The Influence Of Institutional Factors

Published Date: 02 Nov 2017

This research investigates whether the institutional development level of emerging economies influences the level of new business activity of local firms within emerging economies. While the main focus of this thesis includes emerging economies, the empirical part will also include non-emerging economies. Currently, researchers and policymakers have limited knowledge about what factors drive local entrepreneurship towards higher levels in their own domestic market and what possible influences the governments can have in stimulating entrepreneurial activity of local start-up firms. By building on Scott`s (1995) three-pillar institutional framework the regulatory, normative, and cognitive aspects of 8 emerging economies will be measured. The literature part including the institutional components lies at the basis for including the correct institutional variables extracted from the national GEM databases. By analyzing data of 8 emerging economies and 36 non emerging economies this thesis will try to find evidence of whether the institutional development level of these economies influences the level of new business activity of local start-up firms in their own domestic markets. Control variables are added and include 3 economic variables; unemployment rate, total GDP per capita and population growth.

INTRODUCTION

The past two decades the global economy changed in a way that the former protected economies became liberalized and therefore integrated in the worldwide economies (Aulakh & Kotabe, 2008). This change reflects a rise in international business studies who are interested in researching emerging economies with their changed competitive environments. Varying institutional profiles can be found in these emerging economies and these profiles play an important role in fueling international business research (Clercq et al., 2010). This work will focuses on the influence of the institutional development level of emerging economies in relation with the level of new business activity [1] within emerging economies. While the literature part of this thesis will include emerging economies related literature, a number of non-emerging economies will be included in the empirical part in order to verify the quality of the data used for this thesis. To my knowledge no studies included a sample of emerging economies in an attempt to find a relationship with the level of institutional development and new business activity rates.

Entrepreneurial activity can be the cure for stagnant economies and can increase the economic welfare in former planned economies and stimulates economic growth in many other emerging economies (Spencer and Gomez, 2002). Despite the importance of entrepreneurial activity within emerging economies, scholars today have limited knowledge about what factors influence high rates of entrepreneurship in an economy. Also governments from emerging economies struggle in promoting entrepreneurship which can stimulate the growth of an economy (Spencer and Gomez, 2002). However the importance of emerging economies is reflected in the rise of international studies including this topic, research in entrepreneurship can still be critiqued as almost exclusively focusing on developed economies such as the European and North American countries (Bruton, 2008). Also, few studies focus on the role of the institutional development level of emerging economies in relation with new business activity in emerging economies Estrin & Prevezer (2010). For emerging economies, the evidence about how and why some start-up firms succeed is less well established and this emphasizes the importance of examining the role of institutional factors Estrin & Prevezer (2010). Currently, researchers and policymakers have limited knowledge about what factors drive local entrepreneurship towards higher levels in their own domestic market and what possible influences the governments can have in stimulating entrepreneurial activity of local start-up firms (Spencer and Gomez, 2002).

For local firms starting up businesses in emerging economies it is of strategic importance to identify the institutional development level of an emerging economy because this influences the performance of the firm, and knowledge about the institutional development level can maximize returns and minimize investment risks (Chan et al., 2008). For the emerging economy itself, Nickell (1996) argues that the start-up of local firms can stimulate efficiency and productivity and these local firms together can offer innovative ideas. Also according to Cohen and Klepper (1992) an increase in competition can be expected together with an increase in firm diversity. When an increasing number of start-up firms operate from emerging economies it is most likely that these firms will compete with each other by offering diverse products Cohen and Klepper (1992).

Research of Ayyagari et al., (2011) shows that small and medium-sized enterprises are contributing in adding value within emerging economies. Their results show that the SME sector’s (<100 employees) contribution to the economy is comparable of the larger firms. Also the results of the research of Ayyagari et al., (2011) implicate that the SME’s have the largest share of job creation together with the highest growth in employment rates. Therefore the entrance of local start-up firms in emerging economies is expected to increase the availability of jobs, which will stimulate economic growth of an emerging economy (Kirchoff and Phillips, 1988). Therefore, governments, investors and researchers may have interest in assessing the level of new business activity of local start-up firms within emerging economies in relation with the institutional development level.

The understanding of the institutional context within an emerging economy is crucial for a local start-up firm as it can vary greatly from those in more developed economies and even between emerging economies (Bruton, 2008). And it is this variety in institutional environments according to De Clercq (2010) which gives input for international business research. Despite the growing importance of emerging economies, research about institutional factors influencing the local start-up of firms in emerging economies is limited (De Clercq, 2010). The above reasoning leads to the formulation of to the main research question:

"To what degree does the institutional development level of an emerging economy affect new business activity of local start-up firms in emerging economies?"

In order to examine the institutional environment in a systematic way, this study includes the institutional profile concept based on the three components discussed in the work of Scott (1995). His work argues that the institutional environment includes regulatory, cognitive and normative aspects and taken together comprise for the whole institutional environment. In order to measure these three aspects this work will rely on datasets provided by the Global Entrepreneurship monitor. The Global Entrepreneurship monitor (GEM) investigates the entrepreneurial activity on a national level within different countries. Its main goal is to measure what influence entrepreneurial activity has on national economic growth. Further information about GEM will be included in the methodology part of this thesis. By comparing institutional development level data extracted from the Gem databases, this research will compare a total of 8 emerging economies in 4 continents for a total of 4 to 9 years. Also three control variables; GDP per capita, unemployment and population growth rates, will be included which are further discussed in the methodology part of this thesis. While this work includes a dependent variable which is country level based, the number of respondents is limited to the economies included.

This thesis will seek to contribute and better understand the effects of the institutional development levels of emerging economies in relationship with local start-up firms. Given the fact that the institutional development level is responsible for influencing the allocation of local start-up firms within emerging economies, investigating whether the institutional development level influences the decision-making of start-up firms seems necessary.

The expected theoretical and empirical contributions will provide additional insights in whether the institutional development level of an emerging economy affects the level of new business activity of local start-up firms. Studying this relationship is important since this will indicate whether regulatory, normative, and cognitive aspects of an emerging economy hinder local start-up firms from being successful in emerging economies. Since these local start-up firms are known to stimulate the economic growth (Ayyagari et al., 2011), investigating this relation seems necessary. The practical contribution of this research will give the local start-up firms a better insight in whether institutional elements matter within emerging economies.

The above reasoning describes the main issues that will be touched upon in both the theoretical framework and empirical analyses of this thesis. This work will be of interest and helpful for both local start-up firms (entrepreneurs) and governments from emerging economies. The results will also extend the current knowledge within the international entrepreneurship domain. To my knowledge, no studies included multiple years of GEM data when examining the institutional development level of emerging economies. This thesis will continue to build on the institutional theory as introduced by Scott (1995). According to Scott (1995), institutions consist out of three elements which will be discussed in literature review part of this thesis. After the discussion of the institutional development theory, the regulative, normative and cognitive institutional components will be discussed into more detail. Last, there will be a link between start-up firms in emerging economies and the possible influence of the institutional development level of different economies. These possible relationships will result in the formulation of the hypotheses.

2.0 LITERATURE REVIEW AND HYPOTHESES

2.1 INSTITUTIONAL DEVELOPMENT LEVEL

This work is based on two streams in the literature published by William Baumol (1990, 1993, 2005) and Douglass North (1990, 1994, 1997, 2005). Both were responsible for providing theoretical information about entrepreneurial development in environments that differ (for example: emerging versus developed economies). North argues that entrepreneurs and therefore local start-up firms are the main cause of change within an economy. Local start-up firms will have to adapt their strategies and activities in a way that they will fit within the institutional framework which enables them to avoid limitations and make use of opportunities. Each emerging economy has its own formal rules which ideally are formed to stimulate exchange and to reduce transaction costs. Since these institutions and formal rules are created by individuals or groups in ways which might differ, they do not necessary operate according to the interest of the social wellbeing (North 1990). This reasoning is followed by Baumol (1990). He describes institutions as the structural base that provides local start-up firms the incentives for differing economic activity. Both authors agree that local start-up firms will ‘weigh the incentives’ which are present in the economy in the form of regulations, norms and cultural aspects. Both authors also agree that the institutional environment plays an important role in attracting entrepreneurial activity (local start-up firms) and that in the event of a weak institutional environment the level of entrepreneurs operating form these economies will be less than in institutional environments that are more favorable.

The institutional development level of an economy includes rules, social norms and cognitive structures (Scott, 1995) that guide, restrict or benefit domestic entrepreneurial activity (Spencer and Gomez, 2002). Hitt et al., (2005) argue that local firms from emerging economies experience difficulties when operating from emerging economies. The problems both foreign and local firms face are the result of the dynamic, complex and uncertain environment of emerging economies with its underdeveloped institutional development level (Hitt et al., 2005). Especially the last years, researchers included the institutional aspect when researching entrepreneurial behavior (Bowen & DeClercq, 2008, Hessels et al., 2008). More and more governments are stimulating entrepreneurial activity in their economies by favoring their institutional structures. It is argued by Bowen & DeClercq (2008) that the overall economy is shaped by the institutional environment and this environment affects the diversity of entrepreneurial activity within any given economy or country. Among other aspects, Institutions affect the quality of governance and access to capital (Acs, et al., 2008). Institutional structures can be underdeveloped and therefore be considered as institutional burdens hindering local start-up firms from operating effectively and finding business opportunities (Peng, 2003). Nowadays, local start-up firms from emerging economies face difficulties in starting up their businesses since they operate within an economy that is underdeveloped. As mentioned by Manev (2010) on page 70 "knowledge about entrepreneurship can be advanced by a better understanding of the role of different institutional and cultural contexts for the types of entrepreneurial opportunities". It is argued by Hitt et al., (2004) that emerging economies have an institutional development level which is relatively low compared with developed economies where the institutional development level is relatively high. The reason why emerging economies have relatively low institutional development levels is caused by the absence of institutional rules which are also enforced poorly and insufficient (Hitt et al., 2004). Emerging economies differ from developed economies in ways that they lack market information that is reliable. Also unpredictable government actions can hinder local start-up firms from operating efficiently. (Chan et al., 2008). These elements, combined with the lack of efficient bureaucracy create an environment with several "institutional voids" (Khanna and Palepu, 2000). These institutional voids result in transaction costs which are more costly and also make transformations less efficient for local start-up firms (Henisz and Zelner, 2005). Transaction costs in emerging economies are higher due to the fact that firms need to protect their assets form dispossession (Chan et al., 2008). Therefore, local start-up firms that focus their operations in countries with low institutional development levels are more likely to face costly market transactions, whereas local start-up firms operating from developed economies with higher institutional development levels can benefit from the advantages presented by this developed economy (Chan et al., 2008). Institutions which are better developed lower the search, production and transactions costs (North, 1990). Also, the more favorable the institutional development level is, the more positive the profitability is for international start-up firms (Bergara et al., 1998).

Based on the above reasoning, this work will include the institutional perspective in which economies differ rather than the cultural perspective and rely on theories that cover recent institutional theorizing (Berry, Guille´n & Zhou, 2010). North (1990) describes institutions as the societies with their own rules and constrains which shape human interaction. Later, Scott (1995) expanded this view by introducing a three-dimension country institutional context (Chao & Kumar, 2010) which includes regulative, cognitive and normative components of the institutional development level of an economy. These three components will be discussed further in the following part.

2.2 THE REGULATIVE OR LEGAL COMPONENTS OF INSTITUTIONS

This component reflects the existing laws and rules in a specific region or a country that promote specific types of behaviour and restrict other (Kostova, 1997). These Laws and rules are known to influence behaviour and constrain others (Kostova & Roth, 2002). The regulative component of institutions in the context of new business creation also refers to the degree in which tax collection system are efficient (Estrin et al.,2006). An inefficient tax system will result in a burden for local firms starting up businesses and running them. The regulative component also refers to the presence of governments and their policies supporting local firms starting up businesses and their quest for resources (Reynolds et al.,2005), and the ease for getting licences and permits (Djankov & Murrell, 2002). Laws and regulations can make the decision making process of entrepreneurs more efficient in a way that these ‘rules’ indicate which responsibilities the owner has. Laws and regulations also tend to lower the risk involved with starting up a new business (Spencer and Gomez, 2002). Requirements which are complex will hinder the activities of businesses. The findings of Djankov et al. (2002) support the view that institutions with higher levels of regulative burdens are not supportive for positive outcomes such as improved quality of products. Instead, the result support that countries with high regulative burdens have higher levels of corruption and the size of the unofficial economy is larger (Estrin & Prevezer, 2010). Also, high regulative burdens hinder the attraction and creation of firms (Klapper et al., 2006).

2.3.THE NORMATIVE OR SOCIAL COMPONENT OF INSTITUTIONS

This normative component refers to the degree in which the inhabitants of a country admire entrepreneurial activity (Spencer and Gomez, 2002). This component introduces "a perspective, evaluative, and obligatory dimension into social life" (Scott, 1995). This component defines the expected behaviour in a society and specifies the way in which things are expected to be done (Pogrebnyakov & Maitland, 2011) or as North (1990) defines: "the humanly devised constraints that shape interaction’, this includes formal rules and enforcement mechanisms and implicit rules that can take the form of taboos, customs, codes of conduct, routines and so on (North, 1990, pp. 6, 43, 83). Therefore the normative component can be used to measure the degree in which the countries inhabitants ‘welcome’ entrepreneurial activity. When an emerging economy scores low on the normative components this would suggest that the countries inhabitant don’t accept entrepreneurial activity.

2.4 THE COGNITIVE COMPONENT OF INSTITUTIONS

The cognitive or cognitive-cultural component (Scott, 1995), is a reflection of the cognitive structures shared by the people in a particular country or region. According to Kostova (1997), ‘‘The cognitive and normative dimensions of the country institutional context are conceptually close to culture, whereas the regulatory dimension is unique to country institutional context and not captured by culture’’. Cognition here does not refer to individual mental constructs, but to common symbolic systems and shared meanings that are a basis of much stability in the social life. This component contains knowledge and skills of individuals about how to establish new businesses and how to operate these. Some knowledge becomes institutionalized and therefore part of the economy. For example, some countries lack the most fundamental knowledge of managing new businesses than other countries (Busenitz & Lau, 1996). Zucker, (1991) argues that within a country different knowledge sets over time become institutionalized and therefore become a common shared social understanding. If all the skills and knowledge are combined from inhabitants of a specific country in starting up a business and in processing information, than this refers to the cognitive dimension of the institutional profile (Spencer and Gomez, 2002). Ideally, in a country where entrepreneurship is common, the inhabitants should possess the knowledge about how to start up a business and how to manage risk. This knowledge can differ between countries in a way that in some, hardly any knowledge is known about how to run a business (Zucker, 1991). In these low cognitive countries little is known about how to start and run a business. Training programs and the amount of assistance new businesses get from the government when starting up a business can contribute to the cognitive environment and stimulate entrepreneurial skills (Dana, 1987; Hawkins, 1993).

2.5 EMERGING ECONOMIES

About half of the total land mass of this world consists of emerging economies which is illustrated in figure 1. The increasing interest from scholars researching emerging economies is the result of the economic liberalization of these former protected economies which has resulted in a more favorable environment for firms to operate in (Appiah-Adu, 1999). It is no surprise that, for decades; the environment of doing business in emerging economies was unsupportive do to political instability, a bad infrastructure and formal trade barriers and economic stagnation (Bartlett, 1990). These factors were causing bad investment opportunities for both local and international firms (Collins, 1990). The past two decades the global economy changed in a way that the former protected economies became liberalized and therefore integrated in the worldwide economies. This resulted in more supportive environments for firms operating from emerging economies due to regulations which were adjusted in favor of supporting business growth. While most of these emerging economies are highly populated, so far they have hardly any influence on global GDP levels (Kearney 2012). Expectations however indicate that it is only a matter of time before emerging economies will have influence on global GDP levels McKinsey & company (2012). As expectations indicate that emerging economies will continue to grow, they are expected to outperform developed economies and to become the most important economies worldwide. By the year 2025, McKinsey & company (2012), expects that the annual consumption within emerging economies will reach the number of $30 trillion making it one of the most important possible growth markets for start-up firms. Also, Wilson & Purushothaman (2003) argue that by the year 2050, the "BRIC" economies; Brazil, China, India and Russia will outperform the economies of France, Germany, Japan, United Kingdom and the United States in growth rates making them larger.

Fig.1. Emerging economies in 2011

Source: Kearney (2012) p.162.

Local start-up firms operating from emerging economies face certain important institutional burdens in bringing their start-up to a success as discussed in the previous section of this thesis (Bruton & Rubanik, 2002). Emerging economies can be described as having: " a diverse set of business, cultural, economic, financial, institutional, legal, political and social environments within which to test, reassess and renew received wisdoms about how the business world works, to gain deeper insights into prevailing theories and their supporting evidence, and to make new discoveries that will enhance human welfare in all environments including the world's poorest countries, the developing world, the transition countries and the developed world " (Kearney, 2012. P-160). Although the term ‘emerging economy’ is common used in the literature, there is no agreement about its theoretical or operational definition (Kearney, 2012). International financial institutions are mostly responsible for assigning the classification of emerging economies to a certain country. According to the World Bank a country is named ‘emerging’ when "its GDP falls below a certain hurdle that changes through time" (Bekaert et al., p.429. 2002). The obvious idea behind the term is that a country emerges from a less developed status country to a status which is more developed and therefore is emerging. However, while the interest in emerging economies is growing for both businesses and researchers on the global stage, plus the role local start-up firms play in fueling their economy, the understanding of local start-up firms operating from emerging economies is limited (Kiss et al., 2011).

Emerging economies tend to have a large diversity in cultural, language and political aspects (Kearney, 2012). Surprisingly, as is argued by Kearney (2012), most of the physical financial infrastructures of emerging economies are well-developed. The physical financial infrastructure includes different types of banks such as central and commercial banks and the stock exchanges. While these physical infrastructures seem to be well-developed the processes and systems supporting them are less well-developed. Important processes and systems which tend to be less well-developed within emerging economies include regulation, accounting, governance and its liquidity (Kearney, 2012). These less-well developed processes and systems lead to greater uncertainty and increase the risk of operating from emerging economies. So although the liberalization of these emerging economies opened up possibilities for businesses, there are still burdens to overcome for firms starting up businesses in these economies.

As discussed in the introduction part of this work, emerging economies rely heavily on new business activity since this plays a critical role in the economic reform and they function as engines of structural change (Clercq et al, 2010). Entrepreneurial activity has long been viewed as the engine that stimulates innovation and will strengthen the economic development of an economy (Reynolds, 1997). Looking back in time at the history of the development of the industries of both Great Britain and the United States (former emerging economies) Casson (1990) argues that the rapid industrialization in these countries was made possible because entrepreneurial activity was allowed to increase. Still today entrepreneurial activity brings new life into different economies worldwide and has facilitated growth in many other economies (Oviatt & McDougall, 1994). However, scholars have limited knowledge explaining why rates of entrepreneurial activity are different across countries and economies (Aronson, 1991).

An important element for emerging economies to be either attractive or not attractive for local start-up firms is the degree to which these economies have hindering or supportive institutional factors (Estrin & Prevezer, 2010). This concept will be tested in this thesis in the following part of this work and will include the three components view introduced by Scott (1995) These components, instead of the cultural view, nowadays seem more valid for researcher to implement in their studies as it is a much broader concept covering a much wider area then the beliefs and norms distinctive for individuals within a country.

3.0 HYPOTHESIS DEVELOPMENT

By combining the literature consisting of information about the institutional development level and emerging economies the formulation of the hypotheses becomes possible. As there is a clear indication from the literature that the institutional development level can influence the degree of local start-up firms starting up businesses in any given economy, this seems highly relevant in emerging economies where the institutional development level is known to be less favourable then in developed economies. When referring to emerging economies with its underdeveloped institutional development level, the discussed regulative, normative and cognitive components can act as institutional burdens affecting the local start-up firms operating from these emerging economies. Therefore it is highly likely that there will be a relationship between the degree of institutional burdens and the level of new business activity of local start-up firms within emerging economies.

Studies and scholars struggle to identify reasons explaining why entrepreneurial activity varies across economies. While research including the possible relationship of entrepreneurial framework conditions on the conditions stimulating new business foundation failed to come up with consistent results (Hechavarria and Reynolds, 2009), there seems to be a need for another measurements in explaining why rates of new business foundations differs across countries and economies. As discussed before investigating, a possible relationship of culture and new business foundations seems irrelevant as the concept of the institutional development level is a much broader concept covering a much wider area then the beliefs and norms distinctive for individuals within a country. Including institutional theory is better able to answer most of these questions (Pogrebnyakov and Maitland, 2011). The above arguments call for more systematic approaches to both theoretical define and analytical measure the degree in which new business foundation are influenced among different countries and economies (Gartner and Shane, 1995).

3.1 THE REGULATIVE COMPONENT

Scott (1995) argues that the regulative component of the institutional theory reflects policies, laws and rules and regulations, that influence the behavior of individuals and therefore influences economic growth. It is generally accepted that policy measurements are influencing the degree in which entrepreneurial activity takes place within an economy (Storey, 1994). There are different ways in which the government can either encourage or discourage entrepreneurial activity within its economy. Supportive or unsupportive tax collection systems, (Estrin et al.,2006) policies supporting local firms starting up businesses and their quest for resources, (Reynolds et al.,2005) and the ease for getting licences and permits (Djankov & Murrell, 2002) Are three examples of policy measurements. When focusing on emerging economies, these regulative institutional components seem to be more relevant since macro – level structures are supressing the rate in which entrepreneurial activity takes place (El-Namaki, 1988). Regulative rules can either stimulate or hinder entrepreneurial activities because they give an indication of the risk level in starting up a business and these rules affect the behavior of entrepreneurs (Baumol and Strom, 2007). For example, regulations and laws influence the degree in which entrepreneurs have access to means required to start up a new business (Busenitz et al., 2000). Economies which have fewer regulations tend to increase the opportunities for entrepreneurs who engage in starting up a business (El-Namaki, 1988). These regulative rules including administrational, bureaucracy and procedures influence the intensions of individuals in starting up their own business. In an event of a strongly restricted regulative economy, the likely hood of less firms engaging into the formation of a business is more likely than in less restricted regulative economies (Capelleras et al., 2008). This points towards a relationship with both emerging and non-emerging economies where the regulative component tends to be less developed and therefore affecting the decision making of entrepreneurs in starting up a business. The uncertainty of the regulative framework together with the likelihood of corruption will drive the start-up costs up which result in less favorable circumstances for starting up a business (Boettke and Coyne, 2003). Also missing intellectual property rights, corruption and untrustworthy regulations and laws might hinder entrepreneurial activities (Aidis et al., 2008). Since the literature suggests that the regulative environments can either encourage or discourage entrepreneurial activity, this work assumes that the regulative component of the institutional theory is related to the rate in which entrepreneurial activity takes place within an economy. Therefore this work assumes that;

HYPOTHESIS 1:

Supportive regulative components will positively influence the level of new business activity of local start-up firms within economies

3.2 THE COGNITIVE COMPONENT

The cognitive component of the institutional theory reflects the way in which individuals interpret information (Scott, 1995). An important part of these cognitive perceptions include technological uncertainty and risks attitudes which might influence entrepreneurial decision making (Dickson and Weaver, 2008). Studies showed that norms and personal cognitive elements influence the degree in which individuals recognize opportunities (Baron, 2007). The combination of the degree of knowledge the individual has and the degree of motivation and entrepreneurial intentions influences the level of entrepreneurship within economies (Baron, 2007). This individual cognition is likely influenced by the degree of education (Verheul et al., 2002), indicating that education in entrepreneurial related topics will stimulate individuals to start up a business. Therefore this work assumes that it is not only a person’s willingness that is a crucial step in undergoing entrepreneurial activity. In line with the findings from (Krueger et al., 2000) a person’s capability in undergoing entrepreneurial actions is also a very important element. Just recognizing an opportunity is not enough; it is the combination of recognizing and knowledge that, when combined form the ideal combination of an individual to start-up a new business (McMullen et al., 2008). Therefore it is of great importance that individuals have a certain amount of knowledge which can help them to successfully start-up a new business. The combinations of willingness, knowledge and intentions have been studied before and resulted to be of influence to entrepreneurial activity (Alvarez and Barney, 2007). The degree in which individuals are alert towards opportunities or are confident in their own skills to start up a business, are also strengthening the degree in which individuals are likely to start up a business (Arenius and Minniti, 2005). Therefore, the knowledge and skill sets of entrepreneurs are likely influencing the decision making related to starting up a business. Based on the above, this work argues that the extent in which an economy’s educational system gives attentions to entrepreneurship-related topics is likely to be of influence towards the rate in which entrepreneurial activity takes place in a later stage, and therefore assuming that;

HYPOTHESIS 2:

Supportive cognitive components will positively influence the level of new business activity of local start-up firms within economies

THE NORMATIVE COMPONENT

The normative component of the institutional theory includes certain norms, beliefs and values which can be related to the behavior of an individual (Busenitz et al., 2000). Values here refer to the degree in which certain goals are met and whether or not standards are achieved (Stenholm et al, 2013). Norms refer to the way in which businesses are expected to behave when for example starting up a business or what rules apply when 2 businesses work together (Stenholm et al, 2013). It is argued by Krueger et al. (2000) that a social reference group with its own beliefs, attitudes and expectations can influence the mindset of individuals and therefore influencing the entrepreneurial intentions of this individual. There seem to be a relationship between the degree in which entrepreneurial activity is desired within an economy and the degree in which entrepreneurial activity is likely to take place (Stenholm et al,. 2013). Within an economy where entrepreneurs are accepted, it is likely that this entrepreneurial friendly environment stimulates self-employment and therefore entrepreneurial activity (Krueger et al. 2000). The acceptance of entrepreneurs can be family based and/or on cultural level, which include the largest amount of social individuals (Spencer and Gomez, 2002). Values that reflect the degree in which entrepreneurs are welcomed can also lead to the improvement of legal restrictions as well as further strengthening the total cultural norms when still needed (Cuervo, 2005). An economy has different ways in which it can stimulate and promote entrepreneurial activity within its economy. In line with the findings discussed in the cognitive part of this work, Verheul et al., (2002) argues that a supportive educational system, that is, one that stimulates education related to business ownership and media attention can both positively influence the entrepreneurial norms. The acceptance of entrepreneurs within an economy may well be positive when personal wealth and payments are comparable with what normal paid jobs would offer (Spencer and Gomez, 2002). The normative component can therefore be used to measure the degree in which the countries inhabitants ‘welcome’ entrepreneurial activity. When high levels of normative burdens are measured within an economy, it is likely that the inhabitants of this economy are unsupportive and disliking new business activity within their country. Therefore the normative component can be used to measure the degree in which the countries inhabitants ‘welcome’ entrepreneurial activity. When an economy scores low on the normative components this would suggest that the countries inhabitant don’t accept entrepreneurial activity. The above reasoning in combination with the findings from the literature review therefore suggests that;

HYPOTHESIS 3:

Supportive normative components will positively influence the level of new business activity of local start-up firms within economies

Please note that the hypotheses argue for institutional relationships between "economies" and therefore including both emerging and non-emerging economies in the following analyses. Since the non-emerging economies are studied before in relation to this topic, the literature review of this work also argues that emerging economies are possibly influenced by these institutional components.

4.0 CONCEPTUAL MODEL

While covering the institutional development theory this thesis argues that the work of Scott (1995) highlights the three most important components for researching the institutional development level of any given economy. By including the regulative, normative and cognitive components of the institutional development level, this thesis will try to measure if there is a relationship between these three factors and the rate of new business ownership within emerging and non-emerging economies. The methodology part of this thesis will further discuss the chosen variables for the regulative, cognitive and normative institutional development components indicated in the conceptual model as R1,R2,C1,C2,N1,N3 as well as the control variables.

CONCEPTUAL MODEL

R

INSTITUTIONAL

FACTORS

(EMERGING/ NON EMERGING ECONOMIES)

1

NEW BUSINESS OWNERSHIP RATES

(NBOR)

EMERGING ECONOMIES

C

1

2

N

1

2

2

CONTROL VARIABLES

- GDP PER CAPITA

- UNEMPLOYMENT RATES

- POPULATION GROWTH

5. RESEARCH METHODOLOGY

In line with the classification of Scott’s (1995) three pillars concept as discussed in the literature review this thesis will include the regulative, normative and cognitive components of emerging economies and tests whether a relationship exists between the institutional development level of emerging economies and the level of new business activity of local start-up firms from these emerging economies. To do so this thesis will include data from the GEM databases [2] . In line with the findings from the literature review, the chosen institutional variables from the GEM databases will be based on the findings from the literature review.

5.1 DATA SOURCES

In order to study the rate in which entrepreneurial activity takes place within an economy, the entrepreneurship literature offers multiple options to measure this. While multiple options are offered, the usefulness of these measurements in measuring the new business foundation rates across economies remains questionable (Ahmad and Hoffmann, 2008). This is caused due to the fact that scholars today have multiple measures to choose from; individual reports which are selected randomly or data from business registries (Stenholm, 2011). These two types of data collection methods have their limitations since the type of measurements do vary between countries, making it difficult to analyze this data between countries and economies. The OECD was one of the first databases that included data about self-employment across all their member countries. Reynolds et al., (2005) argue that due to the limitations of the data of the OECD, the call for reliable date became apparent and was delivered by the Global Entrepreneurship Monitor (GEM). The datasets and models used by the GEM are promising (Valliere, 2010). The Global Entrepreneurship monitor (GEM) investigates the entrepreneurial activity on a national level within different countries. The 3 main objectives of the GEM research program according to their homepage are:

-"To measure differences in the level of entrepreneurial activity between countries"

-"To uncover factors leading to appropriate levels of entrepreneurship" -"To suggest policies that may enhance the national level of entrepreneurial activity"

Its first publication is from the year 1999 with annual assessments of 10 countries. By the year 2000 this number expanded to 21 countries and by the year 2008 they have reached more than 60 countries. The main goal of GEM is to measure what influence entrepreneurial activity has on national economic growth. An increasing number of individuals are surveyed annually within a specific country to provide measures of the influences entrepreneurs have on the economic development level of the country. The GEM data is unique in that is consists of data which can be compared with other countries. While all countries do collect data on self- employment none of these datasets can be used for country comparison since their definitions about self-employment differ. The main strength of GEM data therefore lies in the fact that is delivers data which is harmonized and therefore can be used to compare multiply countries without having to deal with different measurement variables. Therefore this data is suitable for this research as it will compare data between different emerging economies.

6. DATA COLLECTION

6.1 DEPENDENT VARIABLE

New Business Ownership Rate

This thesis will include data about the new business ownership rate as an indicator for new businesses foundation in emerging economies by local firms. The new business ownership variable refers to: "the percentage of the 18-64 population who are currently an owner-manager of a new business, i.e., owning and managing a running business that has paid salaries, wages, or any other payments to the employers for more than three months, but not more than 42 months". (GEM, key indicator, 2012).

7. INDEPENDENT VARIABLES

7.1 REGULATIVE COMPONENTS

The measure utilized for the regulative component of the institutional development level is the regulative 1 and regulative 2 variable extracted from the GEM database. Since there is no known variable to measure the degree of regulative development level in an emerging or any economy the two regulative variables used for this thesis are based on the literature review. For the regulative components the literature review indicated that (see H1) it is likely that government rules, laws and decisions are influencing the level of new business activity of local start-up firms. REG 1 extracted from the GEM database refers back to the decisions made by the government and REG 2 refers back to the rules and laws. Both REG 1 and REG 2 scores are based on a 5 point likert scale indicating that 1,00= "Completely false" 2,00= "Somewhat false"3,00= "Neither true nor false"4,00= "Somewhat true"5,00= "Completely true".

- REG 1: In my country, the support for new and growing firms is a high priority for policy at the national government level

- REG 2: In my country, new firms can get most of the required permits and licenses in about a week

- REGMEAN: this score becomes available after: (REG1 + REG2) / 2. Since this mean score includes both regulative components, this measurement will be used in further regressions.

7.2 COGNITIVE COMPONENTS

The measure utilized for the cognitive component of the institutional development level is the cognitive 1 (COG 1) and cognitive 2 (COG 2) variable extracted from the GEM database. Since there is no known variable to measure the degree of cognitive development level in an emerging or any economy the two cognitive variables used for this thesis are based on the literature review. For the cognitive components the literature review indicated that (see H2) the inhabitants should possess a certain type of knowledge to start-up businesses on their own. Also the degree in which the availability of training programs are offered in helping local entrepreneurs in starting up a business refers back to a cognitive component and is therefore considered as worthy of investigating.. COG 1 extracted from the GEM database refers back to the degree in which training programs support entrepreneurs in founding their new business. COG2 refers back the degree in which the entrepreneurs possess the right amount of knowledge to start –up a business on their own. Both COG 1 and COG 2 scores are based on a 5 point likert scale indicating that 1,00= "Completely false" 2,00= "Somewhat false"3,00= "Neither true nor false"4,00= "Somewhat true"5,00= "Completely true".

- COG 1: In my country, the level of business and management education provide good and adequate preparation for starting up and growing new firms

- COG 2: In my country, many people know how to start and manage a small business

- COGMEAN: this score becomes available after: (COG 1 + COG 2) / 2. Since this mean score includes both cognitive components, this measurement will be used in further regressions.

7.3 NORMATIVE COMPONENTS

The measure utilized for the normative component of the institutional development level is the normative 1 (NORM 1) and normative 2 (NORM 2) variable extracted from the GEM database. Since there is no known variable to measure the degree of normative development level in an emerging or any economy the two normative variables used for this thesis are based on the literature review. - For the normative components the literature review indicated that (see H3) that the inhabitants of this economy are unsupportive and disliking new business activity within their country. Therefore the normative component can be used to measure the degree in which the countries inhabitants ‘welcome’ entrepreneurial activity. NORM 1 extracted from the GEM database refers back to the degree in which inhabitants respect and welcome entrepreneurs. NORM 2 refers back the degree in which inhabitants see entrepreneurs as resourceful and supportive individuals Both NORM 1 and NORM 2 scores are based on a 5 point likert scale indicating that 1,00= "Completely false" 2,00= "Somewhat false"3,00= "Neither true nor false"4,00= "Somewhat true"5,00= "Completely true".

- NORM 1: In my country, successful entrepreneurs have a high level of status and respect

- NORM 2: In my country, most people think of entrepreneurs as competent, resourceful individuals

- NORMMEAN: this score becomes available after: (NORM 1 + NORM 2) / 2. Since this mean score includes both normative components, this measurement will be used in further regressions.

8. CONTROL VARIABLES

Although this research argues for a relationship between institutional factors affecting the amount of local start-up firms starting up businesses, there might be other factors explaining this phenomenon. It is therefore necessary to include control variables which are known to be of influence to new business foundation. This study includes three economic factors as control variables as possible variables influencing new business foundation.

- Unemployment, total (% of total labor force)

While the definition of unemployment differs per country, the most common explanation refers to the share of the labor force that has no work but is searching for and is available to work. The unemployment data for this thesis is collected from the World Bank databases. Wildeman et al. (1998) suggest that within less developed economies, the unemployment rates are higher compared with developed economies and that in economies with high unemployment rates the possibility of self-employment will increase. It therefore seems likely that individuals within low employment opportunity economies are more likely to start-up their own business. Data about unemployment as total % of the labor force is extracted from the World bank databases [3] .

- GDP per capita (current US$)

"Gross domestic product (GDP) is the monetary, market value of all final goods and services produced in a country over a period of a year" (van den Berg, 2008, p-117). When the GDP is correlated for inflation the real GDP per capita becomes visible and this GDP per capita is often used as a measurement for judging the health of an economy within a specific country. The study of Wildeman et al. (1998) indicated that economies with high per capita GDP, and therefore having a healthy economic environment is unsupportive for local starting-up firms. Within these high per capita GDP economies the level of business activities are on a much higher level due to the use of advanced technologies than compared with less developed economies were less advanced technologies are needed in order to succeed. Therefore it is likely that the higher the per capita GDP rate of an emerging economy, the more likely it is that the number of local start-up firms will be less. Data about GDP per capita is extracted from the World Bank databases [7] 

- Population growth (annual %)

The annual growth of the population can be described as the exponential growth of the midyear population (World Bank, 2012). This demographic factor seems to be of influence on entrepreneurial activity as Armington and Acs (2002) found a positive relationship between population growth and entrepreneurship. Reasons so include that fact that a growing population increases the possibilities for entrepreneurial activity due to a consumer market which is becoming larger. Data about population growth is extracted from the World Bank databases [4] 

To summarize, this study expects that high unemployment rates, low per capita GDP and population growth will stimulate local start-up firm activity within their own domestic market. Therefore these variables will act as control variables. The following table shows an overview of all the included variables and descriptions used for the analyses.

Component

variable

Description

Source

Dependent variable

New business foundation rate

Independent variables

Regulative

Cognitive

Normative

Control variables

GDP per capita

Total unemployment

Population growth

NBOR

REG 1

REG 2

COG 1

COG 2

NORM 1

NORM 2

GDP

UNEMPLOYMENT

POPULATION GROWTH

he percentage of the 18-64 population who are currently an owner-manager of a new business, ie., owning and managing a running business that has paid salaries, wages, or any other payments to the employers for more than three months, but not more than 42 months

- In my country, the support for new and growing firms is a high priority for policy at the national government level

- In my country, new firms can get most of the required permits and licenses in about a week

- In my country, the level of business and management education provide good and adequate preparation for starting up and growing new firms

- In my country, many people know how to start and manage a small business

- In my country, successful entrepreneurs have a high level of status and respect

- In my country, most people think of entrepreneurs as competent, resourceful individuals

- GDP per capita (current US$)

- Unemployment, total (% of total labor force)

- Population growth (annual %)

GEM key indicators

Gem National level data sets (2001-2009 period)

See REG 1&2

See source REG 1&2

See source REG 1&2

See source REG 1&2

World Bank Dataset

World Bank Dataset

World Bank Dataset

9. DATA DETAILS AND MISSING DATA

The data for this study is collected from the annual datasets [5] of GEM and includes data covering the (2001-2009 period). While the GEM offers multiple datasets, the data necessary for this research was extracted from the datasets consisting of National level data which include institutional level elements (regulative, cognitive and normative) collected from respondents from multiple economies. All results from the National datasets are average values per country where the minimum response rate is 2000. While the countries included in these National level datasets include both developed and emerging economies the emerging economies had to be separated. In order to clarify which economies can be considered "emerging "this work will include the emerging economies as stated by the Morgan Stanley Capital International (MSCI) emerging market index. The following information about the MSCI index is gathered from their website [6] . "The MSCI index is able to measure the equity market performance within emerging economies. The MSCI index is also called a "free float-adjusted market capitalization index and includes the following 21 emerging economies: Brazil, Chile, China, Colombia, Czech Republic, Egypt, Hungary, India, Indonesia, Korea, Malaysia, Mexico, Morocco, Peru, Philippines, Poland, Russia, South Africa, Taiwan, Thailand, and Turkey*. The MSCI is constantly reviewing the countries included by using a framework which is called the MSCI Market Classification Framework. In order to classify the emerging economies development level, variables such as size, liquidity and market accessibility are constantly gathered and examined. When necessary, the list of emerging economies is reviewed and changed.

MSCI Emerging Markets Index - Country Coverage [6] 

X:\Data\My Documents\Figure 1 thesis.bmp

The economies included in the National level datasets differ each year. After separating the emerging economies from the datasets for a time span of nine years the following overview becomes visible (Figure 1). The emerging economies highlighted in the MSCI Emerging Markets Index are included. Brazil is the only economy for which data is available in all the National datasets covering the nine years (2009-2001) period.

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The next separation of the data is based on the degree in which the new business ownership rate data is available. This data is extracted from the key-indicators data [7] from the GEM website:

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The remaining emerging economies that will be included in further analyses are Brazil, Chile, China, Hungary, Korea, Mexico, Russia and South Africa. Only these economies have data available for four years or more on national level data and new business ownership rates: Brazil 9 years, Chile 7 years, China 4 years, Hungary 6 years, Korea 4 years, Mexico 4 years, Russia 5 years and South Africa 7 years. Therefore all economies with missing data will be excluded for further analysis and only the economies with complete data will be included. This resulted in a total of 46 cases (N46) which will be included in further analysis. The same rules were applied when gathering data for the non-emerging economies. This resulted in the list of the following non-emerging economies: United States, Greece, Netherlands, Belgium, France, Spain, Italy, United Kingdom, Denmark, Sweden, Norway, Germany, Peru, Argentina, Colombia, New Zealand, Singapore, Thailand, Turkey, Canada, Japan, Ireland, India, Finland, Serbia, Croatia, Ecuador, Uruguay, Hong Kong, United Arab Emirates, Israel, Jamaica, Switzerland, Chile, and Australia

RESULTS

Since this study is interested in the relationship between multiple independent variables, (regulative, cognitive and normative institutional variables and 3 types of control variables) and their possible relationship with the dependent variable new business organization rate (NBOR) this thesis will use multiple regressions taking into account different years. The Multiple Regression test is performed using SPSS software. In order to measure the influence of the institutional variables the NBOR was taken as the dependent variable, and the institutional components and control variables as independent variables. In order to calculate for year influences each year was included as a dummy variable. In order to verify the quality of the results a test for multicollinearity is performed.

Figure 1A and 1B represent the descriptive statistics results for both the emerging and non-emerging economies. The descriptive statistics show a valid N of 46 cases including emerging economies and 197 non-emerging economies.

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Correlation tests will indicate to what degree the variables are correlated with each other and therefore testing for Multicollinearity. Figure 2A and 2B represent the correlation results for both emerging and non-emerging economies.

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Figure 2A including the emerging economies shows a positive correlation for the NORMMEAN (,419** ) and a negative correlation for unemployment (-,468** ). Both are correlated at the significance level of 0.01 (2-tailed). Figure 2B includes the non-emerging economies and shows a negative correlation for the REGMEAN (-,176* ) and a positive correlation with population growth (,171* ) both correlated significant at the 0.05 level (2-tailed). GDP (-,370*) shows a negative correlated relationship with NBOR at the 0.01 level (2-tailed). According to the rule of thumb discussed by Hinkel et al., (2003), having a correlation coefficient of > 0.7 á 0.8, indicates an issue related to multicollinearity. If we look at the results of both figure 1A and 1B then no indications can be found which indicate the problem of multicollinearity. A more precise measure is the VIF which stands for variance inflation factor. If this variance is > +/- 10 then multicollinearity is probably an issue. This seems to an issue in figure 5A where the VIF of COGMEAN scores 17.550 and in figure 5B where the VIF of COGMEAN scores 11,557. However when not taking into account the dummy year variables, no cases of multicollinearity are present in the outputs.

The following part will include the results of the multiple regressions. First tests are performed without taking into account the measurements for the institutional components (REGMEAN, COGMEAN and NORMMEAN), and the dummy years. These dummy years will later function as a robustness check where the influence of years is taking into account. The results of the multiple regression tests only including the control variables, are illustrated in figure 3A (emerging economies) and figure 3B (non-emerging economies).

--- Insert figure 3A here ---

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Figure 3A includes coefficients results of emerging economies only taking into account the control variables and the dependant variable NBOR. UNEMPLOYMENT has the largest standardized coefficient Beta of -,708 and is significant at the ,000 level. GDP is not tested significant (,063) while population growth is (,002). Collinearity statistics indicate no problems with the variables included in figure 3A; (Tolerance = > .10 and VIF is < 10).

Figure 3B includes coefficients results of non-emerging economies only taking into account the control variables and the dependant variable NBOR. GDP has the largest standardized coefficient Beta of -,481 and is significant at the ,000 level. Unemployment is also tested significant (,004) and population growth scores a significance of (,000). Collinearity statistics indicate no problems with the variables included in figure 3B; (Tolerance score are > .10 and VIF is < 10).

The following results include both the control variables and the institutional components (REGMEAN, COGMEAN and NORMMEAN). These results are illustrated in figure 4A and 4B for both the emerging and non-emerging economies.

--- Insert figure 4A here ---

--- Insert figure 4B here ---

Figure 4A includes coefficients results of emerging economies taking into account the control variables, the independent variables REGMEAN, COGMEAN AND NORMMEAN, and the dependant variable NBOR. Comparing the three institutional MEANS the NORMMEAN has the largest standardized coefficient Beta of ,406 and is significant at the ,006 level. COGMEAN has the second largest standardized coefficient Beta of -,306 and is significant at the ,043 level. Interestingly, both the GDP and population growth variables are not significant anymore. REGMEAN is also of no significance (, 128). Collinearity statistics indicate no problems with the variables included in figure 4B; (Tolerance = > .10 and VIF is < 10).

Figure 4B includes coefficients results of non-emerging economies taking into account the control variables, the independent variables REGMEAN, COGMEAN AND NORMMEAN, and the dependant variable NBOR. Comparing the three institutional MEANS the COGMEAN has the largest standardized coefficient Beta of, 219 and is significant at the ,002 level. The remaining institutional MEANS are not significant (<0, 05). The three control variables remain significant in this output. Collinearity statistics indicate no problems with the variables included in figure 4B; (Tolerance = > .10 and VIF is < 10).

The final results function as a robustness check and include the dummy year variables. These dummy year variables function to test for the influence of different years. The results of these tests are illustrated in figure 5A and 5B for both the emerging and non-emerging economies.

--- Insert figure 5A here ---

--- Insert figure 5B here --

Figure 5A includes coefficients results of emerging economies taking into account the control variables, the independent variables REGMEAN, COGMEAN AND NORMMEAN, Dummy year variables and the dependant variable NBOR. Comparing the three institutional MEANS the COGMEAN has th