2007 Global Report On High-Growth Entrepreneurship

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GLOBAL ENTREPRENEURSHIP MONITOR2007 Global Report on High-Growth EntrepreneurshipErkko Autio

Global Entrepreneurship Monitor2007 Global Report onHigh-Growth EntrepreneurshipErkko AutioFounding and Sponsoring InstitutionsBabson College, Babson Park, MA, USLondon Business School, London, UKAlthough GEM data were used in the preparation of this report, their interpretation and use are the sole responsibility of the author. 2007 by Erkko Autio, Babson College, London Business School, and Global Entrpreneurship Research Consortium (GERA)

ForewordMazars is delighted to sponsor this report into high-growth entrepreneurship.Having worked with entrepreneurs around the globe for many years, we understand the issues theyface. We recognise the importance of entrepreneurship in all its forms, and the importance of high-growthentrepreneurship in particular, to a country’s economy through wealth and job creation.We urge governments, policy makers and the business community to create the appropriate economic conditionswhich will encourage and support an entrepreneurial environment and to develop and promote specificinitiatives aimed at increasing levels of high-growth entrepreneurial activity.Alistair FraserGlobal Head of the International Customer Linefor Owner-Managed Businesses at Mazars

Table of ContentsTable of Contents 3List of Tables4List of Figures4Executive Summary5MethodsAdult-population surveyNational expert interviewsStandardized cross-national data6666Terminology8IntroductionContributions of Entrepreneurial Growth Expectations to Job CreationSummary of Job Contribution AnalysisComparison of Global Regions: Prevalence and Anatomy of High-Expectation EntrepreneurshipAdult-population prevalence of High-Expectation Entrepreneurship in World RegionsAnatomy of Entrepreneurship in World RegionsSummary of the Comparison of World RegionsComparison of Individual Countries: Population Prevalence andAnatomy of High-Expectation EntrepreneurshipNascent and New Entrepreneur DataComparison with Established High-Growth EntrepreneurshipSummary of Country Comparison99121212141617171928Profile of High-Expectation Entrepreneurs 29Summary33High-Expectation Entrepreneurship and National Entrepreneurial Framework Conditions 34Summary37Conclusions and Discussion 38References41GEM National Teams 200642GEM Sponsors47

Table of ContentsList of TablesTable 1 GEM Method: Sources of DataTable 2 Expected Job Creation by Growth ExpectationTable 3 Adult-Population Prevalence Rate of High-Expectation (Nascent and New) and High-Growth(Established) Entrepreneurs in GEM 2000 – 2006 CountriesTable 4 Relative Prevalence of High-Expectation Nascent and New (20 or More Expected Jobs) andHigh-Growth Established (20 or More Current Employees) EntrepreneursTable 5 Correlations Between Prevalence Rates of High-Expectation (Nascent and New Entrepreneurs,20 or More Expected Jobs) and High-Growth (Established Entrepreneurs, 20 or More CurrentEmployees) EntrepreneurshipTable 6 Demographic Characteristics of Nascent, New, and Established Entrepreneurs inHigh-Income CountriesTable 7 Demographic Characteristics of Nascent, New, and Established Entrepreneurs inMiddle- and Low-Income CountriesTable 8 Bivariate Correlations Between National Entrepreneurial Framework Conditions andEntrerepeneurshipTable 9 Trade-Offs Between SME and High-Growth Entrepreneurship PoliciesList of FiguresFigure 1 Nascent and New Entrepreneurs Categorized According to Growth Expectation(Global Data, GEM 2000-2006 Countries, Adult-population prevalence Rate)Figure 2 Adult-Population Prevalence of Low-Expectation Entrepreneurial Activity in World Regions(Percentage of Adult-Age Population)Figure 3 Adult-Population Prevalence of High-Expectation Entrepreneurial Activity in World Regions(Prevalence as Percentage of Adult-Age Population)Figure 4 Anatomy of Entrepreneurship: Relative Prevalence of Low-Expectation Entrepreneurship inWorld Regions (Prevalence as Percentage of all Nascent and New Entrepreneurs)Figure 5 Anatomy of Entrepreneurship: Relative Prevalence of High-Expectation Entrepreneurship inWorld Regions (Percentage of all Nascent and New Entrepreneurs)Figure 6 Adult-Population Prevalence of High-Expectation Entrepreneurship(% of 18-64 Year Olds Involved in Nascent or New Firms Expecting 20 or More Jobs)Figure 7 Anatomy of Entrepreneurship: Relative Prevalence of High-Expectation Entrepreneurship(Nascent and New, 20 or More Expected Jobs)Figure 8 Adult-Population Prevalence of High-Growth Established Entrepreneurs(Firm Over 42 Months Old, 20 or More Current Jobs)Figure 9 Anatomy of Entrepreneurship: Relative Prevalence of High-Growth Established Entrepreneurs(Firm Over 42 Months Old, 20 or More Current Jobs)Figure 10 Adult-Population Prevalence of High-Expectation Entrepreneurial Activity(Nascent and New, 20 or More Expected Jobs)Figure 11 Entrepreneurial Anatomy: Relative Prevalence of High-Expectation Activity(Nascent and New Entrepreneurs, 20 or More Expected Jobs, as % of All Start-Up Activity) 711222425313236391013141516181920212627

Executive Summary High-expectation and high-growth entrepreneursrepresent only a small percentage of allentrepreneurial activity.1 Even though 12.3% of theadult-age population in countries that participatedin the Global Entrepreneurship Monitor studybetween 2000 and 2006 are active in emerging andnew entrepreneurial businesses, only 6.5% of newentrepreneurs (owner-managers of entrepreneurialfirms less than 42 months old) expected to have 20or more jobs in five years’ time. Edu ca tion and household income, as well asentrepreneurial activities and attitudes, appearimportant for high-expectation and high-growthentrepreneurship. High-expectation and highgrowth entrepreneurs are better educated thanother entrepreneurs and the general population.High-expectation and high-growth entrepreneursare significantly more likely to have graduateexperience than low-growth entrepreneurs and thegeneral population. Even though high-expectation entrepreneurshipis rare, its contribution to expected job creationis important. Nascent and new entrepreneursexpecting to create more than 100 jobs in fiveyears represent only 1.7% of all nascent and newentrepreneurs, yet they expect to create nearly 50%of all expected jobs. Almost 90% of all expected newjobs are foreseen by less than one-quarter of nascentand new entrepreneurs. High-expectation and high-growth entrepreneursare likely to be wealthier than other entrepreneursand the general population in high-, middle-, andlow-income countries. The general patterns of entrepreneurial growthexpectations vary according to a country’sincome level. Even though high-income countries(generally speaking) have lower rates of overallentrepreneurial activity than do low-incomecountries, they generally have higher rates of highgrowth and high-expectation entrepreneurship. Of all world regions, entrepreneurial activity inAfrica and South America, while high in termsof adult-age population prevalence,2 is the mostheavily tilted toward low-ex pectation activity. Inthe richest world regions, including North America,highly developed Asia, the European Union, andOceania, the anatomy of entrepreneurial activity3is tilted toward high-expectation entrepreneurship,especially in the category of 20 or moreexpected jobs. There are significant differences between individualcountries in terms of both the adult popu lationand the relative prevalence of high-expectationentrepreneurial activity. Among high-incomecountries, the difference between the United States’and Greece’s adult-population pre valence rate ofhigh-expectation entrepreneurship is fifteenfold. High-expectation and high-growth entrepreneursare generally overrepresented in the manu facturingand transportation, communication, and utilitiessectors, but underre pre sent ed in agriculture andconsumer services. The adult population and relative prevalence ofhigh-expectation and high-growth entrepreneurshipare, in general, positively associated with thequality of national entrepreneurial policy conditions.The pattern of positive associations is stronger forthe relative prevalence of high-growth expectations(i.e., percentage of entrepreneurs who expect rapidgrowth). The adult-population prevalence of overall (lowexpectation) entrepreneurship is either nega tively or neutrally associated with the quality ofnational entrepreneurial policy con di tions, possiblydue to the high prevalence of low-expectationentrepreneurship in low-income countries. Both high- and low-expectation entrepreneurshipare, in general, positively associated with nationalcultural and societal framework conditions thataffect entrepreneurship. Thus, different facets ofentrepreneurship react differently to national policyand cultural–societal environments. The world’s two largest emerging economies, Chinaand India, exhibit significantly different levels ofhigh-expectation and high-growth entrepreneurship.The difference be tween China and India isover sixfold.123High-expectation entrepreneurs are nascent and new entrepreneurs who expect more than 20 employees in 5 years’ time.High-growth entrepreneurs are established entrepreneurs who currently have 20 or more employees.Adult-population prevalence refers to the percentage of adult-age population (18–64 years) who are active in entrepreneurship.The anatomy of entrepreneurial activity refers to the percentage of the overall population of entrepreneurs who are growth-oriented.

MethodsSince its inception in 1999, the GlobalEntrepreneurship Monitor’s (GEM) major activityhas been the creation of a large data set andthe construction of harmonized measures ofentrepreneurial activity. GEM collects three typesof data: adult-population surveys, national expertinterviews, and standardized cross-national data.single data file, each respondent having a uniqueidentification number. The GEM coordinationteam then processes the data set to identify peopleconsidered as entrepreneurially active and to computeother variables related to entrepreneurial activity.Adult-Population SurveyEach GEM national team conducts up to 50 faceto-face interviews with experts in their respectivecountries. The interviews are intended to assess anumber of entrepreneurial framework conditions.Experts are selected on the basis of reputation andexperience. In the interviews, experts express theirviews on national strengths and weaknesses as acontext for entrepreneurship and indicate what policyor program changes they believe would enhancethe level of entrepreneurship in their country. Thenational experts also complete a standardizedquestionnaire so that GEM can obtain a quantitativemeasure of their opinions concerning their countryas a suitable context for entrepreneurial activity. Thequestionnaire consists of sets of five to six relateditems grouped on the basis of countries and individualcharacteristics relevant for entrepreneurship. Thesedata are not used in this report but were analyzed inprevious reports.Representative samples of randomly selectedadults, ranging in size from 1,000 to almost 42,000individuals, are surveyed each year in each GEMcountry in order to provide a harmonized measureof the prevalence of entrepreneurial activity. Theannual surveys generally take place between Mayand August and are based on three main elements:the sample of respondents, the interview scheduleused to collect the data, and the creation of measuresestimating entrepreneurship at the national level. Theinterview schedule consists of a set of core questionsused to derive entrepreneurial activity rates andadditional questions concerning the attributes andcharacteristics of the respondents. The interviewschedule is approved by GEM national teams asa collective decision in an annual meeting heldin January each year. Both survey and collectionprocedures are revised annually.All countries in GEM conduct a national adultpopulation survey. All countries use region stratifi cation, except for very small countries like Iceland.Most countries conduct telephone surveys. In somemiddle-income countries where phone penetrationrates are low, interviews are conducted face to faceusing random door-to-door procedures that also resultin a representative national sample.While the survey vendors in each country areamong the best available, virtually every data setprovided by every vendor requires some adjustmentsand corrections. Once all data sets are checkedand harmonized, the files are consolidated into a National Expert InterviewsStandardized Cross-National DataStandardized cross-national data are obtained frominternational data sources such as the World Bank,the International Monetary Fund, and the UnitedNations. These data serve in establishing the linkbetween national levels of entrepreneurial activity andmacroeconomic conditions, as well as the impact of thestate of national conditions required for establishingthis link. While virtually all of the sources of thesecross-national harmonized data are free, it takes someeffort to annually update, organize, and describe thismaterial to provide useful consolidated data sets forthe analysis. GEM’s data sources are summarized inTable 1.

MethodsTable 1. GEM Method: Sources of DataData SourceDescriptionGEM Adult-Population SurveyTelephone and interview survey conducted by a polling organization in each GEM country, of a minimum of 2,000randomly selected respondents. The data is harmonized to be representative of the adult-age (18–64 years old)population of the country.National Expert InterviewsCombined mail questionnaire and interview survey of at least 36 national experts in each GEM countryknowledgeable of national framework conditions for entrepreneurial activity. The survey questionnairecollects data on finance, policy, government programs, education and training, technology transfer, physicaland business service infrastructure, market openness, social and cultural norms, IPR protection, femaleentrepreneurship, and policy support for high-growth entrepreneurial firms.Standardized Cross-National DataCompilation of data from third sources that describe general national conditions: national economy,demographics, society, infrastructure, and institutions. Data are compiled from publicly available sources suchas the United Nations, the World Bank, the Organization for Economic Co-operation and Development, anddedicated international surveys.Typically, GEM annual and special reports are based on a single year of data. Because the focus of thepresent report is on a small subset of the overall entrepreneurial phenomenon, a combined data set coveringyears 2000–2006 is used. Thus, the findings of the present report are based on a rather sizeable data setthat contains 678,714 interviews of adult-age individuals in 53 countries during years 2000–2006.

Terminology EntrepreneurshipGEM defines entrepreneurship as any attempt by individuals to start a new firm, including any attempt for self-employment.Nascent entrepreneurAn adult-age individual (18–64 years old) who: has, during the past 12 months, taken tangible action to start a new business would personally own all or part of the new firm would actively participate in the day-to-day management of the new firm has not yet paid salaries for anyone for more than three monthsNew entrepreneurAn adult-age individual who: is currently actively managing a new firm personally owns all or part of the new firm the firm in question is not more than 42 months oldEstablished entrepreneurAn adult-age individual who: is currently actively managing a firm personally owns all or part of the firm the firm in question is over 42 months oldStart-up attemptNascent or new entrepreneurial firm, as defined above.Total early-stage entrepreneurialactivity (TEA)Total early stage entrepreneurial activity refers to the total rate of early-stage entrepren eurial activity among the adultpopulation aged 18–64 years. In some instances, this rate is less than the combined percentages for nascent and new firmentrepreneurs. This is because, in circumstances where respondents qualify as both a nascent and a new firm entrepreneur,they are counted only once.High-expectation entrepreneurA nascent or new entrepreneur who expects to employ at least 20 employees within five years’ time.High-growth entrepreneurEstablished entrepreneur who currently employs 20 or more employees.Adult-population prevalence rate ofhigh-expectation entrepreneursThe percentage of all adult-age individuals in a given country who qualify as either nascent or new high-expectationentrepreneurs.Relative prevalence rate of highexpectation entrepreneursThe percentage of start-up attempts (either nascent or new entrepreneurs) who qualify as high-expectation entrepreneurs.Anatomy of entrepreneurshipRelative prevalence rate of either high-expectation or high-growth entrepreneurs.

IntroductionSince its inception in 1999, the GlobalEntrepreneurship Monitor (GEM) ResearchConsortium has uncovered complex and non-trivialrelationships between entrepreneurship and economicgrowth (Wennekers et al., 2005). Entrepreneurialprocesses are undoubtedly linked with macroeconomicconditions, but detailed rela tion ships may vary(e.g., as a function of economic development). Boththe GEM data and that from other sources pointto one important conclusion, however: Not allentrepreneurial activity similarly contributes toeconomic growth. Specifically, the importance of highgrowth entrepreneurial activity for job creation isincreasingly emphasized (Birch et al., 1997; Delmar etal., 2003; Storey, 1994). All entrepreneurial activity isimportant, but high-growth entrepreneurial activity isparticularly so.Because high-growth entrepreneurial activity israre, most population-level studies on high-growthentrepreneurship employ post-hoc design and areoverwhelmingly limited to single-country data.International comparative studies on high-growthentrepreneurship are virtually nonexistent, leavingresearchers and policy makers in the dark as theyseek to understand the high-growth entrepreneurshipphenomenon.Thanks to its comparative, multiyear approach,GEM is uniquely positioned to address this gap.GEM measures the growth expectations of bothnascent, new, and established entrepreneurs andentrepreneurial firms. GEM’s is the only data setthat allows international comparisons of the nascententrepreneurial process. The accumulation of dataover several years has created data sets largeenough to allow the kind of fine-grained analysisnecessary to isolate the small number of high-growthentrepreneurial attempts from the overall data onnascent and new entre pre neurs.This report is the second in a series of GEM reviewsof high-expectation entrepreneurial activity. Thisreport expands the global survey of high-expectationentrepreneurship initiated in 2005 (Autio, 2005). Inthis report, we expand on the number of countriesreported and analyze the prevalence of highexpectation entrepreneurial activity in different world456regions.4 We also expand the study of the anatomyof high-expectation entrepreneurial activity indifferent countries and world regions, as well as on thecharacteristics of the individuals who report highexpectation entrepreneurial activity.Contributions ofEntrepreneurial GrowthExpectations to Job CreationStart-up attempts can be categorized accordingto their growth ambition. GEM asks all identifiedentrepreneurial attempts how many employeesthey expect to have within five years’ time. Figure 1shows nascent and new entrepreneurs in the GEM2000–2006 data, categorized according to expectedjob creation.5 The figure shows the population-levelprevalence (as percentage of adult-age populationfrom 18 to 64 years old) of all start-up attempts, bothnascent and new entrepreneurs, at different levels ofgrowth expectation.In the GEM 2000–2006 data set, the adult-populationprevalence of any kind of entrepreneurial activity was12.3%.6 It is interesting to note that nearly one-halfof all start-up attempts do not expect to create anyjobs within five years. Approximately one-half of allentre preneurial activity thus re presents part-timeentrepreneurial activity that may complement incomefrom regular employment.Some 6.3% of the adult-age population in theparticipating GEM countries was involved in nascentor new start-up attempts that envisioned employingat least one person within five years. This per centagefalls rapidly as a function of growth expectation. Some5.5% of the adult-age population was involved withfirms that expected two or more employees withinfive years. Only 2.9% expected to employ at least fiveemployees. Start-up attempts expecting to employ 10or more employees re pre sented only 1.7% of the adultage population. Only 0.9% of the adult-age populationwas involved in start-up attempts expecting 20or more jobs. This percentage halved for the “50 ”category and again for the “100 ” category.Because isolating high-expectation entrepreneurs requires large data sets, it is necessary to combine several years of country data in order tomeaningfully isolate high-expectation entrepreneurs. With every new round of data collection, more countries meet the minimum data thresholdrequired for meaningful analysis.Methodological note: All start-up attempts for which the data concerning expected jobs in five years was missing were set as expecting zerojobs in five years. Figure 1 thus represents a conservative estimate.Methodological note: Weighted according to population and sample size.

Figure 1. Nascent and New Entrepreneurs Categorized According to Growth Expectation(Global Data, GEM 2000–2006 Countries, Adult-Population Prevalence Rate)13%12%11%10%9%8%7%6%5%4%3%2%1%0%0 jobs1 jobs2 jobs5 jobsExpectations of high growth are rare among nascentand new entrepreneurs. Only some 7% of all start-upattempts expected to create 20 or more jobs. As manyas 70% did not expect any job creation at all. And onlysome 3% of all start-up attempts expected 50 or morejobs.The scarcity of high-growth expectations amongnascent and new entrepreneurs does not correspondto their expected contribution to job creation at thecohort level. Overall, the identified nascent and newentrepreneurs expected to employ some 640,000employees in five years’ time (size of base sample:678,714 adult-population interviews). While thisfigure is undoubtedly overoptimistic, the contributionsof different expectation categories are neverthelessrevealing. These are summarized in Table 2.In Table 2, we can see that firms expecting to create20 or more jobs, while only representing 7.4% of allnascent and new firms, expected to create some 73%of all new jobs created by the cohort. The remaining92.6% of all early-stage entrepreneurs contributedonly an additional 27.4% to the cohort job creationtotal. This statistic was quite similar for both nascentand new firms, improving our confidence in the overalldistribution.1010 jobs20 jobs50 jobs100 jobsIt is remarkable how concentrated the job creationpotential is. Even though early-stage entrepreneursexpecting more than 100 jobs represented less than2% (1.7% of all) of the cohort, they expected to createnearly half of the total jobs within the cohort. Startup attempts expecting 50 or more jobs (3.4% of all)represented nearly 60% of total expected jobs. Thus,the high end of the distribution is quite stronglyoveremphasized in terms of job creation potential bynascent and new firms.The distributions observed coincide well withpublished studies of realized growth potential amongentrepreneurial firms, as well as with studies of firmsize distributions (Cabral et al., 2003; Lotti et al.,2001). The observed disproportionate contribution byhigh-expectation start-ups to expected job creation isconsistent with findings reported in studies of realizedgrowth (Audretsch, 2002; Birch et al., 1997; Davis etal., 1996; Delmar et al., 2003; Storey, 1994). Also, thedistributions observed for nascent and new firms arevery similar to one another, suggesting that the shapeof the distribution does not change when nascententrepreneurs enter the entrepreneurial process.

Table 2. Expected Job Creation by Growth ExpectationNumber of cases% of Cohortin categoryIncrementalContribution tocohort total jobs, %% of CohortTotal Jobs281,06846,149100.0%0.0%100.0%1 or more jobs281,06832,30470.0%4.9%100.0%2 or more jobs267,21418,45040.0%8.5%95.1%5 or more jobs243,2829,21720.0%7.8%86.6%10 or more jobs221,2435,35311.6%9.6%78.7%20 or more jobs194,2402,9876.5%15.9%69.1%50 or more jobs149,5341,1012.4%10.4%53.2%100 or more jobs120,3035731.2%42.8%42.8%Nascent Entrepreneurs0 or more jobs380,71041,529100.0%0.0%100.0%1 or more jobs380,71031,14670.0%2.9%100.0%2 or more jobs369,62520,06148.3%6.2%97.1%5 or more jobs345,88310,99926.5%7.0%90.9%10 or more jobs319,0756,46015.6%8.6%83.8%20 or more jobs286,4143,5278.5%10.7%75.2%50 or more jobs245,7431,8944.6%14.8%64.5%100 or more jobs189,3549482.3%49.7%49.7%cohort total0 or more jobs661,77887,677100.0%0.0%100.0%1 or more jobs661,77863,45072.4%3.8%100.0%2 or more jobs636,83938,51143.9%7.2%96.2%5 or more jobs589,16520,21623.1%7.4%89.0%10 or more jobs540,31911,81413.5%9.0%81.6%20 or more jobs480,6546,5147.4%12.9%72.6%50 or more jobs395,2782,9953.4%12.9%59.7%100 or more jobs309,6571,5221.7%46.8%46.8%New Entrepreneurstotal expectedjobs for category0 or more jobs11

Summary of Job Contribution Analysis Expected job contributions are unevenlydistributed across populations of nascent and newentrepreneurs. While some 6.3% of the adult-agepopulation in the GEM countries were involved innascent and new firms expecting any jobs, only 0.9%of the adult-age population expected to create 20 ormore jobs in five years’ time. Even though high-expectation entrepreneurshipis rare, its contribution to expected job creationis important. Nascent and new entrepreneursexpecting to create more than 100 jobs in fiveyears represent only 1.7% of all nascent and newentrepreneurs, yet they expect to create nearly 50%of all expected jobs within the cohort. Almost 90% ofall expected new jobs are foreseen by less than onequarter of nascent and new entrepreneurs. The above observation is consistent with receivedstudies of realized growth in firm populations.The distributions are similar for nascent and newentrepreneurs, when analyzed separately. If nearly 50% of all new jobs are expectedby 1.7% of all new entrepreneurs, this hasimportant implications for the design of SME andentrepreneurship policies. These implications will beexamined later in this report.Comparison of Global Regions:Prevalence and Anatomy of HighExpectation Entre pre neurshipAre there differences between world regions in termsof entrepreneurial growth ambition? Two questionscan be asked here. First, does the adult-populationprevalence rate of high-expectation entrepreneursvary according to global region? And second, does theanatomy of entrepreneurship vary in terms of therelative prevalence of high-expectation entrepreneurs?The first question measures the incidence of highexpectation entrepreneurs relative to the entire adultage population. The second question measures theincidence of high-expectation entrepreneurs relative tothe population of nascent and new entrepreneurs.127Adult-Population Prevalence of HighExpectation Entrepreneurship in World RegionsFigure 2 reports the incidence of low expectationentrepreneurial activity across world regions. Thepopu la tion-level prevalence of nascent and newentrepreneurs expecting zero, one, or five or moreemployees in five years is reported. As is well knownfrom previous GEM global reports, the incidence oflow-expectation entrepreneurial activity is highest inregions with low GDP per capita. The inci dence of anyform of entrepreneurial activity is highest in SouthAmerica, with a population-level ent re preneurialactivity rate of some 15.5%. That is, a total of 15.5%of adult-age population (18–64 years old) in SouthAmerican GEM countries are either nascent or newentrepreneurs. High early-stage entrepreneurialactivity rates are also reported for Africa anddeveloping Asia.For the highly developed economies, the highest ratesof entrepreneurial activity are reported for Oceania(Australia and New Zealand), followed by NorthAmerica. The lowest rates of overall entre preneurialactivity (combines nascent and new entrepreneurs, alllevels of growth expectation) are reported for highlydeveloped Asia and the European Union (includingNorway, Switzerland, and Iceland).The prevalence patterns change for higher levelsof growth expectation. While South America andAfrica7 remain on top for the category of one or moreexpected jobs, developing Asia (including India andChina) falls behind Oceania and North America inthis category. For the category of five or more expectedjobs, Africa also falls behind Oceania and NorthAmerica, and North America draws to level withSouth America. Thus, when moving toward higherlevels of growth aspiration, the prevalence rates ofregions with low levels of GDP per capita tend todrop faster than in regions with high levels of GDPper capita. Highly developed Asia and the EuropeanUnion are exceptions to this pattern, however, asthese two regions signal consistently low levels ofentrepreneurial activity regardless of the level ofgrowth expectation.Methodoligcal Note: GEM’s coverage of African countries is narrow. Uganda and South Africa are the only African countries included in the GEMdata set.

Figure 2. Adult-Population Prevalence of Low-Expectation Entrepreneurial Activity in World Regions(Percentage of Adult-Age Population)17%16%15%14%13%World 12.3%12%11%10%9%8%7%World 6.3%6%5%4%World 2.9%3%2%For even higher levels of growth aspiration, thepatterns are strengthened. North America signalsclearly the highest rate of high-expectationentrepreneurial activity, both for the categories of 20and 50 or more expected jobs in five years. For thecategory of

high-expectation and high-growth entrepreneurship. The difference between China and India is over sixfold. Education and household income, as well as entrepreneurial activities and attitudes, appear important for high-expectation and high-growth entrepreneurship. High-expectation and high-growth entrepreneurs are better educated than

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