Zoltán J. Ács László Szerb Erkko Autio

Transcription

1 2015 Zoltán J. Ács László Szerb Erkko Autio

2 Global Entrepreneurship Index 2015

3 Zoltán J. Ács Professorial Fellow London School of Economics and Political Science, UK University Professor in the School of Public Policy at George Mason University, USA László Szerb University Professor and Director of the Department of Business and Management Studies in the Faculty of Business and Economics at the University of Pecs, Hungary Erkko Autio Chair in Technology Venturing and Entrepreneurship and Director of the Doctoral Programme at Imperial College London Business School, UK The Global Entrepreneurship and Development Institute, Washington, D.C., USA ii

4 Table of Contents About The Global Entrepreneurship and Development Institute... vii Preface: A Compass for Strengthening Entrepreneurial Ecosystems... ix Global Entrepreneurship in xi Chapter 1: Introduction... 1 Chapter 2: The Global Entrepreneurship Index Introduction The S-Shaped Curve The 14 Pillars of Entrepreneurship Entrepreneurial Attitude Pillars Entrepreneurial Ability Pillars Entrepreneurial Aspiration Pillars The Global Entrepreneurship Index, 2015 Rankings The Ranking of the 3As Summary and Conclusion Chapter 3: Performance by Country and Country Group Sub-Saharan Africa Middle East and North Africa (MENA) Asia-Pacific Europe North America South and Central America and the Caribbean Chapter 4: Enhancing Entrepreneurship Ecosystems. A Systems of Entrepreneurship Approach to Entrepreneurship Policy Introduction What Are Systems of Entrepreneurship? Systems of Entrepreneurship and Entrepreneurship Ecosystem Policy Using the GEI Approach for Entrepreneurship Ecosystem Policy Analysis Using the GEI Method for Entrepreneurship Ecosystem Policy Design Chapter 5: Methodology and Data Description Introduction The Index Structure The Individual Variables and Dataset... 68

5 Summary Appendix A Pillar distributions Appendix B The Global Entrepreneurship Sub-Index Rank of Countries in alphabetical order, Appendix C Entrepreneurial Attitudes Sub-Index and Pillar Values of Countries in alphabetical order, Appendix D Entrepreneurial Abilities Sub-Index and Pillar Values of Countries in alphabetical order, Appendix E Entrepreneurial Aspirations Sub-Index and Pillar Values of Countries in alphabetical order, Country Pages Tables, Figures, and Highlight Boxes Figure 1.1: The Structure of the Global Entrepreneurship Index... 3 Table 1.1: The Ten Most Entrepreneurial Countries in Table 1.2: Points and Ranks of the Countries in the 2015 GEI... Table 1.3: The Ten Biggest Gains in GEI Score from 2014 to Table 1.4: The Ten Biggest Declines in GEI Score between 2014 and Table 1.5: The Top Performing Country in Each Region... 7 Map: The 2015 GEI Results... 8 Figure 2.1: The S-Curve of Entrepreneurship Table 2.1: The Global Entrepreneurship Index Rank of all Countries, Figure 2.2: The Three Sub-Indexes in Terms of Per Capita Real GDP ( , all data included) Table 2.2: The Global Entrepreneurship Index and Sub-Index Ranks of the First 25 Countries, Table 2.3: Entrepreneurial Attitudes Sub-Index and Pillar Values for the First 25 Countries, 2015* Table 2.4: Entrepreneurial Abilities Sub-Index and Pillar Values for the First 25 Countries, Table 2.5: Entrepreneurial Aspirations Sub-Index and Pillar Values for the First 25 Countries, 2015* Table 3.1: Country Groups Analyzed in This Chapter Table 3.2: GEI Ranking of the Sub-Saharan African Countries Figure 3.1: Pillar Level Comparison of Africa and the World Figure 3.2: Pillar-Level Comparison of South Africa, Nigeria, and Uganda Table 3.3: GEI Ranking of the Middle East and North African Countries Figure 3.3: Pillar-Level Comparison of MENA and the World iv

6 Figure 3.4: Pillar-Level Comparison of the United Arab Emirates, Tunisia, and Egypt Table 3.4: GEI Ranking of the Asia-Pacific Countries Figure 3.5: Pillar-Level Comparison of Asia and the World Figure 3.6: Pillar-Level Comparison of Australia, China, and Bangladesh Table 3.5: GEI Ranking of the European Countries Figure 3.7: Pillar-Level Comparison of Europe and the World Figure 3.8: Pillar-Level Comparison of the United Kingdom, Greece, and Russia Table 3.6: GEI Ranking of the North American Countries Figure 3.9: Pillar-Level Comparison of North America and the World Figure 3.10: Pillar-Level Comparison of the United States, Canada, and Mexico Table 3.7: GEI Ranking of the South and Central American and Caribbean Countries Figure 3.11: Pillar-Level Comparison of the Latin American Region and the World Figure 3.12: Pillar-Level Comparison of Chile, Brazil, and Suriname Figure 2.1: Dynamic of National Systems of Entrepreneurship Figure 2.2: Entrepreneurship Ecosystem Profiles of the U.S., Japan, and India Table 2.1: Ecosystem Optimization Analysis for UK Home Nations Table 5.1: The Description of the Individual Variables Used in the GEI Table 5.2: The Distribution of the Sample by Countries and the Calculation of the Individual Variables Table 5.3: The Description and Source of the Institutional Variables Used in the GEI Table 5.4: The Correlation Matrix between the Original Indicators ( dataset) Table 5.5: The Correlation Matrix between the Indicators, Sub-Indexes and the GEI Super-Index after Normalizing and Applying the PFB Method ( dataset) Acknowledgements: We would like to thank Ainsley Lloyd for producing the 2015 Global Entrepreneurship Index. She managed the entire production process from start to finish, including the country tables, the artwork, the layout, editing and proofreading. We would like to thank Jonathan Ortmans and Global Entrepreneurship Network for their support and collaboration on the production and dissemination of the 2015 GEI.

7

8 About The Global Entrepreneurship and Development Institute Zoltán J. Ács Founder and President, the GEDI Institute The Global Entrepreneurship and Development Institute (GEDI Institute) is a non-profit organisation that advances research on links between entrepreneurship, economic development and prosperity. The institute was founded by world-leading entrepreneurship scholars from the George Mason University, University of Pécs and Imperial College London. The flagship project of the Institute is the GEI Index, a breakthrough advance in measuring the quality and dynamics of entrepreneurship ecosystems at a national and regional level. The Global Entrepreneurship Index methodology, upon which the data in this report is based, has been validated in rigorous academic peer reviews and has been widely reported in media, including in The Economist, The Wall Street Journal, Financial Times and Forbes.

9

10 Preface: A Compass for Strengthening Entrepreneurial Ecosystems Jonathan Ortmans President, Global Entrepreneurship Network The globalization of entrepreneurship is producing an explosion of programs, startup communities, policy interventions and investments across the world. Now, ideas, capital and talent speed across borders finding founder teams to create new ventures that fuel economic growth and stability. These are exciting times when a new generation of risk takers are leveling the playing field and creating new opportunities for more people. These developments are manifested in the various activities of the Global Entrepreneurship Network (GEN) a community that has arisen from Global Entrepreneurship Week, the annual celebration of entrepreneurs now in more than 150 countries. Started as a grassroots movement anchored in established economies with stable political systems, GEN has evolved and matured into a year-round platform that operates in all types of economies and cultures. A careful look at this entrepreneurial renaissance reveals, however, that new challenges have emerged. In particular, data collection and analysis has not been able to keep pace with the rapid growth of programs and other interventions designed to increase rates of new firm formation. There exists a paucity of data, not just around what works and what does not in supporting new entrepreneurs, but about the overall entrepreneurial performance of our societies. In short, we do not know where and how our efforts are succeeding and failing. Countries seeking to add entrepreneurial resilience to their economies benchmark their regulatory frameworks and ecosystem performance against other economies. At the same time, academics and economists still debate what to measure, which data is credible and which methodologies should be considered reliable. This has given rise to a new dialogue between startup community leaders and government leaders seeking more sophisticated tools, programs and research to help them most efficiently direct their attention and funds to areas that have the greatest impact on future economic growth. Such dialogue is certainly a key part of the experimentation formula that unearths solutions in both the startup and policy worlds and as a broad-based movement of leaders and feeders to the entrepreneurial ecosystem, GEN is actively working to build trust between these players. Coupled with solid data, such dialogue could go much further in helping us all fine-tune our efforts and in a much more efficient way. GEN has therefore partnered with the Global Entrepreneurship and Development Institute to present the Global Entrepreneurship Index (GEI). The Global Entrepreneurship Index, while by no means the definitive answer, seeks to provide more than just a country s relative global ranking. The Index sheds light on the efficiency of national startup ecosystems through analysis of 34 essential individual and institutional variables. It attempts to reveal the bottlenecks that erode hard-won competitive advantages for startup ecosystems and provide rankings by region to provide policymakers regulatory environment comparisons with surrounding economies. The pulse-taking in this report will be updated annually, with a fresh assessment released each November during Global Entrepreneurship Week. Due in part to the efforts of those leading GEW and of the myth-busting work of the knowledge houses that today form the Global Entrepreneurship Research Network, GEN hopes to help governments around the world improve upon and expand their understanding of new and young firm formation. As a platform for all these concerted efforts, GEN is committed to feed that interest and push the frontier forward in terms of academic rigor. The Global Entrepreneurship Index is a firm step in that direction.

11

12 Global Entrepreneurship in 2015 Rank Country GEI Score Top Performers by Region 1 United States 2 Canada 3 Australia 4 United Kingdom 5 Sweden 6 Denmark 7 Iceland 8 Taiwan 9 Switzerland 10 Singapore # 1 # 4 # 20 # 21 # 53 United States (#1) is at a historical high of (#4) leads at (#20) tops the region at (#21) tops the region at (#53) leads at % The world is at 52% of its entrepreneurial capacity -5.2 Asia-Pacific -0.7 Europe 2.0 Middle East / North Africa -2.5 South and Central America / Caribbean 0.3 Sub- Saharan Africa points

13

14

15

16 Chapter 1: Introduction The world economy is facing important medium- and long-term challenges. Whereas rich countries will be challenged to increase their economic productivity to sustain current standards of living as their populations rapidly age, low-income economies will need to integrate more than two billion young adults into the world economy by Economic initiatives by enterprising individuals are likely to be key in addressing the challenges of long-term productivity in rich countries, whereas poor countries will continue to struggle to integrate their rapidly growing populations into their economies. These economic challenges occur unevenly in different regions of the globe. In the developed world, the population of the age group, the core of the labor force, is expected to lose almost 15 percent between 2010 and However, the number of people in that age group in the developing world is still rising rapidly and is expected to increase by 50 percent by 2050, excluding China whose labor force has already stopped growing). In sub-saharan Africa alone, the population aged will increase from 455 million today to over one billion by Thus, the lion s share of the growth in the world labor force in the coming decades will occur in the less developed countries (again excluding China), where the number of 15- to 59-year-olds will increase by 1.3 billion in the next 40 years. Although global population growth is slowing in some regions, the 1980s and 1990s were years of high fertility in most countries of the world, and the exceptionally large cohorts born during those decades are now entering the labor market. Thus we are in the midst of a labor force boom not likely to end for another 30 or 40 years. Clearly, what the world economy most needs now is jobs; the main questions are, how many will we need to create, and how fast. How can more than one billion jobs be created in the developing world within this timeframe, especially in the least developed countries, where poverty and massive unemployment are already the dominant facts of economic life? The approaches used by the development community in the last 50 years have generally not been effective. Simply making capital more readily available in the form of grants and loans has created debt and squandered resources. The idea that, if rich countries build roads, dams, and power stations, jobs will follow, has proved misguided. More recent approaches, such as microcredit, improving the rule of law, and supporting smallholder property registration, all efforts to jumpstart the founding of small businesses, have helped in many localities, but they have yet to produce the increase in large-scale, labor-intensive industries that will create jobs where they are most needed. The one solution that can provide jobs on that scale lies in a combination of innovation and entrepreneurship. Research on economic growth over the last 30 years has strongly emphasized that rapid job creation comes from rapidly growing companies. Therefore, the world s developing countries will be able to provide the jobs their rapidly increasing populations require only by encouraging the founding of companies that grow rapidly by providing widely desired new products or services. Such companies are usually created by exploiting new market niches and offering novel products, services, or processes that have few competitors or substitutes. The combination of novel products, few immediate competitors, and high demand created by new markets can sustain high levels of profitability, which will provide the capital and the incentives for the rapid expansion of production and employment. Some economists believe that developing economies should exploit their comparative advantage of using low-cost labor to produce primary products, while advanced economies provide the technical innovation and entrepreneurship that create new industries. However, this approach has not, and will not, be sufficient to meet the employment challenges facing the developing world. Competing globally by providing low-cost

17 labor was effective when the rich countries seemed able to absorb an unending stream of cheap imports, but that is no longer the case; in fact, only a few nations actually followed this path. Moreover, such a strategy is unlikely to be effective when a billion new workers are looking for employment while the economies of the developed world aging and paying down their accumulated debts are shifting from rapid to tepid growth. Relying on the production of primary products condemns countries to endless cycles of commodity boom and bust, as countries from Russia to Zambia have discovered. To succeed in the rapidly growing markets of the emerging nations will require that new products be developed for these markets that are cheaper, easier to maintain, and vastly more efficient. Only innovation and the creation of new enterprises are likely to offer a long-term solution to the economic needs of developing countries. How can we encourage the spread of innovation and entrepreneurship in the developing world that will be the key to future global prosperity? The answer is entrepreneurship. More than one hundred years ago, in the Theory of Economic Development, Joseph Schumpeter pointed out that entrepreneurs are important for development. Today we can expand on that and say they are the key drivers of economic development. While Schumpeter was describing countries that had similar levels of development, in today s globalized world we are dealing with countries that have very different levels of development. Furthermore, the importance that institutions such as the rule of law and education play in economic development has become increasingly clear to economists and policymakers alike. We now must understand clearly why institutions are important for development and what roles they play. We already know that they are important because they create the incentive structure that determines the behavior of entrepreneurs. Without these positive incentives, entrepreneurs will not engage in productive activities. The Global Entrepreneurship Index (GEI) provides a detailed look at the entrepreneurial ecosystem of nations by combining individual data with institutional components. We have developed a system that links institutions and agents through a National Entrepreneurial System (ecosystem) in which each biotic and abiotic component is reinforced by the other at the country level. This composite index of both individual- and country-level institutional data gives policymakers a tool for understanding the entrepreneurial strengths and weaknesses of their countries economies, thereby enabling them to implement policies that foster productive entrepreneurship. GEI is designed to help governments harness the power of entrepreneurship to address these types of challenges. The GEI is a joint project with the Global Entrepreneurship Network (GEN), the communities, organizations and leaders that have been inspired and brought together from 150 nations to build healthier entrepreneurship ecosystems as a result of Global Entrepreneurship Week. The methodology used for the GEI is significantly different from previous efforts to organize this data done by the Global Entrepreneurship Development Institute. In addition, since the number of countries in the Index has grown, we are now able to provide regional information. For example, we can focus on Africa, whose needs are different from those of Western Europe or the Middle East. However, as a result, previous results cannot be directly compared to the 2015 data given (a) the changes in the variables, (b) the alteration of the pillars, and (c) the adjustment of the benchmark values. The purpose of this index is to measure the quality and the scale of the entrepreneurial process in 130 countries around the world. The GEI provides a rich understanding of entrepreneurship and a more precise ability to measure it. It also captures the contextual features of entrepreneurship by measuring entrepreneurial attitudes, abilities, and aspirations. These data, and the contribution they make to the process of creating businesses, are supported by three decades of research into entrepreneurship across a host of countries. Distinct from both output-based entrepreneurship indexes (i.e., new firm counts) and process-based indexes (i.e., comparisons of policies and regulations), the GEI is designed to profile national systems of entrepreneurship. The GEI is not a simple count of, say, new firm registrations, nor is it an exercise in policy benchmarking. The Index also does not focus exclusively on high-growth entrepreneurship; it also considers the characteristics of entrepreneurship that enhance productivity: innovation, market expansion, being growth oriented, and having an international outlook.

18 Moreover, because entrepreneurship can have both economic and social consequences for the individual, the GEI captures the dynamic, institutionally embedded interactions between the individual-level attitudes, abilities, and aspirations that drive productive entrepreneurship. Finally, the GEI recognizes that entrepreneurship can mean very different things in different economic and institutional contexts. A local horticultural venture, for example, would have different economic consequences for the Kenyan economy than a social media startup in Silicon Valley. Recognizing that entrepreneurship has a different impact in different contexts, the GEI combines individual-level data with data that describe national institutions, as well as economic and demographic structures, to provide an institutionally embedded view of the drivers of productive entrepreneurship. Figure 1.1 shows the structure of the GEI sub-indexes, pillars, and variables. Figure 1.1: The Structure of the Global Entrepreneurship Index Attitudes Sub-Index Abilities Sub-Index Aspirations Sub-Index MARKET AGGLOMERATION OPPORTUNITY POST-SEC EDUCATION SKILL RECOGNITION BUSINESS RISK INTERNET USAGE KNOW ENTREPRENEUR CORRUPTION CAREER STATUS FREEDOM TEA OPPORTUNITY TECH ABSORPTION TECH SECTOR STAFF TRAINING HIGH EDUCATION MARKET DOMINANCE COMPETITION TECH TRANSFER NEW PRODUCT GERD NEW TECHNOLOGY BUSINESS STRATEGY GAZELLE GLOBALIZATION EXPORT DEPTH OF CAPITAL MARKET INFORMAL INVESTMENT OPPORTUNITY PERCEPTION STARTUP SKILLS NETWORKING CULTURAL SUPPORT OPPORTUNITY STARTUP TECHNOLOGY ABSORPTION HUMAN CAPITAL COMPETITION PRODUCT INNOVATION PROCESS INNOVATION HIGH GROWTH INTERNATIONALIZATION RISK CAPITAL Note: The GEI is a super index made up of three sub-indexes, each of which is composed of several pillars. Each pillar consists of an institutional variable (denoted in bold) and an individual variable (denoted in bold italic). If the GEI were a weather report, stormy weather would indicate a higher level of unproductive entrepreneurship, such as rent-seeking and contraband activities that interfere with and undermine a country s economic growth and prosperity. Today s rising barometric pressure means better conditions lie ahead as the world transitions from a managed economy to a more entrepreneurial society. So what does the GEI tell us? First, as we celebrate Global Entrepreneurship Week, which sparks thousands of entrepreneurial activities all over the world, we sometimes wonder how entrepreneurship is actually faring. Are we making real progress? While we have some very good tools to predict the weather, no such simple tool has existed in the world of entrepreneurship. Until now. This is important, because as we look toward the world of 2050 we see storm clouds on the horizon: an exploding population, global warming, increasing urbanization that produces (poorly performing) larger and larger cities, and the lack of opportunity that will ultimately reduce the level of productive entrepreneurship.

19 The GEI measures entrepreneurship across the world and gives it a number that enables us to understand if it is getting stronger or weaker from year to year. Twenty-five years ago, before the Berlin Wall fell, the world was experiencing a very low level of entrepreneurship. With the exception of some enterprising people in a few countries in the West the United States, Canada, the UK, and Australia almost no one was actively pursuing productive entrepreneurship. This was especially true in Brazil, Russia, India, and China, some of today s most rapidly developing economies. In comparison, the world today is operating at better than 50 percent of its productive entrepreneurship capacity, which has been rising slowly over the years. How is the world economy currently faring? Are we sailing on stormy seas, or does the clear evening sky indicate a calm sail ahead? To help answer this, Table 1.1 presents the ten most entrepreneurial countries in the 2015 data for the GEI and compares them to the 2014 rankings. Note that the 2014 rankings have been recalculated with the most recent version of the GEI method (for details, see Chapter 5). Table 1.1: The Ten Most Entrepreneurial Countries in 2015 Country GEI 2015 Rank 2015 GEI 2014 Rank 2014 United States Canada n.a. n.a. Australia United Kingdom Sweden Denmark Iceland Taiwan Switzerland Singapore The United States maintained its number-one position on the 2015 GEI. Moreover, its point value increased sharply, from 82 to 85. Thus the U.S. not only remains the most entrepreneurial country in the world, it also is increasing its lead. The four top countries the United States, Canada, Australia, the UK all had higher GEI point values in 2015 than in As a result, the gap between the U.S. at the top and the Scandinavian countries that follow has increased slightly. The difference between the U.S. and the strongest European nations, Sweden, Denmark, Switzerland, and Iceland is larger than in Singapore and Taiwan increased their level of productive entrepreneurship. Taiwan, with its historically high score of 69, is in eighth place, while Singapore ranks tenth, also making the GEI top ten for the first time. In sum, the top-performing entrepreneurial ecosystems in the world are the four largest English-speaking countries, followed by three Scandinavian nations and two Asian countries; Switzerland rounds out the top ten. Table 1.2 looks at the whole world, with its listing of all 130 countries in the 2015 GEI ranking. The table shows countries in Africa, South America, Asia, and the Middle East. Many African countries were added to the 2015 list; Nigeria, the largest nation in Africa, ranks 84 th, while Uganda and Bangladesh occupy the last two places. The United Arab Emirates (UAE), which continues to lead the Middle East, is clustered with Chile, Estonia, and Israel. The relatively low rankings of India and, surprisingly, China are explained by their large rural and agricultural sectors, which pull down their rankings.

20 Table 1.2: Points and Ranks of the Countries in the 2015 GEI Rank Country GEI Rank Country GEI Rank Country GEI 1 United States Bulgaria Nicaragua Canada Hungary Kazakhstan Australia Cyprus Trinidad & 28.4 Tobago 4 United Kingdom Greece Ecuador Sweden Uruguay Egypt Denmark Italy Bolivia Iceland Lebanon Gabon Taiwan Croatia Iran Switzerland South Africa Philippines Singapore Malaysia Senegal Germany Montenegro Jamaica France Costa Rica Cambodia Netherlands Argentina Rwanda Finland Moldova Brazil Norway Macedonia Gambia. The Belgium Barbados Benin Ireland Brunei Liberia 25.5 Darussalam 18 Austria China India Chile Paraguay Ghana United Arab Tunisia Mozambique 24.3 Emirates 21 Estonia Ukraine Côte d Ivoire Israel Jordan Tanzania Luxembourg Botswana Myanmar Qatar Panama Zambia Turkey Thailand Angola Lithuania Namibia Venezuela Latvia Russia Mali Korea Sri Lanka Burkina Faso Slovenia Lao PDR Cameroon Portugal Libya Madagascar Saudi Arabia Peru Sierra Leone Spain Mexico Swaziland Japan Albania Mauritania Puerto Rico Dominican Indonesia 21.0 Republic 35 Czech Republic Serbia Suriname Colombia Algeria Guatemala Kuwait Honduras Pakistan Poland El Salvador Burundi Oman Morocco Ethiopia Hong Kong Bosnia Chad Slovakia Nigeria Guyana 16.2

21 Rank Country GEI Rank Country GEI Rank Country GEI 42 Romania Vietnam Malawi Bahrain Kenya Uganda Bangladesh 14.4 Table 1.3 shows which countries made the greatest gains in GEI score from 2014 to The ten countries that made the greatest gains changed rankings from as many as ten places to as few as zero. Greece increased 4.5 points, followed by the UAE with 12.8 points. The biggest gainers are six European countries, three in the Middle East, and one in North America. Perhaps the big surprise is Iran, which moved up seven places. Table 1.3: The Ten Biggest Gains in GEI Score from 2014 to 2015 Country Points 2014 Points 2015 Difference in Points Difference in Ranking United Arab Emirates** Latvia Lithuania Turkey Greece Portugal Czech Republic* Iran United States Spain Legend: Included only those countries that have participated in the GEM survey and have not estimated individual data *both 2014 and 2015 individual data are from 2011 **2014 individual data are from 2011 Table 1.4 compares the biggest losers in the 2014 GEI data to their place in the 2015 data. The losses were greater than the gains; for example, Puerto Rico and Indonesia both lost more than ten points. The decline was most notable in Denmark, Finland, and the Netherlands, which all lost ground. However, the European rankings are in general much improved, as the Euro crisis and the recession have eased. Mexico and Peru also lost ground. Table 1.4: The Ten Biggest Declines in GEI Score between 2014 and 2015 Country Points 2014 Points 2015 Difference in Points Difference in Ranking Puerto Rico* Indonesia** Peru Denmark*** Mexico India****

22 Finland Malaysia Netherlands Angola Legend: Included only those countries that have participated in the GEM survey and have not estimated individual data *2013 individual data are from 2007 **2013 individual data are from 2006 ***2014 individual data are from 2012 ****2014 individual data are from 2008 Table 1.5 shows the leading country in each of the six regions of the world: North America, Europe, Sub-Saharan Africa, Latin America, the Middle East North Africa and Asia- Pacific. The United States, Australia and the United Kingdom are the leaders in North America, Asia and Europe. In Sub-Saharan Africa, South Africa is the leader, followed by the UAE in the MENA region and Chile in Latin America. Table 1.5: The Top Performing Country in Each Region World Rank Country Region Per capita GDP Attitudes Abilities Aspirations GEI 1 United States North America Australia Asia-Pacific United Kingdom 19 Chile 20 United Arab Emirates Europe South and Central America / Caribbean Middle East / North Africa South Africa Sub-Saharan Africa

23 Map: The 2015 GEI Results GEI Score 2015 Country GEI Score Country GEI Score Country GEI Score Country GEI Score Country GEI Score United States 85.0 Latvia 54.5 Malaysia 40.0 Algeria 30.2 Ghana 24.8 Canada 81.5 Korea 54.1 Montenegro 39.1 Honduras 29.8 Mozambique 24.3 Australia 77.6 Slovenia 53.1 Costa Rica 37.7 El Salvador 29.6 Côte d Ivoire 24.1 United Kingdo 72.7 Portugal 50.8 Argentina 37.2 Morocco 29.4 Tanzania 23.6 Sweden 71.8 Saudi Arabia 49.6 Moldova 37.2 Bosnia 28.9 Myanmar 23.1 Denmark 71.4 Spain 49.6 Macedonia 37.1 Nigeria 28.9 Zambia 23.0 Iceland 70.4 Japan 49.5 Barbados 37.1 Vietnam 28.8 Angola 22.7 Taiwan 69.1 Puerto Rico 48.9 Brunei Darus 36.9 Kenya 28.5 Venezuela 22.6 Switzerland 68.6 Czech Repub 48.9 China 36.4 Nicaragua 28.4 Mali 22.5 Singapore 68.1 Colombia 47.9 Paraguay 36.0 Kazakhstan 28.4 Burkina Faso 22.1 Germany 67.4 Kuwait 47.7 Tunisia 35.5 Trinidad & To 28.4 Cameroon 22.0 France 67.3 Poland 47.4 Ukraine 33.6 Ecuador 28.2 Madagascar 22.0 Netherlands 66.5 Oman 47.3 Jordan 33.3 Egypt 28.1 Sierra Leone 21.6 Finland 65.7 Hong Kong 45.9 Botswana 33.0 Bolivia 28.0 Swaziland 21.4 Norway 65.6 Slovakia 45.4 Panama 32.2 Gabon 27.7 Mauritania 21.1 Belgium 65.5 Romania 45.3 Thailand 32.1 Iran 27.7 Indonesia 21.0 Ireland 65.3 Bahrain 45.1 Namibia 31.9 Philippines 27.7 Suriname 20.7 Austria 64.9 Bulgaria 42.7 Russia 31.7 Senegal 27.3 Guatemala 20.3 Chile 63.2 Hungary 42.7 Sri Lanka 31.1 Jamaica 27.2 Pakistan 20.1 United Arab E 61.6 Cyprus 42.5 Lao PDR 31.1 Cambodia 26.3 Burundi 18.4 Estonia 60.2 Greece 42.0 Libya 31.0 Rwanda 26.2 Ethiopia 17.2 Israel 59.9 Uruguay 41.4 Peru 30.9 Brazil 25.8 Chad 16.6 Luxembourg 57.2 Italy 41.3 Mexico 30.7 Gambia, The 25.6 Guyana 16.2 Qatar 56.2 Lebanon 40.7 Albania 30.6 Benin 25.6 Malawi 15.6 Turkey 54.6 Croatia 40.6 Dominican Re 30.6 Liberia 25.5 Uganda 15.1 Lithuania 54.6 South Africa 40.0 Serbia 30.6 India 25.3 Bangladesh 14.4

24 References Acemoglu, D., & Robinson, J. (2001). Why nations fail: The origins of power, prosperity and poverty. New York: Crown Press. Acs, Z. J., Szerb, L., & Autio, E. (2014). The global entrepreneurship and development index. Seattle: On Demand. Acs, Z. J., Szerb, L., & Autio, E. (2013). The global entrepreneurship and development index. Cheltenham, England: Edward Elgar. Acs, Z. J., & Szerb, L. (2012). The global entrepreneurship and development index. Cheltenham, England: Edward Elgar. Acs, Z. J., & Szerb, L. (2011). The global entrepreneurship and development index. Cheltenham, England: Edward Elgar.

25

26

27

28 Chapter 2: The Global Entrepreneurship Index Introduction The modern temple of the entrepreneurial ecosystem is like many temples of the ancient world: both are held up by pillars. Today s economic ecosystem is supported by the pillars of development, which are held together by the cement of incentives created by institutions that influence the behavior of individuals. If a fully developed economy is to continue to flourish, these pillars need constant attention, continuous improvement, and careful maintenance, and they must be of similar height and strength. In this chapter, we present the Global Entrepreneurship Index (GEI). We begin by discussing the S-shaped curve of entrepreneurship and the 14 pillars of entrepreneurship. We report country rankings and values in terms of GEI and these 14 pillars. We then present the three sub-indexes: attitudes toward entrepreneurship, entrepreneurial abilities, and entrepreneurial aspirations. Finally, we analyze and compare the different countries and country groups included in the GEI. The S-Shaped Curve Between 1945 and 1980, nearly one hundred colonies in Africa, Asia, and the Caribbean gained their independence and began creating a development strategy for their citizens. 1 Sadly, many of those countries have experienced neither significant per capita growth nor economic development. 2 Indeed, moderate to extreme poverty remains a significant concern for many developing countries. 3 After failed attempts at development through import substitution (protecting domestic producers from the competition of imports) and programs to protect infant industries, as well as somewhat mixed results from export promotion strategies, developing countries are beginning to focus on improving their business environments and creating economic spaces that are conducive to private enterprise, both domestic and foreign. Indeed, in recent years, promoting entrepreneurship and the promulgation of small- and medium-sized enterprise policy have become important prescriptions for development. 4 While focusing on entrepreneurship may seem a novel approach to development, it is consistent with and even complementary to older, more traditional development strategies. As developing economies have moved from centralized economies to market economies, enterprise and entrepreneurship have become increasingly important. As Woolridge writes, The emerging world, long a source of cheap labor, now rivals the rich countries for business innovation. Developing countries are becoming hotbeds of business innovation in much the same way as Japan did from the 1950s onwards. 5 In his classic text, The Stages of Economic Growth, W. W. Rostow suggests that countries go through five stages of economic growth: (1) the traditional society, (2) the preconditions for take-off, (3) the take-off, (4) the drive to maturity, and (5) the age of high mass consumption. 6 While these stages are an oversimplified way of looking at the development of modern economies, they do identify critical events. Michael Porter, who follows recent developments in the economics of innovation while conducting research on the current age of high mass consumption, provides a modern rendition of Rostow s approach by identifying three stages of development: (1) a factor-driven stage, (2) an efficiency-driven stage, and (3) an innovation-driven stage. 7 Entrepreneurship is an important mechanism that can promote economic development through employment, innovation, and welfare, but it does not appear like manna from heaven as a country moves through the stages of development. Rather, it is a process that plays a role in all stages of development and continues over many years. Economists have come to recognize the input-completing and gap-filling capacities of entrepreneurial activity in development 8 in other words, that someone has to create the technology for new products and create the markets

29 where people will buy them. Figure 2.1 shows the relationship between entrepreneurship and economic development. The S-shaped curve shown in Figure 2.1 addresses two important questions about entrepreneurship. First, the S- shaped curve represents the source of poverty, whereas the intersection of the S-curve and the vertical axis suggests that, if individuals in a country are very poor, they may be in a poverty trap where the chances for growing their income or wealth are limited: tomorrow s income may be less than today s, and any attempt to get out of this trap may further reduce future income, since at very low levels of income any investment in future income will result in a decline in current consumption that cannot be afforded. This helps to explain why the poor, and poor countries, are so little involved in entrepreneurship. 9 The S-shaped curve also addresses how much productive entrepreneurship there is in countries at different stages of development and how rapidly it grows. Where the S-curve rises less steeply and then levels off it represents a situation where tomorrow s income is greater than today s, so entrepreneurial activity is possible. 10 How quickly countries modernize depends on the rise of this curve. The area above the curve is a valley of backwardness, which can only be eliminated when nations build better institutions and change their society s incentive structure, all of which requires good government and governance. 11 As institutions become stronger, destructive and unproductive activities decline, and more entrepreneurial activity can focus on productive entrepreneurship, thus strengthening economic development. 12 The second source of backwardness is unproductive entrepreneurship, where one group gives and another only takes. This form of rent-seeking is prevalent in many developed and developing countries. If rent-seeking by governments and other groups persists, entrepreneurs will remain reluctant to make the long-term investments of time and money that are needed to create productive, high-impact firms. If countries have extractive economies where only a few benefit at the expense of others, development will not take place. Therefore, as activity shifts away from destructive and unproductive entrepreneurship, more productive forms of entrepreneurship can have a significant positive effect on the creation of social value. In today s interconnected world, we need to improve institutions and be able to measure this progress. Figure 2.1: The S-Curve of Entrepreneurship entrepreneurshi efficiency-driven stage factor-driven stage innovation-driven stage economic development

30 The 14 Pillars of Entrepreneurship The pillars of entrepreneurship are many and complex. While a widely accepted definition of entrepreneurship is lacking, there is general agreement that the concept has numerous dimensions. 13 We take this into account in creating our entrepreneurship index, as some businesses clearly have a larger impact on markets, create more new jobs, and grow faster and larger than others. We also take into account the fact that entrepreneurship plays a different role at different stages of development. Considering the various possibilities and limitations, we define entrepreneurship as the dynamic, institutionally embedded interaction between entrepreneurial attitudes, entrepreneurial abilities, and entrepreneurial aspirations by individuals, which drives the allocation of resources through the creation and operation of new ventures. 14 The GEI is composed of three building blocks or sub-indexes what we call the 3As: entrepreneurial attitudes, entrepreneurial abilities, and entrepreneurial aspirations. These three sub-indexes stand on 14 pillars, each of which contains an individual and an institutional variable that correspond to the micro- and the macro-level aspects of entrepreneurship. Unlike other indexes that incorporate only institutional or individual variables, the GEI pillars include both individual and institutional variables. These pillars are an attempt to capture the open-ended nature of entrepreneurship; analyzing them can provide an in-depth view of the strengths and weaknesses of those listed in the Index. We now describe the 14 pillars of entrepreneurship. Entrepreneurial Attitude Pillars Pillar 1: Opportunity Perception. This pillar captures the potential opportunity perception of a population by considering the size of its country s domestic market and level of urbanization. This opportunity perception potential is an essential ingredient of entrepreneurial start-ups. Within this pillar is the individual variable Opportunity Recognition, which measures the percentage of the population that can identify good opportunities to start a business in the area where they live. However, the value of these opportunities also depends on the size of the market. The institutional variable Market Agglomeration consists of two smaller variables: the size of the domestic market (Domestic Market) and urbanization (Urbanization). The Urbanization variable is intended to capture which opportunities have better prospects in developed urban areas than they do in poorer rural areas. Market Agglomeration is determined by multiplying the size of the domestic market by the percentage of the population living in urban areas. 15 Pillar 2: Start-Up Skills. Launching a successful venture requires the potential entrepreneur to have the necessary start-up skills. Skill Perception measures the percentage of the population who believe they have adequate start-up skills. Most people in developing countries think they have the necessary skills to start a business, but their skills usually are acquired through workplace trial and error in relatively simple business activities. In developed countries, business formation, operation, management, etc., require skills that are acquired through formal education and training. Hence education, especially postsecondary education, plays a vital role in teaching and developing entrepreneurial skills. Today there are 150 million students enrolled in some kind of education beyond high school, a 53 percent increase in less than a decade. People all over the world see education as a pathway out of poverty. 16 Pillar 3: Risk Acceptance. Of the personal entrepreneurial traits, fear of failure is one of the most serious obstacles, as aversion to high-risk start-up enterprises can retard nascent entrepreneurship. Risk Perception is defined as the percentage of the population who do not believe that fear of failure would prevent them from starting a business. Business Risk reflects the availability and reliability of corporate financial information, legal protections for creditors, and institutional support of intercompany transactions. 17 Pillar 4: Networking. Networking combines an entrepreneur s personal knowledge with their ability to use the Internet for business purposes. This combination serves as a proxy for networking, which is also an important ingredient of successful venture creation and entrepreneurship. Entrepreneurs who have better

31 networks are more successful, can identify more viable opportunities, and can access more and better resources. We define the basic networking potential of a possible entrepreneur by the percentage of the population who personally know an entrepreneur who started a business within the previous two years (Know Entrepreneurs). However, connecting through cyberspace with the rest of the world adds another dimension to networking and opens up much greater opportunities than before (Internet Usage). 18 Pillar 5: Cultural Support. This pillar is a combined measure of how a country s inhabitants view entrepreneurs in term of status and career choice, and how the level of corruption in that country affects this view. Without strong cultural support, the best and brightest do not want to be responsible entrepreneurs, and they decide to enter a traditional profession. Career Status is the average percentage of the population age who consider entrepreneurship a good career choice that enjoys high status. The associated institutional variable measures the level of corruption. High levels of corruption can undermine the high status and steady career paths of legitimate entrepreneurs. 19 Entrepreneurial Ability Pillars Pillar 6: Opportunity Start-Up. This is a measure of start-ups by people who are motivated by opportunity but face regulatory constraints. An entrepreneur s motivation for starting a business is an important sign of quality. Opportunity entrepreneurs are believed to be better prepared, to have superior skills, and to earn more than what we call necessity entrepreneurs. Opportunity Motivation is defined as the percentage of the Total Entrepreneurial Activity (TEA) businesses started to exploit a good opportunity, to increase income, or to fulfill personal aims, which contrasts to those started by people who have no other options for work. The institutional variable applied here is business freedom, one sub-index of the Index of Economic Freedom. The Economic Freedom variable is appropriate for capturing the overall burden of regulation, and the regulatory efficiency of the government in influencing start-ups and operating businesses. 20 Pillar 7: Technology Absorption. In the modern knowledge economy, information and communications technologies (ICT) play a crucial role in economic development. Not all sectors provide the same chances for businesses to survive or their potential for growth. The Technology Level variable is a measure of the businesses that are in technology sectors. The Tech Absorption institutional variable is a measure of a country s capacity for firm-level technology absorption, as reported by the World Economic Forum. The diffusion of new technology, as well as the capability to absorb it, is vital for innovative firms with high growth potential. 21 Pillar 8: Human Capital. The prevalence of high-quality human capital is vitally important for ventures that are highly innovative and require an educated, experienced, and healthy workforce in order to continue to grow. An important feature of a venture with high growth potential is the entrepreneur s level of education. The Educational Level variable captures the quality of entrepreneurs; it is widely held that entrepreneurs with higher education degrees are more capable and willing to start and manage high-growth businesses. Employee quality also has an impact on business development, innovation, and growth potential. The institutional variable Staff Training signifies a country s level of investment in business training and employee development. It can be expected that investing heavily in employees pays off and that training increases their quality. 22 Pillar 9: Competition. Competition is a measure of the uniqueness of a business s product or market, combined with the market power of existing businesses and business groups. The variable Competitors is defined as the percentage of TEA businesses that have only a few competitors offering the same product or service. However, market entry can be prevented or made more difficult if powerful business groups dominate a market. The extent of market dominance by a few business groups is measured by the variable Market Dominance, as reported by the World Economic Forum. 23

32 Entrepreneurial Aspiration Pillars Pillar 10: Product Innovation. New products play a crucial role in the economy of all countries. While rich countries for years were the source of most new products, developing countries today are producing products that are dramatically cheaper than their Western equivalents. New Product is a measure of a country s potential to generate new products and to adopt or imitate existing products. In order to quantify the potential for new product innovation, an institutional variable related to technology and innovation transfer seems to be relevant. Technology Transfer is a complex measure of whether a business environment allows the application of innovations for developing new products. Pillar 11: Process Innovation. Applying and/or creating new technology is another important feature of businesses with high growth potential. New Tech is defined as the percentage of businesses whose principal underlying technology is less than five years old. However, most entrepreneurial businesses do not just apply new technology, they create it. The problem is similar to the New Product variable; whereas many businesses in a developing country may apply the latest technology, they tend to buy or copy it. An appropriate institutional variable applied here is research and development (R&D). Gross Domestic Expenditure on Research and Development (GERD) is the R&D percentage of GDP as reported by the Organisation for Economic Co-operation and Development. While R&D alone does not guarantee successful growth, it is clear that, without systematic research activity, the development and the implementation of new technologies and therefore future growth will be inhibited. 24 Pillar 12: High Growth. This is a combined measure of the percentage of high-growth businesses that intend to employ at least ten people and plan to grow more than 50 percent in five years (the Gazelle variable) with business strategy sophistication (the Business Strategy variable). It might be argued that a shortcoming of the Gazelle variable is that growth is not an actual but an expected rate. However, a measure of expected growth is in fact a more appropriate measure of aspiration than a measure of realized growth. Business Strategy refers to the ability of companies to pursue distinctive strategies, which involves differentiated positioning and innovative means of production and service delivery. 25 High Growth combines high growth potential with a sophisticated strategy. 26 Pillar 13: Internationalization. Internationalization is believed to be a major determinant of growth. A widely applied proxy for internationalization is exporting, which demands capabilities beyond those needed by businesses that produce only for domestic markets. However, the institutional dimension is also important: a country s openness to international entrepreneurs that is, the potential for internationalization can be estimated by its degree of globalization. The Internationalization pillar is designed to capture the degree to which a country s entrepreneurs are internationalized, as measured by the exporting potential of businesses, controlling for the extent to which the country is economically globalized. 27 Pillar 14: Risk Capital. The availability of risk finance, particularly equity rather than debt, is an essential precondition for fulfilling entrepreneurial aspirations that are beyond an individual entrepreneur s personal financial resources. 28 Here we combine two kinds of finance, the informal investment (Informal Investment) and the institutional depth of capital market (DCM). Informal Investment is defined as the percentage of informal investors in the population age 18-64, multiplied by the average size of individuals investment in other people s new businesses. While the rate of informal investment is high in factor-driven economies, the amount of informal investment is considerably larger in efficiency- and innovation-driven countries; combining them balances these two effects. Our institutional variable here is DCM, one of the six subindexes of the Venture Capital and Private Equity index. This variable is a complex measure of the size and liquidity of the stock market, level of IPO, M&A, and debt and credit market activity, which encompass seven aspects of a country s debt and capital market. 29

33 The Global Entrepreneurship Index, 2015 Rankings In this section, we report the rankings of the 130 countries on the Global Entrepreneurship Index and the three subindexes. The pillar values of the three sub-indexes are presented later. We present the rankings in terms of country development, as measured by per capita GDP. The overall ranking of the countries by GEI score is shown in Table 2.1. Anglo-Saxon, Nordic, and Western European countries in the innovation-driven stage of development are in the front ranks. The United States, Canada, Australia, and the United Kingdom lead the rankings. The big surprise is the UK s ranking in 4 th place. Two of the five Nordic countries, Denmark and Sweden, are in the top ten, and Iceland and Finland are 11 th and 14 th, respectively still a good performance. Taiwan, the highest ranked Asian country, is in 8 th place, and Singapore is 10 th. The Netherlands at 13 th it is still among the most entrepreneurial nations of the world and Switzerland is also a surprise ranking in 5 th place. Besides their high entrepreneurial performance, these countries also represent high levels of income.

34 Table 2.1: The Global Entrepreneurship Index Rank of all Countries, 2015 Rank Country GDP 2012* GEI Rank Country GDP 2012* GEI Rank Country GDP 2012* 1 United States Bulgaria Nicaragua Canada Hungary Kazakhstan Australia Cyprus Trinidad & Tobago United Kingdom Greece Ecuador Sweden Uruguay Egypt Denmark Italy Bolivia Iceland Lebanon Gabon Taiwan Croatia Iran Switzerland South Africa Philippines Singapore Malaysia Senegal Germany Montenegro Jamaica France Costa Rica Cambodia Netherlands Argentina Rwanda Finland Moldova Brazil Norway Macedonia Gambia. The Belgium Barbados Benin Ireland Brunei Darussalam Liberia Austria China India Chile Paraguay Ghana United Arab Emirates Tunisia Mozambique Estonia Ukraine Côte d Ivoire Israel Jordan Tanzania Luxembourg Botswana Myanmar Qatar Panama Zambia Turkey Thailand Angola Lithuania Namibia Venezuela Latvia Russia Mali GEI

35 Rank Country GDP 2012* GEI Rank Country GDP 2012* GEI Rank Country GDP 2012* 28 Korea Sri Lanka Burkina Faso Slovenia Lao PDR Cameroon Portugal Libya Madagascar Saudi Arabia Peru Sierra Leone Spain Mexico Swaziland Japan Albania Mauritania Puerto Rico Dominican Republic Indonesia Czech Republic Serbia Suriname Colombia Algeria Guatemala Kuwait Honduras Pakistan Poland El Salvador Burundi Oman Morocco Ethiopia Hong Kong Bosnia Chad Slovakia Nigeria Guyana Romania Vietnam Malawi Bahrain Kenya Uganda * Per capita GDP in PPP 2012 or latest available data, in 2005 constant international dollars Source: World Bank; Hong Kong is from IMF and Puerto Rico is from CIA GEI 130 Bangladesh

36 The United States is in first place. Australia, Canada, and the Netherlands are good performers, but they all have weaknesses in at least one of the sub-indexes. Of the most populous EU countries, only the UK, in 4 th place, is among the top ten countries. The other large European countries rank in the middle: France is 12 th, Germany is 11 th, Poland is 38 th, and Spain is 32 st, followed by Italy in 49 th place. While the UK, France, and Germany are relatively well balanced over the 15 pillars, Poland, Spain, and Italy are entrepreneurially less efficient. A likely explanation for the EU countries relatively weak economic performance over the last decade is their low level of entrepreneurship; the same applies to Japan, which took 36 th place. Factor-driven countries with low GDPs, such as Pakistan, Bangladesh, Uganda and other poor African countries, are at the bottom of the entrepreneurship ranking, as expected. At the same time, these countries entrepreneurial performance is the least unbalanced. However, some countries including two former socialist countries, Serbia and Russia, innovation-driven Italy, and two South American countries, Brazil and Trinidad and Tobago should have higher levels of entrepreneurship, as implied by their development trend lines and more efficient use of entrepreneurial resources. The Ranking of the 3As By definition, the GEI is a three-component index that takes into account the different aspects of the entrepreneurial ecosystem. However, all three components, called sub-indexes, are in themselves complex measures that include various characteristics of entrepreneurial attitudes, entrepreneurial abilities, and entrepreneurial aspirations. Entrepreneurial attitudes are societies attitudes toward entrepreneurship, which we define as a population s general feelings about recognizing opportunities, knowing entrepreneurs personally, endowing entrepreneurs with high status, accepting the risks associated with business start-ups, and having the skills to launch a business successfully. The benchmark individuals are those who can recognize valuable business opportunities and have the skills to exploit them; who attach high status to entrepreneurs; who can bear and handle start-up risks; who know other entrepreneurs personally (i.e., have a network or role models); and who can generate future entrepreneurial activities. Moreover, these people can provide the cultural support, financial resources, and networking potential to those who are already entrepreneurs or want to start a business. Entrepreneurial attitudes are important because they express the general feeling of the population toward entrepreneurs and entrepreneurship. Countries need people who can recognize valuable business opportunities, and who believe that they have the skills required to exploit these opportunities. Moreover, if a nation s attitude toward entrepreneurship is positive, it will generate cultural support, financial support, and networking benefits to those who want to start businesses. Entrepreneurial abilities refer to entrepreneurs characteristics and those of their businesses. Different types of entrepreneurial abilities can be distinguished within the realm of new business efforts. Creating businesses may vary by industry sector, the legal form of organization, and demographics such as age and education. We define entrepreneurial abilities as start-ups in the medium- or high-technology sectors that are initiated by educated entrepreneurs, and launched because a person is motivated by an opportunity in an environment that is not overly competitive. Entrepreneurial abilities also refer to the equal participation of women in start-ups and other opportunities. In order to calculate the opportunity start-up rate, we use the GEM TEA Opportunity Index. TEA captures new start-ups not only as the creation of new ventures but also as start-ups within existing businesses, such as a spinoff or other entrepreneurial effort. Differences in the quality of start-ups are quantified by the entrepreneur s education level that is, if they have a postsecondary education and the uniqueness of the product or service as measured by the level of competition. Moreover, it is generally maintained that opportunity motivation is a sign of better planning, a more sophisticated strategy, and higher growth expectations than necessity start-ups. Entrepreneurial aspiration reflects the quality aspects of start-ups and new businesses. Some people simply hate their employer and want to be their own boss, while others want to create the next Microsoft. Entrepreneurial aspirations is defined as the early-stage entrepreneur s effort to introduce new products and/or services, develop new

37 production processes, penetrate foreign markets, substantially increase their company s staff, and finance the business with formal and/or informal venture capital. Product and process innovation, internationalization, and high growth are considered the key characteristics of entrepreneurship. Here we added a finance variable to capture the informal and formal venture capital potential that is vital for innovative start-ups and high-growth firms. Each of these three building blocks of entrepreneurship influences the other two. For example, entrepreneurial attitudes influence entrepreneurial abilities and entrepreneurial aspirations, while entrepreneurial aspirations and abilities also influence entrepreneurial attitudes. Figure 2.2 shows the relationship between the GEI, the three sub-indexes, and national per capita wealth, based on purchasing power parity GDP. In all the figures, we provide the associated trend line and R 2 values. All the trend lines are based on third-degree polynomial equations. Figure 2.2: The Three Sub-Indexes in Terms of Per Capita Real GDP ( , all data included) Number of observations: 425 As an outlier, UAE has been removed from the graphs.

38 For example, the overall Index shows a good fit and a positive relationship between development and entrepreneurship. The two move in the same direction, with an R 2 = 0.78, which implies a close, strong relationship between entrepreneurship and economic development. Unlike other entrepreneurship measures that find an L- shaped (self-employment rate) or a U-shaped (Total Early-Phase Entrepreneurial Activity Index) relationship between entrepreneurship and development, we find a mild S-shaped relationship. The relationship between the Entrepreneurial Attitudes (ATT) sub-index and development is shown in the right-hand figure. The relationship is similar to the logarithmic function, implying that the overall entrepreneurship attitude increases as the country develops. The explanatory power, based on the R 2 = 0.67, shows a significant, strong correlation between ATT and per capita GDP. The lower-left figure contains the Entrepreneurial Abilities (ABT) sub-index values in terms of economic development. The explanatory power, R 2 = 0.74, is the highest among the three sub-indexes, implying a close and strong relationship between entrepreneurial abilities and development The trend of the Entrepreneurial Aspirations (ASP) sub-index is probably no surprise. The explanatory power of R 2 = 0.67 is significant and strong. Table 2.2 shows the ranking of the top 25 countries by GEI score and their sub-index rankings. The sub-index points and rankings for all 130 countries can be found in the Appendix. For example, the United States is first in the overall Index, and also in two of the three sub-indexes. Australia is 3 rd in attitudes and in abilities but 5 th in aspirations, as it is more interested in high-impact entrepreneurship than in replicative activities. Chile represents a more unbalanced case, ranking 19 th in the overall Index, 6 th in attitudes, 34 th in abilities, and 15 th in aspirations. Generally, countries that rank at the bottom in GEI also rank at the bottom of the three sub-indexes. Table 2.2: The Global Entrepreneurship Index and Sub-Index Ranks of the First 25 Countries, 2015 Country GEI GEI Rank ATT ATT Rank ABT ABT Rank ASP ASP Rank United States Canada Australia United Kingdom Sweden Denmark Iceland Taiwan Switzerland Singapore Germany France Netherlands Finland Norway Belgium Ireland Austria Chile United Arab Emirates

39 Estonia Israel Luxembourg Qatar Turkey Tables list the rankings and the 14 pillar values of the first 25 countries for the three sub-indexes. Each table gives the pillar values for each of the pillars that make up the respective index. The ranks and the pillar values for all the 130 countries can be found in the Appendices. As stated earlier, entrepreneurial attitude is defined as the general attitude of a country s population toward recognizing opportunities, knowing entrepreneurs personally, attaching high status to entrepreneurs, accepting the risks associated with a business start-up, and having the skills to successfully launch businesses. Entrepreneurial attitudes are important because they express the population s general feelings toward entrepreneurs and entrepreneurship. Table 2.3: Entrepreneurial Attitudes Sub-Index and Pillar Values for the First 25 Countries, 2015* Countries ATT Opportunity Perception Start-Up Skills Risk Acceptance Networking Cultural Support United States Canada Australia Sweden Finland Chile Norway Iceland Netherlands United Kingdom Austria Switzerland France Taiwan Germany Denmark Ireland Belgium Estonia Saudi Arabia United Arab Emirates Israel Qatar Spain Singapore *Pillar values are the normalized pillar scores after the average pillar correction.

40 The benchmark individuals are those who can (1) recognize valuable business opportunities, (2) have the necessary skills to exploit these opportunities, (3) attach high status and respect to entrepreneurs, (4) handle start-up risks, and (5) know entrepreneurs personally (i.e., have a network or role models). Moreover, these people can provide the cultural support, financial resources, and networking potential to those who are already entrepreneurs or want to start a business. The United States leads the Entrepreneurial Attitudes Index, followed by Canada, Australia, Sweden, Finland, Chile, Norway, Iceland, Netherlands, and the UK. Chile s 6 th place is a very strong showing for a South American country. Factor-driven African and Asian countries, including Swaziland, Mali, Sierra Leone, Ethiopia, Bangladesh, Pakistan, Malawi, Chad, and Burundi, are at the bottom. High entrepreneurial abilities are associated with start-ups in the medium- or high-technology sectors that are initiated by educated entrepreneurs and launched because of opportunity motivation in a not too competitive environment. Quality differences in start-ups are quantified by the motivation and education level of the entrepreneur, and the uniqueness of the product or service, as measured by the level of competition. Canada ranks number one on the Entrepreneurial Abilities Index and has a very strong showing in two of the four pillars, including Human Capital and Competition. The U.S. ranks second and is relatively weak in Opportunity Startup and Technology Absorption. Australia is stronger than the U.S. in two pillars, Opportunity Start-Ups and Technology Absorption, but weaker in Human Capital and very weak in Competition. The UK ranks 4th, with a significantly lower entrepreneurial abilities score than the United States and Australia, but it is relatively strong in Competition, implying that fresh entrepreneurs are mainly looking for market niches that do not have many competitors. The large share of start-ups initiated in the medium- and high-technology sectors is also a strong point of the UK. The first four countries are followed by Australia, Norway, Sweden, Singapore, Switzerland, and Germany. Table 2.4: Entrepreneurial Abilities Sub-Index and Pillar Values for the First 25 Countries, 2015 Countries ABT Opportunity Technology Human Competition Start-Up Absorption Capital Canada United States Denmark United Kingdom Australia Norway Sweden Singapore Switzerland Germany Ireland France Iceland Netherlands Taiwan Austria Belgium Luxembourg Estonia Finland Qatar

41 Lithuania United Arab Emirates Puerto Rico Latvia *Pillar values are the normalized pillar scores after the average pillar correction. Entrepreneurial aspiration is early-stage entrepreneurs efforts to introduce new products and/or services, develop new production processes, penetrate foreign markets, substantially increase a firm s number of employees, and finance a business with formal and/or informal venture capital. Product and process innovation, internationalization, and high growth are considered characteristics of entrepreneurship. The benchmark entrepreneurs are those whose businesses (1) produce and sell products/services considered to be new to at least some customers, (2) use a technology less than five years old, (3) have sales from foreign markets, (4) plan to employ at least ten people, and (5) have greater than 50 percent growth over the next five years. The Finance variable captures the informal venture capital potential, as well as the development of capital, venture capital, and credit markets, which is vital for innovative start-ups and high-growth firms. Like the two other sub-indexes, the United States leads in the Entrepreneurial Aspiration Index. While showing some weakness in Internationalization, it is very strong in Risk Capital and Process Innovation. Canada is second. Taiwan is third, with a strong showing in High Growth and Product Innovation, followed by Singapore, Australia, Belgium, Israel, Denmark, the UAE, and Switzerland, which round out the top ten. The surprise is the Czech Republic, with a very strong showing in Internationalization but a weak performance in Risk Capital. Table 2.5: Entrepreneurial Aspirations Sub-Index and Pillar Values for the First 25 Countries, 2015* Countries ASP Product Innovation Process Innovation High Growth Internationalization Risk Capital United States Canada Taiwan Singapore Australia Belgium Israel Denmark United Arab Emirates Switzerland Germany France Iceland Ireland Chile United Kingdom Turkey Sweden Czech Republic Austria Finland Estonia

42 Luxembourg Japan Korea *Pillar values are the normalized pillar scores after the average pillar correction. Summary and Conclusion Entrepreneurship is similar to other social creatures, in that it is a multidimensional phenomenon whose exact meaning is difficult to identify. There is only one thing more difficult: how to measure such a vaguely defined creature. Over the decades, researchers have created several entrepreneurship indicators, but none of them has been able to reflect the complex nature of entrepreneurship and provide a plausible explanation of its role in development. The Global Entrepreneurship Index is the first, and presently the only, complex measure of the national-level entrepreneurship ecosystem that reflects the multifaceted nature of entrepreneurship. In this chapter, we have presented the entrepreneurial performance of 130 of the world s countries, including country-level values for GEI entrepreneurial attitudes, entrepreneurial abilities, and entrepreneurial aspirations and for the 14 pillars. While the GEI represents the contextual features of entrepreneurship, it is also possible to analyze changes in entrepreneurship and its components in terms of development. We have presented the relationship between Index values and development, as measured by per capita GDP. While previous studies have found that entrepreneurship, measured primarily in terms of activities, has a U- or L-shaped relationship with national per capita income, we noticed a linear, mildly S-shaped relationship, which indicates that entrepreneurship is higher in richer countries. This finding fits more accurately with our present knowledge of the nature of the entrepreneurial ecosystem than U- or L- shaped relationships between the variables. The final ranking, with Nordic and Anglo-Saxon countries at the top and developing countries at the bottom, also reflects what we expect development trends to look like. In the final part of this chapter, we compared certain factors among some important countries and country groups. The pillar-level analysis provides a proper tool for showing the real differences and variations in entrepreneurship, which is found to vary substantially not only across countries with different levels of development but also among countries with similar per capita GDP. There is no doubt that the United States is the leading entrepreneurial country; despite a minimal decline in its GEI points, the U.S. is now number one not only in GEI score but also in two subindexes. While the leading countries have similar entrepreneurial features, individual European nations and the European Union lag behind the United States, and this gap is widening; this is especially evident in the PIIGS Portugal, Ireland, Italy, Greece, and Spain which lag far behind the larger EU countries and the Nordic fringe. Latin America will also need a substantial increase in entrepreneurship to reach levels comparable to those of North America. Comparing the developing countries shows that the configuration of the 14 pillars is similar in shape but at different levels across the three main parts of the world. In the following chapter we provide a detailed examination of entrepreneurship and the change in its components over the phases of development.

43

44

45

46 Chapter 3: Performance by Country and Country Group How well one country performs relative to others in terms of entrepreneurship is a question of some importance. In this section, we address this question for different country groupings. We do it by groups because the quality and contribution of a country s entrepreneurship vary systematically in accordance with its level of economic development. While the more developed countries tend to have better entrepreneurial processes, there still can be substantial differences between similarly developed countries entrepreneurial strengths and weaknesses. We have grouped the 130 countries into six groups according to their location and level of development (Table 3.1). In the following sections, we analyze the entrepreneurial performance of the different country groups relative to the world average (i.e., the unweighted average of the 130 countries for each GEI pillar). We also take a close look at three countries in each country group: one at the top, one in the middle, and one at the bottom of the regional ranking. Table 3.1 presents the countries in each group. Table 3.1: Country Groups Analyzed in This Chapter Asia-Pacific Europe Middle East and North Africa (MENA) North America South/Central America and Caribbean Australia Albania Algeria Canada Argentina Angola Bangladesh Austria Bahrain Mexico Barbados Benin Sub-Saharan Africa Brunei Darussalam Belgium Egypt United States Bolivia Botswana Cambodia Bosnia and Herzegovina Iran Brazil Burkina Faso China Bulgaria Israel Chile Burundi Hong Kong Croatia Jordan Colombia Cameroon India Cyprus Kuwait Costa Rica Chad Indonesia Czech Republic Lebanon Dominican Republic Côte d Ivoire Japan Denmark Libya Ecuador Ethiopia Kazakhstan Estonia Morocco El Salvador Gabon Korea Finland Oman Guatemala Gambia Lao PDR France Qatar Guyana Ghana Malaysia Germany Saudi Arabia Honduras Kenya Myanmar Greece Tunisia Jamaica Liberia Pakistan Hungary United Arab Emirates Nicaragua Madagascar Philippines Iceland Panama Malawi Singapore Ireland Paraguay Mali Sri Lanka Italy Peru Mauritania Taiwan Latvia Puerto Rico Mozambique Thailand Lithuania Suriname Namibia Vietnam Luxembourg Trinidad & Tobago Nigeria Macedonia Uruguay Rwanda Moldova Venezuela Senegal

47 Asia-Pacific Europe Montenegro Netherlands Norway Poland Portugal Romania Russia Serbia Slovakia Slovenia Spain Sweden Switzerland Turkey Ukraine United Kingdom Middle East and North Africa (MENA) North America South/Central America and Caribbean Sub-Saharan Africa Sierra Leone South Africa Swaziland Tanzania Uganda Zambia Sub-Saharan Africa Africa is the second largest continent by area and the largest by number of countries. The individual countries and economies of Africa exhibit considerable heterogeneity, with significant cultural and economic differences between the north and the south, and between the east and the west. In this analysis, we focus on the sub-saharan African countries; the North African countries are addressed as part of the Middle East and North Africa Region. As shown in Table 3.2, the sub-saharan group includes some of the continent s least developed countries, which is reflected in their GEI rankings and GEI scores. The leading country in this region, South Africa, has a GEI score of 40.0, which puts it 52 nd in the global GEI rankings, making it the only sub-saharan country in the top 50 percent. Uganda, with a score of 15.1, ranks next to last among GEI countries; 22 of the 29 sub-saharan countries rank in the bottom quartile. Even with this low level of development, there are important differences between the sub-saharan countries Attitudes, Ability, and Activities. Generally speaking, the region s most pressing bottlenecks are found in Attitudes, where the sub-index score is a little more than half of its relative strength, Ability. The Aspirations level is close to the Ability level for this region.

48 Table 3.2: GEI Ranking of the Sub-Saharan African Countries GEI Rank Country ATT ABT ASP GEI 52 South Africa Botswana Namibia Nigeria Kenya Gabon Senegal Rwanda Gambia Benin Liberia Ghana Mozambique Côte d Ivoire Tanzania Zambia Angola Mali Burkina Faso Cameroon Madagascar Sierra Leone Swaziland Mauritania Burundi Ethiopia Chad Malawi Uganda Sub-Saharan Africa Average Table 3.2 confirms that, despite encouraging progress in recent years, Africa remains the least developed continent. This is also reflected in the individual GEI pillars, as shown in Figure 3.1. With all African countries combined, the continent ranks below the world average for all pillars. One encouraging note is that Africa comes close to the world average in Technology Absorption capacity, a measure that combines countries institutional capacity to absorb technology with start-up activity in the technology sectors. Because the regional averages combine many countries, the resulting profiles tend to be more or less round. This generally holds true for sub-saharan Africa, with a couple of notable exceptions. First, sub-saharan Africa seems to suffer from a bottleneck in start-up skills. On the surface, this might appear inconsistent with the fact that sub- Saharan African countries exhibit some of the highest self-employment rates in the world. However, the measure is actually indicative of a quality problem, as most African self-employment activity is of poor quality. While starting a need-driven self-employment activity is easy, building a sophisticated start-up is difficult. Moreover, an education is

49 generally required to conduct more sophisticated activity, which reveals Africa s most serious handicap: its gross enrollment in tertiary education (the institutional component of the start-up skills pillar) is the lowest of all regions. Notable weaknesses are also found in Africa in the Attitudes measure; the normalized values of Risk Acceptance, Networking, Cultural Support, and Opportunity Perception are all below 0.20, whereas the values of all other pillars are above that threshold. This points to a general African weakness in Attitudes; the continent s relative strength is primarily in Ability. Overall, entrepreneurship in Africa is held back by institutional factors, a pattern typical in developing countries. At 0.3, the mean score for institutional factors in Africa is the lowest of all regions. The next lowest is in South and Central America, at Africa scores better on individual-level factors, with an overall mean score on a par with other regions. Thus, to exploit their entrepreneurial potential more effectively, African countries need to improve their institutional conditions for entrepreneurship. Figure 3.1: Pillar Level Comparison of Africa and the World In Figure 3.2 we compare the profiles of three African countries. South Africa is the best all-around performer in Africa in terms of entrepreneurship. Nigeria is not far behind, ranking 4 th among the 28 countries analyzed, and Uganda ranks at the bottom. The profiles of the three countries are quite different. South Africa clearly stands apart from Nigeria and Uganda on some of its Ability variables (notably, Competition and Opportunity Start-up) and many of its Aspiration variables (notably, Competition, Product Innovation, Process Innovation, High Growth, and Internationalization). This signals

50 that better institutional conditions should enable aspirational entrepreneurial activity to flourish. In terms of Start-up Skills, however, South Africa is on a par with Nigeria and Uganda. Nigeria stands out in terms of Opportunity Perception and Networking, but it is held back by poor aspirations. Nigeria lags behind South Africa and even Uganda in terms of Risk Acceptance, which reflects a high level of Business Risk due to the country s significant corruption and poor contractual enforcement. Uganda is at the bottom of the African countries, which perhaps reflects its recent internal instability. Although it enjoys relative bright spots in Networking, Cultural Support, and Competition, Uganda has considerable work to do to improve its institutions and introduce internal stability, both of which currently hold back its entrepreneurial potential. All three countries profiles are highly uneven, a pattern typical of developing economies. The uneven profiles suggest that there are bottlenecks holding back entrepreneurial performance, which is even true of the leading country in the region. However, the positive news is that, by focusing on alleviating bottlenecks, these countries could make significant progress relative to the effort expended. This differs from countries with rounder profiles, where opportunities for quick wins tend to be fewer. Figure 3.2: Pillar-Level Comparison of South Africa, Nigeria, and Uganda Middle East and North Africa (MENA) The MENA region comprises 15 countries in the Middle East and North Africa (Table 3.3). Like Africa, this region exhibits a high degree of internal variability. On the one end of the wealth scale, the MENA region includes the oilrich Persian Gulf economies, some of the richest countries in the world (as measured by per capita GDP). It also includes several lower-income economies, some of which continue to experience turmoil due to the Arab Spring. As

51 a group, however, the MENA region is considerably more developed than sub-saharan Africa: its mean GEI score almost is double that of sub-saharan Africa s, with most countries in the top 50 percent of the global GEI ranking (Algeria, Morocco, Egypt, and Iran are the exceptions). The three sub-indexes are quite evenly balanced; the highest mean score is for Attitudes, but Aspirations and Ability are at almost the same level. The leading entrepreneurial economy in this group is the United Arab Emirates (UAE), followed closely by Israel and Qatar. Libya, Algeria, Morocco, Egypt, and Iran have the lowest GEI scores. The common feature of this bottom group of MENA countries is fairly illiberal and controlled economies in which market access is monopolized by a ruling business elite. Table 3.3: GEI Ranking of the Middle East and North African Countries GEI Rank Country ATT ABT ASP GEI 20 United Arab Emirates (UAE) Israel Qatar Saudi Arabia Kuwait Oman Bahrain Lebanon Tunisia Jordan Libya Algeria Morocco Egypt Iran Middle East and North Africa Average The most notable phenomenon to affect this region in recent years is the Arab Spring, the wave of popular revolutions that saw some of the region s most enduring autocrats thrown out of power most spectacularly in Tunisia, Libya, and Egypt. In some countries, such as Bahrain, the ruling families have successfully resisted popular uprisings, whereas the upheaval in Syria led to a violent civil conflict that threatens to undermine the stability of the entire region. The Arab Spring phenomenon is noteworthy for our analysis because it occurred as a reaction to the ruling elites monopolization of opportunity in a number of countries in the MENA region. The memorable wave of upheaval that took place in 2011 was started by the suicide of a street vendor in Tunisia, who had been harassed by corrupt officials. In many countries, such as Tunisia, Libya, and Egypt, the economies had virtually become the private fiefdoms of the ruling elite, who monopolized entire economic sectors to the exclusion of the majority of the population. While much has been said about the democratic aspirations that clearly were an important motivation for the uprisings, it is useful to remember that the spark that ignited the Arab Spring had more to do with exclusion from opportunity than a deficit of democracy. In terms of GEI pillars, the MENA region as a whole performs close to the world average (Figure 3.3). Most pillar values in the region are exactly at the world average or very close to it. The differences are found in Opportunity Perception, Networking, and Risk Capital, where the MENA countries collectively perform better than the world average.

52 Figure 3.3: Pillar-Level Comparison of MENA and the World We next look at three countries that illustrate different categories within the MENA region. The oil-rich UAE is one of the world s wealthiest countries in terms of per capita GDP. Tunisia provides an example of the Arab Spring economies, while Egypt is a bottom performer. Figure 3.4 shows that the UAE is the top performer in the MENA region and a top performer globally for many pillars, most notably Human Capital, Risk Capital, and High Growth, where the UAE s performance is a perfect 1. This reflects not only its monetary wealth but also its high-quality human capital. The UAE s position as an important trading post undoubtedly contributes to its high level of High Growth and Internationalization Aspirations. Overall, the UAE exhibits a high level of Aspirations and a medium level of Attitudes and Ability. Its bottlenecks relate to Start-up Skills, Technology Absorption, and Process Innovation. Given the UAE s uneven overall profile, this suggests that an investment in entrepreneurship training and research capacity could bring about quite substantial improvements in the country s overall entrepreneurial performance. Tunisia s profile is quite different from the UAE s. Tunisia ranks 9 th among the 15 countries in the MENA region and 20th globally. Its GEI score of 35.5 is a little more than half of the UAE s. Unlike the UAE, Tunisia s relative strengths are found in Attitudes, whereas the monopolization of opportunity has held back development of its Ability and Aspirations pillars. The strongest aspect of Tunisia s entrepreneurship ecosystem is Cultural Support for entrepreneurship, and it also shows relative strengths in Start-up Skills (where it outperforms the UAE) and Technology Absorption. Egypt is a laggard in the MENA region, as evidenced by its GEI score of 28.1, which is only a notch above Iran, the bottom performer in this group. Although Egypt exhibits relative strengths in some Attitudes and Aspirations (notably, High Growth, Opportunity Perception, Cultural Support, and Process Innovation), all of its pillar values are lower than

53 the UAE s. The constraining effect of Egypt s pattern of opportunity monopolization probably contributes to its low Ability scores; market access there has been difficult, thus barring many new ventures from entry. Indeed, Egypt s Ability score is the lowest in this group, suggesting that the country urgently needs to liberalize trade and open its markets to aspiring entrepreneurs as well as improve education. Given the continued political turmoil in the country and the reassertion of power by the former army elite, it remains to be seen whether this can be achieved. Egypt s reasonable score for Opportunity Perception suggests that the country has the potential for a considerably higher level of entrepreneurial activity. Figure 3.4: Pillar-Level Comparison of the United Arab Emirates, Tunisia, and Egypt Asia-Pacific The Asia-Pacific region offers some of the greatest potential for economic growth of the countries analyzed in this work, as it contains the behemoth developing economies of China and India, a number of emerging economies such as Malaysia, Thailand, Vietnam, and Indonesia, and well-established, mature economies such as Australia, Japan, Korea, and Singapore (Table 3.4). One the other hand, this region also includes some of the poorest countries in the world, such as Cambodia, Myanmar, Laos, and Bangladesh. The economic potential of this region stems from its large and generally young population, most notably in the developing Asian economies. Table 3.4: GEI Ranking of the Asia-Pacific Countries GEI Rank Country ATT ABT ASP GEI 3 Australia Taiwan Singapore Korea

54 GEI Rank Country ATT ABT ASP GEI 33 Japan Hong Kong Malaysia Brunei Darussalam China Thailand Sri Lanka Lao PDR Vietnam Kazakhstan Philippines Cambodia India Myanmar Indonesia Pakistan Bangladesh Asia-Pacific Average When the profiles of the Asia-Pacific countries are combined, the result is a relatively round profile of pillar scores that does not differ much from the world average (Figure 3.5). However, this even pattern hides the fact that some countries in this group are global top performers while others are global laggards. Figure 3.5: Pillar-Level Comparison of Asia and the World

55 The Asia-Pacific region s striking feature is its diversity in terms of economic and entrepreneurship development. On the one hand, the region includes some of the world s leading entrepreneurial economies, such as Australia (3 rd globally), Taiwan (8 th ), and Singapore (10 th ). On the other hand, it also has global laggards such as Myanmar (109 th ), Indonesia (120 th ), Pakistan (123 rd ), and Bangladesh (at 130 th place, it is the bottom performer in the global GEI ranking). Interestingly, Korea and Japan do not rank at the top (5 th and 6 th in the region, 28 th and 33 rd globally). This signals that the bulk of these countries innovative energy is channeled through large, world-leading corporations. Even though both economies exhibit strong supply chains that include an important number of small- and mediumsized businesses, perhaps too many of these enterprises (relative to the countries innovative potential) content themselves with servicing local supply chains instead of seeking rapid global growth outside these chains. An interesting contrast is also observed between China and India. China s GEI score is more than 50 percent higher than India s, possibly suggesting that the bureaucratic red tape common in India constrains entrepreneurial activity. The bottom five countries in the Asia-Pacific group (India, Myanmar, Indonesia, Pakistan, and Bangladesh) also have this problem in common. The Asia-Pacific region is weakest in Attitudes toward entrepreneurship, whereas Ability and Aspirations are at almost the same level with each another. However, there is great variation within the region; for example, Australia s Attitude score is 77.9, whereas Cambodia s is 9.5, one of the lowest in the global GEI ranking. There is similar variation across other sub-indexes; for example, Aspirations scores range from Taiwan s high of 79.0 to Bangladesh s low of 7.6. Given this diversity, it makes sense to take a separate look at the developing and mature Asia-Pacific economies. The developing Asian countries represent the world s second least developed group, after Africa. The big challenge for these countries appears to be continuing to enhance institutional and regulatory conditions for entrepreneurship. For some countries, including China, this inevitably will also mean gradual democratization to accommodate the desires of the growing middle class. For other countries, such as India and Pakistan, this will mean cutting red tape and strengthening the rule of law to enable ambitious entrepreneurship to flourish. For the emerging economies, most notably Malaysia and Thailand, this will mean strengthening the infrastructure for ambitious entrepreneurship and facilitating competitive market entry in the face of dominant industrial conglomerates. For the weakest economies, such as Cambodia, Laos, and Bangladesh, this will mean strengthening the institutional foundations for entrepreneurial activity and gradually developing human capital and physical infrastructure. Overall, there appears to be good potential for development in the region, as many developing Asian countries have stable governance structures capable of channeling the resources needed to facilitate the desired policy. The mature Asia-Pacific countries include some of the strongest and most dynamic economies in the world, with pillar values above the world average for almost all pillars, except Competition. These countries show also relatively less strength in Opportunity Perception and Start-up Skills, both of which are close to the world average. Apart from Australia, the profiles of the mature Asia-Pacific countries are surprisingly uneven, suggesting systematic bottlenecks in Attitudes balanced against notable strengths in Aspirations. As a general rule, the mature Asia-Pacific countries (except Australia) would likely make the greatest gains by addressing this aspect of their entrepreneurship ecosystems. We now take a closer look at three different economies in the region (Figure 3.6). Australia is a global leader that exhibits strengths across virtually all GEI pillars. China is the world s powerhouse in production, and it continues to see impressive growth rates despite the turbulent world economy; of course there may be major structural challenges ahead for China. Bangladesh is one of the world s poorest countries and it has major development challenges, but it also has a large population and therefore much potential human capital.

56 Figure 3.6: Pillar-Level Comparison of Australia, China, and Bangladesh In Figure 3.6 we see that Australia s entrepreneurial profile is nice and round. This explains the country s high overall ranking and means that Australia is a strong all-around performer with a strong entrepreneurship ecosystem. Australia s greatest strengths are found in Technology Absorption, Risk Capital, Start-up Skills, Opportunity Perception, Opportunity Start-up, and Human Capital; in fact, there are no real weaknesses in Australia s entrepreneurship ecosystem, although it does rank behind China in Product Innovation. This suggests that, although Australia s overall innovation performance is strong, more of it could be channeled through the entrepreneurial sectors. Another relative weakness is Networking, which suggests that, even though Australia is a top performer globally, there are still areas where it can progress further. In contrast, Chin s profile is very uneven. China ranks 4 th in this region, after Malaysia, and Brunei. Its main strengths are in Aspirations: Product Innovation, Process Innovation, and Risk Capital. China also exhibits individual strengths in Ability and Attitudes, most notably Networking and Opportunity Perception. China s major bottlenecks appear to be in Internationalization, Start-up Skills, and Opportunity Start-up. Thus, there is an interesting contrast in China, in that its high level of Opportunity Perception does not appear to be fully converted into Opportunity Start-up activity. Because of China s size and great internal diversity, with a booming east coast and lagging west, general policy prescriptions are not feasible. China clearly needs to adopt an approach that includes developing a national network of regional entrepreneurship ecosystems. China s highly uneven GEI profile suggests that it has the potential to achieve major progress by focusing its policy efforts on bottlenecked areas. The priority in China appears to be to develop its institutional business infrastructure. Reflecting its less developed status, Bangladesh lags behind Australia and China in almost all areas, except for the Opportunity Start-up pillar, where it appears to perform better than China. However, this may be due to a blip in the data. Bangladesh s other strength, Opportunity Perception, suggests that its economy might be in a position to increase opportunity-driven entrepreneurial activity. Unfortunately, this potential is held back by major weakness in several domains, including Product and Process Innovation, Start-up Skills, Risk Acceptance, and

57 Internationalization. Thus there are major bottlenecks in Bangladesh, but its high scores on Opportunity Perception and Opportunity Start-ups, combined with Cultural Support, should provide good leverage in addressing the major challenges. Europe Europe also is a region with notable internal divides. The entrepreneurially mature Europe consists of the old western and northern European countries, plus Slovenia (Table 3.5). These are some of the most developed and mature global economies, which is apparent in their GEI rankings. The United Kingdom is ranked the 4 th most entrepreneurial economy globally, and five of the top ten global performers are found in Western and Northern Europe. Moreover, 13 of the top 20 entrepreneurial economies are in Western and Northern Europe, and all EU countries rank in the top 50 percent globally. These developed European economies exhibit traditional strengths in technology and innovation, and new European businesses benefit from the EU s internal market and the high quality of its infrastructure and institutional set-up. On the other hand, there is also a developing Europe that comprises the former centrally planned European economies, as well as Russia and Ukraine. Given its socialist history, developing Europe carries a legacy of an infrastructure geared toward heavy industries, a weak tradition of entrepreneurial activity, and, perhaps most importantly, a weak tradition of initiative and assumption of responsibility. While traditionally strong in human capital, developing Europe is held back by poor Attitudes and poor Aspirations. Being mostly inculcated in industrial structure and individual attitudes, the post-socialist countries may prove surprisingly resilient, but the remnants of their socialist history may ultimately be erased only through generational change. Table 3.5: GEI Ranking of the European Countries GEI Rank Country ATT ABT ASP GEI 4 United Kingdom Sweden Denmark Iceland Switzerland Germany France Netherlands Finland Norway Belgium Ireland Austria Estonia Luxembourg Turkey Lithuania Latvia Slovenia Portugal Spain Czech Republic

58 GEI Rank Country ATT ABT ASP GEI 38 Poland Slovakia Romania Bulgaria Hungary Cyprus Greece Italy Croatia Montenegro Moldova Macedonia Ukraine Russia Albania Serbia Bosnia and Hercegovina Europe Average A closer look at the European countries offers further notable observations. The Nordic countries (Sweden, Denmark, Iceland, Finland, and Norway) all rank in the top 15 globally. France shows solid strength, thanks to its high-quality infrastructure. Estonia performs strongly and ranks ahead of Luxembourg, Portugal, and Spain. All three Baltic countries (Estonia, Lithuania, and Latvia) are closely ranked. Turkey, which we include in Europe in this analysis, performs strongly, splitting the Baltic countries. Italy s performance, on the other hand, is alarmingly weak, ranking below Portugal, Spain, Cyprus, and Greece, a group of countries that have suffered badly throughout the global financial crisis that started in Indeed, Italy performs worse than many countries with socialist legacies, such as the Baltic countries, Slovenia, the Czech Republic, and even Romania, Bulgaria, and Hungary. This is an alarming situation, especially given that Italy s ranking appears to be on a downward trend. Since 2007, Italy s GEI score has evolved as follows: 2007, 55.0; 2008, 57.6; 2009, 49.4; 2010, 44.3; 2012, 40.9; 2013, 41,.3. Thus, Italy s GEI score has dropped by over 15 points in five years, and has been a consistent trend since The bottom performers in Europe are Ukraine, Russia, Albania, Serbia, and Bosnia and Hercegovina. Despite Europe s heterogeneity, the region s combined pillar performance is consistently above the world average, except for Opportunity Perception, where it is at the world average (Figure 3.7). The Opportunity Perception mean is primarily dragged down by Europe s former centrally planned economies. The region s greatest strengths are found in Internationalization, Networking, Technology Absorption, Process Innovation, and Risk Capital.

59 Figure 3.7: Pillar-Level Comparison of Europe and the World A closer look at three European entrepreneurship ecosystems reveals notable heterogeneity among the European countries. The region s leading entrepreneurial economy, the UK, exhibits a strong all-around entrepreneurial profile. In contrast, with their considerably more uneven profiles, Greece and Russia have a lot of catching up to do (Figure 3.8).

60 Figure 3.8: Pillar-Level Comparison of the United Kingdom, Greece, and Russia The United Kingdom is a traditionally strong entrepreneurial economy, with entrepreneurial traditions extending well back to Victorian times and even earlier. This shows in its GEI profile, which is very round, suggesting a strong allaround performance. The UK s strongest pillar is Competition, followed by Human Capital and Opportunity Start-up, suggesting that the UK s greatest strengths are in Ability. The UK also exhibits strengths in Attitudes, whereas many of its Aspirations pillars show relative softness. Overall, therefore, the UK appears to have some catching up to do in terms of improving the ambitions and aspirations of its start-ups. The most notable aspect remains the overall evenness of the UK s entrepreneurial profile. In contrast, Greece appears to exhibit both outstanding strengths and notable bottlenecks. Greece s strongest pillar is Start-up Skills, but this may be partly due to the country s large grey economy, and its small business orientation, as it has few high-growth new businesses. Greece also exhibits reasonable strengths in Human Capital, Technology Absorption, Internationalization, and Risk Capital. On the other hand, it shows major bottlenecks in Opportunity Perception, Risk Acceptance, High Growth Aspirations, and Cultural Support. It may well be that this uneven profile has been influenced by the deep recession Greece entered in 2008, from which it is only now slowly beginning to emerge. The good news for Greece s economy is that the downward spiral appears to have bottomed out; however, with the economy roughly one-quarter smaller than it was in 2008, the country has much catching up to do. Perhaps the biggest problem is Greece s notorious bureaucracy, which constitutes a real hindrance to its entrepreneurial potential. This is reflected in Greece s low scores in High Growth and Risk Acceptance. While much has been done to address this constraint and move economic activity from the grey economy to the formal economy, Greece still has much to do in terms of harnessing its entrepreneurial potential to economic growth. Greece could draw inspiration from Iceland and Ireland, both of which were hard hit by the economic downturn but have emerged from the recession and entered a steady growth path.

61 Russia s entrepreneurship profile exhibits similar unevenness. Despite its extensive natural resources, the Russian entrepreneurship ecosystem is the fourth weakest in Europe. This suggests that, instead of being a source of strength, the Russian economy s abundant resources are actually a source of weakness, as they have caused Russia to become increasingly dependent on the price of oil for its economic wealth. Helped by the favorable rise of oil prices over the past decade, this has also allowed Russian politicians to delay introducing the political and economic reforms that are needed to facilitate innovation and diversify the Russian industrial base. In fact, rather than diversifying, the Russian industrial base has become even more reliant on energy and raw materials. These developments have resulted in an entrepreneurial profile that is highly uneven and lags behind most other postsocialist countries. Russia s outstanding strength is Human Capital, followed by much weaker Networking and High Growth. These relative strengths are offset by bottlenecks in Internationalization, Cultural Support, Product Innovation, Competition, Risk Acceptance, and Process Innovation. Laden with post-socialist baggage, the Russian entrepreneurship ecosystem continues to exhibit many deficiencies, and the Russian economy s lack of diversification and dependence on energy and raw materials do not help under the prevailing governance structure. It appears that, to escape this dilemma, Russia will need to strengthen its rule of law and its economic and political institutions. North America North America includes the NAFTA countries: the U.S., Canada, and Mexico. The U.S. and Canada are global leaders, 1 st and 2 nd in GEI ranking (Table 3.6). In contrast, Mexico ranks only 75 th, despite some progress in recent years. Whereas the U.S. and Canada profiles show approximately equal strength for all sub-indexes, Mexico s strength appears to be in Attitudes; its entrepreneurial performance is held back by weaknesses in Ability and Aspirations. Table 3.6: GEI Ranking of the North American Countries GEI Rank Country ATT ABT ASP GEI 1 United States Canada Mexico North America Average The North American region exhibits traditional strength in entrepreneurship. This is illustrated by Figure 3.9, which compares the GEI profile of the North American region to the world average. North America stands out as the strongest entrepreneurship ecosystem in the GEI analysis, with all pillars clearly above the world average. Particular strengths are exhibited in Opportunity Perception, but the region performs strongly across all pillars. The profile of this region is relatively round, dominated by the U.S. and Canada.

62 Figure 3.9: Pillar-Level Comparison of North America and the World Comparing the three countries in this region (Figure 3.10), we see that the U.S. is the leading entrepreneurship ecosystem in North America, and it also ranks first globally. A traditional hotspot for entrepreneurship, the U.S. economy boasts strengths in all areas, with the possible exception of Networking. This may signal the highly individualistic U.S. culture and suggests that Networking which is an important requirement in the knowledge economy is an area where a concentrated policy effort could bring significant returns.

63 Figure 3.10: Pillar-Level Comparison of the United States, Canada, and Mexico Canada s entrepreneurial profile is similar to that of the U.S., which is reflected in Canada s 2 nd -place global ranking. Relative to the U.S., Canada exhibits some relative softness in Start-up Skills, Product and Process Innovation, High Growth, and Competition. Thus, it appears that Canada should invest further in entrepreneurship education and training, and in Innovation. A strength of the Canadian economy is that it is close to a large market and can tap into the strong U.S. entrepreneurship ecosystem. Mexico s entrepreneurship ecosystem is considerably less developed than that of the U.S. or Canada. Although it exhibits strength in Opportunity Perception and in Opportunity Start-up, Networking, and Product Innovation, the Mexican entrepreneurship ecosystem appears to suffer from clear bottlenecks in Internationalization, Human Capital, Cultural Support, and High Growth. Thus, Mexico s strengths are mostly in Attitudes, whereas its bottlenecks are primarily concentrated in Aspirations, although some are also found in Attitudes and Ability. It appears that Mexico needs a broad-based, coordinated policy that can coherently addresses its bottlenecks without undermining its strengths.

64 South and Central America and the Caribbean In this analysis, the South and Central America and Caribbean region includes all Latin American economies, except Mexico (Table 3.7). Although considerably less developed than North America, developed Europe, and Asia, this region offers considerable potential for entrepreneurial activity, thanks to its overall growing economy, improving governance, and young population. Many Latin American economies have recorded positive developments in recent years, although progress has been far from uniform. While some countries have instituted strong and open governance systems (e.g., Chile and Uruguay), the continent overall continues to suffer from incompetent governance that holds back its entrepreneurial potential. Table 3.7: GEI Ranking of the South and Central American and Caribbean Countries GEI Rank Country ATT ABT ASP GEI 19 Chile Puerto Rico Colombia Uruguay Costa Rica Argentina Barbados Paraguay Panama Peru Dominican Republic Honduras El Salvador Nicaragua Trinidad & Tobago Ecuador Bolivia Jamaica Brazil Venezuela Suriname Guatemala Guyana South and Central America and Caribbean Average The top performer in this region is Chile, which is also the only country in the region that ranks in the top 20 in the global GEI ranking. Chile, Puerto Rico, and Colombia are close to one another, followed by Uruguay, after which there is a cluster of countries with similar GEI scores: Costa Rica, Argentina, Barbados, and Paraguay. It is notable that Brazil ranks just 19 th among the 23 countries in this group, trailed only by Venezuela, Suriname, Guatemala, and Guyana. Note that GEI ranking does not cover Cuba and Haiti, both of which would likely rank close to the bottom. Collectively, the relative strengths in this group are found in Attitudes and Ability, whereas the region s performance in Aspirations is relatively weak. The region thus faces a challenge in improving Aspirations and in instilling a more

65 innovative, growth-oriented international outlook among its entrepreneurial ventures. This challenge appears particularly acute in Brazil, which ranks at the bottom of the region in this regard. As a group, the GEI profile of the South and Central American and Caribbean region is surprisingly uneven (Figure 3.11). The region beats the world average in Opportunity Perception and Start-up Skills but is equal to or behind the world average in other pillars, notably Process Innovation, Risk Capital, and Technology Absorption. Despite these challenges, the region offers great potential for entrepreneurship, conditioned by its ability to strengthen its economic institutions and governance systems. Figure 3.11: Pillar-Level Comparison of the Latin American Region and the World We look more closely at three countries in this region, Chile, Brazil, and Suriname (Figure 3.12). Chile boasts the strongest entrepreneurship ecosystem in this region, due perhaps to its strong, market-embracing governance systems. Chile ranks 19 th in the 2015 GEI ranking, in spite of its relatively low (globally speaking) per capita GDP, which is clearly the smallest of the top 20 entrepreneurial economies in GEI ranking. (France has the second lowest GDP per capita in the top 20, which is almost double that of Chile.) This is a remarkable achievement, given that the quality of institutions, which is given considerable weight in the GEI, tends to be strongly correlated with economic wealth. Thus, Chile punches above its weight in entrepreneurship, an outcome that we attribute to its sound governance systems. The most important strengths of Chile s system are Opportunity Perception, Product Innovation, and Start-up Skills, with the most significant bottlenecks found in Process Innovation, Competition, and Human Capital. Chile exhibits the greatest overall strength in Attitudes, followed by Aspirations and Ability.

66 Figure 3.12: Pillar-Level Comparison of Chile, Brazil, and Suriname Brazil is among the largest economies in this region, but it only ranks 19 th regionally and 100 th in the global GEI ranking. Brazil exhibits considerably weaker governance systems and economic and political institutions than Chile. These handicaps appear to prevent Brazil from taking full advantage of its large consumer market, which is reflected in the country s entrepreneurial profile. Although Brazil exhibits clear strength in Opportunity Perception, this does not fully compensate for multiple bottlenecks in Aspirations and Ability. The most important bottlenecks in the Brazilian entrepreneurship ecosystem are found in Internationalization, Process Innovation, Product Innovation, and Human Capital. Brazil thus faces a big challenge in improving its entrepreneurial Aspirations. Like many other developing economies, it seems that improving the quality of governance and economic institutions in Brazil will be key to mobilizing its entrepreneurial potential to pursue the perceived opportunities, which is underlined by the big gap between Opportunity Perception and Opportunity Start-up. Suriname s entrepreneurship ecosystem is the worst performing in the region and one of the most poorly performing ecosystems worldwide; it ranks 121 st among the 130 countries in the 2015 GEI ranking. Like most poorly developed entrepreneurship ecosystems, Suriname also has a highly uneven GEI profile, with relative strengths in Human Capital, Networking, Competition, and Cultural Support. In this case the strengths are only relative, although Suriname does have stronger scores than Brazil in Human Capital, High Growth, and Product and Process Innovation. However, Suriname s bottlenecks are severe, especially in Risk Capital, Technology Absorption, Process Innovation, High Growth, and Start-up Skills. These bottlenecks indicate that Suriname faces massive challenges as it strives to develop its entrepreneurial potential.

67 Conclusion This analysis points out important differences between regions of the world in terms of challenges to their entrepreneurial ecosystems. Different regions face very different challenges and priorities, which suggests that there is no one optimal policy approach that will work everywhere. In this regional analysis, we have grouped countries geographically, an approach that has its both strengths and shortcomings. If we had grouped countries according to their level of economic development, for example, the suggested challenges and implied policy priorities would have been different. This would also be true if we had grouped the countries according to their institutional set-up and economic history. The important message here is that each country and region should identify its own strengths and address its own bottlenecks. A much more detailed analysis is needed to identify these in a meaningful way. It should combine hard GEI data with soft insights. In chapter 4, we lay out an approach that uses GEI methods to identify specific policy priorities and actions for individual countries.

68

69

70 Chapter 4: Enhancing Entrepreneurship Ecosystems. A Systems of Entrepreneurship Approach to Entrepreneurship Policy Introduction An ecosystem is a community of living organisms in conjunction with the nonliving components of their environment, interacting as a system. These biotic and abiotic components are regarded as linked together through nutrient cycles and energy flows. 30 Facilitating entrepreneurship is high on many government policy agendas. Policies that support entrepreneurship have become increasingly sophisticated over time, as governments have moved from facilitating the creation of new firms toward supporting high-growth businesses. Many governments currently talk about support ecosystems that cover the entire life cycle of a new venture, from inception to early survival and growth to international expansion. However, while policy portfolios are growing, most policies still reveal a lack of understanding about what drives and constrains productive entrepreneurship in a particular economy. Although policy-makers increasingly talk about entrepreneurship ecosystems, their policies do not in fact consider and address bottlenecks that hold back the performance of these systems. As a result, entrepreneurship policy portfolios remain unfocused and thus are unable to truly change how an ecosystem functions. The lack of academic research and theory on entrepreneurship does not help. Researchers have put little effort into defining what entrepreneurship ecosystems actually means and how they work. As a result, when governments and researchers talk about these ecosystems they may be referring to completely different things. This confusion undermines the design and implementation of policies that effectively support the kind of entrepreneurial activity that can bring real economic growth. To design policies that effectively enhance entrepreneurship ecosystems, policy-makers need to take an ecosystems approach, which means that entrepreneurship is best understood at the country level not as the sum of individual efforts but as a true system. This counters the belief of many policy-makers that the more entrepreneurs there are, the greater the contribution they can make to economic growth. In fact, not all entrepreneurs are the same, and only a few ever grow their business enough to generate a meaningful number of jobs and increase the level of economic productivity. Policies that fail to consider the quality of entrepreneurial activity are therefore not likely to be effective. Moreover, not all economies of course are the same. Different economies have different strengths and challenges, and thus the bottlenecks they encounter also differ. For example, a country s financing policies might not be effective if the bottleneck it faces is a lack of aspiration or well-educated individuals decision not to choose entrepreneurship as a career. Clearly, who starts new firms is more important than how many people do so. Finally, policy-makers must realize that entrepreneurship is not only about individuals, as context also matters. A new business may have very different growth prospects, depending on where it is created. For example, a high-tech startup would be more likely to have an impact in Silicon Valley than in a low-income country that lacks the infrastructure to support productive entrepreneurship. It is important to understand that a country s economic and social contexts that is, its conditions for entrepreneurship not only influence the success of a new venture but who starts the venture in the first place. Policies that ignore this aspect of the entrepreneurial dynamic are not likely to be effective if the individuals who have the right skills and attitudes are not those who start new firms. Because entrepreneurship ecosystems are complex and consist of many interacting elements, they can be very difficult to change. The policy-makers must recognize this and approach the design of policies that support these systems accordingly. The more complex the system, the greater its inertia tends to be, and uncoordinated policy initiatives are not likely to recognize and target bottlenecks that hold back ecosystem performance, thus their effect

71 will not be long lasting. Only coordinated policies that address the bottlenecks of an entrepreneurship ecosystem are likely to bring about lasting change in the ecosystem dynamics. The GEI supports precisely this kind of approach to entrepreneurship ecosystem policy design. What Are Systems of Entrepreneurship? There is a dawning recognition that entrepreneurship policies focused only on the entrepreneur may be too narrow. This is why researchers, policy-makers, and practitioners alike now discuss entrepreneurship ecosystems, support ecosystems, or systems of entrepreneurship. However, these concepts can mean very different things. The following descriptions will help to clarify these definitions. Support ecosystems are what policy-makers usually mean when they talk about entrepreneurship ecosystems, which refers to portfolios of support policies intended to address the life cycle of a new venture. For example, policies that support the early stage of a new venture may include incubation services, start-up and pre-seed financing, and training services for prospective entrepreneurs. Policies that address the consolidation and early growth stages may include science park services, accelerator services, and providing seed and early-stage venture capital. Services in the growth stage may include support for internationalization. From this perspective, ecosystem narrowly refers to support services, which is useful as a model to organize portfolios of support initiatives but tends to ignore where new entrepreneurs come from and what determines their ability and aspirations. Entrepreneurship ecosystems usually refers to constellations of entrepreneurial activities and resources that contribute to a healthy entrepreneurial dynamic in a region or sometimes a nation. One example is Silicon Valley, a famous hotspot for entrepreneurial activity. What makes Silicon Valley work is not only entrepreneurship support policies but, more importantly, the availability of specialized resources, human capital, and infrastructure that support high-growth entrepreneurial activity. Most of these resources are provided not by public-sector agencies but by private-sector operators, such as experienced venture capitalists, law firms that offer specialized services, marketing agencies that specialize in new high-tech ventures, and other similar operations. Thus, the most widespread use of the term entrepreneurship ecosystems extends the notion from a support ecosystem to a regional constellation of specialized resources. However, although this notion works well in individual regions, it may not work as a national policy design. Furthermore, the notion of entrepreneurship ecosystems tends to focus on the provision of resources and gives less attention to how the demand for these resources and services is created. National and regional systems of entrepreneurship offer perhaps the widest perspective on entrepreneurial processes within their specific contexts. This relatively recent term is related to the concept and underlying theory of national systems of innovation (NSI), 31 which has been widely used as a platform to guide innovation policy design. The concept also underpins the European Union s current regional policy emphasis on smart specialization strategies. From an entrepreneurship perspective, the greatest shortcoming of the NSI theory is that it tends to emphasize structure and institutions but ignores individual determinants of entrepreneurial action. According to this theory, once a structure is in place, innovation will follow almost automatically. In contrast, the systems of entrepreneurship framework emphasizes that individuals actions are critical to innovation and entrepreneurship. Simply put, building science parks will not be effective if they are not filled with high-quality activity, which requires individuals who act. Therefore, the entrepreneurship systems framework emphasizes the effects of institutions and infrastructure combined with individual-level attitudes, ability, and aspirations. The GEI draws heavily on the systems of entrepreneurship theory and therefore provides an ideal platform for the design of policies that address entire entrepreneurship ecosystems at both the national and regional level. To explain how and why the GEI methodology is ideally suited to support an ecosystems approach to entrepreneurship policy, we review current indicators of entrepreneurial activity in various countries. There are three essential indicators for measuring country-level entrepreneurship: input, output, and framework. While each has its own strengths, none of them is ideally suited to support an ecosystems approach to entrepreneurship policy.

72 Input indicators survey public attitudes and preferences toward entrepreneurship. A good example is the European SME Observatory, which also tracks individual opinions and preferences regarding entrepreneurship. While useful indicators of the opinion climate, these measures reveal little about how and when attitudes are likely to be converted into high-quality action. Output indicators, on the other hand, tend to count the entrepreneurial entries in a given economy. A good example is the Global Entrepreneurship Monitor, which uses population surveys to track the prevalence of nascent and new entrepreneurs in different countries. Another example is the World Bank s Enterprise Survey, which tracks newly incorporated businesses across different countries. While useful indicators of the magnitude of the entrepreneurship phenomenon in a given country, output indicators tend to focus on quantity rather than quality, and to ignore the regulating effect a country s institutions and infrastructure have on entrepreneurial ability and aspirations. Framework indicators highlight how well a given country s institutional and policy frameworks support entrepreneurship. Perhaps the best known example is the World Bank s ease of doing business index, which tracks regulations that govern the creation and operation of certain types of new businesses across countries. Another example is OECD s Entrepreneurship Indicators program, which also seeks to track a country s framework conditions for entrepreneurship. However, while useful as comprehensive reviews of regulatory quality, framework indexes tell us little about entrepreneurial action and determinants thereof. While different approaches have different merits, none of the existing approaches addresses the dynamics of entrepreneurship ecosystems. Therefore, an approach is needed that addresses all three conditions: inputs, outputs, and framework. This is because we know that institutions and individuals are both critical to entrepreneurship. If individuals do not act there will be no entrepreneurship, no matter how perfect the institutional framework is. On the other hand, individual action will not have much of an impact without an appropriate institutional framework to leverage support for the growth of new businesses. The GEI approach is based on three important premises that provide an appropriate platform for analyzing entrepreneurship ecosystems. First, entrepreneurship is fundamentally an action undertaken and driven by individuals. Therefore, individual-level data is needed to capture the dynamics of an entrepreneurship ecosystem. Second, this individual action is regulated by a country s institutional framework for entrepreneurship. Therefore, country-level data on entrepreneurial framework conditions are also needed to capture the dynamics of an entrepreneurship ecosystem. Third, entrepreneurship ecosystems are complex, multifaceted structures in which many elements interact to produce system performance, thus the index method needs to allow the constituent elements to interact. Therefore, the GEI defines a National System of Entrepreneurship as the dynamic, institutionally embedded interaction between individuals entrepreneurial attitudes, abilities, and aspirations, which drives the allocation of resources through the creation and operation of new ventures. This definition implies that the GEI conceptualizes entrepreneurship as a trial-and-error process of resource allocation that is driven by individuals and regulated by context, and that drives the allocation of resources toward productive use in the economy. In short, entrepreneurs create new firms to pursue perceived opportunities. However, it is impossible to prove in advance that a perceived opportunity is real that is, if it will develop as expected and the only way to test it is to mobilize resources (e.g., human capital, financing). If the opportunity turns out to be real, then these resources will have been put to productive use. However, if the opportunity is not real, or if the country s framework conditions do not support the effective conversion of opportunities into new business growth, entrepreneurs will abandon the opportunity and put the resources to other uses. Thus, the net outcome of this dynamic process is an increase in the country s total factor productivity, a key determinant of economic growth. The GEI approach was designed to capture the ability of a given country s entrepreneurship ecosystem to contribute to total factor productivity and, therefore, to economic growth. This means that the GEI is fundamentally a quality index rather than a quantity index. As noted above, the most important aspect of entrepreneurship from an economic

73 perspective is not the quantity but the quality. The GEI is the only index of entrepreneurship that meaningfully captures the quality of countries entrepreneurship ecosystems that is, their ability to drive total factor productivity. The distinctive aspects of the GEI approach have important consequences for policy practice. Perhaps the most important arises from the penalty of bottleneck approach, which stems from the notion that system elements coproduce system performance and bottleneck factors therefore may hinder that performance. For example, funding policies will be effective only if financing is a bottleneck that is inhibiting the creation and growth of new, productive businesses. However, if the real bottleneck is entrepreneurial skills, providing additional money for new businesses may not improve the economy s entrepreneurial performance. Therefore, to produce real and lasting change in the dynamics of countries entrepreneurship ecosystems, entrepreneurship policies need to address ecosystem bottlenecks in a coherent and coordinated way. We next discuss how the GEI methodology supports this outcome. Systems of Entrepreneurship and Entrepreneurship Ecosystem Policy Although the idea of systems of entrepreneurship is intuitively appealing, what might the implications of an ecosystems approach be for entrepreneurship policy? The two defining features of an ecosystem approach to entrepreneurship policy are coordination across policy domains and a focus on ecosystem constraints. The former implies a broad-based approach to entrepreneurship policy that designs, implements, and orchestrates policy measures that address different aspects of the country s entrepreneurial ecosystem dynamic. A focus on ecosystem bottlenecks goes beyond coordination to support informed resource allocation choices across policy sectors. At present, most entrepreneurship policy initiatives are still implemented without much coordination or with coordination that is limited to different initiatives within the same domain (e.g., alternative policies to provide funding for small and medium-sized firms). Typically, the aim of such coordination is to avoid overlap in policy initiatives that address the same need, such as financing. While such coordination helps avoid the waste of resources that stems from a duplication of effort, it also fails to create and exploit synergies that might result from the kind of dynamic, mutually reinforcing interactions that bring entrepreneurship ecosystems to life. Today, coordinated entrepreneurship policy still primarily refers to avoiding overlap, rather than to maximizing the positive feedback and synergies between complementary actions. For entrepreneurship policies to nurture and facilitate entrepreneurship ecosystems effectively, policy-makers must become more aware of how the different elements of these ecosystems interact. For example, the proliferation of government-sponsored venture capital programs has given rise to complaints in some countries that the real bottleneck is no longer scarce venture funding but the dearth of fundable management teams and innovative business concepts. If there are too few innovative, high-potential start-ups, venture capital initiatives will address the wrong bottlenecks. In an ecosystems approach to entrepreneurship policy, attention is paid to such bottlenecks and policy actions are coordinated to maximize positive synergies across complementary initiatives. This level of coordination is still lacking in entrepreneurship policy today. The distinctive methodological features of the GEI ecosystem approach are (1) contextualizing individual-level data by weighting it with data that describes a country s entrepreneurship framework conditions; (2) the use of 14 contextweighted measures of entrepreneurial Attitudes, Abilities, and Aspirations, which are organized into three subindexes; (3) a recognition that different pillars interact to co-produce system performance; and (4) the consequent recognition that national entrepreneurial performance may be held back by bottleneck factors that is, poorly performing pillars that may constrain ecosystem performance. See chapter 5 for a detailed description of the GEI method.

74 Figure 2.1: Dynamic of National Systems of Entrepreneurship The GEI is a multifaceted index that reflects the complexity of country-level entrepreneurship ecosystems. As shown in Figure 2.1, it measures 14 different aspects of entrepreneurship ecosystems that are organized into Attitudes, Abilities, and Aspirations. Positive attitudes are needed so that competent individuals choose entrepreneurship over alternative occupations. The ability aspect reflects the quality of the resulting new ventures within their national context. Aspirations reflect these ventures potential to achieve rapid growth and high productivity. As explained in the methodological Chapter 5, each pillar is measured as a composite of individual-level data and data that describe relevant framework conditions for entrepreneurship. For example, Start-up Skills captures whether adult individuals think they have the necessary skills to start a new venture, weighted by a measure of the degree of tertiary education in the country. This framework variable is used because the higher a country s level of education, the higher the quality of its entrepreneurial ventures tends to be. As another example, Networking is a combination of how many individuals in the adult population personally know people who have started new businesses, weighted by the prevalence of Internet use in the country. This measure is used because the Internet tends to amplify opportunities for networking. Thus, the GEI approach captures individual-level attitudes, ability, and aspirations; each individual variable is then weighted by a relevant framework condition that regulates a given individual-level variable s potential to contribute to a high-quality entrepreneurial dynamic. In other words, this approach captures the notion that entrepreneurship ecosystems are brought to life by individuals, but the ultimate impact of individual-level action is regulated by entrepreneurial framework conditions. The GEI methodology captures two other important aspects that define entrepreneurship ecosystems. First, it recognizes that the different pillars need to work together to create a high-quality ecosystem dynamic. Traditional indexes fail to capture this aspect. In traditional indexing methods, the different components (pillars) are allowed to substitute for one another. In other words, a traditional index would allow, say, Risk Capital to compensate for the Quality of Human Resources. This notion of substitutability is similar to replacing eggs with flour when baking a cake. Everyone knows that you need both eggs and flour to bake a good cake, and the GEI methodology similarly requires

75 that a high-quality entrepreneurial dynamic needs both Risk Capital and High-Quality Human Resources, in addition to the system s 1 other pillars. If one or more pillars perform poorly, it is likely to hold back the performance of the entire system. Although one in reality can compensate to some degree for, say, Human Resources with Risk Capital, the entrepreneurship ecosystem is likely to ground to a halt if either element is completely absent. The notion of bottlenecks derives directly from the notion that ecosystem elements interact to co-produce ecosystem performance. Because one cannot fully substitute individual pillars for others, poorly performing pillars can create bottlenecks that prevent the ecosystem from fully leveraging its strengths. To simulate this effect, the GEI methodology applies a penalty for bottleneck algorithm, which is explained in Chapter 5. This algorithm systematically penalizes ecosystem pillars according to its poorly performing pillars. To use the cake example, if we do not have enough eggs to bake a cake of a given size, we cannot use our flour effectively, even if we have enough of it. However, the penalty for bottleneck also tells us that by adding a few more eggs we can get a lot more cake, if the other ecosystem pillars are strong. A final implication, therefore, is that an ideal ecosystem is one in which the different pillars are more or less in balance, as this implies that the ecosystem is able to leverage all of its elements effectively. These methodological innovations of the GEI provide important insights into the workings of entrepreneurship ecosystems. Essential to the bottlenecks notion is that some factors may unduly constrain system performance beyond their objective importance. With the penalty for bottleneck methodology, it is possible both to identify where bottlenecks might lurk in any given system and how much the system performance will suffer as a result. These are strengths that no other index approach can offer and that make the GEI approach ideally suited to analyzing entrepreneurship ecosystems. Using the GEI Approach for Entrepreneurship Ecosystem Policy Analysis To illustrate the penalty for bottleneck method, consider a comparison between the U.S., Japan, and India, as shown in Figure 2.2. The figure shows the entrepreneurship ecosystem profiles of the three countries as measured by the GEI approach. Figure 2.2: Entrepreneurship Ecosystem Profiles of the U.S., Japan, and India

76 Figure 2.2 shows that the GEI profile of U.S. entrepreneurship is nice and round, with each pillar showing a strong performance. This is the hallmark of a well-balanced entrepreneurship ecosystem. The absence of major gaps in the U.S. GEI profile means that no major bottlenecks are holding back the performance of the U.S. entrepreneurship ecosystem. There is relative softness in the U.S. ecosystem in terms of Networking and Internationalization, which indicates that the U.S. is not as strong in these areas. The relative softness in Internationalization is understandable, as the large size of the U.S. domestic market makes it possible for entrepreneurs to grow without having to export their products or services. Japan s ecosystem profile is considerably more uneven than that of the U.S., which suggests that the Japanese entrepreneurship ecosystem suffers from real bottlenecks that hold back its performance. The biggest bottlenecks are in Start-up Skills, Opportunity Perception, Internationalization, and Competition. If Japan is seeking to improve its entrepreneurial performance, it should prioritize these areas. Addressing Start-up Skills is relatively straightforward, as it can be addressed with education policies. These policies would likely also strengthen Opportunity Perception, although this pillar also depends on the country s general economic performance. Like the U.S., Japan s large domestic market probably moderates its Internationalization aspirations. Addressing the Competition pillar likely requires altogether different policies. The profile of India s entrepreneurship ecosystem is considerably less developed and more uneven than those of the U.S. and Japan. This pattern is typical of developing economies. The biggest bottlenecks for the India s ecosystem are observed in Opportunity Start-up, Internationalization, High Growth, Product Innovation, and Start-up Skills. The low level of Opportunity Start-ups contrasts interestingly with a relatively healthy level of Opportunity Perception, which is actually at a higher level in India than in Japan. This suggests that India s infamous red tape perhaps inhibits the conversion of perceived opportunities into opportunity-driven businesses. The low level of Start-up Skills no doubt contributes to this imbalance. As a developing economy, India could make considerable progress simply by addressing its basic framework conditions for entrepreneurial and economic activity, such as the rule of law (i.e., equality, objectivity, and predictability in the application of laws, rules, and regulations), equal access to markets, and human capital. It is likely that all developing economies need to address such basic conditions, but the GEI analysis helps highlight specific priority areas for India. The above examples show how the GEI method could be harnessed for use in the analysis and design of entrepreneurship ecosystem policies in different economic contexts. Merely examining the ecosystem profiles of different countries provides interesting clues about country-specific features and the determinants of the quality of a country s entrepreneurial ecosystem. This is important, because it helps policy-makers focus on areas that appear to be constraining a country s entrepreneurial performance. A considerably more detailed analysis can be made by focusing on individual pillar components (only pillar-level analysis was shown here) and choosing benchmarks that are at a similar level of economic development. For example, it probably does not make sense to compare India to the U.S. because the two economies are so different. Better insights could perhaps be gained by comparing India to, say, China, Pakistan, or even a more aspirational benchmark such as Malaysia. This analysis can be taken much further. For example, because the GEI methodology allows the ecosystem pillars to interact, it is possible to conduct sensitivity analyses and simulate different policy scenarios. For example, in a recent policy analysis for the Scottish Enterprise, we analyzed where additional policy efforts should be focused in Scotland and other UK Home Nations (i.e., England, Northern Ireland, and Wales) in order to achieve a 10 percent increase in the overall GEI score. This analysis is presented in Table 2.1, which shows how the additional policy efforts should be allocated across the ecosystem pillars, assuming equal cost to increase pillar performance. The GEI methodology for Scotland, for example, suggests that 13 percent of the additional policy effort should be allocated to Opportunity Perception, 12 percent to Risk Capital, 11 percent each to Start-up Skills, Networking, and Process Innovation, and so on. These figures were calculated by focusing policy efforts on the most pressing bottleneck until it was alleviated, then moving to the next most pressing bottleneck, and so on. While this example obviously includes a number of

77 simplifying assumptions (notably, equal cost to address each pillar; an equally applied bottleneck penalty for all pillars; pillars equal ability to be changed by policy action), it nevertheless demonstrates the GEI methodology s ability to assess different policy scenarios. Although the scenarios should not be taken as prescriptive, the exercise nevertheless highlights priority areas that could be explored further. Another important benefit is that even this simplifying analysis suggests that there may be important differences among the UK Home Nations in terms of policy priorities in facilitating the UK s entrepreneurial ecosystem. Scotland Wales N. Ireland England UK Opportunity Perception 13% 21% 24% 8% 9% Startup Skills 11% 11% 13% 8% 9% NonFear of Failure 4% 3% 6% 5% 5% Networking 11% 11% 9% 9% 9% Cultural Support 3% 0% 0% 6% 6% Opportunity Startup 4% 3% 1% 5% 5% Tech Sector 0% 6% 0% 0% 0% Quality of Human Resources 4% 3% 5% 4% 4% Competition 0% 0% 0% 3% 3% Product Innovation 9% 9% 6% 10% 10% Process Innovation 11% 11% 13% 9% 9% High Growth 9% 6% 7% 11% 10% Internationali ation 7% 6% 4% 10% 10% Risk Capital 12% 11% 12% 13% 11% 100% 100% 100% 100% 100% Table 2.1: Ecosystem Optimization Analysis for UK Home Nations Using the GEI Method for Entrepreneurship Ecosystem Policy Design While the GEI provides the most innovative and powerful platform for entrepreneurship ecosystem policy analysis and design, important challenges remain. As noted above, a number of simplifying assumptions are needed to apply a penalty for bottleneck algorithm in constructing the Index. Such assumptions should be kept in mind when using the GEI approach to simulate the kind of policy scenarios illustrated in Table 2.1. As such, the choice of the ecosystem pillars themselves could be debated. For example, different framework measures might be required when developing a regional version of the GEI, as was done when a version was designed for the 125 EU regions. Importantly, the scenarios in Table 2.1 imply that there may not be one optimal ecosystem configuration for each country and each level of economic development. In fact, it is highly likely that there may be several efficient configurations for different countries at the same level of economic development, and for those at different levels of economic development. As noted earlier, entrepreneurship ecosystems are complex and there is still a great deal to learn about how they really work. One important limitation of the GEI methodology is that it only uses hard data. Entrepreneurship ecosystems are inherently complex, and this complexity extends beyond the quantification of individual ecosystem pillars. The GEI profile indicates which elements of the entrepreneurship ecosystem are in place and in what quantity; however, much like using the same ingredients can produce very different outcomes when baking a cake, depending on how the ingredients are mixed, the GEI tells us little about how the elements should be mixed to produce the best possible

78 outcome for any given country. These soft aspects of entrepreneurship ecosystems are hard to capture using only hard data. Therefore, to facilitate entrepreneurship policy design, it is important to blend hard and soft GEI data to understand how the different ecosystem elements could work together most effectively. For this reason, we have developed a GEI Policy Stakeholder Engagement approach, which is designed to extract the soft, experience-based data to give insights into how the entrepreneurship ecosystem really works and what specific policy actions should be made to address bottlenecks. To extract these soft insights, it is important to engage entrepreneurship ecosystem policy stakeholders who represent different elements of the ecosystem. Because these ecosystems are large and complex, it is likely that no single stakeholder has a full understanding of how they work. Therefore, it is important to allow each stakeholder to contribute their particular insights into what the ecosystem bottlenecks are and how they really work, perhaps by organizing stakeholder workshops. We have developed a stakeholder facilitation process designed to achieve exactly this purpose with the hard GEI data, which suggests that it is possible to organize a coherent, facilitated debate of the analysis to determine which of the bottlenecks are real and how they actually function. For example, the GEI analysis suggested that Risk Capital was one bottleneck for the Scottish ecosystem. Discussions among the Scottish stakeholders confirmed that this was so but they also noted an additional nuanced detail that it was not the amount of funding that constrained Risk Capital but the fact that the capital tended to get stuck in portfolio companies because of limited exit opportunities. In other words, while they confirmed that Risk Capital was a bottleneck, they also learned that the real cause of this bottleneck was insufficient circulation of Risk Capital within the Scottish entrepreneurship ecosystem. This added considerable insight not easily achieved through the analysis of hard data alone, and also provided pointers for targeted policy action. By helping to extract such soft insights, the GEI Policy Stakeholder Engagement process facilitates an evidence-based, coherent understanding of how a given country s entrepreneurship ecosystem really works, what the system-level priorities are, and how the policy actions to alleviate the bottlenecks should be designed, prioritized, and coordinated. Thus, when combined with the GEI methodology, the GEI Policy Stakeholder Engagement process provides a useful platform for designing and operationalizing entrepreneurship ecosystem policies. The GEI Policy Stakeholder Engagement Process comprises several steps: 1. Use the GEI analysis to identify possible bottlenecks in the country s entrepreneurship ecosystem. 2. Examine each bottleneck more closely in order to understand how it really works. To do this, it is important to engage with a group of policy stakeholders who can offer complementary insights into the inner workings of the entrepreneurship ecosystem. It is critical that the discussions be facilitated competently in order to draw out balanced insights and maintain coherence. 3. Conduct a causal analysis of how a bottleneck works by drawing on different sources of qualitative and quantitative data, thereby enabling a coherent discussion on how to alleviate the bottleneck. 4. Design and implement specific, coordinated policy actions to alleviate the country s ecosystem bottlenecks, and use the GEI to help set performance improvement targets. 5. Once consensus has been achieved about what the ecosystem s most pressing bottlenecks are and the associated policy priorities, an action stage should follow. This stage should focus on implementing specific, targeted policy actions collectively designed to bring about a real and tangible change in the ecosystem dynamic. This last stage can (and, in most cases, should) last for several years in order to ensure that it has a lasting impact. Used this way, the GEI and the policy facilitation process can provide a powerful platform to identify and implement real, long-lasting change in how entrepreneurship ecosystems work. Our experiences in countries such as Scotland and Estonia suggest that the approach can identify both key pressure points on entrepreneurship ecosystems and ways to address them.

79

80

81

82 Chapter 5: Methodology and Data Description Introduction In previous publications, we have described the Global Entrepreneurship Index methodology in detail. 32 In this chapter, we describe the GEI structure, the dataset used to create it, and a short summary of GEI methodology. The Index Structure We have defined country-level entrepreneurship as the dynamic, institutionally embedded interaction between entrepreneurial attitudes, entrepreneurial abilities, and entrepreneurial aspirations by individuals, which drives the allocation of resources through the creation and operation of new ventures. In accordance with this definition, we propose four levels of index-building: (1) variables, (2) pillars, (3) sub-indexes, and, finally, (4) the super-index. All three sub-indexes contain several pillars, which can be interpreted as the quasi-independent building blocks of the entrepreneurship index. In this section, we describe the sub-indexes and indicators. In the following section, we describe the variables. The three sub-indexes Attitudes, Ability, and Aspirations constitute the entrepreneurship super-index that we call the Global Entrepreneurship Index. While the Ability and Aspirations sub-indexes (outlined below) capture actual entrepreneurship abilities and aspirations as they relate to nascent and start-up business activities, the entrepreneurial attitude (ATT) sub-index identifies the attitudes of a country s population as they relate to entrepreneurship. For example, the pillar known as Opportunity Perception is essential to recognizing and exploring novel business opportunities. It is also critical to have the proper start-up skills and personal networks to exploit these opportunities. Moreover, fear of failure to start a business can have a negative effect on entrepreneurial attitudes, even when opportunity recognition and start-up skills exist. Entrepreneurial attitudes are thought be influenced by the crucial institutional factors of market size, level of education, the level of risk in a given country, the population s rate of Internet use, and culture, all of which are interaction variables of the indicator. The entrepreneurial abilities (ABT) sub-index is principally concerned with measuring some important characteristics of the entrepreneur and the start-up with high growth potential. This potential is approached with quality measures, including opportunity motivation for start-ups in a technology-intensive sector, the entrepreneur s level of education, and the level of competition. The country-level institutional variables include the freedom to do business, the technology adsorption capability, the extent of staff training, and the dominance of powerful business groups. The entrepreneurial aspiration (ASP) sub-index refers to the distinctive, qualitative, strategy-related nature of entrepreneurial activity. Entrepreneurial businesses are different from regularly managed businesses, thus it is particularly important to identify the most relevant institutional and other quality-related interaction variables. The newness of a product and of a technology, internationalization, high growth ambition, and informal finance variables are included in this sub-index. The institutional variables measure the technology transfer and the R&D potential, the sophistication of a business strategy, the level of globalization, and the depth of the capital market. By applying the penalty for bottleneck approach, GEI methodology captures the notion that systems, by definition, comprise multiple components, and that these components co-produce system performance. These are defining characteristics of any system, which simple summative indexes fail to capture. In a simple summative index, each system component contributes directly and independently to system performance. In the context of entrepreneurship, this would mean, for example, that a national measure of education would, directly and independent of other system components, contribute to national entrepreneurship, while in reality we know that education cannot contribute much to a country s entrepreneurial performance if individuals fail to act. On the other hand, if education were absent, the economic potential of entrepreneurial entries would be severely constrained. Moreover, even if both education and

83 agency were present, country-level entrepreneurial performance would be constrained if, for example, growth aspirations were missing or if there were no financial resources available to feed the growth of new ventures. A simple summative index would fail to recognize such interactions, thereby overlooking crucial aspects of system-level performance. The Individual Variables and Dataset As mentioned previously, an entrepreneurship index should incorporate both individual and institutional/environmental variables. All individual-level variables are from the GEM survey. The institutional variables are obtained from various sources. The full list and description of the applied GEM individual variables can be seen in Table 5.1. Table 5.1: The Description of the Individual Variables Used in the GEI Individual Variable Opportunity Recognition Skill Perception Risk Know Entrepreneurs Career Status Career Status Description The percentage of the population aged that recognizes good conditions to start a business in the next six months in the area where he/she lives The percentage of the population aged that claims to have the required knowledge/skills to start a business The percentage of the population aged stating that a fear of failure would not prevent them from starting a business The percentage of the population aged that knows someone who started a business in the previous two years The percentage of the population aged saying that people consider starting a business a good career choice The percentage of the population aged that thinks people attach high status to successful entrepreneurs The status and respect of entrepreneurs calculated as the average of career and status Opportunity Percentage of the TEA businesses initiated because of opportunity start-up motive Motivation Technology Level Percentage of the TEA businesses that are active in technology sectors (high or medium) Educational Level Percentage of the TEA businesses with owner/managers who have secondary education Competitors Percentage of the TEA businesses started in markets where not many businesses offer the same product New Product Percentage of the TEA businesses offering products that are new to at least some of the customers New Tech Percentage of the TEA businesses using new technology that is on average less thafive5 years old (including one year) Gazelle Percentage of the TEA businesses having high average job expectations (more than 10 more employees and 50 percent growth in five years) Export Percentage of the TEA businesses where at least some customers are outside the country (over 1 percent) Informal Investment The mean amount of three-year informal investment Mean Business Angel The percentage of the population aged that provided funds for a new business in previous three years, excluding stocks and funds, on average Informal Investment The amount of informal investment calculated as INFINVMEAN* BUSANG For the 2015 GEI, we use or earlier Global Entrepreneurship Monitor (GEM) individual data. For the individual variable calculation we include 455,191 individuals from 93 countries of the GEM Adult Survey. Seventy countries individual data are from the years , and 23 countries have individual data from the pre-

84 2010 years. We estimated the individual variables for 37 countries by using nearby and similar country GEM Adult Survey data. Since the availability of the institutional data also limited selection of the countries, we could include only nations that participated in the World Economic Forum in or the Global Competitiveness Report (GCR) survey. Some GCR countries were left out because of a lack of similar or nearby GEM countries. The size of the sample in different years, the participating countries, and the calculation of the individual variables, including the 37 non-gem countries, are reported in Table 5.2. All analyses of countries having data older than 2011 and based on estimates should be considered with caution. Table 5.2: The Distribution of the Sample by Countries and the Calculation of the Individual Variables Country/Year Individual Variable Way of Calculation Albania Average of Bosnia and Macedonia Algeria Average of Angola Average of Argentina Average of Australia Average of Austria Bahrain Average of UAE and Saudi Arabia Bangladesh data Barbados Average of Belgium Average of Benin Average of Nigeria, Ghana, and Malawi Bolivia data Bosnia and Herzegovina Average of Botswana Average of Brazil Average of Brunei Darussalam Average of Malaysia and Singapore Bulgaria Average of Romania and Montenegro Burkina Faso Average of Ghana, Uganda, and Malawi Burundi Average of Ghana, Uganda, and Malawi Cambodia Average of Vietnam and Thailand Cameroon Average of Nigeria, Ghana, and Malawi Canada Chad Average of Ghana, Uganda, and Malawi Chile Average of China Average of Colombia Average of Costa Rica Côte d Ivoire Average of Ghana, Uganda, and Malawi Croatia Average of Cyprus Same as Greece Czech Republic Denmark Average of Dominican Republic Ecuador Average of Egypt

85 Country/Year Individual Variable Way of Calculation El Salvador Estonia Average of Ethiopia Finland Average of France Average of Gabon Average of Namibia and Botswana Gambia Average of Ghana, Uganda, and Malawi Germany Average of Ghana Average of Greece Average of Guatemala Guyana Same as Suriname Honduras Average of Guatemala and Panama Hong Kong Hungary Average of Iceland data India Indonesia Iran Average of Ireland Average of Israel Average of Italy Average of Jamaica Japan Average of Jordan Kazakhstan Kenya Average of Ghana, Uganda, and Malawi Korea Average of Kuwait Same as Saudi Arabia Lao PDR Average of Vietnam and Thailand Latvia Average of Lebanon Liberia Average of Ghana, Uganda, and Malawi Libya Lithuania Average of Luxembourg Macedonia Average of Madagascar Average of Ghana, Uganda, and Zambia Malawi Average of Malaysia Average of Mali Average of Ghana, Uganda, and Malawi Mauritania Average of Ghana, Uganda, and Malawi Mexico Average of Moldova Average of Romania and Russia Montenegro Morocco Mozambique Average of Ghana, Uganda, and Malawi

86 Country/Year Individual Variable Way of Calculation Myanmar Average of Vietnam and Bangladesh Namibia Average of Netherlands Average of Nicaragua Average of Guatemala and Panama Nigeria Average of Norway Average of Oman Average of Saudi Arabia and UAE Pakistan Average of Panama Average of Paraguay Average of Bolivia, Ecuador, and Peru Peru Average of Philippines Poland Average of Portugal Average of Puerto Rico Qatar Average of Saudi Arabia and UAE Romania Average of Russia Average of Rwanda Average of Ghana, Uganda, and Malawi Saudi Arabia Senegal Average of Ghana, Uganda, and Malawi Serbia Sierra Leone Average of Ghana, Uganda, and Malawi Singapore Average of Slovak Republic Average of Slovenia Average of South Africa Average of Spain Average of Sri Lanka Average of India and Pakistan Suriname Swaziland Average of Namibia and Angola Sweden Average of Switzerland Average of Taiwan Average of Tanzania Average of Ghana, Uganda, and Malawi Thailand Average of Trinidad and Tobago Average of Tunisia Turkey Average of Uganda Average of Ukraine Average of Russia and Romania United Arab Emirates United Kingdom Average of United States Average of Uruguay Average of Venezuela Vietnam 2000

87 Country/Year Individual Variable Way of Calculation Zambia Average of Sum The Institutional Variables and Dataset Since the GEM lacks the institutional variables necessary for the Index, we substitute with other widely used relevant data from Transparency International (Corruption Perception Index), UNESCO (tertiary education enrollment, GERD), World Economic Forum (domestic market size, business sophistication, technology absorption and technology transfer capability, staff training, market dominance), International Telecommunication Union (Internet usage), the Heritage Foundation and World Bank (economic freedom), United Nations (urbanization index), KOF Swiss Economic Institute (economic globalization), Coface (business climate risk), and Groh et al. (depth of capital market). 33 We apply the most recent institutional variables available on April 30, The full description of the institutional variables, their sources, and the year of the survey can be found in Table 5.3. Table 5.3: The Description and Source of the Institutional Variables Used in the GEI Institutional Variable Domestic Market Urbanization Market Agglomeration Tertiary Education Description Source of Data Data Availability Domestic market size that is the sum of gross domestic product plus value of imports of goods and services, minus value of exports of goods and services, normalized on a 1 7 (best) scale data are from the World Economic Forum Competitiveness Urbanization that is the percentage of the population living in urban areas, data are from the Division of the United Nations, 2011 revision The size of the market: a combined measure of the domestic market size and the urbanization that later measures the potential agglomeration effect. Calculated as domestic market urbanization* Gross enrolment ratio in tertiary education, 2012 or latest available data. Business Risk The business climate rate assesses the overall business environment quality in a country It reflects whether corporate financial information is available and reliable, whether the legal system provides fair and efficient creditor protection, and whether a country s institutional framework is favorable to intercompany transactions ( It is a part of the country risk rate. The alphabetical rating is turned to a 7-point Likert scale from 1 (D rating) to 7 (A1 rating). December 30, 2013 data Internet Usage The number of Internet users in a particular country per 100 inhabitants, 2013 data Corruption The Corruption Perceptions Index (CPI) measures the perceived level of public-sector corruption in a country. The CPI is a survey of surveys, based on 13 different expert and business surveys. ( 9). Overall performance is measured on a 10-point Likert scale. Data are from World Economic Forum United Nations The Global Competitiveness Report , p ROM/Urban-Rural-.htm Own calculation - UNESCO Coface International Telecommunicati on Union Transparency International d=unesco&f=series%3ag ER_56 omic-studies-and-country- Risks/Rating-table D/Statistics/Pages/stat/defaul t.aspx /

88 Institutional Variable Economic Freedom Tech Absorption Description Source of Data Data Availability Business freedom is a quantitative measure of the ability to start, operate, and close a business that represents the overall burden of regulation, as well as the efficiency of government in the regulatory process. The business freedom score for each country is a number between 0 and 100, with 100 equaling the freest business environment. The score is based on 10 factors, all weighted equally, using data from the World Bank s Doing Business study. ( Data are from Firm-level technology absorption capability: Companies in your country are (1 = not able to absorb new technology, 7 = aggressive in absorbing new technology) Heritage Foundation/ World Bank World Economic Forum /explore The Global Competitiveness Report , p. 511 Staff Training Market Dominance Technology Transfer GERD Business Strategy The extent of staff training: To what extent do companies in your country invest in training and employee development? (1 = hardly at all; 7 = to a great extent) Extent of market dominance: Corporate activity in your country is (1 = dominated by a few business groups, 7 = spread among many firms) These are the innovation index points from GCI: a complex measure of innovation, including investment in research and development (R&D) by the private sector, the presence of high-quality scientific research institutions, the collaboration in research between universities and industry, and the protection of intellectual property Gross domestic expenditure on R&D (GERD) as a percentage of GDP, year 2012 or latest available data; Puerto Rico, Dominican Republic, United Arab Emirates, and some African countries are estimated using regional or nearby country data. Refers to the ability of companies to pursue distinctive strategies, which involves differentiated positioning and innovative means of production and service delivery World Economic Forum World Economic Forum World Economic Forum UNESCO World Economic Forum The Global Competitiveness Report , p. 467 The Global Competitiveness Report , p. 471 The Global Competitiveness Report , p esco/tableviewer/tableview. aspx?reportid=2656 The Global Competitiveness Report , p. 22 Globalization Depth of Capital Market A part of the Globalization Index measuring the economic dimension of globalization. The variable involves the actual flows of trade, foreign direct investment, portfolio investment, and income payments to foreign nationals, as well as restrictions of hidden import barriers, mean tariff rate, taxes on international trade, and capital account restrictions. Data are from the 2013 report and based on the 2011 survey. ( The depth of capital market is one of the six sub-indexes of the Venture Capital and Private Equity Index. This variable is a complex measure of the size and liquidity of the stock market, level of IPO, M&A, and debt and credit market activity. Note that there were some methodological changes over the time period, so comparison to previous years is not perfect. The dataset is provided by Alexander Groh.* For missing data, nearby country data used. For countries having estimated individual data, DCM data are the same way as in the case of individual variables (see Table 2, last column) KOF Swiss Economic Institute EMLYON Business School, France, and IESE Business School, Barcelona, Spain Dreher, Gaston, and Martens** Groh et al.*** 34 *Special thanks for Alexander Groh and his team about the provision of the Depth of Capital Market data. ** Axel Dreher, Noel Gaston, and Pim Martens, Measuring Globalisation: Gauging its Consequences. New York: Springer, ***A. Groh, H. Liechtenstein, and K. Lieser, The Global Venture Capital and Private Equity Country Attractiveness Index 2012 Annual,

89 Missing Variables and Data Imputations Since our basic individual data are provided by the GEM, participation in the GEM survey determines the potential list of countries and sample size. However, there is another potential limitation, the availability of institutional data. Because seven out of our fourteen institutional variables are from the GCI, it is particularly important to have these variables. While there were five additional countries in the GEM 2010 and 2013 surveys, we had to cancel out Tonga, Vanuatu, the West Bank and Gaza Strip, Yemen, and Syria because of the lack of proper institutional variables. 35 A few variables are missing for some countries. Since we did not want to drop any more countries from the sample, we estimated the missing data using expert techniques, as follows: the GERD measure lacked data for Angola, Bahrain, Bangladesh, Barbados, Belize, Benin, Cambodia, Cameron, Chad, Cote d Ivoire, the Dominican Republic, Guyana, Lebanon, Libya, Mauritania, Namibia, Oman, Qatar, Rwanda, Suriname, Swaziland, and Venezuela. In these cases, other government sources and data from similar nearby countries provided adequate estimates. KOF globalization index data for Brunei, Lebanon, Montenegro, Kazakhstan, Hong Kong, Qatar, Puerto Rico, Saudi Arabia, and United Arab Emirates are estimated similarly to GERD, by applying nearby country data points. Puerto Rico s Business freedom dataset is the same as the U.S. All the other data are available for all countries; therefore, we believe that these rough estimates do not influence our results noticeably. 36 Calculating the Global Entrepreneurship Index Scores The GEI scores for all the countries are calculated according to the following eight points. 1. The selection of variables: We start with the variables that come directly from the original sources for each country involved in the analysis. The variables can be at the individual level (personal or business) that are coming from the GEM Adult Survey, or at the institutional/environmental level that are coming from various other sources. Altogether we use 16 individual and 15 institutional variables. 2. The construction of the pillars: We calculate all pillars from the variables using the interaction variable method; that is, by multiplying the individual variable with the proper institutional variable. 3. Normalization: pillar values were first normalized to a range from 0 to 1, according to equation 1: (1) for all j = 1... k, the number of pillars where is the normalized score value for country i and pillar j is the original pillar value for country i and pillar j is the maximum value for pillar j 4. Capping: All index-building is based on a benchmarking principle. We selected the 95 th percentile score adjustment, meaning that any observed value higher than the 95 th percentile is lowered to the 95 th percentile. For the 130 countries in our dataset, we used the benchmark values from the full dataset that contains all 425 observations over the time period. 5. Average pillar adjustment: The different averages of the normalized values of the indicators imply that reaching the same indicator values requires different effort and resources. Since we want to apply the GEI for public policy purposes, the additional resources for the same marginal improvement of the indicator values should be the same for all indicators. Therefore, we need a transformation to equate the average values of the components. Equation F2 shows the calculation of the average value of pillar j :

90 x j n i 1 x n i,, j. (2) We want to transform the x values such that the potential minimum value is 0 and the maximum value is i, j 1: k y x (3) i, j i, j where k is the strength of adjustment, the k -th moment of have to find the root of the following equation for k X is exactly the needed average, j y. We j n k xi, j nyj 0 (4) i 1 It is easy to see, based on previous conditions and derivatives, that the function is decreasing and convex, which means it can be solved quickly using the well-known Newton-Raphson method with an initial guess of 0. After obtaining k, the computations are straightforward. Note that if xj yj k 1 xj yj k 1 xj yj k 1 k can be thought of as the strength (and direction) of adjustment. The adjusted pillar values are calculated for all the time period, and this value and this distribution is applied for the 130 countries in the 2015 data. It means that the average adjusted pillar values of those countries participating in the 2013 GEM cycle are exactly the same in the dataset and in the 2015 GEI data. A note that, of the individual variables of the 130 countries in the 2015 GEI data, 70 are from the 2013 survey, 23 are from previous year GEM surveys, and 37 are estimates. The distribution of the average adjusted pillars can be found in the Appendix. 6. Penalizing: After these transformations, the PFB methodology was used to create indicator-adjusted PFB values. We define our penalty function following as: (5) where is the modified, post-penalty value of pillar j in country i is the normalized value of index component j in country i is the lowest value of for country i. i = 1, 2, n = the number of countries j = 1, 2,. m = the number of pillars 0 a, b 1 are the penalty parameters, the basic setup is a=b=1 7. The pillars are the basic building blocks of the sub-index: Entrepreneurial Attitudes, Entrepreneurial Abilities, and Entrepreneurial Aspirations. The value of a sub-index for any country is the arithmetic average of its PFB-

91 adjusted pillars for that sub-index multiplied by 100. The maximum value of the sub-indexes is 100 and the potential minimum is 0, both of which reflect the relative position of a country in a particular sub-index. where is the modified, post-penalty value of pillar j in country i i = 1, 2, n = the number of countries j = 1, 2,. 14 = the number of pillars 8. The super-index, the Global Entrepreneurship Index, is simply the average of the three sub-indexes. Since 100 represents the theoretically available limit, GEI points can also be interpreted as a measure of efficiency of the entrepreneurship resources where i = 1, 2, n = the number of countries The Underlying Structure of the Data (reflect to the full dataset) While the number of composite indicators has been increasing over the last few decades, some index creators pay little attention to the interrelationship between the different variables. Although the PFB methodology provides a practical solution for how to take this interrelationship into account, it does not save us from examining the underlying structure of the data. It is particularly important to have a well-defined nested structure of the whole index. The arbitrary selection of the variables in our case the pillars would cause confusion, false interpretation, and, finally, a misleading policy interpretation. The OECD handbook of composite indicators suggests analyzing the dataset in two dimensions, pillars and countries. 37 We have already provided detailed analyses at the country level; here we are presenting a pillar-level analysis by calculating the common (Pearson) correlation coefficients. Since we have only estimated data from 37 countries, it is better to examine not the 130 countries involved in our analysis but the full dataset with 425 data points. We report correlations between the normalized and average equated pillars, shown in Table 5.4, and the correlations between the normalized indicators after applying the PFB methodology, shown in Table 5.5. In general, significant medium to high correlations exist between the pillars in both cases. Opportunity Perception has positive and highly insignificant correlation with some other pillars (Human Capital, Process Innovation). Moreover, the correlation between Internationalization and Opportunity Perception is negative significant, but the correlation coefficient is weak, only The PFB pillars, as can be expected, improved the correlation, implying a closer relationship between the entrepreneurial features. The positive connection between the entrepreneurship pillars is vital for proper policy interpretation and suggestions. If the connection between the pillars were negative, it would imply that one pillar can only be improved at the cost of the other pillar. In that case, the improvement of the weakest pillar value would not necessarily improve GEI score. This is not the case.

92 There are other ways to check out the consistency of the dataset and the potentially strong connection between the pillars. Both the Kaiser-Meyer-Olkin measure of sampling adequacy and Bartlett s test of sphericity reinforce the fact that the 14 pillars of the GEI are closely correlated, and it is worth looking for a single complex measure. 38 The most popular test of the internal consistency of the pillars is based on the Cronbach Coefficient Alpha (c-alpha). The c- alpha value for the 14 pillars is 0.92 with the original data and 0.95 after applying the PFB methodology; both are well above the critical 0.7 threshold value. 39 In sum, all of these tests support the internal consistency of the structure as described with the 14 selected pillars.

93 Table 5.4: The Correlation Matrix between the Original Indicators ( dataset) Opportunity Perception **.152 **.152 **.291 **.218 **.161 ** **.258 ** ** *.154 ** 2 Startup Skills **.398 **.315 **.324 **.373 **.221 **.205 **.127 **.175 **.177 **.286 **.327 ** 3 Risk Acceptance **.729 **.742 **.616 **.631 **.620 **.540 **.649 **.398 **.538 **.603 ** 4 Networking **.609 **.525 **.471 **.482 **.397 **.491 **.287 **.540 **.559 ** 5 Cultural Support **.595 **.548 **.704 **.562 **.558 **.380 **.525 **.635 ** 6 Opportunity Startup **.656 **.639 **.457 **.569 **.317 **.524 **.575 ** 7 Technology Absorption **.582 **.537 **.694 **.480 **.526 **.628 ** 8 Human Capital **.523 **.578 **.550 **.496 **.635 ** 9 Competition **.503 **.271 **.492 **.535 ** 10 Product Innovation **.581 **.393 **.593 ** 11 Process Innovation **.537 **.652 ** 12 High Growth **.511 ** 13 Internationalization ** 14 Risk Capital 1 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). The number of observations= 425

94 Table 5.5: The Correlation Matrix between the Indicators, Sub-Indexes and the GEI Super-Index after Normalizing and Applying the PFB Method ( dataset) Opportunity Perception.370 **.374 **.348 **.488 **.641 **.412 **.374 **.313 **.471 **.441 **.442 **.261 **.313 **.147 **.371 **.358 **.500 ** 2 Startup Skills **.553 **.493 **.712 **.486 **.540 **.424 **.409 **.528 **.333 **.380 **.383 **.446 **.496 **.481 **.601 ** 3 Risk Acceptance **.803 **.842 **.805 **.712 **.723 **.722 **.838 **.651 **.736 **.528 **.651 **.704 **.771 **.864 ** 4 Networking **.844 **.709 **.650 **.615 **.618 **.734 **.548 **.623 **.458 **.647 **.669 **.696 **.799 ** 5 Cultural Support **.781 **.711 **.677 **.789 **.834 **.686 **.687 **.537 **.649 **.734 **.776 **.883 ** 6 ATTINDEX **.762 **.705 **.768 **.862 **.678 **.690 **.566 **.652 **.759 **.788 **.930 ** 7 Opportunity Startup **.753 **.739 **.909 **.595 **.681 **.464 **.644 **.684 **.725 **.865 ** 8 Technology Absorption **.687 **.888 **.647 **.769 **.605 **.638 **.730 **.798 **.867 ** 9 Human Capital **.880 **.641 **.683 **.649 **.627 **.735 **.784 **.841 ** 10 Competition **.615 **.636 **.443 **.617 **.656 **.701 **.820 ** 11 ABTINDEX **.786 **.617 **.715 **.796 **.853 **.961 ** 12 Product Innovation **.658 **.538 **.695 **.844 **.791 ** 13 Process Innovation **.642 **.745 **.866 **.832 ** 14 High Growth **.635 **.809 **.709 ** 15 Internationalization **.834 **.782 ** 16 Risk Capital **.870 ** 17 ASPINDEX ** 18 GEI 1 **. Correlation is significant at the 0.01 level (2-tailed). The number of observations= 425

95 Summary In this chapter, we have described the index-building methodology and the dataset. The GEI, a complex index reflecting the multidimensional nature of entrepreneurship, consists of three sub-indexes, 14 pillars, and 31 variables. While some researchers insist on simple entrepreneurship indicators, none of the previously applied measures was able to explain the role of entrepreneurship in economic development with a single indicator. Our index-building logic differs from other widely applied indexes in three respects: it incorporates both individual and institutional variables, it equates the 14 pillar values for equalizing the marginal effects, and it takes into account the weakest link in the system. The institutional variables can also be viewed as country-specific weighting factors. Moreover, institutional variables can balance out the potential inconsistency of the GEM data collection. The weakest link refers to the decreased performance effect of the bottleneck. Practically speaking, it means that the higher pillar values are adjusted to the weakest performing pillar value. While the exact measure of the penalty is unknown, meaning that the solution is not necessarily optimal, it still provides a better solution than calculating the simple arithmetic averages. Consequently, the newly developed PFB can be applied in cases where an imperfect substitutability exists among the variables and the efficiency of the system depends on the weakest performing variable. The method is particularly useful in making policy suggestions. The GEM survey served as a source for the individual variables, which are calculated mainly from the individual dataset, except for the 23 countries that only have data from previous years. Altogether, the sample includes 455,191 individuals from 93 countries. Individual data from 37 other countries are estimated by using similar or nearby country individual data, resulting in a sample of 130 countries. The availability of the institutional variables for all the countries has limited our selection possibilities. The proper interpretation of a particular institutional variable has been an important aspect of the selection. For example, the muddled interpretations of the effect of taxes on other entrepreneurship variables led to the exclusion of taxation. In all cases, we used the latest institutional data available as of April, 30, We summarized the index-building steps in eight points. Further information on these steps is available upon request. We have analyzed the underlying structure of the dataset in the variable level. The correlation coefficients, the Kaiser-Mayer-Olkin measures, and the Bartlett and c-alpha tests all suggested that the 14 pillars have a close relation to one another and that there is a place to construct a composite indicator. These tests were executed with the normalized original, as well as with the PFB adjusted variables. As expected, the PFB methodology improved the internal consistency of the dataset.

96 Appendix A Pillar distributions

97

98

99

100

101

102

103

104 Appendix B The Global Entrepreneurship Sub-Index Rank of Countries in alphabetical order, 2015 GEI ATT ABT ASP Countries GEI ATT ABT ASP rank rank rank rank Albania Algeria Angola Argentina Australia Austria Bahrain Bangladesh Barbados Belgium Benin Bolivia Bosnia Botswana Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Chad Chile China Colombia Costa Rica Côte d Ivoire Croatia Cyprus Czech Republic Denmark Dominican Republic Ecuador Egypt El Salvador Estonia

105 GEI ATT ABT ASP Countries GEI ATT ABT ASP rank rank rank rank Ethiopia Finland France Gabon Gambia, The Germany Ghana Greece Guatemala Guyana Honduras Hong Kong Hungary Iceland India Indonesia Iran Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea Kuwait Lao PDR Latvia Lebanon Liberia Libya Lithuania Luxembourg Macedonia Madagascar Malawi Malaysia Mali Mauritania Mexico

106 GEI ATT ABT ASP Countries GEI ATT ABT ASP rank rank rank rank Moldova Montenegro Morocco Mozambique Myanmar Namibia Netherlands Nicaragua Nigeria Norway Oman Pakistan Panama Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Romania Russia Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovakia Slovenia South Africa Spain Sri Lanka Suriname Swaziland Sweden Switzerland Taiwan Tanzania Thailand Trinidad & Tobago

107 GEI ATT ABT ASP Countries GEI ATT ABT ASP rank rank rank rank Tunisia Turkey Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Venezuela Vietnam Zambia

108 Appendix C Entrepreneurial Attitudes Sub-Index and Pillar Values of Countries in alphabetical order, 2015 Countries ATT Opportunity Perception Start-up Skills Risk Acceptance Networking Cultural Support Albania Algeria Angola Argentina Australia Austria Bahrain Bangladesh Barbados Belgium Benin Bolivia Bosnia Botswana Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Chad Chile China Colombia Costa Rica Côte d Ivoire Croatia Cyprus Czech Republic Denmark Dominican Republic Ecuador Egypt El Salvador Estonia Ethiopia

109 Countries ATT Opportunity Perception Start-up Skills Risk Acceptance Networking Cultural Support Finland France Gabon Gambia. The Germany Ghana Greece Guatemala Guyana Honduras Hong Kong Hungary Iceland India Indonesia Iran Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea Kuwait Lao PDR Latvia Lebanon Liberia Libya Lithuania Luxembourg Macedonia Madagascar Malawi Malaysia Mali Mauritania Mexico Moldova Montenegro

110 Countries ATT Opportunity Perception Start-up Skills Risk Acceptance Networking Cultural Support Morocco Mozambique Myanmar Namibia Netherlands Nicaragua Nigeria Norway Oman Pakistan Panama Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Romania Russia Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovakia Slovenia South Africa Spain Sri Lanka Suriname Swaziland Sweden Switzerland Taiwan Tanzania Thailand Trinidad & Tobago Tunisia Turkey Uganda

111 Countries ATT Opportunity Perception Start-up Skills Risk Acceptance Networking Cultural Support Ukraine United Arab Emirates United Kingdom United States Uruguay Venezuela Vietnam Zambia

112 Appendix D Entrepreneurial Abilities Sub-Index and Pillar Values of Countries in alphabetical order, 2015 Countries ABT Opportunity Startup Technology Absorption Human Capital Competition Albania Algeria Angola Argentina Australia Austria Bahrain Bangladesh Barbados Belgium Benin Bolivia Bosnia Botswana Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Chad Chile China Colombia Costa Rica Côte d Ivoire Croatia Cyprus Czech Republic Denmark Dominican Republic Ecuador Egypt El Salvador Estonia Ethiopia

113 Countries ABT Opportunity Startup Technology Absorption Human Capital Competition Finland France Gabon Gambia. The Germany Ghana Greece Guatemala Guyana Honduras Hong Kong Hungary Iceland India Indonesia Iran Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea Kuwait Lao PDR Latvia Lebanon Liberia Libya Lithuania Luxembourg Macedonia Madagascar Malawi Malaysia Mali Mauritania Mexico Moldova Montenegro

114 Countries ABT Opportunity Startup Technology Absorption Human Capital Competition Morocco Mozambique Myanmar Namibia Netherlands Nicaragua Nigeria Norway Oman Pakistan Panama Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Romania Russia Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovakia Slovenia South Africa Spain Sri Lanka Suriname Swaziland Sweden Switzerland Taiwan Tanzania Thailand Trinidad & Tobago Tunisia Turkey Uganda Ukraine

115 Countries ABT Opportunity Technology Human Competition Startup Absorption Capital United Arab Emirates United Kingdom United States Uruguay Venezuela Vietnam Zambia

116 Appendix E Entrepreneurial Aspirations Sub-Index and Pillar Values of Countries in alphabetical order, 2015 Countries ASP Product Innovation Process Innovation High Growth Internationalization Risk Capital Albania Algeria Angola Argentina Australia Austria Bahrain Bangladesh Barbados Belgium Benin Bolivia Bosnia Botswana Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Chad Chile China Colombia Costa Rica Côte d Ivoire Croatia Cyprus Czech Republic Denmark Dominican Republic Ecuador Egypt El Salvador Estonia Ethiopia

117 Countries ASP Product Innovation Process Innovation High Growth Internationalization Risk Capital Finland France Gabon Gambia. The Germany Ghana Greece Guatemala Guyana Honduras Hong Kong Hungary Iceland India Indonesia Iran Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea Kuwait Lao PDR Latvia Lebanon Liberia Libya Lithuania Luxembourg Macedonia Madagascar Malawi Malaysia Mali Mauritania Mexico Moldova Montenegro

118 Countries ASP Product Innovation Process Innovation High Growth Internationalization Risk Capital Morocco Mozambique Myanmar Namibia Netherlands Nicaragua Nigeria Norway Oman Pakistan Panama Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Romania Russia Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovakia Slovenia South Africa Spain Sri Lanka Suriname Swaziland Sweden Switzerland Taiwan Tanzania Thailand Trinidad & Tobago Tunisia Turkey Uganda Ukraine

119 Countries ASP Product Innovation Process Innovation High Growth Internationalization Risk Capital United Arab Emirates United Kingdom United States Uruguay Venezuela Vietnam Zambia

120 End Notes 1 For a review of the literature, see Z. J. Acs and N. Virgil, Entrepreneurship and Economic Development. Foundations and Trends in Entrepreneurship 6, no. 1 (2011): See Easterly, who identifies the slowdowns in the economies of OECD trading partners of LDCs as a possible cause of the disappointing growth performance. The Lost Decade: Developing Countries' Stagnation in Spite of Policy Reform Journal of Economic Growth 6 (2001): J. Sachs, The End of Poverty: Economic Possibilities for Our Time. New York: Penguin Press, 2005, S. Ketkar and Z. J. Acs, Where Angels Fear to Tread. Journal of International Entrepreneurship 1 (2013): A. Woolridge, Global Heroes: A Special Report on Entrepreneurship. The Economist, March 14, 2009, W. W. Rostow, The Stages of Economic Growth: A Non-Communist Manifesto. Cambridge, England: Cambridge University Press, M. Porter, J. Sachs, and J. McArthur, Executive Summary: Competitiveness and Stages of Economic Development. In The Global Competitiveness Report , ed. M. Porter, J. Sachs, P. K. Cornelius, J. McArthur, and K. Schwab, New York: Oxford University Press, 2002, H. Leibenstein, Entrepreneurship and Development. American Economic Review 38, no. 2 (1968): A. V. Banerjee and E. Duflo, Poor Economics: A Radical Rethinking of the Way to Fight Global Poverty. New York: Public Affairs, W. Baumol, Entrepreneurship: Productive, Unproductive and Destructive. Journal of Political Economy 98 (1990): Z. J. Acs, Entrepreneurship and Economic Development: The Valley of Backwardness. Annals of Innovation & Entrepreneurship 1 (2010): D. Acemoglu and S. Johnson, Unbundling Institutions. Journal of Political Economy 113 (2005): ; Z. J. Acs, P. Braunerhjelm, D. B. Audretsch, and B. Carlsson, The Knowledge Spillover Theory of Entrepreneurship. Small Business Economics 32, no. 1 (2009): The following identify several dimensions of entrepreneurship: W. B. Gartner, What Are We Talking about When We Talk About Entrepreneurship? Journal of Business Venturing 5, no. 1 (1990): 15-28; P. Davidsson, Researching Entrepreneurship. New York: Springer, 2004; S. Wennekers and R. Thurik, Linking Entrepreneurship to Economic Growth. Small Business Economics 13, no. 1 (1999): 27-55; K. Godin, J. Clemens, and N. Veldhuis, Measuring Entrepreneurship Conceptual Frameworks and Empirical Indicators. Studies in Entrepreneurship Markets 7 (2008). 14 Z. J. Acs, E. Autio, and L. Szerb, National systems of entrepreneurship: measurement issues and policy implications. Research Policy, 43 (3): Z. J. Acs and A. Varga, Entrepreneurship, Agglomeration and Technological Change. Small Business Economics, 24 (2005): S. Papagiannidis and F. Li, Skills Brokerage: A New Model for Business Start-Ups in the Networked Economy. European Management Journal 23 (2005): M. Caliendo, F. M. Fossen, and A. S. Kritikos, Risk Attitudes of Nascent Entrepreneurs: New Evidence from an Experimentally Validated Survey. Small Business Economics 32 (2009): S. Shane and D. Cable, Network Ties, Reputation, and the Financing of New Ventures. Management Science 48 (2003): L. Guiso, P. Sapienza, and L. Zingales, Does Culture Affect Economic Outcomes? CEPR discussion paper no. 5505, Retrieved from 20 R. Bhola, I. Verheul, R. Thurik, and I. Grilo, Explaining Engagement Levels of Opportunity and Necessity Entrepreneurs, EIM working paper series H200610, Zoetermeer, Netherlands: EIM Business and Policy Research. 21 A. Coad and R. Rao, Innovation and Firm Growth in Complex Technology Sectors: A Quantile Regression Approach. Research Policy 37 (2008): T. Bates, Entrepreneur Human Capital Inputs and Small Business Longevity. The Review of Economics and Statistics 72 (1990): W. Baumol, R. Litan, and C. Schramm, Good Capitalism, Bad Capitalism, and the Economics of Growth and Prosperity. New Haven, CT: Yale University Press, E. Stam and K. Wennberg, The Roles of R&D in New Firm Growth. Small Business Economics 33, no. 1 (2009): The Global Competitiveness Report , p Z. J. Acs, W. Parsons, and S. Tracy, High Impact Firms: Gazelles Revisited, Office of Advocacy working paper, U.S. Small Business Administration, Available from 27 D. De Clercq, H. J. Sapienza, and H. Crijns, The Internationalization of Small and Medium Firms. Small Business Economics 24 (2005): P. Gompers and J. Lerner, The Venture Capital Cycle. Cambridge, MA: MIT Press, A. Groh, H. Liechtenstein, and K. Lieser, The Global Venture Capital and Private Equity Country Attractiveness Index, Ecosystems, August 4, See Z. Acs, E. Autio, and L. Szerb, National Systems of Entrepreneurship: Measurement Issues and Policy Implications. Research Policy 43 (2014): See Z. J. Acs and L. Szerb. The Global Entrepreneurship and Development Index (GEDINDEX). Foundations and Trends in Entrepreneurship 5, no. 5 (2009): ; Global Entrepreneurship and Development Index, Edward Elgar, 2012, p. 400; Z. J. Acs, L. Szerb,

121 and E. Autio. Global Entrepreneurship and Development Index, Edward Elgar, 201, p. 352; The Global Entrepreneurship and Development Index Seattle: CreateSpace Independent Publishing Platform, March 19, A. Groh, H. Liechtenstein, and K. Lieser. The Global Venture Capital and Private Equity Country Attractiveness Annual Index Available at 34 Groh et al., Global Venture Capital. 35 Some may not consider the West Bank and Gaza Strip an independent country. Tonga and Vanuatu are tiny countries, and Yemen and Syria have been engaged in civil war over the last few years. 36 In order to check potential bias, the index was calculated without these countries; however, the GEI values and the rank order of the involved countries were basically unchanged. 37 OECD, The Kaiser-Meyer-Olkin measures for the original pillar values are 0.91, and 0.94 for the PFB adjusted pillars, well above the critical value of The Bartlett test is significant at the level, excluding the possibility that the pillars are not interrelated. 39 We have calculated the c-alpha values for each of the three sub-indexes. Using the PFB adjusted pillar values, the c-alpha scores are 0.85 (ATT pillars), 0.91 (ABT pillars), and 0.91 (ASP pillars).

122 Section 2: Country Pages

123 Country Page Guide Country name Country flag Country region Geographic regions are from the Index of Economic Freedom ( which classifies all GEI areas except Puerto Rico (which we have placed in the South and Central America / Caribbean region) and Brunei Darussalam (placed in Asia-Pacific). Regional classifications for the GEI are as follows: Asia - Pacific Australia Bangladesh Brunei Darussalam Cambodia China Hong Kong India Indonesia Japan Kazakhstan Korea Lao PDR Malaysia Myanmar Pakistan Philippines Singapore Sri Lanka Taiwan Thailand Vietnam Albania Austria Belgium Bosnia Bulgaria Croatia Cyprus Czech Republic Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Italy Latvia Lithuania Europe Luxembourg Macedonia Moldova Montenegro Netherlands Norway Poland Portugal Romania Russia Serbia Slovakia Slovenia Spain Sweden Switzerland Turkey Ukraine United Kingdom Middle East / North Africa Algeria Bahrain Egypt Iran Israel Jordan Kuwait Lebanon Libya Morocco Oman Qatar Saudi Arabia Tunisia United Arab Emirates North America Canada Mexico United States South and Central America / Caribbean Argentina Barbados Bolivia Brazil Chile Colombia Costa Rica Dominican Republic Ecuador El Salvador Guatemala Guyana Honduras Jamaica Nicaragua Panama Paraguay Peru Puerto Rico Suriname Trinidad & Tobago Uruguay Venezuela Sub-Saharan Africa Angola Malawi Benin Mali Botswana Mauritania Burkina Faso Mozambique Burundi Namibia Cameroon Nigeria Chad Rwanda Côte d Ivoire Senegal Ethiopia Sierra Leone Gabon South Africa Gambia Swaziland Ghana Tanzania Kenya Uganda Liberia Zambia Madagascar World Rank lists the country s rank in the full list of 130 countries covered by the GEI. Regional Rank lists the country s rank within its geographic region and includes the total number of countries in the region. Economy type (Factor Driven, Efficiency Driven, or Innovation Driven) is based on the Global Competitiveness Index (World Economic Forum) Countries listed in the GCI as transitioning from stage 1 to stage 2 are listed here as Factor Driven (stage 1), and transitioning from stage 2-3

124 Overall, Individual and Institutional category scores The represents the overall entrepreneurial performance of a country on a point scale. The Individual Scores are calculated from the equalized pillar values for the 15 individual level pillars that comprise the GEI the same way as the REDI average adjusted pillar scores. For calculation details see the Methodology chapter in this volume. The Institutional Scores are calculated using exactly the same method but using the institutional pillars rather than the individual pillars. Scatterplot shows GEI points plotted against GDP in $ per capita PPP. Each country s geographic region appears in blue. Spider chart shows each country s performance on the 15 pillars that comprise the GEI, along with that country s regional average and the global average. The show population, GDP per capita PPP, and the country s rank in three other business/economic indices: the Doing Business Index ( 2014), the Global Competitiveness Index ( ) and the Index of Economic Freedom ( 2014). The Pillar Score chart shows pillar scores ordered from worst to best. The right-hand column of the chart shows the percentage of new effort that the country should expend on each pillar in order to achieve a 10 point increase in GEI score (e.g. from 54.1 to 64.1).

125 Europe Albania World Rank 76 of 130 Regional Rank 37 of million GDP per capita PPP $8,123 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 3. Risk Acceptance % 5. Cultural Support % 11. Process Innovation % 14. Risk Capital % 12. High Growth % 1. Opportunity Perception % 10. Product Innovation % 7. Technology Absorption % 13. Internationalization % 6. Opportunity Startup % 9. Competition % 4. Networking % 8. Human Capital % 2. Startup Skills %

126 Algeria Middle East / North Africa World Rank 79 of 130 Regional Rank 12 of million GDP per capita PPP $7,400 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 11. Process Innovation % 12. High Growth % 9. Competition % 10. Product Innovation % 4. Networking % 13. Internationalization % 3. Risk Acceptance % 7. Technology Absorption % 8. Human Capital % 2. Startup Skills % 6. Opportunity Startup % 5. Cultural Support % 14. Risk Capital % 1. Opportunity Perception %

127 Sub-Saharan Africa Angola World Rank 111 of 130 Regional Rank 17 of million GDP per capita PPP $5,262 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 3. Risk Acceptance % 11. Process Innovation % 2. Startup Skills % 9. Competition % 5. Cultural Support % 12. High Growth % 7. Technology Absorption % 6. Opportunity Startup % 8. Human Capital % 10. Product Innovation % 4. Networking % 13. Internationalization % 1. Opportunity Perception % 14. Risk Capital %

128 Argentina South and Central World Rank 56 of 130 America / Caribbean Regional Rank 6 of million GDP per capita PPP $16,425 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 13. Internationalization % 3. Risk Acceptance % 10. Product Innovation % 6. Opportunity Startup % 8. Human Capital % 5. Cultural Support % 14. Risk Capital % 11. Process Innovation % 9. Competition % 12. High Growth % 7. Technology Absorption % 4. Networking % 1. Opportunity Perception % 2. Startup Skills %

129 Asia-Pacific Australia World Rank 3 of 130 Regional Rank 1 of million GDP per capita PPP $35,608 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 10. Product Innovation % 4. Networking % 9. Competition % 12. High Growth % 11. Process Innovation % 5. Cultural Support % 3. Risk Acceptance % 8. Human Capital % 13. Internationalization % 1. Opportunity Perception % 6. Opportunity Startup % 2. Startup Skills % 14. Risk Capital % 7. Technology Absorption %

130 Europe Austria World Rank 18 of 130 Regional Rank 13 of million GDP per capita PPP $36,340 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 12. High Growth % 8. Human Capital % 5. Cultural Support % 6. Opportunity Startup % 1. Opportunity Perception % 3. Risk Acceptance % 11. Process Innovation % 10. Product Innovation % 2. Startup Skills % 14. Risk Capital % 4. Networking % 9. Competition % 13. Internationalization % 7. Technology Absorption %

131 Middle East / North Africa Bahrain World Rank 43 of 130 Regional Rank 7 of million GDP per capita PPP $21,543 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 11. Process Innovation % 12. High Growth % 5. Cultural Support % 3. Risk Acceptance % 10. Product Innovation % 2. Startup Skills % 9. Competition % 6. Opportunity Startup % 14. Risk Capital % 8. Human Capital % 1. Opportunity Perception % 13. Internationalization % 7. Technology Absorption % 4. Networking %

132 Asia-Pacific Bangladesh World Rank 130 of 130 Regional Rank 21 of million GDP per capita PPP $1,622 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 13. Internationalization % 3. Risk Acceptance % 10. Product Innovation % 2. Startup Skills % 11. Process Innovation % 4. Networking % 8. Human Capital % 14. Risk Capital % 12. High Growth % 7. Technology Absorption % 9. Competition % 5. Cultural Support % 1. Opportunity Perception % 6. Opportunity Startup %

133 Barbados South and Central World Rank 59 of 130 America / Caribbean Regional Rank 7 of million GDP per capita PPP $23,205 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 7. Technology Absorption % 11. Process Innovation % 1. Opportunity Perception % 14. Risk Capital % 10. Product Innovation % 12. High Growth % 9. Competition % 13. Internationalization % 3. Risk Acceptance % 6. Opportunity Startup % 4. Networking % 8. Human Capital % 5. Cultural Support % 2. Startup Skills %

134 Europe Belgium World Rank 16 of 130 Regional Rank 11 of million GDP per capita PPP $32,680 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 7. Technology Absorption % 4. Networking % 2. Startup Skills % 12. High Growth % 1. Opportunity Perception % 6. Opportunity Startup % 5. Cultural Support % 3. Risk Acceptance % 10. Product Innovation % 14. Risk Capital % 11. Process Innovation % 9. Competition % 8. Human Capital % 13. Internationalization %

135 Sub-Saharan Africa Benin World Rank 102 of 130 Regional Rank 10 of million GDP per capita PPP $1,364 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 4. Networking % 2. Startup Skills % 3. Risk Acceptance % 14. Risk Capital % 11. Process Innovation % 6. Opportunity Startup % 1. Opportunity Perception % 5. Cultural Support % 8. Human Capital % 13. Internationalization % 9. Competition % 10. Product Innovation % 12. High Growth % 7. Technology Absorption %

136 Bolivia South and Central World Rank 92 of 130 America / Caribbean Regional Rank 17 of million GDP per capita PPP $4,552 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 7. Technology Absorption % 11. Process Innovation % 13. Internationalization % 3. Risk Acceptance % 8. Human Capital % 12. High Growth % 14. Risk Capital % 5. Cultural Support % 10. Product Innovation % 6. Opportunity Startup % 9. Competition % 4. Networking % 1. Opportunity Perception % 2. Startup Skills %

137 Europe Bosnia World Rank 83 of 130 Regional Rank 39 of million GDP per capita PPP $7,356 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 11. Process Innovation % 6. Opportunity Startup % 3. Risk Acceptance % 1. Opportunity Perception % 10. Product Innovation % 8. Human Capital % 7. Technology Absorption % 2. Startup Skills % 9. Competition % 14. Risk Capital % 5. Cultural Support % 13. Internationalization % 12. High Growth % 4. Networking %

138 Sub-Saharan Africa Botswana World Rank 66 of 130 Regional Rank 2 of million GDP per capita PPP $14,109 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 2. Startup Skills % 4. Networking % 14. Risk Capital % 10. Product Innovation % 7. Technology Absorption % 11. Process Innovation % 13. Internationalization % 8. Human Capital % 6. Opportunity Startup % 9. Competition % 1. Opportunity Perception % 12. High Growth % 3. Risk Acceptance % 5. Cultural Support %

139 Brazil South and Central World Rank 100 of 130 America / Caribbean Regional Rank 19 of million GDP per capita PPP $10,264 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 10. Product Innovation % 13. Internationalization % 11. Process Innovation % 8. Human Capital % 12. High Growth % 6. Opportunity Startup % 14. Risk Capital % 7. Technology Absorption % 2. Startup Skills % 3. Risk Acceptance % 9. Competition % 4. Networking % 5. Cultural Support % 1. Opportunity Perception %

140 Asia-Pacific Brunei Darussalam World Rank 60 of 130 Regional Rank 8 of million GDP per capita PPP $45,979 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 11. Process Innovation % 13. Internationalization % 1. Opportunity Perception % 2. Startup Skills % 10. Product Innovation % 9. Competition % 6. Opportunity Startup % 5. Cultural Support % 12. High Growth % 7. Technology Absorption % 14. Risk Capital % 8. Human Capital % 3. Risk Acceptance % 4. Networking %

141 Europe Bulgaria World Rank 44 of 130 Regional Rank 26 of million GDP per capita PPP $12,176 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 7. Technology Absorption % 14. Risk Capital % 13. Internationalization % 10. Product Innovation % 12. High Growth % 9. Competition % 3. Risk Acceptance % 5. Cultural Support % 8. Human Capital % 4. Networking % 6. Opportunity Startup % 11. Process Innovation % 1. Opportunity Perception % 2. Startup Skills %

142 Sub-Saharan Africa Burkina Faso World Rank 114 of 130 Regional Rank 19 of million GDP per capita PPP $1,298 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 2. Startup Skills % 4. Networking % 1. Opportunity Perception % 3. Risk Acceptance % 5. Cultural Support % 9. Competition % 13. Internationalization % 12. High Growth % 14. Risk Capital % 11. Process Innovation % 8. Human Capital % 10. Product Innovation % 6. Opportunity Startup % 7. Technology Absorption %

143 Sub-Saharan Africa Burundi World Rank 124 of 130 Regional Rank 25 of million GDP per capita PPP $0,483 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 4. Networking % 2. Startup Skills % 1. Opportunity Perception % 3. Risk Acceptance % 5. Cultural Support % 14. Risk Capital % 13. Internationalization % 11. Process Innovation % 10. Product Innovation % 12. High Growth % 8. Human Capital % 9. Competition % 6. Opportunity Startup % 7. Technology Absorption %

144 Asia-Pacific Cambodia World Rank 98 of 130 Regional Rank 16 of million GDP per capita PPP $2,150 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 4. Networking % 3. Risk Acceptance % 5. Cultural Support % 1. Opportunity Perception % 2. Startup Skills % 6. Opportunity Startup % 11. Process Innovation % 12. High Growth % 10. Product Innovation % 13. Internationalization % 14. Risk Capital % 9. Competition % 8. Human Capital % 7. Technology Absorption %

145 Sub-Saharan Africa Cameroon World Rank 115 of 130 Regional Rank 20 of million GDP per capita PPP $2,025 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 4. Networking % 2. Startup Skills % 3. Risk Acceptance % 5. Cultural Support % 14. Risk Capital % 6. Opportunity Startup % 11. Process Innovation % 8. Human Capital % 13. Internationalization % 1. Opportunity Perception % 12. High Growth % 10. Product Innovation % 7. Technology Absorption % 9. Competition %

146 North America Canada World Rank 2 of 130 Regional Rank 2 of million GDP per capita PPP $36,067 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 2. Startup Skills % 4. Networking % 10. Product Innovation % 11. Process Innovation % 12. High Growth % 7. Technology Absorption % 6. Opportunity Startup % 5. Cultural Support % 3. Risk Acceptance % 9. Competition % 14. Risk Capital % 8. Human Capital % 13. Internationalization % 1. Opportunity Perception %

147 Sub-Saharan Africa Chad World Rank 126 of 130 Regional Rank 27 of million GDP per capita PPP $1,870 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 2. Startup Skills % 4. Networking % 3. Risk Acceptance % 5. Cultural Support % 6. Opportunity Startup % 1. Opportunity Perception % 11. Process Innovation % 9. Competition % 14. Risk Capital % 13. Internationalization % 12. High Growth % 10. Product Innovation % 8. Human Capital % 7. Technology Absorption %

148 Chile South and Central World Rank 19 of 130 America / Caribbean Regional Rank 1 of million GDP per capita PPP $15,848 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 11. Process Innovation % 9. Competition % 8. Human Capital % 6. Opportunity Startup % 7. Technology Absorption % 14. Risk Capital % 4. Networking % 12. High Growth % 5. Cultural Support % 3. Risk Acceptance % 13. Internationalization % 2. Startup Skills % 1. Opportunity Perception % 10. Product Innovation %

149 Asia-Pacific China World Rank 61 of 130 Regional Rank 9 of million GDP per capita PPP $7,958 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 2. Startup Skills % 13. Internationalization % 6. Opportunity Startup % 7. Technology Absorption % 3. Risk Acceptance % 9. Competition % 8. Human Capital % 5. Cultural Support % 12. High Growth % 1. Opportunity Perception % 14. Risk Capital % 4. Networking % 11. Process Innovation % 10. Product Innovation %

150 Colombia South and Central World Rank 36 of 130 America / Caribbean Regional Rank 3 of million GDP per capita PPP $9,143 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 11. Process Innovation % 4. Networking % 7. Technology Absorption % 5. Cultural Support % 3. Risk Acceptance % 14. Risk Capital % 8. Human Capital % 9. Competition % 13. Internationalization % 2. Startup Skills % 6. Opportunity Startup % 10. Product Innovation % 12. High Growth % 1. Opportunity Perception %

151 Costa Rica South and Central World Rank 55 of 130 America / Caribbean Regional Rank 5 of million GDP per capita PPP $11,156 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 8. Human Capital % 13. Internationalization % 10. Product Innovation % 14. Risk Capital % 11. Process Innovation % 7. Technology Absorption % 12. High Growth % 1. Opportunity Perception % 9. Competition % 6. Opportunity Startup % 3. Risk Acceptance % 4. Networking % 5. Cultural Support % 2. Startup Skills %

152 Sub-Saharan Africa Côte d Ivoire World Rank 107 of 130 Regional Rank 14 of million GDP per capita PPP $1,757 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 4. Networking % 2. Startup Skills % 5. Cultural Support % 3. Risk Acceptance % 11. Process Innovation % 1. Opportunity Perception % 9. Competition % 12. High Growth % 13. Internationalization % 6. Opportunity Startup % 14. Risk Capital % 10. Product Innovation % 8. Human Capital % 7. Technology Absorption %

153 Europe Croatia World Rank 51 of 130 Regional Rank 31 of million GDP per capita PPP $16,002 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 1. Opportunity Perception % 10. Product Innovation % 8. Human Capital % 6. Opportunity Startup % 5. Cultural Support % 4. Networking % 3. Risk Acceptance % 9. Competition % 7. Technology Absorption % 11. Process Innovation % 2. Startup Skills % 12. High Growth % 14. Risk Capital % 13. Internationalization %

154 Europe Cyprus World Rank 46 of 130 Regional Rank 28 of million GDP per capita PPP $23,452 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 5. Cultural Support % 1. Opportunity Perception % 8. Human Capital % 4. Networking % 11. Process Innovation % 2. Startup Skills % 9. Competition % 3. Risk Acceptance % 14. Risk Capital % 10. Product Innovation % 12. High Growth % 6. Opportunity Startup % 7. Technology Absorption % 13. Internationalization %

155 Europe Czech Republic World Rank 35 of 130 Regional Rank 22 of million GDP per capita PPP $23,824 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 5. Cultural Support % 8. Human Capital % 1. Opportunity Perception % 6. Opportunity Startup % 9. Competition % 4. Networking % 2. Startup Skills % 3. Risk Acceptance % 14. Risk Capital % 10. Product Innovation % 7. Technology Absorption % 12. High Growth % 11. Process Innovation % 13. Internationalization %

156 Europe Denmark World Rank 6 of 130 Regional Rank 3 of million GDP per capita PPP $32,291 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 5. Cultural Support % 2. Startup Skills % 13. Internationalization % 1. Opportunity Perception % 12. High Growth % 3. Risk Acceptance % 11. Process Innovation % 4. Networking % 14. Risk Capital % 7. Technology Absorption % 8. Human Capital % 6. Opportunity Startup % 9. Competition % 10. Product Innovation %

157 Dominican Republic South and Central World Rank 77 of 130 America / Caribbean Regional Rank 11 of million GDP per capita PPP $8,794 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 7. Technology Absorption % 14. Risk Capital % 11. Process Innovation % 6. Opportunity Startup % 10. Product Innovation % 3. Risk Acceptance % 5. Cultural Support % 9. Competition % 13. Internationalization % 12. High Growth % 8. Human Capital % 2. Startup Skills % 1. Opportunity Perception % 4. Networking %

158 Ecuador South and Central World Rank 90 of 130 America / Caribbean Regional Rank 16 of million GDP per capita PPP $8,443 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 13. Internationalization % 14. Risk Capital % 11. Process Innovation % 7. Technology Absorption % 12. High Growth % 6. Opportunity Startup % 3. Risk Acceptance % 8. Human Capital % 5. Cultural Support % 4. Networking % 9. Competition % 10. Product Innovation % 2. Startup Skills % 1. Opportunity Perception %

159 Middle East / North Africa Egypt World Rank 91 of 130 Regional Rank 14 of million GDP per capita PPP $5,795 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 6. Opportunity Startup % 10. Product Innovation % 8. Human Capital % 13. Internationalization % 9. Competition % 7. Technology Absorption % 3. Risk Acceptance % 14. Risk Capital % 2. Startup Skills % 5. Cultural Support % 11. Process Innovation % 4. Networking % 1. Opportunity Perception % 12. High Growth %

160 El Salvador South and Central World Rank 81 of 130 America / Caribbean Regional Rank 13 of million GDP per capita PPP $6,125 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 11. Process Innovation % 13. Internationalization % 7. Technology Absorption % 3. Risk Acceptance % 6. Opportunity Startup % 4. Networking % 2. Startup Skills % 14. Risk Capital % 8. Human Capital % 5. Cultural Support % 1. Opportunity Perception % 10. Product Innovation % 9. Competition % 12. High Growth %

161 Europe Estonia World Rank 21 of 130 Regional Rank 14 of million GDP per capita PPP $19,070 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 14. Risk Capital % 1. Opportunity Perception % 8. Human Capital % 3. Risk Acceptance % 5. Cultural Support % 10. Product Innovation % 12. High Growth % 6. Opportunity Startup % 2. Startup Skills % 9. Competition % 7. Technology Absorption % 4. Networking % 11. Process Innovation % 13. Internationalization %

162 Sub-Saharan Africa Ethiopia World Rank 125 of 130 Regional Rank 26 of million GDP per capita PPP $0,971 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 4. Networking % 13. Internationalization % 3. Risk Acceptance % 2. Startup Skills % 14. Risk Capital % 7. Technology Absorption % 10. Product Innovation % 8. Human Capital % 1. Opportunity Perception % 12. High Growth % 9. Competition % 5. Cultural Support % 6. Opportunity Startup % 11. Process Innovation %

163 Europe Finland World Rank 14 of 130 Regional Rank 9 of million GDP per capita PPP $31,611 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 14. Risk Capital % 9. Competition % 8. Human Capital % 12. High Growth % 13. Internationalization % 2. Startup Skills % 1. Opportunity Perception % 7. Technology Absorption % 6. Opportunity Startup % 3. Risk Acceptance % 10. Product Innovation % 11. Process Innovation % 5. Cultural Support % 4. Networking %

164 Europe France World Rank 12 of 130 Regional Rank 7 of million GDP per capita PPP $29,819 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 2. Startup Skills % 1. Opportunity Perception % 14. Risk Capital % 12. High Growth % 6. Opportunity Startup % 3. Risk Acceptance % 8. Human Capital % 9. Competition % 13. Internationalization % 5. Cultural Support % 4. Networking % 11. Process Innovation % 10. Product Innovation % 7. Technology Absorption %

165 Sub-Saharan Africa Gabon World Rank 93 of 130 Regional Rank 6 of million GDP per capita PPP $13,811 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 2. Startup Skills % 4. Networking % 3. Risk Acceptance % 10. Product Innovation % 6. Opportunity Startup % 14. Risk Capital % 9. Competition % 5. Cultural Support % 8. Human Capital % 12. High Growth % 1. Opportunity Perception % 13. Internationalization % 11. Process Innovation % 7. Technology Absorption %

166 Sub-Saharan Africa Gambia World Rank 101 of 130 Regional Rank 9 of million GDP per capita PPP $1,667 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 2. Startup Skills % 3. Risk Acceptance % 5. Cultural Support % 1. Opportunity Perception % 4. Networking % 11. Process Innovation % 13. Internationalization % 6. Opportunity Startup % 12. High Growth % 10. Product Innovation % 14. Risk Capital % 9. Competition % 8. Human Capital % 7. Technology Absorption %

167 Europe Germany World Rank 11 of 130 Regional Rank 6 of million GDP per capita PPP $35,453 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 2. Startup Skills % 4. Networking % 8. Human Capital % 1. Opportunity Perception % 3. Risk Acceptance % 13. Internationalization % 14. Risk Capital % 10. Product Innovation % 7. Technology Absorption % 5. Cultural Support % 12. High Growth % 6. Opportunity Startup % 11. Process Innovation % 9. Competition %

168 Sub-Saharan Africa Ghana World Rank 105 of 130 Regional Rank 12 of million GDP per capita PPP $1,764 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 8. Human Capital % 10. Product Innovation % 7. Technology Absorption % 13. Internationalization % 11. Process Innovation % 14. Risk Capital % 2. Startup Skills % 12. High Growth % 4. Networking % 6. Opportunity Startup % 3. Risk Acceptance % 9. Competition % 5. Cultural Support % 1. Opportunity Perception %

169 Europe Greece World Rank 47 of 130 Regional Rank 29 of million GDP per capita PPP $21,275 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 1. Opportunity Perception % 3. Risk Acceptance % 12. High Growth % 5. Cultural Support % 10. Product Innovation % 4. Networking % 9. Competition % 11. Process Innovation % 6. Opportunity Startup % 14. Risk Capital % 8. Human Capital % 13. Internationalization % 7. Technology Absorption % 2. Startup Skills %

170 Guatemala South and Central World Rank 122 of 130 America / Caribbean Regional Rank 22 of million GDP per capita PPP $4,397 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 8. Human Capital % 11. Process Innovation % 7. Technology Absorption % 12. High Growth % 14. Risk Capital % 13. Internationalization % 3. Risk Acceptance % 4. Networking % 2. Startup Skills % 5. Cultural Support % 6. Opportunity Startup % 1. Opportunity Perception % 10. Product Innovation % 9. Competition %

171 Guyana South and Central World Rank 127 of 130 America / Caribbean Regional Rank 23 of million GDP per capita PPP $2,930 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 3. Risk Acceptance % 13. Internationalization % 11. Process Innovation % 7. Technology Absorption % 12. High Growth % 8. Human Capital % 14. Risk Capital % 1. Opportunity Perception % 2. Startup Skills % 5. Cultural Support % 6. Opportunity Startup % 9. Competition % 10. Product Innovation % 4. Networking %

172 Honduras South and Central World Rank 80 of 130 America / Caribbean Regional Rank 12 of million GDP per capita PPP $3,657 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 5. Cultural Support % 11. Process Innovation % 2. Startup Skills % 3. Risk Acceptance % 4. Networking % 1. Opportunity Perception % 6. Opportunity Startup % 9. Competition % 13. Internationalization % 14. Risk Capital % 10. Product Innovation % 12. High Growth % 8. Human Capital % 7. Technology Absorption %

173 Asia-Pacific Hong Kong World Rank 40 of 130 Regional Rank 6 of million GDP per capita PPP $44,770 Rank in Doing Business Index / 189 Rank in Global Competitiveness Index / 144 Rank in Economic Freedom Index / 178 Percentage of total new effort for a 10 point improvement in GEI score 9. Competition % 2. Startup Skills % 7. Technology Absorption % 1. Opportunity Perception % 11. Process Innovation % 5. Cultural Support % 4. Networking % 8. Human Capital % 13. Internationalization % 6. Opportunity Startup % 14. Risk Capital % 3. Risk Acceptance % 12. High Growth % 10. Product Innovation %