Environmental conditions and entrepreneurial activity:

A cross country comparison

Claudia Alvarez

Autonomous University of Barcelona Business Economics Department, Spain

and

University of Medellin, School of Economics and Management, Colombia

Building B 08193 Bellaterra (Cerdanyola del Vallés) - Barcelona

Tel. 935811209 / Fax. 935812555

claudiapatricia.alvarez@uab.es

David Urbano

Autonomous University of Barcelona

Business Economics Department, Spain

Alicia Coduras

IE Business School, Spain

Abstract

In this paper we consider institutional economics to analyse the influence of environmental factors on entrepreneurship at country level, according to the stage of the entrepreneurial process (nascent entrepreneur and new business) and economic development. We combine the two main sources of the Global Entrepreneurship Monitor (GEM) data for the period 2006–2009: National Expert Survey (NES) and Adult Population Survey (APS). The main findings indicate that to start a business the perception of knowledge and skills is very relevant. However, subsequent to this decision, it is crucial that society endorses and values the entrepreneurial career in order to move the new business forward and to overcome obstacles in the early stages. The paper contributes to both theoretical (model of conditioning factors to entrepreneurship) and practical perspective (design of governmental policies to foster the entrepreneurial spirit in society, distinguishing between nascent entrepreneurs support and assistance to new business owners).

Keywords: Entrepreneurship, entrepreneurial activity, environmental conditions, Global Entrepreneurship Monitor (GEM).

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1. Introduction

The importance of new firms for social and economic development is generally recognized (Audretsch, & Keilbach, 2004; van Stel et al., 2005; Wennekers, & Thurik, 1999: Wennekers et al., 2005). Also, different governmental organizations have shown particular interest in the design of policies and strategies for the promotion of entrepreneurship. Simultaneously, academics have become interested in this phenomenon, especially in the factors that determine entrepreneurial activity.

From a general perspective, the research in the field of entrepreneurship could be analysed from four broad approaches. First, in the economic approach economic rationality prevails and it proposes that entrepreneurship is due to purely economic issues (Audretsch, & Keilbach, 2004; Audretsch, & Thurik, 2001; Parker, 2004; Wennekers et al., 2005, among others). Second, the psychological approach postulates that individual factors or the psychological traits of people are determinants of the decision to start a business (Carsrud, & Johnson, 1989; Collins et al., 1964; McClelland, 1961; among others). Moreover, the resource-based view approach focuses his interest on the firm’s resources and capabilities concerning to the new firm formation process (Andrews, 1971; Penrose, 1962; Barney, 1991; among others). Finally, the sociological or institutional approach argues that the socio-cultural environment influences entrepreneurial activity (Aldrich, & Zimmer, 1986; Berger, 1991; Busenitz et al., 2000; Manolova et al., 2008; Shapero, & Sokol, 1982; among others).

In this paper we use the latter approach as a conceptual framework. In particular, we consider institutional economics (North, 1990 and 2005) to analyse the influence of environmental factors on entrepreneurship at country level, according to the stage of the entrepreneurial process (nascent entrepreneur and new business) and economic development. We combine the two main sources of the Global Entrepreneurship Monitor (GEM) data: National Expert Survey (NES) and Adult Population Survey (APS), for the period 2006–2009.

The main findings of the research indicate, on the one hand, that nascent entrepreneurship rates are related to formal institutions, such as low levels of commercial and services infrastructures and high levels of physical infrastructures, and informal institutions, such as higher education and high abilities and knowledge to start up. On the other, the results show that new business ownership is related to formal institutions, such as low levels of commercial and services infrastructures and high levels of physical infrastructures, and informal institutions, such as entrepreneur social image. Thus, these results indicate that to start a business, the perception of knowledge and skills is very relevant. However, subsequent to this decision, it is crucial that society endorses and values the entrepreneurial career in order to move the new business forward and to overcome obstacles in the early stages.

This paper contributes to both the theoretical and practical perspectives. From the theoretical point of view, although the works on environmental factors as key elements of entrepreneurship are increasing, little research is based on institutional economics. From the practical perspective, the results could be very useful in designing governmental policies and strategies to foster the entrepreneurial spirit in society, distinguishing support to nascent entrepreneurs from assistance to new business owners.

The paper is structured in five sections. After this brief introduction, the conceptual framework is explained. In Section 3 the methodology of the research is presented. Section 4 discusses the main results. Finally, Section 5 includes the conclusions and implications of the research.

2. Conceptual framework

North (1990) considers both formal and informal institutions. Formal institutions (North, 1990) include rules, contracts, constitutions, laws and property rights. Examples of formal institutions influencing entrepreneurship are the political and economic constitution, the legal framework and the financial system (Welter, 2005, 2011), costs, procedures and regulations to create new firm (van Stel et al., 2007; Stephen et al., 2009) and support organisms (Urbano, 2006). In this research we use several variables to capture differences in formal institutions

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(Alvarez et al., 2011). According to the GEM definition of entrepreneurial framework conditions1

(Bosma, & Levie, 2010), we classified the following conditions as formal institutions and divided them into two groups:

a) Support policies and legal conditions:

- Finance: the availability of financial resources, equity and debt for new and growing firms, including grants and subsidies.

- Government policies: the extent to which government policies are reflected in taxes or regulations, or the application of either is either size-neutral or encourages new and growing firms.

- Government programmes: the presence and quality of direct programmes to assist new and growing firms at all levels of government (national, regional, municipal).

- R&D transfer: the extent to which national research and development will lead to new commercial opportunities and whether or not these are available for new, small and growing firms.

- Intellectual property rights: the extent to which the intellectual property of new and growing firms is protected and enforced under the law.

b) Infrastructure and market conditions

- Commercial and services infrastructure: the presence of commercial, accounting and other legal services and institutions that allow or promote the emergence of new, small or growing businesses.

- Market openness: the extent to which commercial arrangements undergo constant change and redeployment as new and growing firms compete and replace existing suppliers, subcontractors and consultants.

- Physical infrastructure: ease of access to available physical resources (communication, utilities, transportation, land or space) at a price that does not discriminate against new, small or growing firms.

North (1990) also defines informal institutions as constraints (codes of conduct, attitudes, values, norms of behaviour and conventions) that come from socially transmitted information and are part of the heritage that we call culture. Concerning entrepreneurship, informal institutions could be such as attitudes or behaviour towards entrepreneurial activity or more generally entrepreneurial culture (Alvarez et al., 2011; Thornton et al., 2011). Thus, according to the definition of informal institutions and in the context of GEM entrepreneurial framework conditions (Bosma, & Levie, 2010), we classified as informal institutions the following conditions, also divided into two groups:

a) Individual conditions:

- Education: the extent to which training in creating or managing small, new or growing businesses is incorporated within the educational and training system at all levels.

- Abilities and knowledge to start up: the extent to which people know how to start and manage a business.

- Opportunities to start up: the extent to which people perceive, identify and discover good opportunities for the creation of new firms.

b) Social conditions:

- Cultural and social norms: the extent to which existing social and cultural norms encourage, or do not discourage, individual actions that may lead to new ways of conducting business

1 Reynolds et al. (2005) established nine framework conditions according to the academic literature in the field of

entrepreneurship. Later, other factors have been added such as women’s entrepreneurship support, high growth

support, innovation topic, etc. Each framework condition is evaluated by means of batteries of questions on each one

of them, and a construct underlies each of these batteries. Levie, & Autio (2008) have demonstrated that it is possible

to obtain stable principal components (one or two) that represent the state of each of the framework conditions

evaluated by the experts.

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or economic activities and may, in turn, lead to greater dispersion of personal wealth and income.

- Entrepreneur social image: the extent to which people consider that becoming an entrepreneur is a desirable career choice and that entrepreneurs have a high level of status and respect.

- Women’s support for start-up: the extent to which women are encouraged to become entrepreneurs.

- High growth business support and encouragement.

- Interest in innovation: the extent to which innovation, especially in new products and services and new technologies, is highly valued by companies and consumers.

As mentioned before, formal institutions consist of entrepreneurship support policies and legal conditions related to the creation of new firms, and the infrastructure for new business and market conditions. On the one hand, in the first phases of the entrepreneurial process, favourable laws, regulations, and government policies provide support for new businesses and facilitate entrepreneurs’ efforts to acquire resources (Busenitz et al., 2000). Also, laws and regulations can specify the responsibilities of small business owners and assign property rights (Spencer, & Gomez, 2004). Inefficient government regulation in the economy may be negatively perceived, especially by nascent entrepreneurs (Gnyawali, & Fogel, 1994). Variables such as the number of procedures, time, and costs of starting a business have a negative effect on entrepreneurship (Begley et al., 2005; Djankov et al., 2002; Dana, 1990; Young & Welch, 1993). The availability of financial resources would determine the frequency of new business start-ups (Blanchflower, & Oswald, 1998; Evans, & Jovanovic, 1989; Evans, & Leighton, 1989; Gnyawali, & Fogel, 1994). Several studies have found that policies for increasing access to bank credit by lowering capital requirements, the creation of investment companies, credit with low interest rates, and credit guarantee schemes contribute to the promotion of new businesses in the early entrepreneurial stages (Gnyawali, & Fogel, 1994; van Gelderen et al., 2005).

On the other hand, commercial and legal infrastructures could help new business owners in the advanced stages of the creation of their firms (Brenner, 1992; Ruef, 2005; Suzuki et al., 2002). Also, physical infrastructure helps the success of their entrepreneurial activities (Dubini, 1989; Hansen, & Sebora, 2003; Trulsson, 2002; van de Ven, 1993). Market openness, industry structure and technology life cycle affect entrepreneurial activity (Kirzner, 1997; Leibenstein, 1987). In the early stages, new firm entry is an important driving factor of market dynamism, but market dynamism, in itself, also opens opportunities for entry by entrepreneurial ventures (Levie, & Autio, 2008).

In general, formal institutions provide the regulatory and infrastructure framework for entrepreneurship. However, literature has pointed out that the first is related to nascent entrepreneurs (i.e. according to this research, firms of less than 3 months), the latter concerns new business owners (i.e. in this study, firms of more than 3 months but less than 42 months). Therefore, we formulate the following hypotheses:

Hypothesis 1: Formal institutions influence the level of entrepreneurial activity.

H1a: Favourable policies and legal conditions are positively associated with nascent entrepreneurship.

H1b: Adequate infrastructure and market conditions are positively associated with new business ownership.

According to our theoretical framework, informal institutions consist of individual and social conditions. While individual conditions (education, abilities and perception of opportunities) are generally related to the starting point of the entrepreneurial process (nascent entrepreneurs), social dimensions (cultural and social norms, entrepreneur social image, role models, society support to women’s entrepreneurship, interest and encouragement in innovation and growth) are associated with the development of new businesses (new business owners).

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The literature reports that people’s entrepreneurial behaviours would be guided by their education, knowledge and skills, and that the identification of the business opportunity is a key element in the entrepreneurial process.

Empirical evidence shows that a higher level of education has a positive effect on the likelihood of starting a business (Davidsson, & Honig, 2003; De Clerq, & Arenius, 2006). Other studies found that a low level of technical and business skills could prevent motivated entrepreneurs from starting a new venture (Davidsson, 1991; Gnyawali & Fogel, 1994). Thus, nascent entrepreneurs will be more inclined to start a business if they have the necessary skills (Arenius, & Minniti, 2005; Boyd, & Vozikis, 1994; Chen et al., 1998; Davidsson, & Honig, 2003; Scott, & Twomey, 1988). Kollinger et al. (2007), also discuss the theory that individuals who believe themselves to have the skills and ability to start a new business are more likely to take an optimistic view of their prospects and overestimate their chances of success. Many scholars suggest that the perception of the opportunity is one of the most important characteristics of the entrepreneurial process (Arenius, & Minniti, 2005; Kirzner, 1973, 1979; Kollinger et al., 2007). Specifically, Kirzner (1973, 1979) argues that entrepreneurship is alertness, that is, the ability to perceive unexploited opportunities.

Cultural and social norms constitute an important determinant of entrepreneurship (Davidsson, 1995; Hayton et al., 2002; Shane, 1992, 1993), indicating the degree to which a society considers entrepreneurial behaviours, such as risk taking and independent thinking, to be desirable. During the socialization process, individuals learn the conventions, moral rules and social norms of their society; when they start their businesses they reflect their learning in the new business (Mantzavinos et al., 2004). The literature on role models highlights a positive relationship between the presence of business owners in society, and specifically, entrepreneurs among relatives, and the emergence of entrepreneurship. Collins et al. (1964) showed the first results on the influence of family background on new venture creation. Scott and Twomey (1988) proposed that parental role models and experience lead to the perception of oneself as an entrepreneur. Scherer et al. (1989) showed that a high percentage of entrepreneurs had entrepreneurial role models. Also, literature on intentions models (Kolvereid, 1996; Krueger, 1993; Matthews, & Moser, 1995; Scherer et al., 1989; among others) pointed out that family background affects entrepreneurial intentions. Shapero and Sokol (1982) argue that entrepreneurial activity is related to beliefs about the desirability and feasibility of starting a new business. Differences in the socio-cultural context may influence, among others, the status and social recognition of entrepreneurs, promoting or inhibiting the entrepreneurial career choice (Gnyawali, & Fogel, 1994).

According to Baughn et al. (2006) the legitimation and encouragement of women’s entrepreneurship contribute to a higher level of female participation in new venture activities. Also, specific support for female entrepreneurship impacts on the proportion of female entrepreneurs in a society. Interest in innovation, understood as ‘the successful implementation of creative ideas’ (Amabile, 1996, p. 1), is one of the most important elements of entrepreneurship. Innovation influences the improvements and revenues of organizations and society (Harrison, & Huntington, 2000; Porter, 1990; West, & Farr, 1989).

Informal institutions influence the social acceptability of an entrepreneurial career (Tiessen, 1997; Mueller, & Thomas, 2001; Welter, 2005) and determine the collective and individual perceptions of entrepreneurial opportunities (Welter, & Smallbone, 2003, 2011).

In general terms, individual conditions affect the early stages of entrepreneurial activity (nascent entrepreneurs) and social conditions impact on the new business owners. Thus, we propose:

Hypothesis 2: Informal institutions influence the level of entrepreneurial activity.

H2a: Individual dimension is positively associated with nascent entrepreneurship.

H2b: Social dimension is positively associated with new business ownership.

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3. Methodology

As mentioned before, this paper analyses the influence of environmental factors on entrepreneurship at country level, according to the stage of the entrepreneurial process (nascent entrepreneur and new business owners) and economic development, using data from the GEM. We considered as dependent variables the nascent entrepreneurship rate, defined as the percentage of the adult population actively involved in setting up a business that is less than 3 months old, and the new business ownership rate, defined as the percentage of the adult population who are owners/managers of a business that is more than 3 months, but no more than 42 months old (Reynolds et al., 2005). Both data are taken from the APS, the main research tool of the GEM project.

In the context of institutional economics, the selected independent variables were the GEM framework conditions, from the NES: formal institutions (entrepreneurial finance, government policies and governmental programmes, R&D transfer, commercial & services infrastructures, market openness, physical infrastructure, and intellectual property rights) and informal institutions (education and training, cultural and social norms, opportunities to start up, abilities and knowledge to start up, entrepreneur’s social image, women’s support to start up and interest in innovation).

The NES2 is based on interviewing 36 experts in each country every year, using a

questionnaire with multiple items for each environmental factor condition. Factor analysis was used to aggregate all items on a single scale for each environmental factor condition.

Finally, given that a country’s level of economic development is a key factor in explaining entrepreneurial activity (Carree et al., 2007; Wennekers et al., 2005), we use as the control variable the gross domestic product at purchasing power parity per capita from the International Monetary Fund (IMF).

As noted previously, entrepreneurial activity is influenced by environmental factors, measured through formal and informal institutions. Therefore, we propose the following general model:

ititititiit CVIIFIurshipEntreprene 1321(1)

where:

FIit-1: matrix of formal institutions in country i in year t IIit-1: matrix of informal institutions in country i in year t CVit-1: matrix of the control variable in country i in year t-1

Our final sample consists of an unbalanced panel with data on 120 observations in 44 countries

3 in the period 2006–2009. Panel data can be modelled by treating the individual

effects either as fixed or random. We conducted a Hausman’s specification test to determine the appropriate analytical approach. The results of the Hausman’s test rejects the null hypothesis that errors are independent within countries (χ

2(8)=8.54, Prob>χ

2=0.3828), thus we

estimated all the regressions using country random effects. Moreover, given that it is likely that the entrepreneurship rate in period t is associated with the entrepreneurship rate in period t-1, a test is applied for serial correlation in the idiosyncratic errors of a linear panel-data model. The Wooldridge test for autocorrelation in panel data showed that autocorrelation problems exist (F(1, 12)=3.767, Prob>F= 0.0761).

Finally, we investigated potential multicollinearity problems. High values of the variance inflation factor were found in R+D transfer (VIF=7.18), high growth business (VIF = 6.90) and intellectual property rights (VIF=5.85), indicating that these variables were highly correlated with other variables. However, these values are below the rule of thumb threshold value of 10 indicative of multicollinearity problems. Also, we controlled for group heteroscedasticity, estimating models with panel corrected standard errors.

2 A detailed account of GEM’s expert survey method is provided in Reynolds et al. (2005).

3 Although the panel data refers to the period 2006–009, the number of observations depends on the annual regularity

with which the countries participate in the GEM project.

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4. Results and discussion

This section presents the main results of our analysis.

Table 1. Descriptive statistics and correlation matrix

Mean Desv 1. 2. 3. 4. 5.

1. Nascent entrepreneurship 1.47 0.60 1 .00

2. New business ownership 1.24 0.67 0.68*** 1.00

3. GDP-PPP 9.83 0.70 -0.47*** -0.48*** 1.00

4. Finance 0.03 0.99 -0.23* -0.35*** 0.46*** 1.00

5. Governments policies 0.01 0.98 -0.19* -0.12 0.54*** 0.55*** 1.00

6. Governments programs 0.04 0.95 -0.22* -0.17* 0.62*** 0.60*** 0.78***

7. R+D transfer 0.05 0.93 -0.28** -0.29** 0.61*** 0.75*** 0.69***

8. Commerc & serv. infraest. 0.04 0.97 -0.28** -0.32*** 0.53*** 0.70*** 0.59***

9. Market openness -0.05 0.98 -0.20* -0.04 0.11 0.24** 0.23*

10. Physical infraestructure 0.03 0.95 0.02 0.00 0.46*** 0.52*** 0.66***

11. Intellectual Prop. rights 0.07 0.95 -0.27** -0.29** 0.72*** 0.67*** 0.74***

12. Primary education 0.02 0.87 -0.17* -0.27* 0.39*** 0.50*** 0.43***

13. Higher education 0.02 0.89 0.38*** 0.29* -0.27** -0.13 -0.16*

14. Cultural and social n. 0.01 0.99 0.10 0.15 0.28** 0.44*** 0.44***

15. Opportunities -0.02 0.99 0.19* 0.20* 0.06 0.46*** 0.41***

16. Abilities 0.01 0.99 0.08 0.01 0.38*** 0.49*** 0.49***

17. Social image 0.00 0.96 0.04 0.23* 0.04 0.37*** 0.26**

18. Women’s support 0.02 0.93 0.02 0.07 0.35*** 0.36*** 0.63***

19. High growth business 0.02 0.97 -0.27** -0.15* 0.55*** 0.70*** 0.74***

20. Interest in innovation 0.04 0.98 0.02 0.06 0.37*** 0.55*** 0.56***

6. 7. 8. 9. 10. 11. 12.

6. Governments programs 1.00

7. R+D transfer 0.77*** 1.00

8. Commerc & serv. infraest. 0.48*** 0.75*** 1.00

9. Market openness 0.56 0.20* 0.17* 1.00

10. Physical infraestructure 0.57*** 0.63*** 0.63*** 0.18* 1.00

11. Intellectual Prop. rights 0.77*** 0.78*** 0.68*** 0.11 0.65* 1.00

12. Primary education 0.40*** 0.56*** 0.58*** 0.25** 0.38*** 0.53*** 1.00

13. Higher education -0.11 -0.04 -0.15* -0.02 -0.04 -0.30*** -0.06

14. Cultural and social n. 0.30*** 0.49*** 0.43*** 0.40*** 0.41*** 0.34*** 0.41***

15. Opportunities 0.29*** 0.29** 0.30*** 0.36*** 0.45*** 0.36*** 0.29**

16. Abilities 0.36*** 0.52*** 0.62*** 0.36*** 0.53*** 0.50*** 0.57***

17. Social image 0.12 0.26** 0.23* 0.39*** 0.15* 0.17* 0.22*

18. Women’s support 0.43*** 0.45*** 0.48*** 0.09 0.59*** 0.52*** 0.50***

19. High growth business 0.80*** 0.74*** 0.58*** 0.19* 0.50*** 0.76*** 0.46***

20. Interest in innovation 0.47*** 0.62*** 0.55*** 0.35*** 0.51*** 0.50*** 0.51***

13. 14. 15. 16. 17. 18. 19.

13. Higher education 1.00

14. Cultural and social n. 0.17* 1.00

15. Opportunities -0.01 0.55*** 1.00

16. Abilities 0.01 0.72*** 0.48*** 1.00

17. Social image 0.10 0.78*** 0.54*** 0.47*** 1.00

18. Women’s support -0.08 0.51*** 0.47*** 0.60*** 0.28** 1.00

19. High growth business -0.26** 0.46*** 0.46*** 0.43*** 0.42*** 0.51*** 1.00

20. Interest in innovation 0.15 0.75*** 0.51*** 0.65*** 0.60*** 0.57*** 0.63***

*** p<0.001; ** p<0.01; * p<0.1

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Table 1 reports means, standard deviations, and correlations for all variables. For our sample of countries, the average percentage of nascent entrepreneurship and new business ownership are 5.28% and 4.36% respectively. Almost all formal institutions are negatively and significantly correlated with nascent entrepreneurship, while fewer formal institutions are correlated with new business ownership. The negative sign of these correlations could be explained by the highly, positive and significant correlations between formal institutions and GDP-PPP. Also, informal institutions such as education, opportunities, social image and high growth business are significantly correlated with nascent entrepreneurship and new business ownership. Finally, several variables related to formal and informal institutions show a significant correlation between all of them.

Table 2 reports regression results for the different effects of environmental conditions on entrepreneurship, differentiated by nascent entrepreneurship (0–3 months old) and new business ownership (3–42 months old). Random-effect coefficients, corrected standard errors and significance levels are shown in this table. For each dependent variable, three regression models were examined: A first model which includes as the control variable the effect of formal institutions on the dependent variable, a second model which includes as the control variable the effect of informal institutions, and a third model which includes only the significant variables.

Hypothesis 1 suggests that formal institutions influence the level of entrepreneurship. Specifically, Hypothesis 1a proposes that favourable policies and legal conditions are positively associated with the nascent entrepreneurship rate. Models 1 and 3 empirically test this hypothesis. Model 1 includes as the control variable the formal institutions that are related to the nascent entrepreneurship rate, and Model 3 shows only the significant variables. Both models are highly significant (p<0.00), and they explain more than 51% of the nascent entrepreneurship variation across countries. As we expected, the coefficient estimate for the control variable GDP-PPP is negative and significant. This result is consistent with the literature, which indicates a negative and significant correlation between entrepreneurship and level of economic development (Wennekers et al., 2005). This finding could be explained by necessity entrepreneurship (people who start their own businesses because other employment options are either absent or unsatisfactory), which usually happens in less developed countries (Reynolds et al., 2001). Both Models 1 and 3 show that commercial and services infrastructures and physical infrastructure are highly significant; negative and positive, respectively. Other formal institutions are not significant. Favourable policies and legal conditions are not associated with nascent entrepreneurship and thus, Hypothesis 1a is rejected.

Hypothesis 1b suggests that an adequate infrastructure and market conditions are positively associated with the new business ownership rate. Models 4 and 6 empirically test this hypothesis. Model 4 includes as control variable the formal institutions that are related to the nascent entrepreneurship rate, and Model 6 shows only the significant variables. Both models are highly significant (p < 0.00), and they explain more than 42% of the new business ownership variation across countries.

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Table 2. Results of Regression Analyses

Nascent entrepreneurship New business ownership

Model 1 Model 2 Model 3

Model 4 Model 5 Model 6

Control variable

GDP-PPP -0.26*** (0.09) -1.89* (0.10) -0.28*** (0.08) -0.32*** (0.11) -0.17 (0.14) -0.30*** (0.09)

Formal institutions

Finance -0.01 (0.07) -0.17*** (0.06)

Government policies -0.04 (0.09) 0.03 (0.08)

Government programs -0.12 (0.09) 0.06 (0.10)

R&D Transfer 0.06 (0.10) -0.02 (0.10)

Commercial & serv. infrast. -0.21*** (0.07) -0.24*** (0.06) -0.15** (0.07) -0.28*** (0.06)

Market openness -0.09* (0.05) 0.02 (0.05)

Physical infrastructure 0.03*** (0.07) 0.17*** (0.06) 0.29*** (0.08) 0.27*** (0.07)

Intellectual property rights 0.02 (0.09) -0.32 (1.02)

Informal institutions

Primary education -1.79*** (0.07) -0.18** (0.08)

Higher education 0.12** (0.05) 0.11** (0.05) 0.13* (0.07)

Cultural and social norms -0.31 (0.10) -0.05 (0.10)

Opportunities to start-up 0.15** (0.06) 0.06 (0.07)

Abilities 0.10 (0.07) 0.14*** (0.05) 0.01 (0.09)

Entrepreneur social image -0.05 (0.08) 0.14* (0.09) 0.15*** (0.05)

Women’s support to start-up 0.04 (0.07) 0.12 (0.08)

High growth business 0.18** (0.09) -0.07 (0.10)

Interest in innovation 0.12 (0.09) 0.04 (0.10)

Constant 4.0*** (0.88) 3.31*** (1.00) 4.20*** (0.81) 4.37*** (1.09) 2.89** (1.38) 4.23*** (0.92)

R-squared 0.5266 0.5174 0.5382 0.4286 0.2817 0.4305

Wald chi2( ) 36.13 57.65 48.81 45.66 38.54 48.77

Prob > chi2 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

*** p<0.01; ** p<0.05; * p<0.1 Note: Panel-corrected standard errors in parentheses

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As shown in Models 4 and 6, the coefficient of commercial and services infrastructures and physical infrastructure are highly significant, the first unexpectedly negative and the second, as expected, positively, similar to the results for the nascent entrepreneurship rate. Other formal institutions are not significant, and thus Hypothesis 1b is rejected. The negative sign of the commercial and services infrastructures coefficient could indicate that the lack of market infrastructure and services is an opportunity for entrepreneurs who create businesses in such areas.

Hypothesis 2 postulates that informal institutions influence the level of entrepreneurial activity. Particularly, Hypothesis 2b proposes that the individual dimension is positively associated with the nascent entrepreneurship rates. The results of Model 2 show that higher education and abilities and knowledge to start up are positively and significantly associated with the nascent entrepreneurship rate (p < 0.05). Therefore, the findings offer support for Hypothesis 2b and are in line with those of authors such as Kollinger et al. (2007), demonstrating that individuals who believe themselves to have the skills and ability to start a new business are more likely become entrepreneurs.

Finally, Hypothesis 2b suggests that social dimension is positively associated with the new business ownership rate. Model 2 shows entrepreneur social image to be significant (p<0.001) and positive, thus, the data support this hypothesis. However, the coefficients of other variables related to the social dimension (cultural and social norms, women’s support to start up, high growth business, and interest in innovation) are not significantly associated with the new business ownership rate. This result is in line with earlier studies which have suggested that the extent to which a society respects and admires entrepreneurs is a better predictor of entrepreneurship than other cultural measures (Spencer, & Gomez, 2004).

5. Conclusions

In this paper longitudinal panel data (period 2006–2009) is used to investigate empirically the relationship between institutions and entrepreneurial activity at country level. From an institutional approach (North, 1990 & 2005) applied to the field of entrepreneurship and the entrepreneurial framework conditions of GEM, we analyse the influence of formal and informal institutions on entrepreneurial activity according to the stage of the entrepreneurial process (nascent entrepreneur and new business).

The research generates two key results. First, the nascent entrepreneurship rate is related to formal institutions, such as low levels of commercial and services infrastructures and high levels of physical infrastructure, and informal institutions, such as higher education and high abilities and knowledge to start up. Second, new business ownership is related to formal institutions, such as low levels of commercial and services infrastructures and high levels of physical infrastructure, and informal institutions, such as entrepreneur social image. Thus, these results indicate that to start a business the perception of knowledge and skills needs to be determined. However, subsequent to this decision, it is crucial that society endorses and values the entrepreneurial career in order to move the new business forward and to overcome obstacles in the early stages.

Regarding future research lines, it is suggested that progress should be made in the characterization of entrepreneurial activity and the factors that determine it, distinguishing opportunity entrepreneurship (starting a business by taking advantage of an entrepreneurial opportunity) versus necessity (starting a business because other employment options are either absent or unsatisfactory). Finally, we reaffirm institutional economics as an appropriate and robust theoretical framework for the study of the environmental factors that influence entrepreneurial activity, specifically in the context of the GEM project (Urbano et al., 2010; Thornton et al., 2011; Alvarez, & Urbano, 2011).

REFERENCES

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