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Procedia Economics and Finance 3 ( 2012 ) 193 – 198
2212-6716 © 2012 The Authors. Published by Elsevier Ltd.
Selection and peer review under responsibility of Emerging Markets Queries in Finance and Business local organization.
doi: 10.1016/S2212-5671(12)00139-6
Emerging Market Queries in Finance and Business
Entrepreneurship in international perspective
Dan
a,
*
a
Abstract
This paper analyses the entrepreneurial activity at international level, mainly in the European area, in the context of the
current international crisis. The research results are based on data and information collected from Eurostat and Global
Entrepreneurship Monitor data bases. In order to obtain available results, we have applied Principal Components Analysis
PCA, using SPSS software package. The results are showing countries with different economic development level are
distributed based on their entrepreneurial activity during the international crisis.
© 2012 Published by Elsevier Ltd. Selection and peer-review under responsibility of the Emerging
Markets Queries in Finance and Business local organization
Keywords: entrepreneurship, Principal Components Analysis, social-economic indicators,
1. Introduction
Entrepreneurship is considered one of the most important elements of nowadays development process. The
concept of entrepreneurship is well described in the literature - Cantillon, 1755; Marshall, 1890; Knight, 1921;
Shumpeter, 1934, 1949; Stevenson, 1985; Drucker, 1985; Reynolds, 1991;Scott, 1991, but also in the
documents of the international organizations. The current international context shows many changes in the
*Corresponding author. Tel.: +40265219034/309; fax: 0040265219034.
E-mail address: daniela.stefanescu@ea.upm.ro
Available online at www.sciencedirect.com
© 2012 The Authors. Published by Elsevier Ltd.
Selection and peer review under responsibility of Emerging Markets Queries in Finance and Business local organization.
194 Daniela Ştefănescu / Procedia Economics and Finance 3 ( 2012 ) 193 – 198
evolution of the European economies, thus, studying the entrepreneurial activities in correlations with other
social-economic indicators could be helpful in order to understand and to anticipate further evolutions.
2. Entrepreneurship
a complex concept
centuries, starting with
Richard Cantellion, 1755 considering entrepreneurship as self-employment of any sort involved in a process of
bearing the risk to organize factors of production to deliver a product or service demanded by the market,
continuing with Alfred Marshall, 1890 who defined entrepreneurship as an important factor of production
together with land, capital and labour, Knight, 1921 who underlined the risk-bearing dimension of
entrepreneurship. We can add as an important contribution to the development of entrepreneurial concept to
Say, 1803, Von Mises, 1949, Walras, 1954, Penrose, 1959.
Shumpeter, 1934 added a new dimension to the concept: the innovation, and as a result, the entrepreneur as
an innovator. Peter Druker, 1985 developed the innovation dimension of underlying the fact that an
entrepreneurship represents the exploitation of existing resources through the ability to produce something new.
Another significant definition belongs to the Commission of the European Communities, 2003:
entrepreneurship is the mindset and process to create and develop economic activity by blending risk-taking,
creativity and / or innovation with sound management, within a new or an existing organization.
We conclude this literature review with another important definition: entrepreneurship is a multifaceted and
heterogeneous activity - Audretsch and Thurik, 2001; Audretsch, 2002. Taking into consideration the wide and
complex content of the entrepreneurship concept, we identified numerous correlations with other economic
aspects. A relatively recent approach, entrepreneurship is studied along with sustainable development,
globalization, and economic growth.
In the literature related to the entrepreneurship there are insights regarding the way sustainable development
could be obtained, as it is explained by Knight, 1921, argued the entrepreneurial implications of sustainable
development - Matos and Hall, 2007.
3. Methodology
3.1. Research Goal
In order to analyze and identify the similarities and differences between European countries regarding
entrepreneurship and social economic development indicators we applied Principal Components Analysis PCA.
The basic principle of this method is to extract the smallest number of components to recover as much of the
total information contained in the original data, these new components expressing new attributes of individuals
and constructed so as to be uncorrelated with each other, each of these new variables is a linear combination of
original variables -Giannelloni, J. L., Vernette, E., 2001.
This method provides a graphical view of the countries distribution map of the study, according to the
similarities between them and the variables map according to their correlations. G. Saporta and M.V.
Stefanescu 1996 indicate two kinds of interpretations to be made in the case of PCA, the "internal"
interpretation namely the correlations between components and original variables represented by the circle of
correlations and the "external" interpretation between variables and additional individuals, the explanation of
the results being based on data that was used to obtain them.
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Daniela Ştefănescu / Procedia Economics and Finance 3 ( 2012 ) 193 – 198
3.2. Data collection
This research is based on the results obtained in a previous study which analyzed the correlations between
entrepreneurship indicators and sustainable development social economic indicators, during a period before the
international crisis. Data collected from Global Entrepreneurship Monitor GEM regards the main important
entrepreneurship indicators, respectively 4 rates Bosma N., Harding R 2007; Bosma N., Levie J. 2009: nascent
entrepreneurial activity nea, new business owner-manager nbom, early-stage entrepreneurial activity tea,
established business-owner managers ebom.
The European countries considered are those which are included in GEM data base. GEM divided the
analysed countries in three categories: factor-driven economies; efficiency-driven economies and innovation-
driven economies. The countries analysed in this study belong to the last two categories described above, as
follows:
innovation-driven economies: Belgium BL, Denmark DK, Germany GM, Iceland IC, Ireland IR, Greece
GR, Spain SP, France FR, Italy IT, Netherlands NE, Portugal PR, Slovenia SL, Finland FL, Sweden SW,
United Kingdom UK, Norway NW, Switzerland SD.
efficiency-driven economies: Latvia LV, Hungary HU, Romania RO, Croatia CR, Turkey TK.
The social economic indicators, used by Eurostat, and included in our research are as follows: real GDP per
capita, growth rate gdp_cap; investment by institutional sectors as percentage in GDP invest_s; net national
income as % of GDP nni; household saving rate % h_saving; total R&D expenditure percent of GDP r_d; real
effective exchange rate reer; energy intensity of the economy as Gross inland consumption of energy divided
by GDP kilogram of oil equivalent per 1000 Euro, eie; employment rate ert; employment rate, by highest level
of education attained, as % of age group 25-64 years er_ed; unemployment rate urt; unemployment rate, by age
group ur_age.
This study is based on 4 variables regarding entrepreneurship indicators and 11 variables related to social
economic indicators. The data collected characterized the European considered countries two crisis years: 2008
and 2009. Based on these data we are focus to analyze the situation of the Romanian economy compared with
all the others countries considered in this study.
Our hypothesis is that countries are distributed differently, depending on their economic development level,
and Romania is placed next to the countries which belong to the same category.
4. Results
On the data described above we have applied the method PCA, and we have obtained, for the analysed
period, four components, which explain 79.763% of the total variance. Before rotation, first component -CP1
explains 28.196% of variance, and the second component
CP2, 22.388% of variance. After rotation, there is
registered a redistribution of the total variance explained by each component, thereby the first component CP1
explains 25.789% of the total variance, the second component- CP2, explaining 22.388% from the total
variance, and the last two components explain less then 20% of total variance.
In table 1, it is presented the structure of the four components formed after the rotation process. CP1 is the
result of all 4 entrepreneurship indicators combination used in this study. Thus, we can consider CP1 as being
the entrepreneurial component. CP2 is based on all four social indicators, regarding employment and
unemployment rates, and only one economic indicator, respectively growth rate real of GDP per capita.
Based on its structure, we can consider component CP2, as social component, formed by the employment
and unemployment rates. The third component CP3 includes 3 indicators, all related to economic aspects, such
as; household saving rate, net national income as % of GDP and total R&D expenditure percent of GDP, thus
this component is considered as CP3
economic component.
196 Daniela Ştefănescu / Procedia Economics and Finance 3 ( 2012 ) 193 – 198
The last formed component, CP4, results as a combination of other three economic considered indicators. As
result, we can consider the last two components being economic components.
The strongest correlation was registered for the entrepreneurial component case.
The analysis contains also the countries distribution, obtained by taking into consideration the formed
components, but separated two by two. Being a period characterized by the crisis condition, we present the
combination between the entrepreneurial component and the social component. The countries distribution is
presented in the Fig. 1.
Table 1. Rotated Component Matrix 2008-2009
CP1
CP2
CP3
CP4
tea
0,98
0,03
-0,001
0,002
nbom
0,962
0,007
0,029
-0,028
nea
0,919
0,047
-0,009
0,011
ebom
0,916
-0,022
0,055
-0,052
urt
0,089
0,927
-0,001
0,087
ur_age
0,108
0,908
-0,036
0,141
er_ed
0,171
-0,757
0,215
-0,254
ert
0,148
-0,741
0,536
-0,018
gdp_cap
-0,095
-0,504
-0,204
0,277
h_saving
-0,098
0,224
0,833
0,225
net_inco
0,371
-0,143
0,786
0,057
r_d
-0,226
-0,267
0,707
-0,233
invest_s
-0,003
0,064
0,404
0,87
reer
0,017
0,05
-0,093
0,833
eie
-0,149
0,382
-0,53
0,601
Thus, based on the analysis of the graphical representation of the countries surveyed in bi-dimensional
space, it is shown in which quadrant a country is placed and also if it is close to other countries from the same
category.
In the first quadrant -Q1 +,+, mostly the ex-socialist countries are found, as follows: Croatia, Hungary,
Latvia, considered efficiency-driven economies. Despite the fact that Romania, other ex-socialist country,
belongs to the same category, it is not found in this quadrant.
In the second quadrant 2 -Q2 +,- are situated mainly countries from the north part of Europe, Norway,
Sweden, Netherland, United Kingdom, Ireland, Iceland, Finland, but also other innovation-driven economies:
Greece, Slovenia. The third quadrant -Q3 -,- , respectively the negative space created by the components CP1
and CP2 shows an atypical situation for Switzerland which is placed in this quadrant in 2008, but it moves in
the second quadrant in 2009, being placed at a significant distance from both components. In this quadrant we
identified also Sweden, Portugal, Denmark, and Germany. Romania is placed also in Q3 in 2008, being at equal
distance by the two components. The fourth Quadrant - Q4 -,+ includes a limited number of countries, most of
them being part of innovation-driven economies, such as: Belgium, France, Germany, Italy. For 2009, we can
notice the presence of two ex-socialist countries: Croatia and Romania.
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Daniela Ştefănescu / Procedia Economics and Finance 3 ( 2012 ) 193 – 198
Fig. 1. REGR factor for CP1- entrepreneurial component and CP2 social component
The same type of analyses could be considered further on, obtaining images of countries distribution based
on the components formed as result of applying PCA.
5. Conclusions
PCA method allows us to identify the combinations between entrepreneurship and social-economic
indicators at international level, in a very difficult period for national European economies. Based on the results
obtained, we noticed, on one hand, that entrepreneurial indicators formed a distinguished principal component,
none of the entrepreneurial indicator being combined with any other social-economic indicators considered. On
the other hand, the social indicators were grouped in the same category; meanwhile the economic indicators
were divided into two components. One of our expectations was to verify if several indicators from different
categories will be combined with entrepreneurial indicators, but in the analysed period this situation is not
presented.
Most of the countries are placed around the origin of the two axes defined by the components considered,
but in each quadrant we find several countries behaved in an atypical way, based on the influence of the
variables combination that formed the two components analysed.
Each combination of the components reveals the particularities of the considered country and also allows us
to identify the changes registered by each country in time.
Our hypothesis was partially confirmed by the results, meaning that most of the innovation-driven
economies are grouped together, meanwhile efficiency-driven economy are placed at some distance from the
first group of countries.
Countries with a lower level on entrepreneurial activity, from efficiency-driven economies category, such as
Hungary, Latvia, and Croatia are positively placed from entrepreneurial component CP1 in entire period
studied. The only one efficiency-driven economy which behaved substantial different is the Romania case.
Thus, in the analysed combination of the components, Romania is placed only in the quadrants Q3 or Q4,
aspect that shows a totally particular situation then all the others efficiency-driven economies, being negatively
correlated with entrepreneurial component.
A limit of this study is the large number of the principal components formed, thus in further studies is
necessary to reduce their number, by eliminating some of the social-economic indicators which registered a
198 Daniela Ştefănescu / Procedia Economics and Finance 3 ( 2012 ) 193 – 198
low level of correlation with the others indicators. Under these circumstances, the combinations will
concentrate better the information contained by the indicators considered separately.
Taking into account the continuous evolution of the international crisis, this type of studies should be
repeated in order to identify the new particularities, which could affect the countries with different economic
development level. In the same time is necessary to measure the correlation between the entrepreneurial and the
social-economic indicators.
Acknowledgements
Note: This work was supported by the project "Post-Doctoral Studies in Economics: training program for
elite researchers - SPODE" co-funded from the European Social Fund through the Development of Human
Resources Operational Programme 2007-2013, contract no. POSDRU/89/1.5/S/61755.
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