No. 17, May 6, 2010

On the Correlation between Globalization and Vulnerability in Times of Economic Crisis — A Statistical Analysis for Europe

Pim Martens and Bas Amelung
Maastricht University
International Center for Integrated Assessment and Sustainable Development (ICIS)

Abstract: In this paper, we test the hypothesis that more globalized countries in Europe are equally vulnerable to the current crisis as less globalized European countries. To determine the level of globalization, we use the Maastricht Globalization Index (MGI). We measure the severity of the economic crisis with five key economic indicators. The results seem to suggest that the rising level of globalization increases vulnerability to economic crises on the one hand, while, on the other, higher levels of globalization increase the opportunities to deal with a crisis.

Keywords: economic crisis, EU expansion, globality, globalization, indicators, Maastricht Globalization Index, measuring globality

Globalization is something more than a purely economic phenomenon manifesting itself on a global scale. During the last few decades, human dynamics, institutional change, political relations, and the global environment have become more intertwined. Among these visible manifestations of globalization are the greater international movement of goods and services, financial capital, information and people. In addition, there are technological developments, new and enhanced legal systems, and institutions that facilitate these flows. The growth of international cultural exchanges and the spread of multiculturalism and cultural diversity within many countries are changes on the cultural front. The freer trade of more differentiated products as well as tourism facilitates such developments. Flows of immigration – both legal and illegal – also contribute to today’s melting pot societies.

For many commentators there is little doubt that globalization has produced significant gains at the global level (Bhagwati 2004). Foreign trade in goods and services, capital, technology and labor all move more freely across borders. In recent years, evidence has suggested that globalization is a key driver in helping emerging economies to apply knowledge, regulations, and standards acquired from their Western counterparts in order to become more mature, reliable, and hence stable (Pazarbasioglu, Goswami, and Ree 2007). Thus, globalization may have raised stability; stable economic development is one of the cornerstones of a strong and well-functioning economic system, domestically as well as globally.

At the same time, globalization is also perceived to be creating new threats: to individuals, societies, and eco-systems. There are fears that it may exacerbate the gap between rich and poor – both within and between countries – creating new threats to human security in terms of financial volatility, political and cultural insecurity, and environmental degradation. During the transition to greater globalization, risks may arise as application of new economic methodologies outpaces their understanding and control. Hence, a high globalization speed may also generate opportunities for speculation, uncertainty, and risk (Spahr 2008).

The current economic crisis constitutes a serious test for the merits of globalization. Do the more globalized societies enjoy additional stability that cushions the most extreme effects of the crisis, or are these societies more exposed and vulnerable to shocks in other parts of the world precisely because of their global connectedness? The answer to this question may have important policy implications as it is connected to the choice between protectionism and free trade as the guiding principle to combat the economic crisis.

In this paper, we test the hypothesis that more globalized countries in Europe are equally vulnerable to the current crisis as less globalized European countries. To determine the level of globality, we use the Maastricht Globalization Index or “MGI” (Martens and Zywietz 2006) and five key economic indicators as a proxy for the severity of the economic crisis.

The Maastricht Globalization Index and Economic Indicators

The MGI was developed to improve upon the existing indices. Reflecting the need for a balance between broad coverage, data availability, and quality motivated the following choice of indicators (see Table 1) with data for 117 countries. For a detailed discussion on the use of indicators to measure globalization, we refer to Dreher, Gaston and Martens (2008).

 

Table 1: MGI Variables

Category Variable name Variable definition
Political Domain Embassies Absolute number of in-country embassies and high commissions
Organizations Absolute number of memberships in international organizations
Military Trade in conventional arms as a share of military spending
Economic domain Trade Imports + exports of goods and services as a share of GDP
FDI Gross foreign direct stocks as a share of GDP
Capital Gross private capital flows as a share of GDP
Social & Cultural Domain Migrants Those who changes their country of usual residence per 100 inhabitant
Tourism International arrivals + departures per 100 inhabitants
Technological Domain Phone Incoming + outgoing international telephone traffic in minutes per capita
Internet Internet users as a share of population
Ecological Domain Eco footprint Ecological deficit in global hectares

 

The MGI is constructed in a four-stage process (see also UNDP 2002). The first stage is conceptual and choices are made about which variables are most relevant and should be included in the index. In the second stage, suitable quantitative measures are identified for these variables. In the third stage, following Dreher (2006), each variable is transformed to an index with a scale ranging from zero to a hundred (this differs from earlier calculations constructing the MGI). Higher values denote more globalization. The data are then transformed – on the domain level – according to the percentiles of the base year (2000) distribution (using the formula ((Vi-Vmin)/(Vmax-Vmin)*100). In the last and final stage, a weighted sum of the measures is calculated to produce the final score, which is then used to rank and compare countries. The “most globalized” country has the highest globality score. Within each domain, every variable is equally weighted. The MGI scores are simply added, that is, all domains receive the same weight. In this paper, we use the MGI calculated for 2008.

The MGI values were taken from the global studies for 2000 and 2008. For the analyses in this paper, 29 countries in Europe were selected (see Table 2 for a list), a group of countries for which recent, reliable, and sufficient data were available to determine the MGI as well as the economic crisis indicators. To capture the key facets of the economic crisis, we used the following five indicators (see Eurostat).

 

Table 2: Maastricht Globalization Index (2008)

Country Rank MGI
2008
Change score
2000-2008
Change rank
2000-2008
Ireland 1 72.0 20.2 1
Belgium 2 68.4 18.5 3
Switzerland 3 68.3 9.8 -2
Netherlands 4 68.3 19.7 3
France 5 62.5 17.6 7
Austria 6 62.1 12.2 0
United Kingdom 8 58.7 7.4 -5
Germany 9 54.8 8.8 1
Denmark 10 53.8 7.0 -1
Spain 11 53.1 14.9 7
Italy 13 51.7 13.1 3
Sweden 14 51.6 4.5 -6
Estonia 15 50.5 11.5 0
Czech Republic 17 49.3 12.2 2
Norway 20 48.0 -3.0 -16
Greece 21 47.8 12.0 0
Portugal 22 46.8 7.6 -8
Croatia 24 45.5 15.2 4
Slovenia 26 43.2 14.0 5
Hungary 27 43.0 7.7 -5
Bulgaria 29 39.5 13.1 8
Poland 30 37.0 6.5 -3
Slovakia 31 36.3 9.0 4
Finland 32 36.3 -0.6 -12
Romania 35 33.4 8.5 7
Turkey 40 32.1 6.6 -1
Lithuania 47 30.6 9.3 17
Latvia 50 30.2 7.6 2
Macedonia 58 28.6 6.1 0

 

Real GDP Growth Rate

Gross domestic product (GDP) is a measure of the economic activity, defined as the value of all goods and services produced less the value of any goods or services used in their creation. The calculation of the annual growth rate of GDP volume is intended to allow comparisons of the dynamics of economic development both over time and between economies of different sizes. For measuring the growth rate of GDP in terms of volumes, the GDP at current prices are valued in the prices of the previous year and the thus computed volume changes are imposed on the level of a reference year; this is called a chain-linked series. Accordingly, price movements will not inflate the growth rate.

Employment Rate

The employment rate is calculated by dividing the number of persons aged 15 to 64 in employment by the total population of the same age group. The indicator is based on the EU Labor Force Survey. The survey covers the entire population living in private households and excludes those in collective households such as boarding houses, halls of residence and hospitals. Employed population consists of those persons who during the reference week did any work for pay or profit for at least one hour, or were not working but had jobs from which they were temporarily absent.

Annual Average Inflation Rate

Harmonized Indices of Consumer Prices (HICPs) are designed for international comparisons of consumer price inflation. HICP is used for example by the European Central Bank for monitoring of inflation in the Economic and Monetary Union and for the assessment of inflation convergence as required under Article 121 of the Treaty of Amsterdam.

Total Investment

This indicator is defined as total gross fixed capital formation (GFCF) expressed as a percentage of GDP, for the public and private sectors. GFCF consists of resident producers acquisitions, less disposals of fixed assets plus certain additions to the value of nonproduced (usually natural) assets realized by productive activity. It also includes certain additions to the value of non-produced assets realized by productive activity, such as improvements to land. The ratio gives the share of GDP that is used by the public and private sector for investment (rather than being used for consumption or exports).

General Government Debt

General government debt comprises total combined debt of central, state, and local governments plus social security funds as a percentage of GDP at current market prices. Debt is valued at nominal (face) value, and foreign currency debt is converted into national currency using end-year market exchange rates. All non-euro data are converted into euro using end-year exchange rates provided by the European Central Bank.

Results

In search of links between the MGI and economic performance, we first looked for correlations between the MGI and the economic indicators. In 2008, all economic variables except for total investment are significantly correlated with the MGI. In 2000, in contrast, this only applies to the employment rate and the level of inflation. On the level of the individual domains and variables of globalization for the year 2008, the correlations between the MGI and employment rate and inflation are largely driven by the technological and economic domain of globalization (see Table A.1 for details). The political domain furthermore influences inflation, total investment, and general government debt as well. In addition, there is a strong correlation between the social and cultural domain and employment rate, and between the ecological domain and general government debt.

To compare the difference in more and less globalized countries, the countries are separated into two sub-samples according to their overall index score. Except for the employment rate and inflation, no significant differences in the economic indicators were found between more and less globalized countries for 2000 and 2008 (details are in Table A.2). More globalized countries seem to do better in terms of employment, and have less inflation. The economic crisis, starting to have its impacts in 2008, affected more and less globalized countries about equally (see Table A.3 for details). Inflation, total investment, and general government debt did not significantly change between 2000 and 2008, whereas GDP growth and employment rates did change significantly for both groups of countries.

Discussion and Conclusions

The effects of globalization on economic processes have frequently been analyzed using conventional measures of globalization. Edison et al. (2002) who find that no robust relationship exists provide a detailed analysis of the impact of several indicators on financial integration and growth. In this paper, we searched for differences between the economic performance of more and less globalized countries after the start of the latest economic crisis.

The economic performance indicators for 2008 have undoubtedly been affected by the current economic crisis that started that same year. It is very difficult, however, to determine the magnitude of this influence and its relevance for the changes between 2000 and 2008. In this paper, we provide a first and rough assessment. No evidence was found for significant differences in economic performance between European countries that score relatively high and those that score relatively low on the MGI index of globalization. This supports the idea that, although countries with a higher level of globalization tend to have more mature economic systems with well-established regulations and sophisticated financial instruments, they suffer just as much in crises.

To determine whether one country is more vulnerable to the economic crisis than another requires a comparison between the situation before and during or after the crisis. A challenge in such cases is to determine what part of the observed changes is attributable to the specific phenomenon in which one is interested. In this paper, the major challenge was to attribute changes in economic performance to the economic crisis and, subsequently, to correlate these attributed changes to differences in MGI scores. Between the reference period of 2000 and 2008, large changes have taken place in the economic performance of many of the countries analyzed. In particular, countries with lower MGI scores seem to have been catching up. Lower-scoring countries experienced higher growth, a larger increase in employment and investment, and a stronger reduction in inflation and government debt. A main driver of these changes seems to be the expansion of the European Union. New member states and countries aspiring EU membership are overrepresented in the group of countries with low MGI scores, which coincides with the group of countries that have been catching up.

In follow-up studies, it is advisable to try to reduce the effect of EU expansion as a confounding factor by a) reducing the gap between the pre-crisis reference period and the post-crisis period, b) shortening these periods, and c) using time series data. One could consider using quarterly or monthly data, rather than annual data; taking the four quarters of 2007 as the reference periods, rather than the year 2000; and looking at the subsequent quarters (starting with the first quarter of 2008) to analyze how the crisis unfolded.

Furthermore, what is clear is that the increasing complexity of our global society means that globalization cannot be addressed from a single perspective, country or scientific discipline. The vulnerability to economic crises as experienced in the context of globalization is far more complex than most problems that had to be tackled in the past. To adapt policies and planning to the impacts of the consequences of globalization requires new paradigms and innovative methods. It is our hope that a further analysis of globalization may help in adjusting and optimizing the process of globalization on every level in the direction of a more sustainable development, including a robust economy.

 

Appendix: Detailed Statistical Results

Table A.1 lists Spearman’s rho values, representing the correlation between MGI scores and the economic indicators. Spearman rank correlation is a non parametric test that is used to measure the degree of association between two variables. Correlations tagged with a * or a ** mark are significant at the 0.05 level and the 0.01 level respectively. Figure A.1 show the scatter plots of the linear regressions.

Table A.1: Spearman’s rho correlations for MGI and the economic indicators

  GDP growth rate Employment rate Inflation Total investment General government debt
MGI 2000 -0.218 0.707** -0.469* 0.057 0.171
MGI domains          
Political -0.229 0.152 -0.502** -0.157 0.610**
Economical 0.081 0.493** -0.060 0.253 -0.351
Social & cultural 0.174 0.286 -0.280 0.393* -0.174
Technological -0.167 0.674** -0.457* 0.058 0.099
Ecological -0.358* 0.110 -0.185 0.200 0.268
MGI variables          
Embassies -0.348 0.210 -0.404* -0.217 0.571**
Organizations -0.247 0.421* -0.519** -0.199 0.476*
Military -0.170 -0.107 0.246 -0.381* 0.163
Trade 0.221 -0.032 0.276 0.431* -0.427*
FDI 0.025 0.520** -0.290 0.146 -0.130
Capital -0.038 0.490** -0.463* 0.182 0.004
Tourism 0.106 0.333 -0.153 0.393* -0.074
Migrants 0.141 0.360 -0.496** 0.052 -0.199
Internet -0.251 0.808** -0.484** -0.134 0.170
Phone -0.172 0.697** -0.383* 0.075 0.110
Eco footprint -0.366* 0.159 -0.194 0.160 0.288

 

         
MGI 2008 -0.386* 0.446* -0.694** -0.348 0.456*
MGI domains          
Political -0.196 0.001 -0.504** -0.493** 0.709**
Economical -0.144 0.533** -0.117 0.008 -0.166
Social & cultural -0.192 0.512** -0.151 0.261 0.013
Technological -0.448* 0.777** -0.636** -0.247 0.153
Ecological -0.049 -0.031 -0.447* -0.238 0.509**
MGI variables          
Embassies -0.176 -0.020 -0.440* -0.425* 0.620**
Organizations -0.331 0.250 -0.659** -0.606** 0.644**
xMilitary 0.227 -0.386* 0.283 -0.012 0.056
Trade 0.127 0.059 0.284 0.437* -0.435*
FDI -0.428* 0.625** -0.526** -0.265 0.144
Capital -0.558** 0.672** -0.550** -0.330 0.173
Tourism -0.221 0.336 -0.201 0.111 0.071
Migrants -0.473* 0.638** -0.427* -0.072 0.032
Internet -0.403* 0.795** -0.488** -0.261 0.015
Phone -0.416* 0.672** -0.794** -0.449* 0.414*
Eco footprint -0.009 -0.031 -0.415* -0.225 0.509**

* Significant at the 0.05 level (2-tailed)

** Significant at the 0.01 level (2-tailed)

 

Figure A.1: Scatter plots and linear regression between MGI and the economic indicators

 

The following tables show the t-values resulting from the t-test of the null hypothesis that there is no difference between (the means of) less and more globalized countries in terms of their economic performance in 2000 and 2008 (Table A.2), and between 2000 and 2008 (Table A.3). A two-sided t- test is a statistical test used in inference, in which a given statistical hypothesis , H0 (null hypothesis) is rejected when the value of the statistic is either sufficiently small or sufficiently large. T-values tagged with a * or a ** mark are significant at the 0.05 level and the 0.01 level respectively. The threshold used to distinguish between less and more globalized countries is the average of the 2008 global index mean and maximum values.

Table A.2: T-test (means between less and more globalized countries within a given year)

Year GDP growth rate Employment rate Inflation Total investment General government debt
2000 -0.635 5.040** -2.240* -1.390 0.593
2008 -1.659 2.252* -3.642** -1.910 1.169

* Significant at the 0.05 level (2-tailed)

** Significant at the 0.01 level (2 tailed)

 

Table A.3: T-test (means between less and more globalized countries between 2000 and 2008)

Year GDP growth rate Employment rate Inflation Total investment General government debt
All countries 3.793** -4.804** 0.903 -1.961 1.286
Less globalized 2.324* -3.418** 1.039 -2.083 0.967
More globalized 4.001** -4.497** -1.856 0.015 0.579

* Significant at the 0.05 level (2-tailed)

** Significant at the 0.01 level (2 tailed)


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