Student: Palamarciuc Roman

352351

Supervisor: C.A. Rietveld Msc

Erasmus University Rotterdam

Bachelor Thesis

What is the relationship between entrepreneurship, corruption

and institutions?

Table of Content

1.1 Introduction 3

2.1. Entrepreneurship 5

2.2 Revival of entrepreneurship 5

2.3 Impact on economic growth

6

2.4 Measuring entrepreneurship 7

2.5 Opportunity entrepreneurship 7

3.1 Corruption 9

3.2 Types of corruption 9

3.3 Causes of corruption 10

3.4 Consequences of corruption 10

3.5 Measuring corruption 11

4.1 Entrepreneurship and Corruption 14

4.2 Institutions and corruption 14

4.3 Institutions and entrepreneurship 15

5.1 Data and Methodology 18

6.1Methodology 20

7.1 Results 22

8.1 Conclusion 26

9.1 Limitations 26

1.1 Introduction

With the emergence of the entrepreneurial era smaller companies become more and more important.

Entrepreneurship has been recognized as one of the major drivers of economic growth (Baumol, 1990).

It has an effect on economic growth through different drivers like competition, job creation and

innovation. The significance of entrepreneurship has been recognized all around the world and has

become a primary focus for researchers and policy makers (Thurik, 2007). However, economic and

entrepreneurial activities are falling short of expectations in some developing countries that have all the

premises needed for steady growth (MUNEMO, 2011). This can be partially explained by the

disfunctionality of official institutions and inefficiency of resources used. Corruption is seen as one of the

main causes for these issues, which prevent countries from reaching efficiency and setting up a proper

institutional system. Corruption is a misuse of a certain power that one can use for private gains and

which leads to fewer infrastructures, to inefficiency, to disproportional flow of funds, to unfair

competition, to reduction in quality, to violation of democratic values, to depression of innovations and

eventually to a decrease in economic growth (Mo, 2001). Because entrepreneurship and corruptive

activity are both closely related to the economic development, there could be a link between the two.

Research has not yet explicitly examined this relationship and therefore this is the primary focus of my

thesis.

This thesis starts by separately evaluating both entrepreneurship and corruption in terms of

characteristics, causes and consequences. In the first section I discuss what productive entrepreneurship

is and describe how it shapes economic growth. In the second part, the origin of corruption is discussed

and how destructive corrupt activity is for the aggregate economic development. In the first two

sections I am looking for some links between entrepreneurship and corruption in order to answer the

main research question, namely “What is the relationship between entrepreneurship, corruption and

institutions?” Later in the paper I am eventually combining both concepts and putting emphasis on their

main intersection point - “Institutions”. Institutions turn out to be an important part in understanding

the relation between corruption and productive entrepreneurship. This fact leads to the idea that

corruption violates the quality of institutions and negatively affects productive entrepreneurship.

Eventually it is analyzed whether corruption ends up being in between institutions and productive

entrepreneurship.

Regression analysis is performed in order to find the association between Corruption and Productive

Entrepreneurship as well as Productive Entrepreneurship and Institutions. The Sobel Test is performed to

test whether Corruption mediates the relationship between Institutions and Productive

Entrepreneurship. The dataset is taken from Transparency International, Global Entrepreneurship

Monitor and World Bank data sources. Results of the empirical analysis make it possible to answer main

hypotheses, which aid to understand the relationship between corruption, entrepreneurship and

institutions in general.

The key contribution of my thesis is that it aims to find one more way of how corruption destructively

affects economic growth. And since entrepreneurship has become an inseparable part of economic

development, fighting against corruption could also stimulate economic growth through entrepreneurial

activity.

2.1. Entrepreneurship1

By looking at entrepreneurship from a historical point of view, one may conclude that it is a multiplex

phenomenon that has a fast progressing origin and comes from antiquity. Progression of market trade in

Ancient Greece, China and Rome became the primary cause for business activity in the domain of trade

and usury. During that time entrepreneurial activity was just about buying products and selling them

abroad with a premium (Demidova & Kolesnik, 2013). Today the definition of entrepreneurship includes

many different dimensions and concepts such as being a leader, owning a business or creating

innovations. To be an entrepreneur also includes to see and to use opportunities in order to drive the

market towards equilibrium or to affect the equilibrium through "creative destructions" (which means

to destroy the old one and to create the new one (Abernathy, 1985)). The definition of entrepreneurship

also includes starting a business in a team or on your own and as a result creating and capturing new

value (Gedeon, 2010).

2.2 Revival of entrepreneurship

By analysing the entrepreneurial era we can understand the reason why entrepreneurship currently gets

that much attention. A lot of effort was put by researchers in order to define the revival of

entrepreneurship, notably R. Thurik mentioned the transition from the so-called Managed Economy to

the Entrepreneurial Economy that took place couple of decades ago (Thurik, 2007). His work suggests

that the attention paid to big firms during the Managed Economy was replaced by the attention to

smaller firms during the Entrepreneurial Economy. In the time of Managed Economy, that was prevalent

two decades ago, growth occurred through stability, specialization, homogeneity, economies of scale,

certainty and predictability, while flexibility, turbulence, innovation, diversity and novelty are the main

drivers of growth in the Entrepreneurial Economy. This transition was strengthened by Technological

and ICT revolutions, which made it easier to reach customers in general and decreased transaction

costs. The recognition that entrepreneurial activity received from social media has also played a crucial

role in increasing individual awareness of self-employment. Individuals started to value self-employment

as an appreciative profession choice and a substitute for the well-established "job culture". Path

towards service economics with fewer barriers to entry and exit has also accelerated the revival of

entrepreneurship. Less spending are needed when entering the service market in comparison to the

1 Section 2.1, 2.2 and 2.3 are based on my earlier work for the course Seminar Entrepreneurship and Organization (2013-2014).

production of goods with high fixed costs. The emergence of entrepreneurship was defined by

combination of all the above-mentioned conditions.

The main role of entrepreneurship has substantially changed over the last years. Entrepreneurial activity

has become an important part in the organization of economies. The relevance of entrepreneurship has

increased and has been identified even on the governmental level. Policy makers and politicians have

put high emphasis on entrepreneurship as an economic driver. For instance policies of European

countries take into consideration that independence and creativity of entrepreneurs are essential in

order to increase the level of economic growth. The domain of scientific research has recognized the

importance of this topic and has significantly contributed to the study of entrepreneurship by evaluating

it in terms of its determinants and consequences (Thurik, 2007).

2.3 Impact on economic growth

Many researchers have studied the influence that entrepreneurial activity has on economic growth.

Adam Smith whose aim was to understand the process of wealth creation also evaluated it. One of his

treatises even began with the lesson that the division of labour has boundaries by the extent of the

market. A. Smith came to the conclusion that while markets grow and develop, entrepreneurship

stimulates innovative activity, which in turn leads to increased division of labour and increased

productivity (Baumol, 1996).

Certain favourable results have been reached with the emergence of entrepreneurial economics with

entrepreneurs as the key figures. These positive results can be branched into two different subgroups by

the intangibility and tangibility of their benefits (Acs, 1992). The first cluster of benefits can be

represented by indirect and direct effects of entrepreneurial activity on economic development. It was

investigated that entrepreneurship affects economic growth through various economic drivers such as

innovative activity, industry evolution and job creation. Innovations are transformed into new products

and new techniques which through an increase in efficiency help society to face global challenges.

Innovations also lead to evolution of industry due to innovative implementations which decrease

production costs and time and as a result lead to an increase in economic growth (Gerguri & Ramadani,

2010). A decrease in unemployment through job creation leads to more consumption what in fact

stimulates all other businesses in the certain location and positively affects the economic growth on the

aggregate level. The second cluster of benefits captures intangibles, namely the satisfaction of people

which is increased as a result of more autonomy in occupational choice. Because only an abstract

assessment of intangibles can be done, we are primarily focusing on the first cluster of benefits that

directly and indirectly affects economic growth.

A different way of how entrepreneurial activity affects economic development was suggested by Thurik

and Audretsch (Audretsch & Thurik, 2004). They state that economic growth is affected by the process

known as knowledge spillovers, where knowledge that is employed in a certain activity creates new

opportunities. In order to create new value these opportunities are commercialized and applied in other

different domains. Another way is through firms' diversity which influences the growth of the

geographic area by the exchange of complementary techniques and knowledge across different firms.

The last way is through an increase in rivalry which leads to idea creation and more efficiency.

2.4 Measuring entrepreneurship

There is much discussion on how to measure the aspects of entrepreneurial activity. One of the options

to measure entrepreneurial activity on a macro level is to use the variable called "self-employment

rate". Nevertheless, this particular proxy can have some lack of accuracy in case if I want to measure

entrepreneurship that affects economic growth. This is the case because most of the self-employed

possess nothing more than their human capital and are not necessary entrepreneurs that innovate or

create working spots. In this thesis I would like to focus on entrepreneurs who affect economic growth

through various economic drivers because that would make the research relevant. That is why it would

be better to find a different estimate for entrepreneurial activity. Another proxy for entrepreneurial

activity is the variable called "number of business establishments"; it is at least better because it can

capture the size of the firm. Entrepreneurs who affect economic growth through different drivers are

something more than just an owner of the fast food stand. This means that we have to be careful if we

want to choose a right proxy for entrepreneurs who capture important aspects that affect economic

growth (Glaeser, Rosenthal, & Strange, 2009).

2.5 Opportunity entrepreneurship

It is also essential to investigate the different types of entrepreneurship because different

entrepreneurial motives have different effect on economic growth. Many reasons exist for people who

open their own start-up; nevertheless, two main opposing motivations are “pull” versus “push”

(Verheul, Thurik, Hessels, & Zwan, 2010). Pull means positive motivation and push means negative,

whereas the distinction between the two originates from the origins of opportunity and necessity.

However, the definition of opportunity and necessity entrepreneurship is very broad, commonly, pull

motivation is related to opportunity and push motivation is related to necessity entrepreneurship.

Necessity entrepreneurship originates from the lack of employment opportunities, when there is no

option left other than to open your own business and try to somehow sustain yourself and your family.

On the other hand opportunity entrepreneurship originates from different existing economic

opportunities, which can be captured by entrepreneurs in order to create value.

Opportunity and necessity entrepreneurship differ not only in their origin; they also differ in results and

aggregate effects. Poh Kam Wong (2005) suggests that only opportunity entrepreneurship contributes

to economic growth. Because opportunity entrepreneurship attracts more skilled individuals and

exploits opportunities, it stimulates economic growth, employment and innovation (Wong, Ho, & Autio,

2005). It is intuitive because necessity entrepreneurship has a low growth potential, since the initial idea

of necessity start-up is to acquire a minimum wage rather than to expand.

Opportunity entrepreneurship can be measured as a share of total entrepreneurship, in this case it is

not important anymore which estimate to use (such as self-employment rate or business establishment

rate), because even if we take the share of all self-employed and manage to distinguish between

opportunity and necessity, it would be enough for satisfying the aim to concentrate on productive

entrepreneurs who affect economic growth.

3.1 Corruption

Unequal distribution of wealth, poverty and health are currently typical world problems. The economic

growth in some countries varies from very low to negative rates. Countries from Soviet bloc with highly

educated skilled labor as well as some countries with rich natural resources have relatively low growth

trends. This means that countries that fulfil the requirements for steady economic growth sometimes

lag behind their potential. This paradox can be explained by the disfunctionality of private and public

institutions. Poor performances of certain countries that have a high economic potential are caused by

the inefficiency with which resources are used (Rose-Ackerman, 1999). Corruption was always and

continues to be a problem that prevents countries from developing a proper institutional system with

corresponding high efficiency. According to the World Bank, around one trillion dollars per year are

given as bribes. As a result, corruption gained much attention and became the reason for the adaptation

of the United Nations Convention against Corruption in December 2003(Goel & Nelson, 2010).

According to the website oriented on corruption issues, the basic definition of corruption is: “Corruption

is the misuse of public power (by elected politician or appointed civil servant) for private gain.”

Nevertheless, emphasis of this paper is rather put on the lower level officials than politicians and is

subject to an alternative definition: “Corruption is the misuse of entrusted power (by heritage,

education, marriage, election, appointment or whatever else) for private gain.” (Hulten, 2012). On the

base of these definitions we can conclude that corruption has the same origin independently of the

dimension where it occurs. It is generally a misuse of certain power that someone can use for private

gains on every official level possible.

3.2 Types of corruption

We can distinguish three types of corruption: petty corruption, grand corruption and looting (Ngunjiri,

2010). Petty corruption is the subject of insignificant sums of money or presents for individuals holding

minor official positions. An example of petty corruption would be bribing a police officer to neglect an

expired car registration. Grand corruption involves higher level officials such as government and high

rank businessmen. This type of corruption has more significant aims of and causes for bribery and as a

result cash amounts that are paid are much higher. Examples of grand corruption are kick-backs, which

are certain cash compensations paid to the choosing party for signing public work contacts. The looting

type of corruption is the most destructive one and is described as a large-scale economic crime. Looting

is very typical for third world countries with relatively weak governmental institutions. This type of

corruption involves huge frauds that affect macroeconomic aspects very quickly and as a result can

cause inflation to raise, banks to go bankrupt and currency to depreciate (Ngunjiri, 2010).

3.3 Causes of corruption

It is not enough known what causes the level of corruption to be higher in one country than another.

From the theoretical point of view corruption brings a lot of benefits to individuals that are involved in

it, while the main cost is the probability of getting caught and punished. This means that the risk of

corruption in different countries varies according to existing legal systems and the importance of law in

social norms. So theoretically speaking if punishment for corruption has severe consequences, like

getting into jail or high penalties, bribery is less likely to occur. Nevertheless, if in social norms

corruption is a common practice, then even high official penalties cannot prevent it since everyone can

get bribed in order to avoid punishment (Treisman, 2000).

The World Bank suggests that there are four different causes of corruption. First of all it is a clear

opportunity to receive a bribe for something you are responsible for. This means that only people that

hold certain positions that are a subject to bribery can be involved in the corruption process; contrary to

a hotdog seller who would never receive a bribe because there will not be any incentive for that to

happen. The second cause is the low chance of bribery disclosure which occurs as a result of low

accountability and transparency. The third cause is insecurity induced by the high probability of losing

your job soon or simply not earning enough to sustain yourself. Finally, the last cause is the average

perception of the law or circumstances that make people disrespect the law. Low level of law credibility

can occur only due to historical reasons and is very hard to boost up back (Causes of Corruption,World

Bank).

3.4 Consequences of corruption

From the theoretical point of view there is no common opinion regarding the consequences of

corruption. Some researchers say that corruption can be beneficial because it helps to overcome certain

bureaucratic procedures and inefficient regulations. However, most of the empirical researches show

different results and prove that corruption is indeed destructive for the economy. Pak Hung Mo in his

paper “Corruption and Economic growth” concludes that a 1 % increase in the level of corruption

decreases the level of economic growth by 0.72 % (Mo, 2001). Other findings show that corruption that

comes from government official’s purchases negatively affects economic growth opportunities in the

long run. This is the case because governments cannot offer enough inputs to private economic activities

as a result of that. With the existence of corrupt transactions, certain resources are the matter of waste,

which leads to inefficiency and as a result to fewer infrastructures (Monte & Papagni, 2001).

Corruption leads not only to inefficiency in general, it also leads to inefficient allocation of expenditures.

Evidences show that corruption reduces expenditures allocated to higher education, corrections and

public welfare and increases spending on health and hospital, community development, natural

resources and housing. It is also shown that inefficiency is caused by a disproportional flow of funds to

regions with better governmental institutions (Cordis, 2014).

Different views suggest that corruption has other destructive consequences like promoting inequality

within companies, which leads to unfair competition and reduction in the quality of goods. Political

corruption leads to the loss of credibility of government and violates equality and democratic values. It

also benefits bad government by strengthening it through undermining the rule of law by low

transparency and accountability. Corruption affects the social sector of a country by negatively

impacting productivity, labour, income, poverty reduction, innovations and life quality. Eventually,

corruption violates the functioning of institutions that are essential for government improvements;

nevertheless we will talk about it in more detail in the next section (Nazmi, 2009).

3.5 Measuring corruption

It is relevant to mention that an internationally accepted meaning of corruption does not yet exist. This

particular issue has a direct effect on corruption rankings across the globe. Because corruption has

different sides and natures, it is very hard to find a good proxy in order to measure it. Data itself is very

hard to acquire because of the unofficial origin of corruption, while a universal system that measures

corruption level is not invented yet. It is therefore concluded that all existing proxies for corruption are

imperfect in their origin (Rohwer, 2009).

Nevertheless, there are three accepted indicators of corrupt activity: Perception – based indicators;

Indicators based on a single data source and Proxy indicators. The perception-based indicator is based

on the perception of people in a certain country. This indicator also takes into account actual bribes

offers to firms and individuals. The second indicator which is based on a single data source is the most

popular indicator to measure corruption. It is produced by certain organizations on the base of a third

party’s data that is analysed by them. The last indicator, which is the proxy indicator, measures the

corruption level in an indirect way by evaluating as many signals of corruption as possible. Sometimes

this indicator measures the opposite, namely transparency, of institutions and good government in

order to derive the actual level of corruption (Rohwer, 2009).

There is no agreement which particular indicator is the most useful because all of them are biased

towards certain dimension of corruption. Nevertheless, I already lean towards a perception based

indicator because of its availability and the important aspects that it captures.

4.1 Entrepreneurship and Corruption

The literature suggests that the pursuit of entrepreneurial opportunities depend on the proportion of

the created value that entrepreneurs are able to capture, meaning that the more they can capture the

more they can reinvest in the company growth. However, in the case of corruption, entrepreneurs face

uncertainty from those engaged in their value chain. In addition, with the improper enforcement of law,

it becomes risky to rely on official contracts. Because of that, individuals who have capabilities and

willingness to become entrepreneurs may value these opportunity costs in favor of another less risky

option such as wage-work (Anokhin & Schulze, 2009).

Corruption also creates certain constrains for innovation and investment activity. It happens due to the

imperfection of financial markets, the selection of less efficient projects by bribed officials and

intentional delays (Prashanth, 2008). As a result of these issues, increasing transaction costs limit the

scope and scale of trade and thus impede productivity (Anokhin & Schulze, 2009). As innovations and

investments are inseparable parts of entrepreneurship, these corollaries may play a destructive role for

entrepreneurship and everything that it later affects (for example economic growth).

4.2 Institutions and corruption

One of the intersection points of corruption and entrepreneurship are legal institutions. Formal

institutions are the regularities that shape the life of individuals. They are a formally accepted set of

regularities and certain rules that are implemented to define the legal set-up of a specific county.

Generally speaking, the literature is scarce on the investigation of corruption and institutions.

Nevertheless, some recent studies have evaluated the effect of formal institutional constraints on

corruption while other studies focused on the relation between transaction costs and the enforcement

of deals that involve bribery (Tonoyan, Strohmeyer, Habib, & Perlitz, 2010). The overall results of such

investigations have shown that the initial quality of institutions is important for determining corruption,

and that better quality of formal institutions reduces the level of corrupt activities. However, other

findings show that the relation between legal institutions and corruption is ambiguous (Dreher,

Kotsogiannis, & McCorriston, 2009). We can therefore conclude that the high quality of institutions is an

effective tool for fighting against corruption; nevertheless it is still hard to understand the relationship

between both.

Other findings show that a well-organized market system with transparent laws and rules, a properly

functioning accountability system and a fair environment for rivalry reduces the incentives for corrupt

activities. They also suggest that without a transparent financial system, barriers to entry and exit have

increased intensity for the real sector, what eventually increases incentives for bribery. It is therefore

concluded that corruption violates the functioning of legal institutions and in order to reduce incentives

for illegal actions, policy makers have to create effective reforms that encourage the proper functioning

of legal institutions (Broadman & Recanatini, 2011). This again supports the idea that the quality of

institutions has to be boosted up in order to decrease corruption. By combining the above stated view

with the information from the previous section, (namely, “Eventually corruption violates institutions

that are essential for government improvements; (Nazmi, 2009)”), the idea was established that

corruption violates the quality of legal institutions and therefore can be eradicated by increasing that

quality. This implies that there could be double way causality, meaning that the higher quality of

institutions negatively affects the level of corruption, whereas the higher level of corruption negatively

affects the quality of institutions.

4.3 Institutions and entrepreneurship

The literature on entrepreneurship and institutions is scarce as well, due to the complexity of their

relationship. According to Parker (2009), it is found that protected property rights make

entrepreneurship in general more attractive and as a result foster innovations. Abiding the legal system

encourages planning, co-ordination and acquisition of resources. In some countries there are no

institutions that are responsible for supervising free rivalry and maintaining property rights which can

guarantee just resolution of official disputes. In this case, entrepreneurs who eventually decide to take

risk might redirect their entrepreneurial spirit and effort to rent seeking activities. By doing that,

entrepreneurs can obtain private benefits at the expense of other individuals and will eventually affect

the overall social prosperity (Parker, 2009).

By evaluating Baumol’s (1990) research, it is found that the quality of institutions is strongly correlated

with the overall entrepreneurial productivity and it supports the idea that the quality of institutions

contributes to income and wealth through productive entrepreneurship. According to Baumol (1990), in

order for the state to grow richer, more productive rather than unproductive entrepreneurship is

needed for the economy. In this case we can make a parallel between productive and opportunity

entrepreneurship because they have similar characteristics. A way to promote productive

entrepreneurship is to improve the framework and quality of institutions (Sobel, 2008).

One more important finding suggests that because of the violated institutional system, growth

aspirations of entrepreneurs are constrained due a to low level of power of the law. And as a result it

becomes a threatening factor for becoming an entrepreneur (Estrin, Korosteleva, & Mickiewicz, 2013).

We can clearly see that institutions play an important role in shaping both corruption and

entrepreneurship. However, the relation between corruption and institutions and entrepreneurship and

institutions is very complex. In spite of the fact that there is some evidence that entrepreneurship can

affect institutions in certain cases, it is generally the other way around. Institutions create the

environment for entrepreneurs and shape the rules of the game, whereas entrepreneurs adapt to these

rules and can slightly affect them back. In turn, corruption is not one of the rules set by institutions; it is

rather a self-appearing phenomenon that represents social perceptions of the law and eventually

violates the initial functioning and legitimacy of already existing institutions. Thus, corruption appears to

be in the middle of the relationship between Institutions and Entrepreneurship. On the base of these

conclusions we came up with three hypotheses:

H1:“There is a negative association between the level of corruption and productive entrepreneurial

activity”

H2: “There is a positive association between the quality of institutions and productive entrepreneurial activity”

As we have concluded, corruption violates the functioning of institutions while low quality of institutions

has a negative effect on entrepreneurship. This means that in the relationship between Institutions and

Entrepreneurship, Corruption appears to be in-between. Therefore the third hypothesis looks as follows:

H3:“Corruption mediates the relation between Institutions and entrepreneurship”

These three hypotheses will help us in answering the main question of our research, namely: “What is

the relationship between corruption and entrepreneurship?”

The first hypothesis will contribute to the understanding of the overall relation between both, while the

second and third hypotheses will provide knowledge about their intersection point.

5.1 Data and Methodology

In this section I describe the data that is used in the research as well as the implemented methods. The

data consists of 68 countries from all around the world and tracks information from 2008 until 2013,

giving us a sample that consists of 402 observations. Our dataset is acquired from multiple sources like

the Global Entrepreneurship Monitor, World Bank and Transparency International. Regression analysis

and the Sobel Test are used in order to process all the data available. We will start from introducing all

the dependent and independent variables used in our models.

Opportunity entrepreneurship

As our dependent variable it was decided to take opportunity entrepreneurship as a share of total early

stage entrepreneurial activity (TEA). Our dependent variable opportunity entrepreneurship is the share

of the population between 18-64 involved in TEA, who stated that their incentives to become an

entrepreneur are driven by opportunity reasons and they made this choice to increase their income or

to become more independent. This is opposed to necessity entrepreneurship where the main incentive

is no other work option. Entrepreneurship data is taken from the Global Entrepreneurship Monitor

database from 2008 until 2013 (http:www.gemconsortium.org).

Corruption

Our main independent variable and a proxy for corruption is the Corruption Perception Index. I chose

this variable because of its broad availability and because it captures corruption in the public sector

rather than in private or political. CPI ranks different countries according to their perceived corruption

level in the public sector. The index has a composite origin; it is a mix of assessments and surveys

acquired by many respectable institutions on corruption activity. The CPI index ranges from 100 when

there are no corruption issues to 0 when corruption is at a disastrous level. Corruption data is taken

from Transparency International from 2008 until 2013(http:www.transparency.org).

Institutions

As an indicator for institutions I was decided take the variable Rule of Law. This indicator shows

perceptions of people regarding the confidence of social rules, namely property rights, police, courts,

contract enforcement and the risk of violence or crime. The Rule of Law estimate ranges from -2.5 when

the perception is low to 2.5 when the perception is high. This data was acquired from the World Bank

database from 2008 until 2013(http:www.worldbank.org).

Another proxy for institutions is the variable Regulatory Quality. This indicator reflects how the

government is able to formulate proper policies in order to promote development of the private sector.

The Regulatory Quality estimate ranges from -2.5 when the perception is low to 2.5 when the

perception is high. These data were acquired from the World Bank database from 2008 until 2013.

(http:www.worldbank.org)

6.1Methodology

In order to check the relationship between Entrepreneurship and Corruption it was decided to construct

four regression models. Our variables consist of the data from 2008 to 2013 and this gives us an

increased number of observations. A bigger sample is always preferred because it leads to more

accurate results due to smaller standard errors. Because of that five dummy variables are created, each

taking the value 1 for the corresponding years 2013, 2012,2011,2010,2009 and 0 otherwise.

Our regression models are looking as follows:

M1: Opp .entrep=c+βCPI+D2013+D 2012+D 2011+D 2010+D2009+¿

(M1: is the main model that evaluates the relationship between corruption and entrepreneurship)

M2: Opp .en trep=c+γLaw+D2013+D 2012+D2011+D2010+D 2009+¿

M3:Opp .entrep=c+αReg+D 2013+D 2012+D2011+D2010+D 2009+¿

(M2 and M3: are used in order to check the relationship between our proxies for institutions and

entrepreneurship)

M4: Opp .entrep=c+βCPI+γLaw+D 2013+D 2012+D 2011+D 2010+D2009+¿

M5: Opp .entrep=c+βCPI+γReg+D 2013+D 2012+D 2011+D 2010+D2009+¿

(M4 and M5: is used to check whether variable Law becomes insignificant when we add CPI, this is done

in order to check if the mediation effect is the subject to occur)

Where Opp.entrep stands for the Opportunity entrepreneurship, CPI for the corruption perception

index, Law for the Rule of Law, Reg for the Regulatory Quality and D2009-2013 for the dummy variables

A significant positive coefficient for CPI (higher CPI stands for Lower level of corruption) in our regression

model would be in line with our first hypothesis, while a significant positive coefficient of Law and Reg

would be in in line with our second hypothesis.

In order to test the mediator effect, the Sobel Test is used. In the relation between the dependent and

independent variable, a mediation effect is an indirect effect of a third variable. When the mediator

variable is included in the model, the effect and significance of the initial independent variable goes

down whereas the mediator variable is still significant. The Sobel Test that is used is a specialized T-test

that helps to determine whether the effect of the mediator variable is statistically significant or not. In

this case, the variable Rule of Law is taken as the only proxy for institutions as it is argued to be the best

indicator for institutions (Hartog, Stel, & Storey, 2010).

In order to measure the mediation effect three separate regression models are used where

Entrepreneurship is a dependent, Institutions an independent and Corruption a mediator variable. This

particular test will help us to answer the third hypothesis of our research.

7.1 Results

In this section we are presenting and discussing all the results that we got from our empirical research.

Table 1. Countries used

Algeria Ecuador Israel Netherlands Slovenia VietnamAngola Estonia Italy Nigeria South Africa ZambiaArgentina Finland Jamaica Norway Spain Belgium France Japan Panama Suriname Bosnia and Herzegovina Germany Korea (South) Peru Sweden Botswana Ghana Latvia Philippines Switzerland Brazil Greece Libya Poland Taiwan Canada Guatemala Lithuania Portugal Thailand Chile Hungary Luxembourg Puerto Rico Trinidad and Tobago China India Macedonia Romania Uganda Colombia Indonesia Malawi Russia United Kingdom Croatia Iran Malaysia Singapore United States Czech Republic Ireland Mexico Slovakia Uruguay

Table 2. Descriptive Statistics

CPI OPP Law RegN Valid 400 290 402 402

Missing 2 112 0 0

Mean 50.4375 46.8034 .3593 .4773

Std. Deviation 20.94464 13.22258 .96440 .94511

Minimum 15.00 7.00 -1.40 -2.53

Maximum 94.00 76.00 1.98 1.96

Table 3. Regression statistics

Model 1 Model 2 Model 3 Model 4 Model 5 Constant 31.57*** 46.01*** 45.84*** 32.87*** 29.078*** CPI 0.32*** - - 0.294*** 0.251*** Reg - - 4.974*** - 0.457 Law - 6.331*** - 0.698 - D2013 -1.05 -1.001 -0.826 -1.043 -1.021 D2012 -1.449 -1.368 -1.061 -1.447 -1.321 D2011 -2.041 -2.678 -2.295 -2.117 -1.912 D2010 -4.700* -5.191** -5.098* -4.749* -3.981* D2009 -0.769 -1.073 -1.031 -0.797 -0.698 N 290 290 290 290 290 N-countries 67 67 67 67 67 R-Square 0.266 0.231 0.141 0.266 0.231 Adj-Rsq 0.25 0.215 0.122 0.248 0.210 Significant at 10% level* Significant at 5% level ** Significant at 1% level ***

Table 1 represents all (67) countries used in the empirical research while Table 2 summaries descriptive

statistics of variables taken. From the Table 1 it can be seen that our sample takes countries from

different continents and with different economic development stages. Table 2 shows that some

observations are missing which is a subject to certain limitations. Table 3 contains the main part of our

research and is a subject to more detailed evaluation.

First of all we are evaluating the Model 1, which tracks the relationship between CPI and Opportunity

Entrepreneurship, in order to answer our 1st hypothesis:

H1:“There is a negative association between the level of corruption and productive entrepreneurial

activity”

Results of the Model 1 show that a 1 unit increase in the CPI index (decrease in corruption) leads to a

0.32 percentage point increase in the share of Opportunity Entrepreneurship. As a higher CPI score

stands for a lower level of corruption, we can conclude that there is indeed a negative relationship

between corruption and productive entrepreneurship. When the CPI index goes down (increase in the

corruption level,) the share of productive entrepreneurship decreases. Therefore our first hypothesis

gets its empirical support.

Other results show that when the separate effect of institutions on productive entrepreneurship is

measured in “Model 2” and “Model 3”, both proxies for institutions show that better institutional

quality is positively correlated with opportunity entrepreneurship and that the effect is statistically

significant. These results support our second hypothesis:

H2: “There is a positive association between the quality of institutions and productive entrepreneurial activity”.

In order to test our third hypothesis, it was decided to use the Sobel Test. After performing it, we got the

following results:

Table 4. Results of the Sobel Test

Variables Direct and total effects Coeff. S.E T Sig(two)

Y = Law b(YX) 0,0117 0,0019 6,0226 0,00X = Opp b(MX) 0,2975 0,0419 7,0965 0,00M = CPI b(YM.X) 0,042 0,001 43,11 0,00 b(YX.M) -0,0008 -0,0009 -0,9327 0,35Sample: 402

Sobel test: Indirect effect and its significance

Value S.E Z Sig(two) Effect: 0,0125 0,0018 7,0005 0,00

The idea of the Sobel Test is to find out whether the relationship between Institutions and

Entrepreneurship disappears when we add corruption to our model. Generally speaking, mediation is

said to occur 1) when our variable Law significantly affects the mediator CPI, 2) when Law significantly

affects Opp.entrepin the absence of the mediator CPI, 3) the mediator CPI has a unique significant effect

on Opp.entrep, 4) and the effect of Law on Opp.entrep shrinks when adding the mediator CPI to the

model.

We can see that the P-value of the statistical test is equal to 0.00, meaning that it is statistically

significant. This implies that all the above mentioned cases are satisfied: 1) Law significantly affects CPI;

2) Law significantly affect Opp.entrep in the absence of the mediator; 3) CPI has a significant unique

effect on Opp.entrepand 4) the effect of Law on Opp.entrep disappears when CPI is added.

Therefore we can conclude that the relationship between Institutions and Entrepreneurship is indeed

mediated by Corruption. This supports our third hypothesis: H3:“Corruption mediates the relation

between institutions and entrepreneurship”.

8.1 Conclusion

This paper has examined the relationship between Corruption, Entrepreneurship and Institutions. We

used the variable Rule of Law as a proxy for Institutions, Opportunity Entrepreneurship as a proxy for

productive entrepreneurship and Corruption Perception Index (CPI) as a proxy for Corruption. In order to

empirically investigate the relation between the variables we used regression analysis and the Sobel

Test.

Two conclusions emerge from our results. The first conclusion is related to the finding that there is a

negative relationship between corruption and productive entrepreneurship. This means that when the

corruption level increases, the share of productive entrepreneurship goes down. By taking into account

the information from section 4.1 regarding the causality, we can conclude that Corruption has a

negative impact on Productive Entrepreneurship which is a driver of economic growth. This conclusion

can be beneficial for organizations fighting against corruption, because entrepreneurial activity can be

added to the group of economical drivers constrained by corruption. It is also beneficial for policy

makers who focus on promoting entrepreneurship, since one way to increase entrepreneurial activity is

to lower the existing corruption level.

The second conclusion is based on the findings that there is a positive relation between institutions and

productive entrepreneurship and that corruption mediates this relationship. It is therefore concluded

that better quality of institutions has a positive effect on productive entrepreneurship. In turn,

corruption violates the quality of institutions and tends to decrease the level of productive

entrepreneurship. This information is beneficial since it suggests a way to increase productive

entrepreneurship through an increase in the quality of institutions, because an increase in the quality of

institutions helps to eradicate corruption. It can be used by policy makers as a tool against corruption or

as a tool to increase productive entrepreneurship.

9.1 Limitations

Due to certain limitations this topic is a subject for further research. In this section some room for

improvements are listed in order to enhance future investigations. The first limitation of the research is

the fact that standard errors were not clustered by country, what could lead to incorrect inference in a

sample. The second limitation is that our data is scarce in terms of countries and years, since it tracks

information of 67 countries from 2008 until 2013. The third limitation is that we do not control for the

country differences like GDP, so our model can potentially lack more variables. Our proxies are an

additional limitation, since it is very hard to find the best estimate and measure of entrepreneurship,

corruption and institutions. Eventually, another limitation is that we take opportunity entrepreneurship

as a share of total entrepreneurial activity, meaning that we do not take prevalence into account.

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