LINKS BETWEEN GOVERNANCE AND ...

LINKS BETWEEN GOVERNANCE AND DEVELOPMENT Veli Himanen Relate Partnership, Finland [email protected] ABSTRACT This paper aims to link public governance with economic and social development. The aim brings forth two research questions: how to assess the quality of governance and how to determine links between governance and development. Our approach combines categories of social orders with indicators available in public databases. Then we screen data on 143 countries in 2007 in order to check the usability of this approach and to find out links between governance and development. Our analyses prove that corruption perception index scores (CPI scores) explain best differences between countries in the quality of governance as well in economic and social development. Additional explanations can be searched from ease of doing business and from economic inequality. Still, there is room for differences originating from regional characteristics. Even though the paper is addressing an extensively studied area, the new approach could still promote a distinctive contribution for the current scientific debate. Keywords: Economic development, International comparison, Public governance, Social development. 1 INTRODUCTION The paper aims to highlight possible links between the quality of governance and economic and social development. Therefore, the paper analyses: first, the quality of public governance in 143 countries in 2007;i second, possible links between the quality of governance and economic development; third, possible links between the quality of governance, economic development, and social development, and fourth, observed development paths. We start our search by generating a new approach for assessing the quality of governance and then use it in the following analyses. 2 QUALITY OF PUPLIC GOVERNANCE It is not at all clear how to define the quality of public governance. It seems that many authors consider that democracy is synonym for good governance. According to the following analyses, corruption perception index score (CPI score) provides the best indicator for the quality of governance.ii Our analyses below prove that governance has also special regional features. 2.1 Theoretical Approaches As a concrete attempt to categorise governing regimes, the Polity IV Project has calculated authority indexes for all countries based on a scale ranging from -10, meaning a hereditary monarchy, up to +10, meaning a consolidated democracy.iii According to the Project, the number of consolidated democracies was around 25. There are, of course, many other approaches for assessing the quality of governance. Marshall and Cole (2008, pp. 16-17) have provided so called fragility index that describes the efficiency and legitimacy of governments. A total of 19 countries got the best value and 13 the next best. Lijphart (1999, p. 48) claimed that there were 36 countries (with population over 250,000) that had been continuously democratic since 1977. North et al. (2009) claimed that today we have, in principle, only two types of social orders:

limited access orders and open access orders. The difference between these two types stays in the limits to form organisations. The first ones restrict the rights to form organisations for the national elites and the last ones leave them open to all citizens. They stated that only 25 countries had open access orders and the rest had limited access orders or had reached threshold conditions between these two. Thus, there have been differences between authors how to measure the quality of governance, and the number of the countries with the best governance system has varied between 19 and 36. Roskin (2004) turned the question upside down by claiming that in order to assess different regimes, it is best to study their results. Next we shall develop own approach for assessing the quality of governance that combines above mentioned categories of social orders with some indicators. But we shall remember also Roskin’s advice. We can divide social orders into economic and political spheres that are, of course, tightly knighted in countries with limited access orders. There are some indicators available in public databases which provide possibilities to measure the scale of access into these spheres. On the economic sphere, it seems at first sight obvious that ease of doing business describe this.iv In order to find indicators that describe access into the political sphere, we have to consider basic characteristics of the limited access societies that are driven by the elites. When economic and political issues are there interlinked, it is obvious that traditional gift exchange is common. Thus, we can use CPI scores as proxies for the access into the political sphere. The share of national income for the richest decile could also be used for the same purpose, because it is probable that the elites take a bigger share in the limited access than in the open access societies. However, when considering these three indicators in detail, we can notice limitations in their use. First, because good ranking in ease of doing business needs obviously a highly developed administration, it is clear that the indicator is also showing access to the political sphere – not only to the economic one. In addition to that, a more serious problem is related to the ordinal ranking provided by the database that does not reveal the amount of differences between countries achievements.v Second, the use of data on the share of the richest decile is limited because of inaccuracies and differences between national studies. According to Human Developed Report 2007/2008, some countries have studied income and some expenditure and the studies are from different years; from 1993 to 2005. On the other hand, CPI scores seem to be well suited for our purposes. It is interesting to notice that CPI scores correlate well with average GNI (PPP) per capita. They explain 78 per cent of variation between countries and when removing big oil exporters, 84 per cent. Therefore, we start next analysis with CPI scores and, when necessary, complete them with other indicators. 2.2 Quality of Governance in 143 Countries in 2007 The distribution of CPI scores (cp. Figure 1) show a diminishing difference between countries from the biggest scores to the smallest ones. In addition, we may notice a clear drop around the score 6. In order to be able to analyse the included countries further on, we have divided them into six baskets according to their CPI scores (see Table 1).

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101 106 111 116 121 126 131 136 141

CPI score

10 9 8 7 6 5 4 3 2 1 0

Figure 1: CPI scores in 2007 in 143 countries (data source: Transparency International, 2007). Transparency International has provided confidence intervals for CPI scores that give the range inside which a score is according to 90 per cent probability. Therefore, we can see that there existed quite clear difference between the first two baskets. However, differences between the other baskets were not that clear, e.g. Basket Three had 11 countries with the lower ends of their Table 1: The quality of governing in 143 countries in 2007 according to CPI scores (order according to CPI scores and the countries with the same score are in the alphabetic order). One Denmark Finland New Zealand Singapore Sweden Netherlands Switzerland Canada Norway Australia United Kingdom Hong Kong Austria Germany Ireland Japan France United States Belgium Chile Spain Uruguay Slovenia Estonia Portugal Israel

Two Botswana Hungary Italy Czech Rep. Korea Rep. Malaysia South Africa Costa Rica Slovakia Latvia Lithuania Jordan Mauritius Oman Greece Namibia Kuwait Poland Tunisia Bulgaria Croatia Turkey El Salvador

Basket Three Four Colombia Algeria Ghana Armenia Romania Dominican R Senegal Lebanon. Brazil Mongolia China Albania India Argentina Mexico Bolivia Morocco Burkina Faso Peru Egypt Georgia Eritrea Saudi Arabia Guatemala Serbia Moldova Trinidad and T. Mozambique Bosnia and Her. Rwanda Gabon Uganda Jamaica Benin Lesotho Malawi Macedonia FYR Mali Swaziland Ukraine Thailand Nicaragua Madagascar Niger Panama Mauritania Sri Lanka Timor-Leste Tanzania Vietnam Zambia

Five Burundi Honduras Iran Libya Nepal Phlippines Yemen Cameroon Ethiopia Pakistan Paraguay Syria Gambia Indonesia Russia Togo Angola Guinea-Bissau Nigeria

Six Azerbaijan Belarus Congo Republic Côte d'Ivoire Ecuador Kazakhstan Kenya Kyrgyzstan Liberia Sierra Leone Tajikistan Bangladesh Cambodia Central African R. Papua New Guinea Turkmenistan Venezuela Congo Dem. Rep Guinea Laos. Chad Sudan Uzbekistan Haiti

confidence intervals dropping down to Basket Four and correspondingly Basket Four had 8 countries with the upper ends of their confidence intervals reaching to Basket Three. In principle, we can state that for individual countries near the lower or upper end of their baskets (excluding the border between the first two baskets) it is not sure to which basket they actually belonged. But this uncertainty does not disturb general conclusions to be drawn below. However, it means that small differences between countries’ scores are uncertain for comparison. Thus, we cannot be certain, e.g. if there were less corruption in the United Kingdom than in Hong Kong, but quite certain that there were less corruption in the United Kingdom than in France and the United States but more than in Sweden and Singapore. There exists regularity among the baskets, so that also average ease of doing business scores and average GNI (PPP) per capita diminish from basket to basket (see Table 2). Average GNI (PPP) per capita in Basket Five forms the only anomaly. This is probably due to many big oil exporters in that basket. As proved by Himanen (2013, p. 104), big oil exporters can have high affluence compared to their CPI scores. Table 2. Average CPI and ease of doing business scores and average GNI per capita in 143 countries divided into six baskets according to their CPI scores (Himanen 2013, p. 143)

Basket One Two Three Four Five Six

Total/average

Number of countries 26 23 25 26 19 24 143

Average Average ease of Average GNI CPI score doing business (PPP) per capita in 2007 score in 2007 (1 in 2007 ($) 7.9 8.9 33490 4.7 7.2 16560 3.4 5.6 7110 2.8 3.7 3520 2.4 3870 3.3 2.0 3230 3.3 4.0

5,4

11700

When comparing the above baskets with the other approaches referred above, we may notice that the number of countries in Basket One is about the same as in many other estimates of the best governed countries. When aligning our baskets with the approach of North et al. (2009), we can form three categories of states: i) Basket One includes countries with the open access social orders; ii) countries in Baskets Two and Three have reached threshold conditions for moving into open access orders; and iii) countries in the last three baskets have stayed in limited access orders. We will consider the stability of these three categories below in the connection of development paths. 3 GOVERNANCE AND ECONOMIC DEVELOPMENT Above we noticed very strong correlation between average GNI (PPP) per capita and CPI scores in 2007. This is most interesting result when the relationship between governance and economic development is a thoroughly studied subject, but the current literature leaves a reader – to say the least – in a bewildered state. We screen next recent literature on the subject and then discuss own results for different countries and regions.

3.1 Bewildering Theories Acemoglu and Robinson (2012, pp. 44-69) argued that the current big differences in countries’ affluence cannot be explained by the earlier proposed theories. They named the following failed theories: i) the geography hypothesis, advocated in his time by philosophy Montesquieu and later on by Diamond (1997) and Sachs (2006); ii) the cultural hypothesis, starting from Max Weber’s idea about the importance of the Protestant ethic, and recently advocated again by Landes (1999, p. 510); and iii) the ignorance hypothesis that citizens and governments do not know how to improve situation. Acemoglu and Robinson concentrated in explainingon why poor nations got it wrong, and their answer includes solving basic political problems and thereby establishing good institutions and governance. However, Banerjee & Duflo (2011, pp. 233-43) proved that the major figures in development economics, like Acemoglu, Robinson, Easterly, and Sachs had got it wrong. The correct answer can be found in marginal stepwise improvements (policies instead of politics) under the current (imperfect) institutions because wholesale changes in institutions are very rear and can also be counterproductive. De Soto (2001, p. 6) stated that development was restricted because possessions already existing in poor countries are not adequately documented and therefore cannot be turned into capital, but Sachs (2006, p. 321) claimed that de Soto had got it wrong. On the top of this, we can notice that Keen (2011) proved that the current mainstream concept of economics, neoclassical one, is fundamentally flawed and therefore have led macroeconomics into a totally wrong direction. In addition to the above mentioned broad approaches, we may notice exercises aimed to find statistical relationships between governance and economic development. However, according to North et al. (2009, pp. 2- 3), it has remained open if there is a causal link. Actually, we noticed above very strong correlation between GNI (PPP) per capita and CPI scores, and in order to check the meaning of this correlation we screen next the exceptions. 3.2 Exceptions Confirm the Rule When considering a country to have exceptional character if its GNI (PPP) per capita is more than 10 per cent out of the general patterns of a basket, we found 47 countries (of a total of 143) of which 21 were richer and 26 poorer than the common limits for the relevant baskets. The reason for greater richness in 14 countries was income from oil and gas exports. Regarding the remaining seven countries without big oil or gas exports, we can notice that: i) Greece had the lowest CPI score and ease of doing business score in Western Europe and therefore it is possible that a regional impact has increased Greece’s affluence into a higher level than Greece’s scores suggested; ii) Italy has been relatively losing affluence that can be due to the poor quality of governance (the second lowest ease of doing business and CPI scores) when compared to other Western European countries; iii) South Korea’s GNI (PPP) per capita was not very much over the upper limit of Basket Two and therefore the necessary explanation can be found in the high rank in ease of doing business; iv) Argentina has been relatively losing affluence for a long time possibly due to the poor quality of governance like Italy above; v) Lebanon’s special features originate probably from the long civil war; vi) both Ukraine and Belarus had higher affluence than there CPI scores could explain and we may suspect some regional impact. Twenty sub-Saharan countries were included in the group of 26 poorer countries. The reasons for the over-representation of sub-Saharan countries can be the colonisation period and the civil wars that made these countries so poor that it takes a long time before improved governance can

increase affluence. In addition, we have to remember the impacts of malaria and HIV/AIDS. Regarding the four countries from South America, we may claim that in these countries there still existed some restrictive features like low ease of doing business and/or high economic inequality. Behind the relative poverty of Tunisia and Jordan we can expect some regional cause added by somewhat low ease of doing business score in Jordan. As a conclusion for the above analysis, I want to state that, in principle, good governance (assessed according to CPI scores) explains well differences between countries’ GNI (PPP) per capita. The exceptions of this rule are mainly due to oil and gas exports and to some kind of regional effect. Thus we can agree with Acemoglu’s and Robinson’s statement above that good governance is most important but still insist that, in addition, there exists some regional impacts originating from geography, history, religion, culture or whatever. After this discussion on governance and economy, we will consider how these are related to social development. 4 SOCIAL DEVELOPMENT The definition of social development is, of course, a complicated issue. Without going into theoretical discussions, we consider next how well countries have succeeded to empower and protect citizens. The aim is to highlight countries’ achievements in 2007 explained either by national income per capita or by the quality of governance. 4.1 Empowering Citizens Empowerment includes here three domains: education, economic equality, and average life expectation at birth. Achievements in education are next considered according to primary enrolment rates, PISA scores, and top university rates. Differences in education are quite difficult to define because no indicator is suitable for all categories of countries: primary enrolment rates are suitable for poor and middle-income countries, PISA scores for middle-income and rich countries, and top university rates for rich countries. Primary enrolment rates followed countries’ GNI (PPP) per capita (R2=0.44) better than CPI scores (R2=0.26). The lower correlation of the latter was mainly due to the fact that many postSoviet countries had quite high enrolment rates despite their low CPI scores and the same was also true for some Asian countries. In principle, sub-Saharan countries had lower than average enrolment rates. That was not totally due to their low affluence, but was also a regional feature. However, we may notice that some poor African countries in baskets 3 and 4 had reached enrolment rates around 90 per cent, i.e. relatively good governing had improved education options despite of poverty. We can notice also that among the rich countries (GNI (PPP) over $15,000 in 2007) there were five countries (including both oil exporters and post-Communist countries) with somewhat low enrolment rates. These all were actually from Basket Two, and thus worse governing (compared to other rich countries in Basket One) could be a reason. An enrolment rate describes the share of children receiving the basic education. The efficiency of education has been assessed by the PISA studies. PISA scores correlated quite well with GNI (PPP) per capita (R2=0.74) and almost as well with CPI scores (R2=0.62). There were quite interesting regional differences, even when considering the limited number of countries included in the PISA studies. First, the Pacific was clearly the best region. Second, Eastern Europe (including also the Baltic States and Russia) had quite similar results as Western Europe. Third, some countries from South America had quite low scores. The top universities were very much

concentrated into the rich countries.vi Most of them had at least two top universities per ten million inhabitants. The exceptions that did not have any were either big oil exporters or quite small countries. The rate of top universities per ten million inhabitants correlated as well with GNI (PPP) per capita (R2=0.82) as with CPI scores (R2=0.81). We will discuss economic equality with the aid of inequality ratio that is the share of national income for the richest decile divided by that for the poorest decile. Economic inequality correlates neither with GNI (PPP) per capita nor with CPI scores. However, there is a regularity that all rich countries had ratios below 20 (there was no data of the big oil exporters: Kuwait, Saudi Arabia, and Oman), and correspondingly there was only one country, Chile, with inequality ratio over 20 in Basket One. Economic inequality seems to be very much a regional phenomenon; low inequality ratios were common in Eurasia when high ratios were common in Latin America and Southern Africa. Average life expectancy at birth correlated well with GNI (PPP) per capita (R2=0.67) and CPI scores (R2=0.66). The high explanation powers were due to the fact that rich countries had also high CPI scores and long life expectancy at birth when poor sub-Saharan countries had very low life expectancy at birth as well as low CPI scores. Two regional characteristics were obvious: first, very short life expectancy in sub-Saharan Africa almost disregarding of wealth or CPI scores; and second, the post-Soviet countries had clearly low life expectation at birth, even if considering differences in income. 4.2 Protecting Citizens Here we will discuss homicides, road traffic deaths and prisoners. The rate of homicides correlated almost as well with GNI (PPP) per capita (R2=0.35) as with CPI scores (R2=0.29). Thus, homicide rates were usually higher in the countries with low affluence and/or low CPI score, but there were a lot of exceptions. The modest explanation power was probably due to rather strong regional impacts; especially in Latin America there were many countries with very high rates. Also, most post-Soviet countries had, compared to other Eurasian states, high rates. Road traffic death rates correlated as well with GNI (PPP) per capita (R2=0.50) as with CPI scores (R2=0.49). Relatively high explanation power is due to the money needed for construction, maintenance, and control of road networks as well as to the capable administration needed for law enforcement. However, only a half of differences between countries could be explained by the above indicators, and we may suppose that the other half can be attached to some historical or regional reasons, like high road traffic death rates in Africa. In a way, CPI score analysis complement GNI (PPP) per capita analysis. For example, Greece and Kuwait had quite high road traffic death rates when compared to their affluence, but quite normal if compared to their CPI scores. Prisoner rates did not correlate with GNI (PPP) per capita or with CPI scores. Regional influence was a major explaining factor, so that most Western European countries had low rates, most postSoviet countries had high rates, and the United States had the highest rate. In addition, we have to remember that low income countries (average GNI (PPP) per capita below $3000 in 2007) had low rates, probably due to their inefficient legal systems.

We may conclude that both GNI (PPP) per capita and CPI scores influence empowerment and protection of citizens. This is, of course, an expected result when these indicators are strongly correlated, but as we noticed above they may have also somewhat separate influences. In addition, some regional features seem to have big independent impacts. 5 DEVELOPMENT PATHS Historical evidence proves that most countries – but not all – have got richer during the last decades, even though there have been big differences in economic growth rates. During 19702007, only 20 countries (of the included 143 countries) had average annual real growth rate per capita of at least three per cent that means that their citizens’ average GNI (PPP) per capita increased three times during these years.vii About a half of these countries were from Asia and the rest were spread around the world. During more recent years 1996-2007, there were 20 countries with economic growth rates of at least 4.5 per cent that means some 70 per cent increase in their citizens’ affluence during these years. A half of these were post-Communist countries and almost a half of the rest were again Asian countries. Thus behind these high growth rates, we can see both regional causes – whatever they are – and wholesale regime changes. As a recent great example of wholesale regime changes, we discuss next post-Communist countries and after them try to assess the direction of changes in the quality of governance. 5.1 Post-Communist Countries As a starting point, we have to remember that the Communist regimes were extremely restrictive regarding access to political and economic spheres. Both were reserved mainly for the members of the ruling Communist party that formed therefore the national elites. Because these elites were better educated and had better networks and financing opportunities than other citizens, they could exploit the opportunities that the change of the regime provided. This meant for them options to capture political and economic power also after the regime change. Therefore, based on the original changes around 1990 and later development, quite different regimes have emerged. As a rough structure for the situation in 2007, we can divide the post-Communist statesviii into three major blocks according to the liberalisation of access to political and economic spheres (cp Table 1): i) liberal access countries included Slovenia and Estonia; ii) threshold countries included most Eastern European countries and Lithuania, Latvia, Georgia, and China; iii) limited access countries: included Albania, most post-Soviet countries added by Mongolia, Vietnam, Laos and Cambodia. Although the national Communist parties have kept power in China, Vietnam, and Laos, these countries have liberated access to the economic sphere. In principle, it is clear that European post-Communist countries had better public governance than Asian ones. However, we have to notice that China was included in the threshold countries. 5.2 Progress or Regress? We concluded above that CPI scores formed the best indicators for assessing the quality of governance. With the aid of these scores, we divided the included countries into three categories according to their development stages. We try next to assess possible general tendencies in development by analysing countries movements between these three categories from 2007 to 2011. We will consider that a change has happened if the CPI scores differ from each other at least by 0.4 that correspondence with the common confidence range in 2007.ix The average CPI score for all 143 countries was 3.9 both in 2007 and 2011. However, there were 44 countries that

had a significant (at least 0.4) change in their CPI scores from 2007 to 2011, of which 27 scores were reduced and 17 improved. In Basket One, CPI scores were increased in two and decreased in four countries. However, all countries could still be included in Basket One. Among the threshold countries, CPI scores were improved in five and decreased in fifteen countries. Botswana had the highest CPI score in 2007 in Basket Two and had still improved position so that Botswana could be upgraded into Basket One in 2011as a first country from Africa. On the other hand, Senegal and Mexico from Basket Three had so low CPI scores in 2011 that they could be moved to Basket Four, i.e. out of the threshold category. Instead of them, Rwanda, Zambia, and the Gambia, could be moved from the limited access order countries to the threshold category in 2011. As noticed above, the average CPI score for all countries had not changed from 2007 to 2011, even though, there were more countries with decreased than increased scores. In principle, the above defined three categories were quite stable. The countries with changes in CPI scores were spread all over the world. A minor tendency that the development was most positive in subSaharan countries and most negative in European countries is, of course, quite uncertain due to the small number of changes per region. When interpreting these results, we may remember that the financial crisis that started in 2008 was still ongoing in 2011. The crisis was worst in Europe that could explain reductions in CPI scores in many European countries when a positive economic growth in many sub-Saharan countries could explain a more positive development there. These speculations would provide some support for the connection between economic growth and the quality of governance. 6 CONCLUSIONS Our new approach for assessing the quality of governance by CPI scores divides the world into three distinct categories: 26 countries with open access social orders; 48 countries with threshold conditions; and 69 countries with limited access social orders. In principle, there is no certainty that states are improving their governance; we could notice both progress and regress. CPI scores explain well differences in countries’ affluence, and exceptions are mainly caused by oil and gas exports added by some regional effects. Many phenomena related to empowering and protecting citizens could be explained either by affluence or by the quality of governing. However, on top of that, we could notice the impact of regional features. Thus short average life expectancy at birth was a sub-Saharan feature and in a milder form also found in post-Soviet countries. Economic equality was best in Eurasia and worst in Latin America. High rates of homicides were common in Latin America and relatively high also in post-Soviet countries. Road traffic death rates were high in Africa. The highest rate of prisoners was in the United States and also quite high rates were common in most post-Soviet countries. The use of CPI scores for assessing the quality of governance can be complemented by two other indicators that aid to explain many differing characteristics: ease of doing business and economic inequality. It is possible that CPI scores highlight, in addition to corruption and access to the political sphere, also the general business climate in the country and by that way reflect access also to the economic sphere. In principle, this paper has opened a simple approach, by using CPI

scores as proxies for the quality of governance, to analyse many interlinking phenomena of our complex world. 7 BIBLIOGRAPHY 1. Acemoglu, D. and Robinson, J. A. (2012). Why Nations Fail: The Origins of Power, Prosperity, and Poverty. New York: Crown Publishers. 2. Banerjee, A. V. & Duflo, E. (2011). Poor Economics: A Radical Rethinking of the Way to Fight Global Poverty. New York: Public Affairs. 3. De Soto, H. (2001). The Mystery of Capital: Why Capitalism Triumphs in the West and Fails Everywhere Else. London: Black Swan. 4. Diamond. J. (1999). Guns, Germs, and Steel: The Fates of Human Societies. New York: W.W. Norton & Company. 5. Himanen, V. (2013). Missing decent living for everybody; Success and Failure in 143 Countries. (to be published) 6. Keen, S. (2011). Debunking Economics: The Naked Emperor Dethroned. London: Zed Books. 7. Landes, D. S. (1999). The Wealth and Poverty of Nations: Why Some Are So Rich and Some So Poor. New York: W.W. Norton & Co. 8. Lijphart, A. (1999). Patterns of Democracy: Government Forms and Performance in ThirtySix Countries. New Haven and London: Yale University Press. 9. Marshall, M. and Cole, B. R. (2008). Global Report on Conflict and State Fragility. Foreign Policy Bulletin 18.1. (pp. 3-21) -21. Cambridge University Press. Retrieved from: http://www.systemicpeace.org/Global Report 2008.pdf. 10. North, D. C., Wallis, J. J. and Weingast, B. R. (2009). Violence and Social Orders: A Conceptual Framework for Interpreting Recorded Human History. New York: Cambridge University Press. 11. Sachs, J. D. (2006). The End of Poverty: Economic Possibilities for Our Time. New York: Penguin Books. 12. Human Development Report 2007/2008. (2007). New York: Palgrave Macmillan. 13. 2007 Corruption Perceptions Index. (2007). Retrieved 12.10.2008 from http://www.transparency.org/policy_research/surveys_indices/cpi/2007. i

All countries with at least a million inhabitants and necessary data in 2007 are included. For details of corruption perception index score see: http://www.transparency.org. iii Polity IV Project is led by Monty G. Marshall, for details see: www. sytemicpeace.org/polity/polity4.htm. iv World Bank Group and International Finance Corporation provide a yearly ranking list of countries according to ease of doing business. v Himanen (2013) has transformed the ordinal ranking list to a cardinal one (ease of doing business scores) but that cannot overcome the original lack of data on the amount of differences between countries. vi Academic Ranking of World Universities in 2007 retrieved 20.10.2007 from www.arwu.org. vii The ERS International Macroeconomic Data Set retrieved 20.12.2007 from www.ers.usda.gov/Data/Macroeconomics. viii I have divided Europe into three parts: Western Europe includes countries that stayed out of communism; Eastern European countries got communism after WW II; and the post-Soviet countries were annexed into the Soviet Union. ix CPI scores for 2011are from Transparency International’s Annual Report 2011 retrieved 10.12.2012 from www.transparency.org. ii