be seen as a lowerbound for the gains from financial integration because risk-sharing benefits are not fully captured.

Note that the stock variables enter as averages over the sample period, that is, 1998 to 2005(unless noted otherwise). The same time period is used when considering changes in financialintegration. In order to minimise endogeneity problems, the use of starting values of the stockvariables would be preferable. However, in our case, the starting values do not reflect actualdifferences in financial integration in the considered time period because all financial integrationmeasures increased sharply between 1998 and 2005 in the transition region.

13Strictly speaking, what we call “flows” are valuation effect-adjusted changes in stocks over the sample period.14We do not consider portfolio equity flows because they are quantitatively insignificant in the transition region.15“Foreign bank number shares” are measured as an average from 1998 to 2005, and “foreign bank asset shares”

as an average between 2000 and 2005 due to missing data.

14

4.3 Results

We now discuss the results from the baseline regression (1), shown in Table 3. The columnsshow the regressions using different measures of financial integration in the interaction terms.16

In all regressions, the industry share enters negatively as expected and is significant at the 1 percent level (see first line of the table, p-values are in parentheses). The next two lines in the tablereport the coefficients of the two interaction terms. The second line shows the coefficients of theRajan-Zingales interaction term (corresponding to δ0 in equation 1). It is to be interpreted as theeffect of financial integration, depending on external dependence, for countries not belonging toemerging Europe (called “other countries” in the table). If there were a sectoral growth effect forthis group of countries, this coefficient should be significantly negative for the first two measuresof financial integration (where a higher value indicates less financial integration) and significantlypositive for the remaining measures. In line with the existing literature, we find no evidence of asectoral growth effect of financial integration for these countries. The coefficient is insignificantin all regressions, and it even has the “wrong” sign in some cases.

The third line shows the differential sectoral growth effect in European transition countries, rela-tive to the effect of other developing countries (corresponding to δ1 in equation 1). We find thatthis coefficient goes in the expected direction in 8 out of 9 cases and is statistically significant in6 cases. Hence, there appear to be significant differences between European transition countriesand other developing countries: industries in European transition economies benefit more fromfinancial integration than those in other developing countries. The total sectoral growth effect forEuropean transition countries can be seen in the fourth line, which is the sum of the coefficientsfrom the second and third line (corresponding to δ0 + δ1). We see that the total sectoral growtheffect shows the expected sign in 8 out of 9 cases and is significant in all these cases at the 5 percent level. The exception are foreign debt flows, which show the “wrong” sign and are insignif-icant. Hence, a large change in foreign debt does not seem to be conducive to economic growth(whereas a high level is beneficial). This finding can be explained by the fact that high debt flowsoften go along with credit booms and other types of vulnerabilities, which make a country moreprone to adverse shocks, and is well in line with the existing literature (see, for example, Koseet al., 2009b).17

In order to get a sense of the economic significance of the coefficients, we calculate differen-tials in real growth rates, as suggested by Rajan and Zingales (1998). That is, we consider twoindustries at the 25th and 75th percentile of external dependence, and two countries at the 25thand 75th percentile of the respective measure of financial integration. Then we compare the dif-ference between the sectoral growth rates of the two industries across the two countries. Thenumber of 1.55 in the fifth line of the first column then implies that an externally dependent in-dustry grows by 1.55 percentage points faster than a hardly externally dependent industry if itis based in a financially integrated country rather than in a hardly financially integrated coun-try (holding constant industry shares). We hence see that the sectoral growth effect of financial

16We use robust standard errors throughout. Clustering by country or sectors yields very similar results.However, in a cross-sectional framework with fixed effects in both dimensions, clustering does not seem to benecessary. Moreover, the number of clusters is relatively small, which reduces the reliability of clustered standarderrors.

17Debt flows also show a different pattern than other financial integration measures in all following regressions.

15

Table 3: Baseline regression results

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integration is substantial in European transition countries: it ranges between 0.72 and 1.92 per-centage points. The sixth line finally displays the difference in the differentials in real growthrates between European transition countries and other developing countries. We see that thisdifference is substantial in economic terms. The value of 2.43 in the first column, for example,implies that the differential real growth rate (as calculated above) in emerging Europe exceedsthat in other developing countries by 2.43 percentage points.

Hence, there is strong evidence for European transition countries that industries depending onexternal financing grow relatively faster (compared with industries not depending on externalfinancing) in financially integrated countries than in less integrated countries. There exists nosuch effect for developing countries outside of emerging Europe.

16

5 Why is emerging Europe different? Evidence from thresh-old regressions

5.1 Empirical model

Given these strong results on the differences between the European transition region and otherdeveloping countries, the question arises what drives these remarkable differences. Thresholdeffects and other types of non-linearities have become popular explanations of the difficulty todetect growth effects of financial integration in broad country samples. One of the first papersto find evidence of threshold effects is by Borensztein, De Gregorio, and Lee (1998) who detectthreshold effects in human capital regarding the effect of FDI on economic growth. Brezigar-Masten, Coricelli, and Masten (2008) examine whether financial development and financial in-tegration have non-linear effects on economic growth, using macroeconomic and industry-leveldata for Europe. The authors conclude that the benefits of financial integration become significantat higher levels of financial development. Kose et al. (2009c) examine various types of thresholdeffects for financial integration (for example, financial development, institutional quality, regu-lation, trade openness, macroeconomic policies) in a sample of 84 countries (21 industrial and63 developing countries) over the period 1995-2004. The results indicate that thresholds exist,but their level depends on the type of capital examined (i. e., thresholds are lower for FDI andportfolio equity flows). Abiad et al. (2009) provide evidence that part of the observed differencebetween Europe and other countries can be explained by threshold effects in institutional qual-ity and financial integration itself. However, Imbs (2009) stresses in a comment on that paperthat a significant part of the European effect remains unexplained, even after including thresholdeffects.

However, since most of these studies include both developing and developed countries, their re-sults may be driven by the difference between developing and developed countries, and not by dif-ferences within the group of developing countries. We therefore test for threshold effects withinour sample of developing countries, using the same sectoral analysis as above (Section 4.1). Wecheck for threshold effects in several dimensions: financial development (as suggested by Prasadet al., 2007), institutional quality and financial integration itself (as suggested by Abiad et al.,2009), and in addition also trade integration, the second pillar of the “development model” in theEuropean transition region.

In order to test for the presence of threshold effects, we add another interaction term to thebaseline model, which multiplies the original interaction term with a threshold dummy variableindicating whether some other variable (measuring financial development, institutional quality,trade integration, or financial integration itself) is above the sample median. Hence, we estimate

17

the following model:

Growth j,k = αk +β j + γ · industryshare j,k

+δ0 · (ext.dependence j · f in.integrationk)

+δ1 · (ext.dependence j · f in.integrationk) ·Emerg.Europe dummyk

+δ2 · (ext.dependence j · f in.integrationk) · threshold dummyk + ε j,k, (2)

Our estimation strategy is to see whether the interaction term with the emerging Europe dummyremains significant, once we introduce threshold effects. If not, threshold effects are able toexplain the difference between European transition countries and other developing countries. Ifyes, there must be something else that explains the observed differences.

5.2 Threshold variables

The threshold dummy variables are equal to one if the respective threshold variable (financialdevelopment, institutional quality, trade integration, or financial integration itself) is above thesample mean of countries, and zero otherwise. Financial development is measured by privatedomestic credit over GDP and is taken from Beck, Demirguc-Kunt, and Levine (2000). Insti-tutional quality is measured by the variable “Regulatory quality” provided by the World Bank(Worldwide Governance Indicators). The variable refers to the year 1998. Trade integration vari-able is measured by an “adjusted trade intensity” according to Pritchett (1996). It is created bytaking the residuals from a regression of openness on the log of population, size, remoteness,income per capita (as well as its square) and indicator variables for oil exports and landlocked-ness of a country. Estimation takes place in a panel framework, but the variable is created fromthe resulting 1998 value. The cutoff values of these threshold dummies, as well as the valuesfor individual countries are displayed in Table 4. Financial integration is measured by the samevariables as above. See Table 2 for cutoff levels.

5.3 Results

The first set of regressions (Table 5) considers threshold effects in financial development (privatecredit/GDP). The idea is that financial integration may be more beneficial if the financial systemof the developing country is sophisticated enough to efficiently absorb foreign funds. Let us firstexplain the interpretation of the coefficients in the threshold regressions. The coefficients in thesecond line (corresponding to δ0 in equation 2) now denote the sectoral growth effect for coun-tries that are neither in the transition region, nor above the median of financial development. Thecoefficient in the third line (corresponding to δ1) has a similar interpretation as before: it denotesthe differential sectoral growth effect in European transition countries relative to other developingcountries (holding constant financial development). Lastly, the coefficient in the fourth line (cor-responding to δ2) gives the differential sectoral growth effect in countries above the median of

18

Table 4: Threshold variables

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We find only weak evidence of threshold effects in financial development. The coefficient ofthe threshold interaction (fourth line) is mostly insignificant (apart from the coefficient on debtflows, which again has the “wrong” sign, and the two FDI measures which are significant atthe 10 per cent level). Hence, threshold effects can be found only with respect to foreign directinvestment. Most importantly, the emerging Europe interaction term remains significant in allcases, compared with the baseline regression.18 Moreover, the difference in the differential inreal growth rates between emerging Europe and other developing countries actually increasesin most instances (on average, it increases by about one third).19 Hence, threshold effects infinancial development cannot explain why emerging Europe appears to be different.

The results are similar in the regressions including a threshold dummy interaction for institutionalquality (see Table 6). Here the threshold interaction never has a significant effect on economicgrowth, and the emerging Europe interaction term again stays significant in all cases. The differ-

18It also turns significant for debt flows, but again in the opposite direction.19As an alternative, we measured financial development by stock market capitalisation. These regressions yield

the same results: there is little evidence of threshold effects, and the emerging Europe interaction term remainssignificant.

19

Table 5: Evidence on threshold effects - financial development

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ence in differential growth rates between the two groups of countries is almost unchanged. Hence,threshold effects in institutional quality cannot explain either why the European transition regionis different.20

The third threshold specifications focus on trade integration. The results are again similar to theprevious threshold specifications (see Table 7). The interaction term with the threshold variable isinsignificant in all cases. In line with the specifications for financial development and institutionalquality, the emerging Europe interaction term remains significant in all cases. The difference inthe differential in real growth rates between emerging Europe and other developing countries isslightly below that in the baseline specification. Hence, these results imply that threshold effectsin trade integration cannot be an explanation for the observed difference either.

The final threshold specification focuses on financial integration itself. We ran regressions forall of our financial integration measures. For most measures, the results are virtually identical tothe preceding threshold specifications. Some noteworthy results are, however, obtained for thefinancial integration measures related to multinational banking. Table 8 presents the results forthe regressions using foreign bank asset share as interaction variable; Table A.4 in the Appendixdisplays the results for the regressions using foreign bank number shares.21

While there is again no evidence of threshold effects, the coefficient of the emerging Europeinteraction term now becomes smaller (in absolute value) in all regressions and is insignificantin all but two regressions (see Table 8). The difference between emerging Europe and other

20Again, we also tried an alternative measure of institutional quality, namely “rule of law.” The results areunchanged.

21From a conceptual point of view, the first variable is preferred. However, the second may be subject to lessmeasurement error.

20

Table 6: Evidence on threshold effects - institutional quality

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developing countries in terms of the differential in real growth rates decreases markedly (byabout one fourth on average). Results are similar when using the foreign bank number shareas threshold variable, though the reduction in the coefficients and in differential growth rates issomewhat smaller. These results are remarkable. They suggest that the presence of foreign banksin the region may be related to the question of why emerging Europe appears to be different. Buteven here, the unexplained part of the difference remains substantial.22

The large unexplained difference even remains when we include all four threshold interactions(financial development, institutional quality, trade integration and financial integration, measuredeither by foreign bank asset or number share) at the same time (see Tables 9 and A.3). In fact,the difference between emerging Europe and other developing countries even increases in someregressions, compared with the baseline regression.

As a further robustness check, we repeated all regressions using different thresholds, such as the25th and 75th percentiles. For all threshold variables, the main result is robust: the emergingEurope interaction term remains statistically significant in most cases. In addition, we re-ran allregressions using continuous interactions terms instead of threshold dummies. Hence, the thresh-old dummy in equation 2 would be replaced, for example, by financial development itself. Again,the emerging Europe interaction term remains significant in most cases, even in the regressionsusing foreign bank asset or number shares as interaction variables. Taken together, these re-sults imply that none of the considered factors can satisfactorily explain the differences betweenemerging Europe and other developing countries. As a final step, we therefore analyse whetherpolitical integration may explain why financial integration appears to work better in Europeantransition countries than elsewhere.

22These results are broadly in line with the country-level results by Abiad et al. (2009).

21

Table 7: Evidence on threshold effects - trade integration

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6 Why is emerging Europe different? The role of political in-tegration

6.1 Empirical model

The analysis of financial, institutional and trade threshold effects has shown that the differencebetween European transition countries and other countries is not easily explained. Only financialintegration in the form of multinational banking manages to explain at least part of the difference.Therefore, we now turn to the third pillar of the development model in the European transitionregion, political integration. The interactions between financial and political integration havehardly been analysed in the literature.23 For European transition countries, the degree of politi-cal integration with the European Union is certainly one of the most important determinants ofeconomic and political conditions.

Political integration may affect economic growth in several ways. First, it may increase politicalstability. This can even happen when several developing countries in the same region concludea regional integration agreement. The effect will be even stronger if the regional integrationagreement includes developed countries. Second, there may be positive institutional spillovereffects among politically integrated countries. This effect will again be strongest if developingcountries join a regional integration agreement with highly developed countries, as is the case inthe European Union. Here one would expect an “export” of institutions from the country with

23Campos and Coricelli (2009) analyse the relationship between democratisation and financial reforms.

22

Table 8: Evidence on threshold effects - financial integration (foreign bank asset share)

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more developed institutions to the developing country.24 Such effects may result in an (expected)increase in total factor productivity (TFP). The expectation of improvements in political stabilityand institutional quality influences foreign investors’ behaviour. If, for example, political integra-tion raises expectations of future reforms and of a firm commitment to sound economic policy,investors may be willing to pursue potentially growth-enhancing investment strategies that oth-erwise would not be profitable, or excessively risky. For example, they may be willing to enterlong-term commitments. The creation of branches and subsidiaries of foreign banks in easternEurope is a good example. Such investments may speed up the transition to a higher steadystate, or even increase steady state growth rates, for example, through financial deepening. Giventhese arguments, we would expect the benefits of financial integration to be largest when it isaccompanied by political integration.

To analyse the role of political integration, we start from the basic specification and add anotherinteraction term:

Growth j,k = αk +β j + γ · industry share j,k

+δ0 · (ext.dependence j · f in.integrationk)

+δ1 · (ext.dependence j · f in.integrationk) ·Emerg.Europe dummyk

+δ2 · (ext.dependence j · f in.integrationk) · political integrationk + ε j,k,

(3)

The estimation strategy is the same as in the section on threshold effects (Section 5). The critical

24However, we have even seen such spillover effects among developed countries in the European Union.Consider, for example, the effects of European Union competition policy on countries like Germany.

23

Table 9: Regression results when all interaction effects are included jointly

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question is how to define political integration.

6.2 Political integration index

In the literature, there are several approaches to measure political integration. Beckfield (2006)measures political integration as the number of cases referred from national courts to the Euro-pean Court of Justice. Lee and Barro (2006) measure political proximity by the extent to whichtwo states have common foreign policy interests. The latter are proxied by the voting correla-tions in the UN General Assembly. Dreher (2006) and Dreher and Martens (2008) constructthe KOF-Index of Globalisation, which contains a political dimension that comprises the num-ber of embassies and high commissions in a country, the number of international organisationsto which the country is a member, the number of UN peace missions a country participated in,and the number of treaties signed between two or more states since 1945. All these measurescapture only very specific aspects of political integration. We therefore construct a broad indexof political integration (see Appendix A.3 for an in-depth description of the construction of theindex).

We follow the work by Nye (1968), which theoretically identifies four dimensions of the polit-

24

Table 10: Political integration index

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ical integration process: an institutional dimension, a policy dimension, an attitude dimension(subdivided in attitudes of the government and the public) and a stability dimension. We thenoperationalise each of these dimensions by creating a corresponding subindex that takes on avalue between 0 and 10. Lastly, we combine all subindices into a composite index - also rangingon a scale from 0 to 10, where 10 denotes the highest level of political integration. For each ofour sample countries, we identify the regional integration agreement that we consider the mostimportant one. A full list is displayed in Table 10.

The dimensions are operationalised as follows: the institutional dimension is supposed to capturethe degree of supranationality of each regional integration agreement. We approximate it bysetting the corresponding organisational budgets in relation to the number of member countriesin the respective regional integration agreement. The policy dimension is supposed to measurethe variety and extent of policy coordination that a regional integration agreement implies. Itconsists of five subcomponents that evaluate different types of policies (that is, security policy,trade policy, monetary policy, free movement of people, further integration intentions). Theattitude dimension is split in two parts. First, to measure the conformity of government viewsacross countries, we examine the correlation of voting behaviour in the UN General Assemblybetween each country and a corresponding base country over the period 1998 to 2005 (cf. Leeand Barro, 2006). Second, to capture the attitude of the public towards a regional integrationagreement, we use a set of questions from the World Values Survey concerning confidence in

25

the local regional integration agreement.25 Lastly, the stability dimension is supposed to proxyfor the stability of the political integration agreement in the future, based on the current and pastpolitical stability in a country. Here, we use the Political Stability and Absence of Violence indexfrom the Worldwide Governance Indicators provided by the World Bank.

By assigning a weighting scheme of 30 per cent, 40 per cent, 20 per cent and 10 per cent, wethen combine the four subindices to a composite index of political integration (see appendix).The resulting index values for all sample countries are shown in Table 10. As expected, countriesfrom emerging Europe obtain high scores of political integration (see last column of Table 10).However, we also observe some variation within this group of countries. For example, Romaniareceives a score of 7.7, compared with a score of 9.1 for the Slovak Republic, even though bothcountries are European Union members. It is also interesting to see that a country like (South)Korea obtains a very low value of political integration. Even though Korea is a relatively opencountry, it is not strongly politically integrated in the region. It is not even a regular member ofASEAN, but only serves as a dialogue country.

We refrain from estimating threshold effects of political integration because a threshold dummyhere would be almost indistinguishable from the emerging Europe dummy. Therefore, it is almosttautological that the emerging Europe interaction becomes insignificant if a threshold dummyof political integration is introduced. By using the index as a continuous variable instead of athreshold variable, more information is provided that may help distinguish between the regionaldummy and the index of political integration.

6.3 Results

The results are revealing (see Table 11). For the first time, all coefficients of the emerging Eu-rope interaction term become insignificant and their p-values take on much higher values thanbefore. Hence, there are no longer significant differences between the growth effects of financialintegration in emerging Europe and other developing countries once we control for an interac-tion with political integration. However, the interaction terms with political integration are alsostatistically insignificant. These findings can be explained by the high correlation between theemerging Europe dummy variable and the political integration index (the correlation coefficientis 0.92). Indeed, the two interaction terms are jointly significant in most cases. Hence, thisapproach is not able to disentangle the effects of the two variables due to the high correlationbetween them.

To circumvent this multicollinearity problem, we present an alternative specification where werestrict the sample to the transition region only. Thus, we focus on the variation in the politicalintegration index within the transition region. In this specification, we no longer include a re-gional interaction term (that is, δ1 does not exist here), as the sample corresponds almost exactlyto the emerging Europe region used to define the regional dummy. The difference consists ofonly three countries (Armenia, Moldova, and Georgia), which belong to the transition sample,

25Data from this survey was also used by Ekinci, Kalemli-Ozcan, and Sorensen (2008) who analyse the effect ofsocial capital on the degree of financial integration of regions within the European Union.

26

Table 11: Regressions including interaction term with political integration - World sample

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:?<EEF ;<E=; =<?@? :E<==> ;<??G ;<F?B ;<>G? ;<?>> ;<;GFC;<FED C;<AED C;<EGD C;<>?D C;<?BD C;<>GD C;<?GD C;<FAD C;<BD

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but not to emerging Europe.

The results from the second approach, based on a sample of 15 countries from the transition re-gion, are presented in Table 12. Most strikingly, the interaction term with the political integrationindex has the expected sign in all but one regression (again debt flows) and is mostly significantat the 5 per cent level. Two of the three cases where the interaction term is not significant are inregressions using foreign bank presence as a measure of financial integration. This is presumablydue to the fact that the variation of foreign bank presence within the group of transition countriesis relatively small; thus, it may be difficult to estimate its effect precisely in a sample that isrestricted to transition countries.

The effect of political integration is also economically important. Raising the political integra-tion index from the level of Albania (5.3) to that of Poland (8.3) increases the differential in realgrowth rates by between 0.39 and 1.92 percentage points. Changing the index from the low-est value (Korea, 2.1) to the highest (Slovak Republic, 9.1) would amount to a change in thedifferential in real growth rates of up to 4.48 percentage points. This is a substantial effect.

Taken together, these results suggest that political integration may play a crucial role in explainingwhy emerging Europe was different in the considered time period. In the European transitionregion, financial integration was accompanied by political integration with the European Union,which may have provided an anchor for relatively stable economic and political prospects. Thisin turn may have influenced the way foreign investors employed their capital in the region. Thestrong presence of foreign banks in European transition countries could itself be a consequenceof political integration. This explanation would rationalise the lack of statistical significance ofthe emerging Europe interaction term in the threshold regressions for financial integration whenthe latter was measured by foreign bank presence. Overall, these results indicate that the benefits

27

Table 12: Regressions including interaction term with political integration - transitioncountry sample

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a country can reap from financial integration are much larger if it is accompanied by politicalintegration.

28

7 Conclusion

Using the methodology by Rajan and Zingales (1998) based on industry-level data from a sampleof low and middle income countries, we have shown that the European transition region benefitedmuch more strongly from financial integration in terms of economic growth than other developingcountries since the late 1990s. The effect of financial integration on growth is not only statisticallysignificant, but also economically important. Hence, the experience of emerging Europe seemsto conform to neoclassical growth theory, which predicts that openness to foreign capital shouldallow countries to grow faster towards their steady state income levels.

The difference between the effect of financial integration in emerging Europe and elsewhere inour sample period cannot be explained by threshold effects in financial development, institutionalquality, and trade integration. There is no evidence of such threshold effects in our sample, andthe emerging Europe interaction term remains significant in these regressions. However, there issubstantial evidence that the finding can be explained by the region’s high level of political inte-gration with the European Union. Within the group of transition countries, the effect of financialintegration was found to be strongest for countries that are most highly politically integrated withthe European Union. This suggests that political and financial integration are complementary andthat political integration can considerably increase the benefits of financial integration. A pos-sible explanation of our findings is that the process of political integration with Europe createdexpectations of a stable political and economic environment in the European transition countriesand of the eventual catch-up of their institutions with those of western European countries. Thisin turn made it profitable for foreign investors to engage in projects that would otherwise havebeen considered too risky, with beneficial effects on economic growth.

We also found some evidence that threshold effects in financial integration in the form of foreignbank presence help explain why financial integration “worked” in the transition region. In therespective threshold specification, the emerging Europe interaction term became insignificant inmost regressions. There are two interpretations of this result. First, a high degree of foreignbank presence may simply be picking up the political integration effect that we find separately.Second, European parent banks may have provided their subsidiaries in the transition region withresources and knowledge, with beneficial effects on financial systems at large. This may haveallowed for a more efficient allocation of foreign capital.

Our results have important policy implications. They suggest that the negative side effectsof financial integration that became evident in the current crisis, such as credit booms, over-indebtedness of firms and households, and especially a high exposure to foreign currency debt,must be weighed carefully against clear evidence that financial integration has had significantgrowth effects in the transition region. This does not imply that the risks associated with finan-cial integration do not need to be taken seriously, but it does suggest that policy should seekvarious ways to better manage those risks, rather than push back against financial integration perse (see also European Bank for Reconstruction and Development, 2009, 2010).

Furthermore, our results suggest that financial integration works best when accompanied by aprocess of political integration with more advanced countries. In fact, the same forces stimulating

29

growth in the presence of political integration may also lower costs in times of crisis. Indeed,there is evidence of a protective role of foreign banks in the current crisis (see Berglof et al., 2009;Herrmann and Mihaljek, 2010).26 Emerging Europe provides the most prominent example ofsuch a political integration process, and in this respect, it is indeed different from other developingcountries. But, in the medium term, the European model might also be replicable elsewhere.

26See also De Haas and Van Lelyveld (2010) on internal capital markets of multinational banks.

30

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A Appendix

A.1 Country selection

Starting with all countries contained in the UNIDO (Revision 3) database, the sample is narroweddown by excluding those countries that satisfy one of the following four criteria (similar to Prasadet al., 2007).

1. To obtain a homogenous sample of middle and low income countries, we exclude countrieswhere the average purchasing power adjusted GDP per capita over the period 1994-2008is more than US-$ 20,000. In addition, we also exclude Portugal from the sample, whichnowadays is considered a high income country, but would not be eliminated by this selec-tion criterion.

2. We exclude small open island economies (which typically have extremely high financialintegration measures) if they are smaller than 30,000 sq. km.

3. We eliminate countries with an average value of oil exports over GDP of more than 10 percent to avoid the problem that potential growth effects in highly financially integrated coun-tries are overshadowed by windfall profits and corresponding current account surpluses incommodity exporting countries.

4. Lastly, we drop countries that on average received development aid of more than 15 percent of GDP over the period 1994 to 2008 to focus on the growth effects of private capitalflows.

A.2 Sectoral data

Output growth We use industry output data from the 3rd revision of the Industrial Statis-tics Database with 4-digit level International Standard Industrial Classification of All EconomicActivities (ISIC codes) provided by the United Nations Industrial Development Organization(UNIDO). To calculate real output growth, we deflate output in current prices in national curren-cies, using national GDP deflators from the International Financial Statistics database.

Sector definitions Since the industry-level data from Rajan and Zingales (1998) consists of amixture of 3-digit and 4-digit level ISIC codes that are consistent with UNIDO data from the 2ndrevision, they differ from the 4-digit level classification that is applied in the 3rd revision, whichwe are using. While external dependence ratios exist for 36 industries in their sample (of which27 are at the 3-digit level and 9 are at the 4-digit level), our dataset contains 127 industries at the4-digit level. Unfortunately, there is no straightforward conversion method to convert industriesfrom the 2nd to the 3rd revision or vice versa, since some of the industry definitions mutuallycontain each other. However, a correspondence table for converting industries from the 3rd to

34

the 2nd revision is provided by the United Nations Statistics Division. Based on this table, weproceed in the following way.

• All external dependence ratios with a 4-digit level ISIC code from the 2nd revision, caneasily be matched with the corresponding industries in the 3rd revision.

• For all other sectors, we use the 3rd digit of the 4-digit level ISIC code in the 3rd revision(which unfortunately is still more detailed than the 3rd digit of the 3-digit ISIC code inthe 2nd revision) and match it with the external dependence ratio of the suggested industryaccording to the correspondence table or, in case of more than one corresponding industry,the industry that is obviously dominating.

• However, in the case of 7 sectors, where each industry from the 3rd revision is correspond-ing to a greater number of industries from the 2nd revision and none of them is obviouslydominating, we use the average of these industries’ external dependence ratios.

• Lastly, in three cases, where an external dependence ratio of a sub-industry in the 3rdrevision data is available, we redefine the top-level industry by excluding this separatelylisted industry from the definition to avoid inconsistencies.

A.3 Political integration index

Our index of political integration is based on the work by Nye (1968) who suggests severaldimensions of political integration: an institutional dimension, policy dimension, attitude dimen-sion (split into government and public opinion), and a stability dimension.

In each geographical region, we focus on the regional integration agreement that we consider themost important one, or the one that delivers the highest degree of political integration: EuropeanUnion (EU) for all transition countries; Union of South American Nations (UNASUR) / South-ern Common Market (MERCOSUR) for South America; Central American Integration System(SICA) for Central American countries; Association of Southeast Asian Nations (ASEAN) forAsian countries; African Union (AU) for African countries; League of Arab States (Arab League)for countries in the Middle East.

For each dimension of political integration, a subindex is constructed that ranges from 0 to 10,where a value of 10 denotes the highest level of political integration. By assigning a weight toeach subindex, we construct the composite index of political integration. Nye (1968) does notsuggest any weighting scheme. We decided to give the highest weight to the institutional andthe policy dimensions (30 per cent and 40 per cent, respectively), and somewhat smaller weightsto the softer factors as attitude (20 per cent) and political stability (10 per cent). The results arenot sensitive to this choice.27 In the following, the construction of each subindex is described indetail.

27Regressions using an index constructed on the basis of equal weights yield virtually the same results.

35

Institutional dimension (30 per cent) We capture the degree of supranationality of each re-gional integration agreement by setting the organisational budgets in relation to the number ofmember countries in the respective regional integration agreement. We collect annual budget fig-ures of all regional integration agreements from various sources for the year 2010. The primarysource is the Yearbook of International Organizations 2010/11, as it provides comparable andup-to-date US dollar figures. We complement these numbers by considering web pages, annualreports, press statements, and newspaper articles.

EU candidate, aspirant, and Eastern Partnership countries in the transition region clearly tendtowards the European Union, but are no official members yet, and thus do not contribute to thebudget. To reflect expectations about future European Union membership, we assigned a shareof the European Union budget to each of them: 25 per cent for candidate countries, 10 percent for aspirant countries, and 1 per cent for Eastern Partnership countries. These numbers arerather conservatively chosen. Similarly, Korea - who is not a full member state of ASEAN, but adialogue partner - is assigned a 75 per cent share of the ASEAN budget figure. In the next step,the corresponding budget figures are divided by the number of member states listed in the CIAWorld Factbook (excluding associated countries and observer countries). The resulting numbersrange from around US-$ 467,000 in the case of UNASUR/MERCOSUR to US-$ 7.2 billion in thecase of the European Union. These numbers are translated into our index scale in the followingway. All European Union countries receive a value of 10. As the distance to all other agreementsis enormous (the ratio between the European Union budget per member state and the secondhighest budget per member state, that from the African Union, is 1539!), all other agreementsare assigned a value of 1. EU aspirant countries are assigned a value of 2, candidate countries avalue of 3.

Policy dimension (40 per cent) The policy dimension is comprised of five subcomponentsthat take on values between 0 and 2, and thus also add up to an index between 0 and 10 (seeTable A.4). The subcomponents are the following.

1. Foreign/security policy coordination: Formal foreign/security policy agreement: 2 (forexample, “European Foreign and Defence Policy”/NATO members), Less formal agree-ments: 1 (for example, “Partnership for Peace” members), No agreement: 0 (for example,Panama).

2. Trade policy coordination: Custom Union: 2 (for example, EU Common Market); Re-gional Trade Agreement: 1 (for example, Rep. Korea: Free Trade Agreement with ASEAN);No Regional Trade Agreement: 0 (-); source: WTO Regional Trade Agreements gateway.

3. Monetary/currency policy coordination: Currency Union: 2 (for example, Euro-membercountries); Moderate policy coordination: 1 (for example, EWS II member countries); Nopolicy coordination: 0 (for example, Brazil).

4. Movement of people Free movement to base country: 2 (for example, Schengen coun-tries); no visa for travel to neighbour/base country required and no visa in return: 1 (for

36

example, Brazil; base country: Argentina); no free movement/visa required: 0 (for ex-ample, Armenia; base country: Germany); for base country definitions, see attitudes -government; source: http://projectvisa.com.

5. More integration intended? Plans to intensify integration: 2 (for example, UNASUR- “to model a community after the European Union which will include a common cur-rency, parliament, passport, and defense policy”); integration as a goal: 1 (for example,African Union - “to accelerate political, social, and economic integration”); no intention ofintegration: 0 (League of Arab States - “promote economic, social, political, and militarycooperation”); sources: CIA World Factbook and subjective assessment.

Attitude dimension - Government (10 per cent) To measure the conformity of governmentviews across countries, we examine the correlation of voting behaviour in the UN General As-sembly (source: Erik Voeten and Adis Merdzanovic, “United Nations General Assembly VotingData”) between each country and a corresponding base country over the period 1998 to 2005(the results are not sensitive to this selection). We use the following base country concept. In afirst step, we usually take the country with the highest US dollar GDP in each regional integra-tion agreement in 2005 as a base country. In case the largest country is included in the sampleitself, we use the second largest country as a corresponding base country. The only exception isthe African Union as the distance between the countries and their corresponding base countries istoo large to assume that a high degree of political integration occurs. Here we use South Africa asa base country for Botswana and Madagascar, and Botswana as a base country for South Africa.We also conduct a number of robustness checks in which we look at the second or even thirdlargest country of the region, but in all cases the correlations are very close. To fit the percentagenumbers to our 1 to 10 scale, we multiply each correlation by 10. In case of negative correlations,a value of 0 is assigned.

Attitude dimension - Public opinion (10 per cent) To capture the attitude of the public to-wards a regional integration agreement, we use data from the World Values Survey. We use thetwo latest waves (1995/1998 and 1999/2000), which are available for a broad list of countries.We focus on the question in the “politics and society” section that asks for the “confidence” in thelocal regional integration agreements. Questions are posed with respect to the following agree-ments: European Union, MERCOSUR, ASEAN, African Union, and the League of Arab States.Thirteen sample countries have been surveyed in both waves, and thus we take the average. Sevencountries in the sample were surveyed only once, so we include the available result. Five coun-try/regional integration agreement pairs are not included in the survey. In the case of Botswanaand Madagascar, we take the value of South Africa with respect to the African Union. For Koreaand Uruguay, we use the confidence in the United Nations by each of the countries as a proxy.For Panama where this question is not available either, we use the survey result for Puerto Ricowith respect to the confidence in the NAFTA as a proxy.

The answer options in all surveys comprise “A great deal,” “Quite a lot,” “Not very much,” and“None at all,” and answers for each category are reported in per cent. The index value of thissubcategory is then constructed as follows: we multiply the given percentage values by 10, 5, -5,

37

and -10, and add 5. This would imply for a country with equally distributed answers (that is, 50per cent would be have confidence in the agreement and 50 per cent not) to receive a score of 5.The value of Albania, which obtains a score of 10.6, is adjusted to the maximum value of 10.

Political stability dimension (10 per cent) Nye (1968) recommended using the number ofhostile incidents over a specified period. We do not find this concept appropriate, therefore we useinstead the Political Stability and Absence of Violence index from the World Bank’s WorldwideGovernance Indicators (WGI) for the years 1998 to 2005. For each country, we compute anaverage value of the Political Stability and Absence of Violence index over this period. Theoriginal index ranges from -2.5 to 2.5 and thus has to be multiplied by 2 and augmented by 5 tofit into the 0 to 10 scale of our index.

A.4 Appendix charts and tables

Chart 5: Current account balances and sector growth in developing countries, 1994-2008

!"#$%&'()*+,&-./"0)+1-0)2(3.)+$.&)1-("24

!"#$%&'()'*%'+,$-+.$'/0--$1#'+//"01#'",$-'2345'+%'0%$6'*1'#7$'-$.-$%%*"1%8'2-"9#7'*%'+,$-+.$'"0#:0#'.-"9#7'+#'#7$'%$/#"-';$,$;8

38

Chart 6: Current account balances and sector growth in European transition countries,1994-2008

!"#$%&'()'*%'+,$-+.$'/0--$1#'+//"01#'",$-'2345'+%'0%$6'*1'#7$'-$.-$%%*"1%8'2-"9#7'*%'+,$-+.$'"0#:0#'.-"9#7'+#'#7$'%$/#"-';$,$;8

Table A.1: Sector-level descriptive statistics

!"#$"%&' (%)'#*"+,-) .'"- /01234'*2 .$- ."5

!"#$%&'#(')*$+!"#$%&"'()*%+,(-,(%.*)/(0 112 3456 52478 9:8486 384:2;<=>#$%;<?,@(*A%&0#*" 112 8482 848: 8488 84:3BC("*<#$%D"-"<?"<'" 112 84E7 84EF 984:3 54:1

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

;->>9%8'#(')*$BS"*I=<I%B,*)-"%D,SSA 112 843E 8438 8 5

?3@$#%A@#$+@"*7%&'#(')*$+L*=O#("%G*"?=(%)O"*%.DL 112 84E5 8422 848E 84F3!"I,$#()*A%T,#$=(A 112 84:3 843F 98475 54E1U*#?"%;<("I*#>)< 112 743 274F 9:145 F847L)$=>'#$%;<("I*#>)<%;<?"C 112 341 246 245 145

39

Table A.2: Evidence on threshold effects - financial integration (foreign bank numbershare)

!" #$%" #%#& ## '%& %#& #

%()*+,-./0-1.

022*3.240)*

%()*+,-./0-1.

-56/*).240)*

&-7523)8.240)* 9:;<=> 9:;<?: 9:;<:? 9:;<:@ 9:;<?= 9:;<?A 9:;<?: 9:;<?< 9:;<=<

B:;:?C B:;:?C B:;:?C B:;:?C B:;:?C B:;:?C B:;:?C B:;:?C B:;:?C

:;>:= 9:;=?D :;?=@ :;@:= :;::E 9:;:>: 9:;:?F :;::< 9:;:EF

B:;=EC B:;@DC B:;A>C B:;?@C B:;ADC B:;AC B:;DFC B:;FAC B:;>AC

9:;EA> 9:;E@< ?;:>F 9:;@ED :;:<@ :;?== :;:E@ :;:@@ :;:AA

B:;:FC B:;<?C B:;>EC B:;<?C B:;:>C B:;?=C B:;:@C B:;<@C B:;?<C

9:;<FF 9:;:A< :;=== 9:;E<= :;:?< :;:@: :;:>F :;:=F :;:A>

B:;<AC B:;F<C B:;EEC B:;?>C B:;><C B:;@DC B:;?DC B:;@DC B:;<DC

!"#$%&#+G*)*-H*.+-.7+G*)*-I0J.+-.)*0J.,)(K34.)03*2

?;F@ ?;<: ?;:< 9:;F? :;E= :;D< ?;<< :;F? ?;:?

L/2*)M0I(-2 FF= FF= FF= FF= FF= FF= FF= FF= FF=

$56/*).(N.!(5-3)+*2 =@ =@ =@ =@ =@ =@ =@ =@ =@

$(3*O.%+-0-H+0J.+-3*,)0I(-.+2.6*025)*7./8.34*.N()*+,-./0-1.-56/*).240)*.N)(6.!J0*22*-2.*3.0J;.B=::EC;.%().(34*).2(5)H*2.0-7.*PQJ0-03()8.-(3*2R.2**.S0/J*2.=R.<R.0-7.

3*P3;

#+G*)*-I0J.2*H3()0J.,)(K34.*G*H3.+-.

T6*),+-,.T5)(Q*

#+G*)*-I0J.2*H3()0J.,)(K34.*G*H3.+-.

H(5-3)+*2.K+34.0/(M*96*7+0-.U-0-H+0J.

+-3*,)0I(-

'()"*($+,&"-"./*&01&2131.03+&01/"4)35$1&67$)"041&8319&1:#8")&*(3)";%

!"#$"%%&'()*'"+*&"(,%-)./0123"%)&().1$"(,4"%"%-)5"."(5"(,)01$&162"7)10"$1#")#$'8,4)&()%"*,'$12)'3,.3,9):;;</=>>?

%+-0-H+0J.+-3*,)0I(-.B%&C.6*025)*

V*H3()0J.,)(K34.*G*H3R.7*Q*-7+-,.(-.

*P3*)-0J.U-0-H*R.+-.(34*).H(5-3)+*2.K+34.

/*J(K96*7+0-.U-0-H+0J.+-3*,)0I(-

40

Table A.3: Regression results when all interaction effects are included jointly, using foreignbank number share

!" #$%" #%#& ## '%& %#& #%()*+,-./0-1.022*3.240)*

%()*+,-./0-1.-56/*).240)*

789:: 789:8; 789:<= 789:< 789:<> 789::? 789::@ 789:@; 789::AB898@C B898@C B898@C B898@C B898@C B898@C B898@C B898@C B898@C

89?<A 898?= 7@9=;= <98<> 7898<8 789@?< 7898=D 8988: 789@8?B89<C B89D=C B89@;C B898<C B89=?C B89A:C B89:C B89D;C B89A@C

7@98;: 7@98:8 @9D<: 7@9;:> 898:D 89@>A 898>: 898;< 898D@B89@C B89:DC B89<<C B898AC B898>C B898;C B89@;C B89<>C B89@=C

789:=D 789;;: 89DD: 7@9:@> 898@< 89@8: 8988? 898A: 898:<B89ADC B89A=C B89<DC B898>C B89??C B89<;C B89D<C B89:?C B89?;C

89@?= 789@<= 89<;> 7898AD 8988= 898<; 898<? 7898@8 898@DB89;=C B89>;C B89;C B89D:C B89;>C B89;DC B89??C B89>AC B89;@C

789A8> 89?8; 89=D= 789:@8 898@< 898A@ 898AA 898@: 898:AB89?<C B89=AC B89?C B89=@C B89?@C B89;@C B89<>C B89;;C B89AAC

898D8 789:<? 789<8A 789D@8 8988D 89888 898<; 8988A 898A<B89>DC B89;=C B89>DC B89@=C B89?DC B@C B89AAC B89DAC B89=<C

!"#$%&#+E*)*-F*.+-.G+E*)*-H0I.+-.)*0I.,)(J34.)03*2<9A8 @9?= @9>> 7<9;8 89D8 89D? @9:8 @9@D @9<8

K/2*)L0H(-2 DD< DD< DD< DD< DD< DD< DD< DD< DD<$56/*).(M.!(5-3)+*2 <? <? <? <? <? <? <? <? <?

!"#$"%%&'()*'"+*&"(,%-)./0123"%)&().1$"(,4"%"%-)5"."(5"(,)01$&162"7)10"$1#")#$'8,4)&()%"*,'$12)'3,.3,9):;;</=>>?

%+-0-F+0I.+-3*,)0H(-.B%&C.6*025)*

#+E*)*-H0I.2*F3()0I.,)(J34.*E*F3.+-.F(5-3)+*2.J+34.0/(L*76*G+0-.+-2H35H(-0I.N50I+3O

#+E*)*-H0I.2*F3()0I.,)(J34.*E*F3.+-.F(5-3)+*2.J+34.0/(L*76*G+0-.P-0-F+0I.+-3*,)0H(-

#+E*)*-H0I.2*F3()0I.,)(J34.*E*F3.+-.F(5-3)+*2.J+34.0/(L*76*G+0-.3)0G*.+-3*,)0H(-

$(3*Q.%+-0-F+0I.+-3*,)0H(-.6*025)*G./O.34*.M()*+,-./0-1.-56/*).240)*9.%().2(5)F*2.0-G.*RSI0-03()O.-(3*2T.2**.U0/I*2.<T.:T.0-G.3*R39

&-G523)O.240)*

V*F3()0I.,)(J34.*E*F3T.G*S*-G+-,.(-.*R3*)-0I.P-0-F*T.+-.(34*).F(5-3)+*2.J+34./*I(J76*G+0-.L0I5*2.(M.0II.34)*24(IG.L0)+0/I*2

#+E*)*-H0I.2*F3()0I.,)(J34.*E*F3.+-.W6*),+-,.W5)(S*

#+E*)*-H0I.2*F3()0I.,)(J34.*E*F3.+-.F(5-3)+*2.J+34.0/(L*76*G+0-.P-0-F+0I.G*L*I(S6*-3

41

Table A.4: Political integration index subscores

!"#$%&' ()*+"$,-.+$%)*&,/"$.,*&))0)$% 1"-+2'.3+0)$4+"$.4#542"&)4

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

!"#$%&'($)#*+"'%&'($',$,-

<+3-.S)T4-).>1)+9)34-)UL-),+">1%.),+**-.5+%E.)3+)34-).,+*-)V(+"&,CV)&%)T$#"-)60I)O+*)$)E-3$&"-E)E-.,*&5Q+%)+9).+>*,-.)$%E)5*+,-E>*-.N).--)3-W3I

.$/0#1(2 3#*,$!"'$(*#2%4"51/2

!"6$7$'(%"8%4$"95$

42