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Women In Entrepreneurship

The Entrepreneurial Advantage Of Nations: First Annual Global Entrepreneurship Symposium

United Nations Headquarters April 29, 2003

Maria Minniti, Ph.D. Pia Arenius


WOMEN IN ENTREPRENEURSHIP Maria Minniti, Ph.D. Babson College Pia Arenius Helsinki University of Technology

In 1999 the Global Entrepreneurship Monitor (GEM) program was initiated by Babson College and London Business School with sponsorship from the Kauffman Foundation to: • • • • Measure differences in the level of entrepreneurial activity between countries. Probe for a systematic relationship between entrepreneurship and national economic growth. Uncover factors that lead to higher level so of entrepreneurship. Suggest policies that may enhance the national level of entrepreneurial activity.

Data were assembled for each participating country from four basic sources: 1) surveys of over a hundred thousand adults; 2) in-depth interviews with almost a thousand national experts on entrepreneurship; 3) standardized questionnaires completed by the national experts, and 4) a wide selection of standardized national data from such sources as the World Bank, International Monetary Fund, United Nations and the like. The 37 countries participating in 2002 provides a truly global assessment of these issues. The Kauffman Foundation and the Business Council for the United Nations recently convened the first international policy discussion related to these issues at The Entrepreneurial Advantage of Nations: The First Annual Global Entrepreneurship Symposium. Held at the U.N. Headquarters, the symposium featured various experts who explored the social, financial, educational and demographic underpinnings related to the creation and support of national entrepreneurial activity. The enclosed report provide an analysis of one of the four special topics addressed at the symposium: patterns of female entrepreneurship, sources of financial support, high-potential entrepreneurship, and the prevalence of family-sponsored new ventures. These reports provide new and more precise information on these issues, which should enhance the effectiveness of relevant government policies.


INTRODUCTION Since the beginning of the GEM project in 1999, data has shown that the participation of women in entrepreneurship is significant, that its range varies significantly from country to country, and that, in spite of national variations, women participation rates across countries is measurable at about two-thirds that of men. These results suggest that women are influenced by many of the same factors that affect men when making entrepreneurial decisions. On the other hand, the systematically lower rate of female participation indicates that some differences also exist. Unfortunately, the nature and causes for these differences are not fully understood. The purpose of this on Women in Entrepreneurship is to expand and develop the analysis presented in the global report by discussing some of these differences and their causes. Evidence suggests that entrepreneurship contributes in various ways to economic development and job creation. As a result, adult women represent a readily available pool of potential entrepreneurial activity that countries may leverage to improve their economies. Moreover, this potential exists among nations in various stages of development and with different demographic patterns and labor force conditions. In addition to providing valuable information about how to increase the incidence of business start-ups, the entrepreneurial behavior of women is also relevant to issues related to social equity. In addition to quantitative results, this report pays particular attention to the qualitative aspects of gender differences.



The female Total Entrepreneurial Activity (TEA) index measures the percentage of women in the labor force who are either actively involved in starting a new business or who own/manage a business less than 42 months old. Figure 1 shows the comparative results for men and women in each country.1 Clearly, the participation of women in entrepreneurship varies significantly across the 37 GEM 2002 countries, ranging from 0.6 percent (6 per 1,000) in Japan to 18.5 percent (185 per 1,000) in Thailand.

Figure 1

Country-specific characteristics determine the differences in prevalence rates for both sexes across countries. Figure 1 also shows that the differences between men and


women are remarkably stable. There is no country where women are more active than men, but there are a few where the differences are not statistically significant such as Thailand, China and South Africa. On average, participation rates for men tend to be 50 percent higher that those of women. In addition, the correlation between the overall measure of entrepreneurial activity and the overall measure for women entrepreneurial activity is 0.96, and the overall level for women correlates 0.88 with the overall level for men. Thus, countries with higher overall and men prevalence rates also have higher percentages of women involved in entrepreneurship. GEM data also reveal that patterns in entrepreneurial attitudes do not vary from country to country and across gender with respect to age. While it is true that women prevalence rates are systematically lower than those of men, the distribution of women entrepreneurial involvement across age brackets follows that of men. For both men and women, for example, the peak years to become involved in entrepreneurial activities are ages 25-34. Those ages 35-44 are next, followed closely by the 19-24 age group. Those over 55 have the lowest rate of entrepreneurship. Overall, men are 50 percent more likely than women to start a new business: 13.9 percent of men become entrepreneurs compared to only 8.9 percent of women. The same pattern is found when the prevalence rates of “nascent firms,” “new firms” and “opportunity entrepreneurship” are considered. Nascent firms describe individuals who have committed resources to the creation of a new business but have not paid salaries for more than three months. New firms describe individuals who have been active as owner-managers for less than 42 months but have paid salaries for more than three months.


Finally, opportunity entrepreneurship estimates the number of people who choose to start their own business as one of several desirable career options. According to the data, 9.3 percent of men become opportunity entrepreneurs while only 4.9 percent of women decide to choose this career path. This ratio of male-to-female entrepreneurship changes sharply, however, when “necessity entrepreneurship” is considered. Necessity entrepreneurship estimates the number of people who start their own business because other employment options are either absent or unsatisfactory. In this category, the numbers of men and women are about the same regardless of age, with 4.2 percent of men and 3.8 percent of women fitting this description.. In fact, selfemployment and home-based work have expanded opportunities for women's participation in the labor force in recent years, trends that are characterized by lack of security, lack of benefits and low income. This observation suggests that entrepreneurship may represent for women an important means to circumvent unemployment and, in some countries, a way out of poverty.


Entrepreneurship is clearly a complex and multifaceted phenomenon. Changes in the economy and the restructuring of labor markets in terms of employee qualifications, nature of the work contents and work contracts have raised the profile and importance of entrepreneurship within the global economy. Despite the rapid growth of women in professional and managerial jobs, the gender gap in entrepreneurship remains significant.


Women are still less likely to start new businesses than men, although the discrepancy seems to be declining.2 Clearly, female entrepreneurship is a cross-cultural phenomenon with culturespecific aspects. As a result, understanding it has two different, though related, components. First, there are variables that influence entrepreneurial behavior across countries and across gender. These variables are universal determinants of entrepreneurial behavior, although they may have gender specific effects. In other words, they influence both sexes but not necessarily in the same way or with the same intensity. For example, the stability of the ratio of female-to-male entrepreneurship, and the stability of prevalence rates for different age groups, both indicate that women and men are influenced by many of the same variables when making entrepreneurial decisions. However, the fact that male entrepreneurship rates are systematically and significantly higher than female entrepreneurship rates indicates an asymmetry of universal factors across the sexes that may cause men and women to behave differently with respect to entrepreneurship. Second, there are aspects of entrepreneurial behavior that are country specific. Indeed, the differences in entrepreneurship prevalence rates across countries shown in Figure 1 suggest that entrepreneurial attitudes are influenced by country-specific factors. Unfortunately, a detailed study of country specific variables is beyond the scope of this report. Nevertheless, some clear differences in country and gender specific variables exist for groups of countries with similar income levels.


The 37 countries in the sample can be divided into two groups: high income countries and low income countries. The break at US$18,000 per year (in 1999) is justified by a major gap in the distribution of per capita annual income between US$15,860 to US$19,160.3 The purpose of this report is to identify what universal variables are most significant for female entrepreneurship and how their influence varies between high income and low income countries.


In spite of the growing number of female entrepreneurs, the share of female entrepreneurship is still significantly low when compared to their participation rate. For example, female entrepreneurs account for approximately 30 percent of the total number of entrepreneurs in the Western world, whereas more than 40 percent of employees are female.4 Thus, it is important to understand what factors may favor or hinder female entrepreneurship, such as the combination of social and economic responsibilities and the consequences of these specific barriers. There are several variables that are important in influencing the level of female entrepreneurship across countries. Table 1 shows the correlations between a set of relevant variables and overall TEA, TEA opportunity, and TEA necessity for both men and women in high and low income countries.


Table 1
Table 1: Correlations Between Entrepreneurial Activity and Selected Factors Believed to Affect Women’s Participation in Entrepreneurship Women Women Women Men Men TEA Men TEA TEA TEA TEA TEA Opportunity Necessity Overall Opportunity Necessity Overall High Per Capita Income Countries (More than $18,000/yr)

DEMOGRAPHIC ENVIRONMENT AND FAMILY STRUCTURE Population growth: 1996-2002 0.06 0.09 0.21 0.25 0.22 0.46*

LITERACY AND EDUCATION Female illiteracy rate n/a Socio-Economic Environment Unofficial economy as -0.19 % of GDP Social security as % of -0.46* GDP n/a -0.38 -0.49* n/a 0.16 -0.32 n/a -0.14 -0.50* n/a -0.22 -0.50* n/a -0.30 -0.54*

Labor Force and Employment Female current -0.11 -0.24 unemployment Female long term -0.3 -0.47* unemployment Female/male labor force 0.12 0.22 participation ratio Employment by Sectors and Economic Growth % Women in public 0.37 0.43* agency management % Women in private 0.52** 0.31 management % Women work in -0.09 -0.23 agriculture % Women work in -0.42* -0.50* industry % Women work in 0.42* 0.52* services

-0.01 0.07 -0.42* 0.04 0.51** -0.14 0.12 -0.02

-0.24 -0.34 0.04 0.15 0.39 -0.14 -0.27 0.32

-0.31 -0.44* 0.11 0.24 0.32 -0.20 -0.40 0.37

-0.42* -0.38 -0.29 -0.10 -0.24 -0.28 -0.14 0.28


Table 1 continued Women Women Women TEA TEA TEA Overall Opportunity Necessity Low Per Capita Income Countries (More than $18,000/yr)

Men TEA Overall

Men TEA Opportunity

Men TEA Necessity

DEMOGRAPHIC ENVIRONMENT AND FAMILY STRUCTURE Population growth: 19962002 0.63** 0.50** 0.49** 0.77*** 0.76*** 0.49*

LITERACY AND EDUCATION Female illiteracy rate 0.49* Socio-Economic Environment Unofficial economy as % 0.18 of GDP Social security as % of -0.42** GDP 0.34 0.17 -0.42 0.49* 0.11 -0.19 0.45* 0.17 -0.47* 0.51* 0.11 -0.56* 0.24 0.18 -0.14

Labor Force and Employment Female current -0.58* -0.51* unemployment Female long term -0.64* -0.55 unemployment Female/male labor force -0.34 -0.05 participation ratio Employment by Sectors and Economic Growth % Women in public -0.2 -0.23 agency management % Women in private -0.36 -0.22 management % Women work in 0.52* 0.68* agriculture % Women work in -0.47 -0.29 industry % Women work in -0.28 -0.49* services

-0.35 -0.72* -0.54* -0.07 -0.42 0.04 -0.56* 0.2

-0.56* -0.58 -0.47* -0.13 -0.58* 0.15 -0.55* 0.09

-0.57* -0.55 -0.32 -0.15 * -0.46 0.25 -0.46 -0.03

-0.31 -0.48 -0.55* -0.02 -0.56* -0.06 -0.52* 0.27

Statistical significance: *

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