CHAPTER 4

ENTREPRENEURSHIP AND

GROWTH: WHAT CAUSES WHAT?

Sana El Harbi, Gilles Grolleau and Insaf Bekir

ABSTRACT

Purpose – The purpose of this chapter is to investigate empiricallywhether entrepreneurship causes growth or whether growth creates aprosper environment for entrepreneurship.

Design/methodology – We perform a co-integration analysis using anerror correction model on data from 34 countries spanning 13 years toassess the causality issue between growth (proxied by GDP per capita)and entrepreneurship (proxied by self-employment). Our analysis alsoincludes other variables deemed to influence growth.

Findings – The results from an error correction model show that self-employment Granger causes GDP per capita while the opposite directionis not statistically accepted. Moreover, these results suggest that increasesin self-employment increase GDP per capita over the short-term but leadsto a GDP per capita decrease at a long-term horizon.

Research limitations and implications – We use a linear model toestimate the relationship between self-employment and Growth. Conse-quently, a more complex model allowing for nonlinearities and additionalvariables might be more accurate. The empirical investigation is limited to

Entrepreneurship and Global Competitiveness in Regional Economies: Determinants

and Policy Implications

Advances in the Study of Entrepreneurship, Innovation and Economic Growth, Volume 22, 73–91

Copyright r 2011 by Emerald Group Publishing Limited

All rights of reproduction in any form reserved

ISSN: 1048-4736/doi:10.1108/S1048-4736(2011)0000022007

73

SANA EL HARBI ET AL.74

self-employment, which is one facet of entrepreneurship, hence it will beinteresting to introduce other measures of entrepreneurship. A directimplication of our study is that rather to be a sustainable economic driver,self-employment seems to resolve only a short-term problem.

Value – The chapter contributes by analyzing the relationship betweenself-employment and growth by using a co-integration analysis. Conse-quently it offers a more rigorous appreciation of the direction of causalityas well as the long- vs. short-term relationships.

Keywords: Co-integration; causality; economic growth;entrepreneurship

JEL classifications: E24; O40.

INTRODUCTION

Entrepreneurship is often perceived as a catch-all solution for economicdevelopment issues. Consequently, policymakers are frequently urged topromote entrepreneurship, especially by fostering a favorable institutionalcontext. For example, Holcombe (1998) asserts that ‘‘the engine of economicgrowth is entrepreneurship.’’ Nevertheless, despite a recent increase ofempirical studies investigating the relationship between entrepreneurship andeconomic development, the causality between entrepreneurship and growthremains a puzzling issue. Indeed, most existing empirical studies are devotedto test whether entrepreneurship has a positive impact on growth and ifso, how strong is it and whether the level of entrepreneurship depends on thelevel of economic growth for a recent literature review. Our main researchquestion relates to the causality direction between entrepreneurship andgrowth, which remains unclear. In other words, does entrepreneurship createwealth or does economic growth create a prosper entrepreneurship? Unlikemost previous studies we use dynamic panel data analysis rather than purelycross-sectional data to add rigorous empirical evidence regarding thecausality issue. Interestingly, we show that self-employment, export orienta-tion, and some institutional variables have a causal impact on GDP. We alsofind that self-employment rate actually increases per capita income in theshort run, but decreases it in the long run.

The remainder of this chapter is organized as follows. The next sectionintroduces briefly the entrepreneurship concept. The third section overviews

Entrepreneurship and Growth: What Causes What? 75

the relationship between entrepreneurship and growth in the economicliterature and develops the main hypotheses. Fourth section is devoted tothe empirical analysis. The last section concludes the chapter and gives somedirections for future research.

ENTREPRENEURSHIP: A CENTRAL BUT ELUSIVE

CONCEPT IN THE ECONOMIC LITERATURE

Entrepreneurship is a multidimensional and elusive concept (Verheul,Wennekers, Audretsch, & Thurik, 2002). Wennekers and Thurik (1999)mention 13 definitions of entrepreneurship. From Cantillon (1964[1755]) toBaumol (1996), the concept of entrepreneurship has been used with variousmeanings, which can be positioned on a continuum from a focus on the

Table 1. Some Key Definitions of ‘‘Entrepreneurship’’ in theEconomic Literature.

Authors Definition

Cantillon

(1964[1755])

‘‘The entrepreneur is specialist in taking on risk. He insures workers by

buying their products (or their labor services) for resale before

consumers have indicated how much they are willing to pay for them’’

Knight (1921) ‘‘Entrepreneurship is the characteristic phenomenon of modern economic

organization and is essentially the device for specializing uncertainty-

bearing or the improvement of the economic control’’

Schumpeter

(1934)

‘‘An entrepreneur is a person who is willing and able to convert a new idea

or invention into a successful innovation’’

McClelland

(1961)

‘‘An entrepreneur is someone who exercises control over production that

is not for his own personal production (y) the entrepreneur is primarily

motivated by an overwhelming need for achievement. He has a strong

‘urge to build’’’

Kirzner (1979) ‘‘The entrepreneur recognizes and acts upon market opportunities’’

Baumol (1993) ‘‘Entrepreneurs are always with us and always play a substantial role. But

there are a variety of roles among which the entrepreneur’s efforts can

be reallocated, and some of those roles do not follow the constructive

and innovative script that is conventionally attributed to that person.

Indeed, at times the entrepreneur may even lead a parasitical existence

that is actually damaging to the economy’’

Hisrich, Peters,

and Shepherd

(2010)

‘‘Entrepreneurship is the process of creating something new with value by

devoting the necessary time and effort, assuming the accompanying

financial, psychic, and social risks, and receiving the resulting rewards of

monetary and personal satisfaction and independence’’

SANA EL HARBI ET AL.76

individualistic characteristics of the entrepreneur to an emphasis on theinstitutional context.Without pretending to be the exhaustive, Table 1 providesthe main definitions of the entrepreneurship concept in a chronological order.Despite this variety in characterizing the entrepreneur, the lowest commondenominator could be to be self-employed. It is clear that self-employment canencompass more than ‘‘entrepreneurs’’ as they are defined in various theories.Without negating the limitations of using interchangeably these two terms, wewill do it in the following, for sake of exposition and empirical investigation.

THE RELATIONSHIP BETWEEN

ENTREPRENEURSHIP AND GROWTH

Growth1 and entrepreneurship are closely related. It seems intuitivelyconvincing that without entrepreneurs, there is no growth, leading someauthors to associate systematically entrepreneurship and growth (e.g.,Davidsson, Delmar, &Wikland, 2006). Nevertheless, such an affirmation doesnot explain how entrepreneurship leads to growth. Audretsch and Thurik(2004) analyzed the links between entrepreneurship and economic growth andstressed the crucial role of knowledge spillover (Romer, 1986) and competition.In short, individuals create new companies thus create jobs, promoteknowledge spillover and intensify competition which increases productivity,which in turn induces higher levels of economic wealth. The empirical studiesdealing with the assessment of the relationship between entrepreneurship andgrowth are quite rare and the results are mixed. For example, a strong positivecorrelation is found in Reynolds, Bygrave, Autio, Cox, and Hay (2000, 2002)and Reynolds, Camp, Bygrave, Autio, andHay (2001) found also a significantcorrelation between entrepreneurship and economic growth, which is positivefor developed countries but negative for developing countries. Blanchflower(2000) found that increases in self-employment increase the real growth rate.However, Blanchflower and Shadforth (2007) found no evidence that changesin self-employment are correlated with neither change in real GDP, nor innational happiness. When Acs (2006) regressed the opportunity-necessityentrepreneurship ratio2 and a country’s income using the GEM data, he foundthat they fitted a polynomial regression line. He then argued that a U-shapedrelationship may exist between entrepreneurial activity and economicdevelopment in the global economy.3 Table 2 summarizes the main findingsof the empirical literature related to the relationship between entrepreneurshipand growth.

Table 2. The Relationship between Self-Employment and Growth.

Authors The Studied Relation Main Findings

Reynolds et al.

(2000, 2002)

Self-employment/growth Positive

Van Stel, Carree,

and Thurik (2005)

Self-employment/growth Positive for developed

countries and negative for

developing countries

Blanchflower and

Shadforth (2007)

Self-employment/growth Not significant

Acs (2006) Opportunity-necessity

entrepreneurship ration/

growth

U-shaped relationship

Entrepreneurship and Growth: What Causes What? 77

EMPIRICAL STRATEGY

We study the relationship between self-employment (SE) and growth (grossdomestic product, GDP per capita) by using Granger methodology on paneldata. We use Granger Causality Tests from an Error Correction Model(Hamilton, 1994). When time series for the considered variables arenonstationary and are integrated of order one (i.e., the corresponding timeseries of first differences are stationary) and the variables are co-integrated,they admit the Granger representation. Our analysis also includes otherfactors deemed to influence growth, which are:

� The institutional context: As we are dealing with entrepreneurship, thefundamental, and relevant institutions are those which protect theeconomic freedoms of individuals. Tran, Grafton, and Kompas (2009)explain that by providing information, more secure property rights,stringent enforcement mechanisms, and guarantees that individuals’ gainswill not be stolen or expropriated, the institutional context will enhancethe economic-related outcomes. To capture this institutional context,we use Trade Freedom (TF), Financial Freedom (FF), and PropertyRights (PR).� The economy openness: Economists generally agree that economicprosperity is greatly enhanced through openness which intensifies thecompetitive pressure and allows access to larger markets.4 To capture thisvariable, we use export measured as a percentage of GDP (X).

SANA EL HARBI ET AL.78

Data Description

As stated before we consider self-employment as a measure of entrepreneur-ship in a given country.5 Self-employment is defined as the number of self-employed relative to the labor force. The self-employment rate has beenwidely used to compare entrepreneurship across countries (Blanchflower,2000, 2004; Le, 1999; OECD, 1998, 2000; Parker, 2004; Parker & Robson,2004). Noteworthy, the widespread use of the self-employment rate isprimarily due to the relative availability of this measure and to theconsistency of its definitions across countries. Indeed, self-employmentdatabase is available in The OECD Factbook 2009: Economic, Environmentaland Social Statistics. This database contains information on more than 80socioeconomic factors from 1980 to 2007 and encompasses data for all theOECD countries. Consequently, we included in our database 34 OECDcountries described in the OECD Factbook 2009 for a 12-year period (1996–2007). Although that the available data for the self-employment rate allowsto go back before 1996, the choice of this period is constrained by theavailability of other explanatory variables for the same period. In this study,we approximate economic growth through the per capita GDP.6 Thisvariable is available in several data sources. In this chapter, we consider theGDP per capita from the World Economic Outlook (WEO) database of themonetary fund. The definitions, sources, acronyms, and some descriptivestatistics (either for Raw and First-Differenced Variables) of otherexplanatory variables are indicated in Tables 3 and 4.

The Long-Run Relationship

The long-term equation can be expressed as follows:

GDPkt ¼ a0 þ a1SEkt þ a2Xkt þ a3FFkt þ a4TFkt þ a5PRkt þ ekt (1)

where GDP is the natural logarithm of per capita gross domestic productbased on purchasing-power-parity. SE is the self-employment rate, X theexport of goods and services, FF the financial freedom index, TF the tradefreedom index, PR the property rights index, and e the error term. The k andt subscripts correspond respectively to each country in the data set at a givenyear. Estimating Eq. (1) by using the panel data technique enables to obtaincoefficients for each exogenous variable useful to estimating the long runrelationship that run the six variables. Results of time-series/cross-sectional

Table 3. Description and Data Source for Variables.

Variable and

Acronym

Data Source General Description

GDP per capita

(GDP)

World Economic Outlook

(WEO) database of the

monetary fund

Gross domestic product based

on purchasing-power-parity

GDP per capita

Self-employment

rate (SE)

OECD Factbook 2009 The number of self-employed

relative to the labour force

Export (X) World development indicators

(World Bank)

Export of goods and services

(percent of GDP)

Trade freedom (TF) Heritage foundation the Wall

Street Journal

An indexed measure of a

country’s perceived level of

trade freedom measured

using a scale from 0 to 100

Financial freedom

(FF)

Heritage foundation the Wall

Street Journal

An indexed measure of a

country’s supposed level of

financial de freedom

measured using a scale from

0 to 100

Property rights (PR) Heritage foundation the Wall

Street Journal

An indexed measure of the

effectiveness of a country’s

system of property rights

measured by assigning to it a

scale from 0 to 100

Table 4. Descriptive Statistics for Raw and First-Differenced Variables.

Variable Mean Standard Deviation Minimum Maximum

Raw variable

Log of GDP per capita 9.87 0.63 7.42 11.28

Self-employment 74.26 329.50 2.1 2007

Export 43.00 26.55 7 173

Trade freedom 76.15 8.98 20 89.2

Financial freedom 65.69 17.94 30 90

Property rights 74.90 17.61 20 90

First difference of variable

Log of GDP per capita 0.053 0.034 �0.09 0.307

Self-employment �0.185 0.803 �3.59 5.1

Export 1.16 3.19 �10 16

Trade freedom 0.99 4.42 �17.8 23.4

Financial freedom 0.25 6.59 �40 20

Property rights �0.20 3.95 �20 20

Entrepreneurship and Growth: What Causes What? 79

Table 5. Co-integrating Equation Results, Dependent Variable: Log ofGDP Per Capita.

Independent Variable Coefficient-Value p-Value

Self-employment �.0194��� 0.000

Export .0140��� 0.000

Financial freedom .0053��� 0.000

Trade freedom .0138��� 0.000

Property rights �.0042��� 0.002

Sample size¼ 406

R2 within¼ 0.5970

R2 between¼ 0.0492

R overall¼ 0.0516

���Means statistically significant at the 99% confidence level.

SANA EL HARBI ET AL.80

regression analysis on the panel data using the basic co-integrating equationdepicting the natural logarithm of per capita GDP as the dependent variableare given in Table 5.

A close examination of these results provides some insights, which areconsistent with previous findings. First, among all the considered variables,export has the greatest impact on economic growth. In rough terms, asexport in a country increases, GDP per capita increases. Second, apart fromthe property rights index, institutional variables are positively correlatedwith economic growth. This means that, as economic freedom in a countryincreases, GDP per capita increases. Third, the self-employment coefficientfrom the regression in Table 5 is negative, but weak. This result is consistentwith previous researches which argue that ‘‘necessity’’ entrepreneurship isrelated to poverty and does not create wealth, whereas ‘‘opportunity’’entrepreneurship is associated with a long-term economic growth (Acs, 2006;Reynolds, Camp, Bygrave, Autio, & Hay, 2001; Thurik, Carree, Van Stel, &Audretsch, 2008). To go further, we will use co-integration techniques.Co-integration analysis developed in the mid-1980s introduced the idea thateven if underlying time series are nonstationary, linear combinations ofthese series might be stationary. After verifying that the series for ourconsidered variables are nonstationary and are integrated of order one (i.e.,the corresponding time series of first differences are stationary), we employthe Pedroni (1999) methodology to determine whether a co-integratingrelationship exists.

Entrepreneurship and Growth: What Causes What? 81

Tests for Unit Roots

A univariate analysis of each of the time series variables was undertaken toexamine for the presence of a unit root. The unit root test employed in thischapter is the Fisher test (Fisher, 1932). The Fisher test assumes that allseries are nonstationary under the null hypothesis against the alternativethat at least one series in the panel is stationary. Interestingly, the Fisher testdoes not require a balanced panel. In the Fischer test, Ho means that allpanels contain unit roots while H1 means that at least one panel isstationary. The results are displayed in Table 6.

The co-integration existence implies that the nondifferenced variablesshould be nonstationary (unit root) and error correction terms should revealstationarity. Nonstationarity is found in all six nondifferenced variables.Stationarity is revealed in the error correction terms for GDP per capita(EC-GDP per capita), self-employment (EC-self-employment) and financialfreedom (EC-financial freedom).

Table 6. Fisher Test for Unit Roots.

H0: Unit Root Variable Tested p-Value

Nondifferenced variables

DP per capita 1.00

Self-employment 0.17

Export 0.93

Financial freedom 0.99

Trade freedom 0.10

Property rights 1.00

Error correction terms

EC-GDP per capita 0.102

EC-self-employment 0.0164

EC-export 1

EC-financial freedom 0.0381

EC-trade freedom 1

EC-property rights 0.98

Notes: The first error correction term comes from the co-integrating equation in Table 5.

The other three error correction terms were calculated with the three respective independent

variables from Table 5 used as dependent variables and GDP per capita as an independent

variable.

SANA EL HARBI ET AL.82

The Error Correction Model (ECM) Analysis

The ECM can be expressed as follows:

DGDPkt¼b1þXh

a1kDGDPk;t�Lþg1LDSEk;t�Lþj1LDXk;t�Lþy1LDFFk;t�L

þs1LDTFk;t�Lþm1LDPRk;t�Lþl1DECk;t�1þ�1i

ð2Þ

Or equivalently as:

DSEk ¼ b2 þXh

a2LDGDPk;t�L þ g2LDSEk;t�1 þ j2LDXk;t�L þ y2LDFFk;t�L

þ s2LDTFk;t�L þ m2LDPRk;t�L þ l2DECk;t�1 þ �2i

ð3Þ

where e1 and e2 are pure white noise random disturbances anda1k; g1l ;j1l ;y1l ;s1l ;m1l and l1(respectively a2l ; g2l ;j2l ;y2l ;s2l ;m2l and l2) arethe parameters of the ECM. Note that DECk;t�1 which is called the errorcorrection term, is a measure of the extent by which the observed past valuesdeviate from the long run equilibrium relationship. The coefficientsl1 and l2 of the error correction term in the Eqs. (2) and (3) (whichmeasures the rate of this adjustment process) are therefore called theadjustment parameters. The parameters g1l ; and a2l in Eqs. (2) and(3) determine the nature of causality between GDP and SE. Morespecifically, if g1la0 and a2l ¼ 0 cannot be rejected then SE is said toGranger cause GDP. On the contrary, if g1l ¼ 0 and a2la0 cannot berejected then GDP is said to cause SE. In the case where g1la0 and a2la0cannot be rejected, the causality between the two variables is defined to bebi-directional. Finally when g1l ¼ 0 and a2l ¼ 0 cannot be rejected Grangercausality between GDP and SE is said to be absent. The absence of GrangerCausality for co-integrated variables requires the additional condition thatthe speed of adjustment coefficient be equal to zero. In this set up, statisticalsignificance of the estimated adjustment parameters l1 and l2 should helpqualify further the nature of causality relationship between GDP and SE.Before having performed regressions, we tested for the stationarity of ourvariables. We also run for each regression theHausman test (to select rigorouslyeither fixed or random effect) and the Breusch–Pagan test for heteroscedasticity.

Once the error correction term is obtained, an Akaike InformationCriteria (AIC) estimate is computed for increasing lag lengths. The laglength that corresponds to the minimized AIC estimate is considered to bethe correct lag length. AICs for various lag lengths were estimated from 1to 4. AIC was minimized at a lag length of 1 for each independent variable

Entrepreneurship and Growth: What Causes What? 83

tested. Once appropriate length is found, a final regression analysis is run,using Eq. (2).

The ECM for the other considered variables is as follows:

DXk ¼ b3 þXh

a3LDGDPk;t�L þ g3LDSEk;t�L þ j3LDXk;t�L þ y3LDFFk;t�L

þ s3LDTFk;t�L þ m3LDPRk;t�L þ l3DECk;t�1 þ �3i

ð4Þ

DFFk ¼ b4þXh

a4LDGDPk;t�Lþ g4LDSEk;t�Lþj4LDXk;t�Lþ y4LDFFk;t�L

þ s4LDTFk;t�Lþ m4LDPRk;t�Lþ l4DECk;t�1þ �4i

ð5Þ

DTFk¼b5þXh

a5LDGDPk;t�Lþg5LDSEk;t�Lþj5LDXk;t�Lþy5LDFFk;t�L

þs5LDTFk;t�Lþm5LDPRk;t�Lþl5DECk;t�1þ �5i

ð6Þ

DPRk ¼ b6þXh

a6LDGDPk;t�Lþ g6LDSEk;t�Lþj6LDXk;t�Lþ y6LDFFk;t�L

þ s6LDTFk;t�Lþ m6LDPRk;t�Lþ l6DECk;t�1þ �6i

ð7Þ

A significant li (i¼ 1, y, 6) means that past equilibrium errors impactcurrent results. Provided that li is statistically significant, Granger causality

Table 7. Error Correction Model Results.

From Equation 2: Dependent Variable¼DGDP Per Capita (Year t)

Independent Variable Coefficients p-Value

Error correction term 0.0066686��� 0.100

DGDP per capita (year t�1) 0.6810163��� 0.000

D Self-employment (year t�1) 0.0045513��� 0.012

D Export (year t�1) �0.0000289 0.952

D Financial freedom (year t�1) 0.0000429 0.857

D Trade freedom (year t�1) 0.0004214 0.214

D Property rights (year t�1) �0.0001296 0.739

Sample size¼ 334

R2 within¼ 0.2679

R2 between¼ 0.9278

R overall¼ 0.4427

��Statistically significant at the 95% confidence level (p-value).���Statistically significant at the 99% confidence level (p-value).

SANA EL HARBI ET AL.84

exists even if the coefficients of the lagged independent variables (SE, X, FF,TF, and PR) are not statistically significant (Abdulai & Jaquet, 2002).Table 7 shows the results of the analysis of the error correction term forGDP per capita (EC-GDP per capita). Results from the analysis of Eq. (2)shed light on the co-integrating relationship. The obtained results imply thatthe null hypothesis of co-integration was not rejected. SE and GDP areco-integrated. Moreover, the statistical significance of the self-employmentcoefficient suggests that changes in self-employment cause GDP per capitachanges. The coefficients of the lagged independent economic freedomvariables (financial freedom index coefficient, the trade freedom indexcoefficient, and the property rights index coefficient) are not statisticallysignificant. This suggests that changes in economic freedom will not causeover the short-term perceptible effects on wealth.

Table 8. Tests for Alternative Direction of Causality.

Equation

Dependent

Variable

Year¼ t

(3)

SE

(4)

X

(5)

FF

(6)

TF

(7)

PR

Error

correction

term

0.76���

(0.045)

2.758���

(0.087)

7.464���

(0.028)

17.382���

(0.000)

�4.891���

(0.013)

DGDP

year¼ t�1

�2.233

(0.145)

�21.547���

(0.001)

�25.575���

(0.050)

�3.507

(0.641)

8.776

(0.269)

DSEyear¼ t�1

�0.225

(0.702)

�0.079

(0.750)

�0.827

(0.111)

�0.376

(0.194)

�0.263

(0.388)

DXyear¼ t�1

�0.005

(0.713)

�0.114���

(0.053)

�0.281���

(0.022)

0.022

(0.739)

�0.102

(0.156)

DFFyear¼ t�1

0.009

(0.180)

�0.004

(0.866)

�0.138���

(0.022)

�0.079���

(0.019)

0.054

(0.123)

DTFyear¼ t�1

0.010

(0.268)

�0.044

(0.285)

0.081

(0.341)

�0.450���

(0.000)

0.087

(0.082)

DPRyear¼ t�1

0.005

(0.637)

�0.002

(0.964)

0.057

(0.560)

0.081

(0.140)

�0.043

(0.455)

Sample size 334 334 334 334 334

R2 within 0.0329 0.0495 0.0623 0.3711 0.0534

R2 between 0.0012 0.1139 0.0042 0.0352 0.1909

R overall 0.0028 0.0607 0.0198 0.0422 0.0000

Note: Number in parentheses ( ) denotes corresponding p-value.��� Statistically significant at the 99% confidence level (p-value).

Table 9. Results Summary.

Independent

Variable

Leading

Wealth

From Table 7 From Table 5

Statistical

significance

of EC term

EC model

regressed

coefficient

Statistical

significance

of EC model

regressed coefficient

Independent

variable

regressed

coefficient

Statistical

significance

of regressed

coefficient

Self-employment ��� 0.0045513 ����0.0194 ���

Financial

freedom

��� 0.0000429 0.0053 ���

Trade freedom ��� 0.0004214 0.0138 ���

Property rights ����0.0001296 �0.0042 ���

Export ����0.000289 0.0140 ���

Entrepreneurship and Growth: What Causes What? 85

Direction of Causality

We consider now the direction of causality between GDP per capita versusself-employment, economic freedoms, and export. Table 8 provides theresults of the error correction model from Eqs. (3)–(7) testing direction ofcausality in relation of GDP per capita.

To analyze the direction of causality between GDP per capita and theother five independent variables, Eqs. (3)–(7) should be examined. Note thatthe statistical significance of the EC term in all equations implies thatco-integration exists in each of these equations. However, we found that theGDP per capita coefficient is not statistically significant in Eqs. (3), (6), and(7) which leads us to conclude that GDP per capita does not Granger causeself-employment, trade freedom, and property rights. This is not the case forEqs. (4) and (5) where the GDP per capita coefficients are statisticallysignificant, leading to think that GDP per capita Granger causes financialfreedom and export. Given the fact that these coefficients are negative, itappears that an increase in GDP per capita causes, at short run, a decreasein the percentage of export in GDP and in financial freedom (Table 9summarizes the results).

CONCLUSION

The regression results from the error correction model show that an increase inthe self-employment rate might result in an actual short-term increase in GDPper capita.However, the results also indicate that, over the long term, this trend

SANA EL HARBI ET AL.86

reverses: self-employment rate is negatively related to GDP per capita over thelong term. This short-run/long-run discrepancy may help explain theinconclusive results concerning the relationship between GDP and entrepre-neurship found in previous studies (Acs, 2006; Blanchflower & Shadforth,2007; Reynolds et al., 2002). Our results also suggest that the self-employmentseems not to generate the expected results, which implies that the aforemen-tioned mechanisms do not operate as anticipated. In the long term, higher self-employment rates do not lead to the predictable increase in productivity andwealth as expected. Unlike numerous policy recommendations in favor of self-employment, our study sheds light on potential bottlenecks.

Self-employment seems then to resolve a short-term problem, a sort ofsoothing but our findings question whether it can constitute a sustainablegrowth driver. Our results are consistent with Acs’ (2006) proposition thatself-employment is associated with necessity entrepreneurship. Our resultssuggest that necessity entrepreneurship cannot be easily transformed inopportunity entrepreneurship. It seems that self-employment is related tounemployment rather than a long-term productivity and wealth-generatingprocess. One possible explanation for this result might be that self-employedpersons were constrained to create their enterprises in an unemploymentcontext, so they content themselves with the simple viability of theirenterprises without taking further risks to enhance their profitability.Consequently their attitude toward venture remains mainly passive. Thecomplex relationship between GDP per capita and self-employment isfurther illustrated when regressions are run with GDP per capita asindependent variable. Although co-integrated, the self-employment causesgrowth but growth does not cause self-employment.

Self-employment partly overlaps enterprise creation with an entrepre-neurial spirit. Indeed, self-employment can result from a continuum ofmotives from a survival strategy to a very entrepreneurial one. Hence, ourlong-term results may reflect the fact that the fraction of nonentrepreneurialself-employment is more important relatively to the fraction of reallyentrepreneurial one. This is especially plausible in light of the fact that thesolo-employed (or one-person businesses) who are generally pushed bylabor market deficiencies to entrepreneurship, are growing steadily. Dieterand Uwe (2009) report that in Germany for example, the steady rise in thenumbers of self-employed is due to the fact that more than 50% of all self-employed people in the period 1990–2005 belong to the category of solo-self-employment. Explicitly, the increase in the number of created firms mayintensify competition and increases productivity in the short term. However,if an important part of the created enterprises are not really entrepreneurial,

Entrepreneurship and Growth: What Causes What? 87

this increase in productivity is very likely to be not sustainable. Indeed, asnecessity entrepreneurs are deemed to (i) have limited skills so thatknowledge spillovers, the leverage of long-term growth, will simply notoccur and (ii) be conditioned by the logic of firm survival rather than firmexpansion, they are not in position to invest in innovative alternatives tocounteract the decreasing productivity. This necessity self-employed attitudeof not considering investing in innovative activities can also be explained inthe light of the prospect theory (Kahneman & Tversky, 1979) in that theseindividuals evaluate their current income relative to a given reference point,that is their salary when/if they were employees. Consequently, those whohave reached an income around this reference point can exhibit riskaversion, which prevents them to bear additional risk to expand theiractivities. In some cases, necessity entrepreneurship can evolve toopportunity entrepreneurship, but at the aggregate, this seems to not bethe case. In sum, we contend that these mechanisms contribute to explainthat in a long-term perspective, excessive self-employment rates induce anegative effect on wealth.

As in any other regression analysis, there is always the possibility thatthere are other variables not included in the model that influence both self-employment and GDP per capita. Consequently, a more complex modelallowing for nonlinearities and additional variables might shed further lighton the relationship between GDP and self-employment. Given that we usedself-employment in the Knightian sense (i.e., owning a business), a naturalextension is to check whether our results are robust to other measures ofentrepreneurship and development. Innovation is for example anotherdimension of entrepreneurship that is considered as crucial determinant ofcompetitiveness and national progress. Hence our results (especially thenegative long-term relationship) may change when considering this variableas reflecting the entrepreneurship activity.

In the same vein, we considered economic prosperity through the averageincome in a country. Even though it is a very important and commonmeasure,income is actually the outcome of a complicated social and psychologicalprocess. From this point of view, self-employment may not have the negativelong-term impact that we empirically found in that it may be perceived associally and individually desirable per se. Following this reasoning, it will beinteresting to test whether and in which directions self-employment impact jobsatisfaction and life satisfaction over different time horizons.

Because our study is at the aggregate level and because GDP per capita is apurely quantitative and mono-dimensional variable whereas growth(and development a fortiori) also entails social values, several aspects have

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eluded from our analysis. Arguably, even if self-employment increase impliesa decrease in growth at the long term, it may have other beneficial societaleffects. At the regional level, even not entrepreneurial, enterprise creationmay induce a regional dynamics especially in rural contexts. Self-employmentmay be beneficial to several dimensions of development conducive such aspreventing delinquency due to unemployment, facilitating the insertion ofmarginalized groups into the society and reducing poverty. From this point ofview self-employment may improve the levels of human development.

The findings of our study are also very relevant in the context of developingcountries. In these economies increasing revenue is essential for the ‘‘catching-up’’ goal.However, these nations often face endemic unemployment. In thewakeof economic liberalization, these countries may consider business creation as theonly way to fight unemployment, especially over a political time horizon. Byshowing that in the long run this strategy may deteriorate income per capita,developing countries may be cautioned to adjust their priorities. Balancinggrowth and self-employment emerges as a difficult long-term challenge. Last butnot the least, our empirical study shows that self-employment plays a positiveeffect in the short run and a negative one in the long run, but it does not explainthe underlying mechanisms. In short, we argue that to transform entrepreneur-ship into growth, policies promoting entrepreneurial activity should not inducethe unemployed into self-employment but rather focus on how to create afavorable environment where entrepreneurship is fully chosen and achieved.Rather than adopting a ‘‘one-size-fits-all’’ pro-entrepreneurship policy, policy-makers can target subgroups of the population who have the entrepreneurialspirit. So, more self-employment may not be better (Blanchflower, 2004), butimproving self-employment can be the key to economic growth.

NOTES

1. Although growth encompasses more than increase in economic wealth, theempirical nature of our contribution leads us to focus on the measurable increase ofgross domestic product per capita.2. Necessity entrepreneurship refers to the absence of employment option,

whereas opportunity entrepreneurship refers to the active choice to start anenterprise based on the detection of an opportunity and/or innovation.3. He explains ‘‘Countries likeUganda, Peru and Ecuador are all countries with high

levels of entrepreneurial activity but very low levels of per capita income. Countries withmuch lower levels of entrepreneurial activity (e.g., Brazil andArgentina) appear to havehigher levels of per capita income and aremoving toward lower levels of entrepreneurialactivity. The middle represents a set of countries that appear to be transitioning from amiddle-income level to a higher-income level and some have rising levels of

Entrepreneurship and Growth: What Causes What? 89

entrepreneurial activity. High-income countries, such as Germany, France, Belgium,Italy, andFinland, have relatively low levels of entrepreneurial activity. Two outliers areJapan, with one of the lowest levels of entrepreneurial activity, and the United States,with one of the highest levels of entrepreneurial activity.’’4. There are pioneering and influential papers that empirically found a negative

association between barriers to trade and economic growth: Dollar (1992, 2002),Ben-David (1993), Sachs and Warner (1995), Edwards (1998), and Frankel andRomer (1999). Furthermore, when developing economies are considered accordingto their degree of openness, countries such as Hong Kong, Malaysia, Singapore, andThailand are near the top of the list. These economies are roughly the same ones thatin the region’s so-called growth miracle.5. What dimension of entrepreneurship is self-employment actually measuring?

Self-employment rate is related to the Knightian approach of entrepreneurship butwithout being incompatible with the Kirznerian view. However, it is evident that theself-employment rate is far from being an indicator of Schumpterian entrepreneurship.6. Economic growth is not an obvious concept. It could consist of a higher living

standard, an increase in per capita income, a shift of the production possibilityfrontier, a capital accumulation. Some other definitions introduce even politicaldimensions such us personnel freedom and peace

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