Drivers of entrepreneurship: linking with economic growth and employment generation (a panel data analysis).
Rasool, Farhat ; Gulzar, Ahmed ; Naseer, Shaheen 等
1. INTRODUCTION
The need for entrepreneurs for economic development has always been
crucial in history because they are the leaders who invent innovative
ideas that give spark to economic activities. They are responsible for
the combination of factors of production by capital formation, creating
employment opportunities, wealth distribution that facilitates
development and growth. A well explained definition of entrepreneurship
in the words of Wennekers and Thurik (1999) that successfully makes the
functional roles of entrepreneurs is:
"... the manifest ability and willingness of individuals, on their
own, in teams within and outside existing organisations, to
perceive and create new economic opportunities (new products, new
production methods, new organisational schemes and new
product-market combinations) and to introduce their ideas in the
market, in the face of uncertainty and other obstacles, by making
decisions on location, form and the use of resources and
institutions." (46-47)
High and sustained economic growth is the fundamental objective of
every developed or developing country's governmental policy.
Economic growth is a long term expansion of the productive potential of
the economy. It generates employment in the economy and raises the
living standards of the nation. Economic growth promotes business
activities in private sector, increases company profits and enhances
investor confidence.
Growth process, in general, of the country is profoundly influenced
by entrepreneurial activities at different levels. Entrepreneurship is a
key determinant of sustainable growth in modern time. Mostly jobs are
produced by small businesses started by entrepreneurial mind persons,
many of them set up large companies. Entrepreneurship is frequently
expressed in terms of higher self esteem, to exercise creative freedoms,
and an overall greater sense of control over their own lives. Many
economists and educators believe that these types of experienced
entrepreneurs foster the robust entrepreneurial culture that exploit
personal and communal economic and social success at sub-national,
national, and international level.
Education starting from elementary school to degree programmes and
learning activities develop the standards for supporting performance
indicators in students. More the challenging educational activities and
experiences; more will be the discoveries, innovations ideas that enable
individuals to develop the insight needed to discover and create
entrepreneurial opportunities. These results in high expertise to start
and manage own businesses to take advantage of these opportunities. The
need for entrepreneurship for sustainable growth becomes more important
for Asia as this region is the home of sixty percent of the world
population with rich natural resources. Almost in all Asian economies
entrepreneurial opportunities are low because of narrow industrial
zones, limited export sector (except China), weak private sector and
limited internal markets. So to promote the entrepreneurial education,
trainings and seminars is crucial for Asia.
Entrepreneurial education can certainly impact an apprentice at all
levels in a variety of manners. But there are some other factors like
government stability, patent rights, institutions, research and
development socioeconomic conditions, investment profile and consumption
factors that can influenced the growth process.
In current years policy makers have publicised increasing interest
in the role of entrepreneurship to promote economic growth and
development. This has been stimulated by the rapid growth of the
business sector in Asian Economies such as China, Brazil and India. As
shown in the figure below, there are structural, economic, institutional
and geographical factors which generate and promote entrepreneurship at
its different stages: Necessity Based Entrepreneurship, Improvement
Driven
Entrepreneurship and Growth Led Entrepreneurship. Further, it
explains the way those factors affect economic growth and employment
generation indirectly through promoting entrepreneurship or directly.
The task of this study is to identify those factors along with the
role of education, research and development activities which
significantly explain the entrepreneurial potential and skills and at
the second stage, to examine the impact of those entrepreneurial skills
on economic growth and employment. To complete the task, micro panel
data approach with different economic models and econometric estimation
techniques (i.e. Stepwise Least Square with Forward Selection Method and
Pooled Least Square without random and fixed effects) is used. The panel
data includes the observations on eight upper middle and lower middle
income countries over the period ranging from 2005 to 2011.
The organisation of the paper is as follows; Section 2 deals with
the relevant review of literature, Section 3 explains the methodological
setup, Section 4 explains data type and estimation technique, Section 5
deals with the results and interpretations, Section 6 includes
conclusion and policy recommendations.
[ILLUSTRATION OMITTED]
2. REVIEW OF LITERATURE
Richard Cantillion (1955) introduces the term entrepreneur first
time in the pages of economic literature. According to Klundert and
Smulders (1992) entrepreneurship is a "creative destruction".
The different historical arguments of an economist give an expanded
perspective on the term "Entrepreneurship" as it is a
fundamental agent in most production, distribution and growth theories.
A lot of studies have been done about connection between
entrepreneurship and economic growth. The new classical economist
focused that steady state equilibrium is only possible under the
umbrella of strong entrepreneurship for they are the innovator and the
founder of economics of innovation. Now question is that what are the
forces and basic circumstances that imprint strong entrepreneurship.
Solow and Swan (1970) believed that these are the labour and
capital which contribute in the process of economic expansion.
Technological change remains as exogenous (Manna from Heaven). The basic
idea in endogenous growth theory was that these are the endogenous
variables that effect productivity growth through entrepreneurship. The
new classical axioms of perfect competition are strongly restricted
incentive for innovative opportunities. The models of general
equilibrium do not talk about dynamics of entrepreneurship. In
Romer's (1990) version research sector is tank engine of growth by
assuming increasing returns to scale as it provides the monopolist the
justification of monopolistic competition. The blue prints of new varity
of capital goods that are produced and used in goods producing sector
[Chamberlin (1933)]. Lucas, (1978) explored the fact that education
increases managerial abilities and thus the propensity to become an
entrepreneur to handle with complex business environment.
Throughout intellectual history, the entrepreneur has worn many
faces and fulfilled many roles. A lot of distinct roles for the
entrepreneur have been identified in the economic literature [Hebert
(1982)].
Shultz (1980) thought quantity and quality both need to be
addressed for economic growth that are controlled through the abilities
of entrepreneurs. Therefore it is the entrepreneur who is responsible
for restoring equilibrium of economic growth. But endogenous growth
theory is silent on the underlying conditions needed for
entrepreneurship and innovation.
Peretto (1999) found that growth is driven by the process of
technological advance and knowledge accumulation brought about by
R&D efforts brought by owners of the firms.
Baumol (1990) has mentioned several forms of entrepreneurship. He
further explains that entrepreneur is an individual who is creative
enough to add his own wealth and prestige. But overall environment is
tremendous importance in determination of innovative entrepreneurial
process.
Different dimension of entrepreneurship has been studied by
economists: Lucas is of the opinion that entrepreneurial attitude is the
deterministic element between the worker and employer.
Calvo and Wellisz (1980) extended the Lucas' paper and
examined the role of individual capability, age, and knowledge on
entrepreneurial allocation. Gordon (1998) analysed the impact of fiscal
policy especially government stability, socio-economic conditions, tax
burden and incentives in the US economy. Kihlstrom and Laffont (1979)
study risk aversion and Van Praag and Cramer (2001) extend it to include
individual abilities, subsidies and investment strategy to the engine of
entrepreneurial activity.
Eakin, et al. (1994) and Quadrini (2000) have mentioned the
financial constraints on entrepreneurship especially liquidity and
savings.
Blanchflower (2000) found that self-employment is high for those at
the tail of the education distribution. Individuals with the least
education have the highest probability of being self-employed which also
confirm the views of Le (1999).
Acs, et al. (2005) using country-level data for the years 1981-1998
has empirically examined through fixed effect and a simultaneous model.
They have introduced variables such as investment in research and
development, self-employment rate and level of entrepreneurship. They
concluded that countries with higher degree of education entrepreneurial
activity and training are on higher steady state.
Audretsch and Keilbach (2005) introduced the concept of
entrepreneurship capital, referring to society's capacity to create
entrepreneurial activity specifically to generate new firms. Their study
measured the impact of entrepreneurship on regional labour productivity
and on the regional growth of labour productivity and employment
generation in Germany. Entrepreneurship capital was measured using the
number of startup enterprises relative to the region's population.
In additions they involve R&D as well as greater financial risks.
The results revealed that entrepreneurship capital significantly affect
a region's labour productivity. However, the growth of labour
productivity significant effects only for R&D based industries.
Van Stel and Suddle (2005) inspect the relationship between new
firm configuration and change in regional employment for the
Netherlands. They have measured the time and sector wise the degree of
urbanisation. The results showed the employment growth as the dependent
variable regressed against the startup rate, wage growth, and population
density. To check asymmetry data was divided into two time periods and
that confirmed the impact of new firm's growth to employment growth
has been stable and was the same in both periods.
Camp (2005) had examined the efficiency of entrepreneurial regions
and least entrepreneurial regions in the U.S. and reported that the
former had 109 percent higher productivity, 125 percent higher
employment growth and 58 percent higher wage growth as compared to the
later. This study also chains the view that entrepreneurship is the link
between innovation and regional economic growth that ultimately is road
map to economic development. The results exposed significant
coefficients for entrepreneurship activity, and high levels of expected
variation in growth.
Henderson (2006) studied the effect of entrepreneurship activity
and economic growth for urban and rural areas. The empirical results
imply that entrepreneurial activity is positively affecting employment
growth. Considering the analysis between metropolitan and
non-metropolitan areas, the study found that employment growth was
stronger in urban areas rather than in rural areas. However, there is no
significant difference on the relationship between high growth business
startups and employment growth between urban and rural areas.
Vijverberg (2008) provides a meta-analysis of empirical studies
into the impact of formal schooling on entrepreneurship selection and
performance in developed countries. Five main conclusions result from
this meta-analysis. First, the impact of education on selection into
entrepreneurship is insignificant. Second, the effect of education on
performance is positive and significant. Third, the return to a marginal
year of schooling is 6.1 percent for an entrepreneur. Fourth, the effect
of education on earnings is smaller for entrepreneurs than for employees
in Europe, but larger in the USA. Fifth, the returns to schooling in
entrepreneurship are higher in the USA than in Europe, higher for
females than for males, and lower for non-whites or immigrants. The
conclusion provides a number of policy implications to move the research
frontier in this area of inquiry. The entrepreneurship literature on
education can benefit from the technical sophistication used to estimate
the returns to schooling for labour force.
Skogstram 2011 presents a theory on the relationship between
educational choice and entrepreneurship in a labour market with
asymmetric information. The model shows that, in a labour market where
education is used as a signalling device, an imperfect relationship
between productivity in education and in the labour market can lead to
an equilibrium where a fraction of the high-ability individuals choose
to quit school and become entrepreneurs. Le (1999) divided the impact of
educational choice for entrepreneurship through signalling channel in
the labour market. He found that people having low levels of education
with high ability have higher opportunities of entrepreneurship and
self-employment. Berglann. et al. (2011) has also confirmed this fact
that entrepreneurship rates were higher among individuals with low
levels of education than among individuals with higher levels of
education.
3. METHODOLOGICAL SETUP
A strand of literature explains different categories of
entrepreneurship, which are of paramount importance in explaining the
economic growth, employment and population. The first task is to
identify those factors along with the role of education, research and
development activities which significantly explain the entrepreneurial
potential and skills and at the second stage, to examine the impact of
those entrepreneurial skills on economic growth and employment. Eliss
and William (2011) explain different types of entrepreneurship. The
categories of entrepreneurship in quantifiable terms are as follows;
[E.sub.n] = [E.sub.1n], [E.sub.2n], [E.sub.3n]
Where
[E.sub.n] = Total Entrepreneurial Activity
[E.sub.1n] = Necessity Driven Entrepreneurship Activity
[E.sub.2n] = Improvement Driven Opportunity Entrepreneurial
Activity
[E.sub.3n] = Growth Expectations of Entrepreneurial Activity
At first stage, we select those factors which explain all types of
entrepreneurial activities and skills to make the analysis more policy
oriented. The functional forms made below are consistent with the Eliss
and William (2011). Our contribution is that we incorporated other
economic and structural factors and redefined these variables.
[E.sub.n] = [E.sub.1n], [E.sub.2n], [E.sub.3n]
[E.sub.n] = f(g, pg, PG, PR, Ins, SE, SEm, GS, R & DE, Inv, TO)
... (1)
[E.sub.1n] = f(g, pg, PG, PR, Ins, SE, SEm, GS, R & DE, Inv,
TO) ... (2)
[E.sub.2n] = f(g, pg, PG, PR, Ins, SE, SEm, GS, R & DE, Inv,
TO) ... (3)
[E.sub.3n] = f(g, pg, PG, PR, Ins, SE, SEm, GS, R & DE, Inv,
TO) ... (4)
Where;
PR = Socio-economic conditions and
Ins. = Institutions
SE = Secondary Education
Em = Employment Rate
GS = Govt. Consumption Expenditures
R&DE = Research and Development Expenditure
Inv = Investment Profile
TO = Government Stability
PG = Population Growth
g = GDP Growth
pg = Per capita Growth
The equation represents the general functional form of production
function that exhibit constant elasticity of substitution equal unity
everywhere and is linear homogeneous. The statistical forms of equations
are as follows for estimation.
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]. (5)
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]. (6)
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]. (7)
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]. (8)
The model used for estimation at the second stage by incorporating
explained and unexplained factors of different types of entrepreneurial
activities (i.e. [ESS.sub.En E1n E2n E3n], [RSS.sub.En, E1n, E2n, E3n])
along with other factors which explain the changes in employment, per
capita income and population while maintaining an economic relationship
among population (P), employment (E), and income (I). The basic idea of
incorporating ESS and RSS of entrepreneurial activities as independent
variables is to separate the institutional, structural and economic
impact of entrepreneurial activities from their geographical,
traditional and regional specific impact on dependent variables. The
model is near consistent with Deller, et al. (2001), Nzaku and Bukenya
(2005), and Deller (2007), Mojica, et al. (2009). The general form of
the three-equation model is:
[P.sup.*] = f([E.sup.*], [I.sup.*], /[[OMEGA].sup.*P]) ... ... ...
... ... (9)
[E.sup.*] = g([P.sup.*], [I.sup.*], /[[OMEGA].sup.*E]) ... ... ...
... ... (10)
[I.sup.*] = h([P.sup.*], [E.sup.*], [[OMEGA].sup.*I]) ... ... ...
... ... (11)
Where
[P.sup.*], [E.sup.*] and [I.sup.*] represent the equilibrium levels
of population, employment, and per capita income, respectively, and
[[OMEGA].sup.*P] [[OMEGA].sup.*E] [[OMEGA].sup.*I] are a set of
variables describing initial conditions, explained and unexplained
variations of different types entrepreneurial activity ([ESS.sub.En E1n
E2n E3n], [RSS.sub.En, E1n, E2n, E3n]) for example GDP Growth,
socio-economic conditions, government stability, R & D expenditures,
secondary education, investment profile, per capita growth, employment
and population and other variables that are traditionally linked to
economic growth, employment and population. A simple linear relationship
as quoted Mojica-Howell, et al. (2012) has been coined here. This
framework explains the relationship of variables in the equilibrium
setup such as.
[P.sup.*] = [[alpha].sub.0P] + [[beta].sub.1P][E.sup.*] +
[[beta].sub.2P][I.sup.*] + [summation][[delta].sub.IP][[OMEGA].sup.P]
... ... ... ... ... (12)
[E.sup.*] = [[alpha].sub.0E] + [[beta].sub.1E][E.sup.*] +
[[beta].sub.2E][I.sup.*] + [summation][[delta].sub.IE][[OMEGA].sup.E]
... ... ... ... ... (13)
[I.sup.*] = [[alpha].sub.0I] + [[beta].sub.1I][E.sup.*] +
[[beta].sub.2I][E.sup.*] + [summation][[delta].sub.IE][[OMEGA].sup.I]
... ... ... ... ... (14)
Mills and Price (1984) and Mojica Hoval (2009) narrated that by
incorporating the initial conditions, the variables of the equilibrium
framework (population, employment and income) will adjust accordingly.
The considerations are incorporated as distributed lag adjustments and
are expressed as;
[P.sub.t] = [P.sub.t-1] + [[gamma].sub.P]([P.sup.*] - [P.sub.t-1])
... ... ... ... ... ... (15)
[E.sub.t] = [E.sub.t-1] + [[gamma].sub.E]([E.sup.*] - [E.sub.t-1])
... ... ... ... ... ... (16)
[I.sub.t] = [I.sub.t-1] + [[gamma].sub.t]([I.sup.*] - [I.sub.t-1])
... ... ... ... ... ... (17)
Population, Employment and Per Capita Income depend on initial
conditions and ([P.sub.t-1], [E.sub.t-1], and [I.sub.t-1]) respectively
and speed of change ([[gamma].sub.P], [[gamma].sub.E], and
[[gamma].sub.I]) coefficients. The larger the values the faster growth
rate is claimed. As suggested by Mojica, et al. (2009), current
employment, population and income levels are functions of their initial
conditions and the change between the equilibrium values and initial
conditions at their respective values of speed of adjustment ([gamma]).
Substituting Equations 15, 16, and 17 into Equations 12, 13 and 14 and
rearranging the terms gives the model to be estimated and expressed as:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] ... (16)
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] ... (17)
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] ... (18)
The regional changes in population, employment and per capita
income by [DELTA]P, [DELTA]E, [DELTA]I respectively. To investigate the
relationship between entrepreneurship and economic growth,
entrepreneurship and employment, entrepreneurship and population, the
set of equations is treated as individual linear equations where changes
in population, employment, and per capita income are regressed
individually against explained and unexplained variations of different
types entrepreneurial activity ([ESS.sub.En E1n E2n E3n], [RSS.sub.En,
E1n, E2n, E3n]) and other factors including socio-economic conditions,
government stability, R&D expenditures, secondary education,
investment profile, per capita growth, employment and population
influencing change in per capita income, change in employment and change
in population. These linear equations are as follows:
[DELTA]P = [[alpha].sub.0P] + [[delta].sub.IP][[OMEGA].sup.*P] +
[[epsilon].sub.p] ... ... ... ... ... ... (19)
[DELTA]E = [[alpha].sub.E] + [[delta].sub.IE][[OMEGA].sup.*E] +
[[epsilon].sub.E] ... ... ... ... ... ... (20)
[DELTA]I = [[alpha].sub.0I] + [[delta].sub.II][[OMEGA].sup.*I] +
[[epsilon].sub.I] ... ... ... ... ... ... (21)
Where
[[alpha].sub.p] = [b.sub.1p][P.sub.t-1] + [b.sub.2p] [E.sub.t-1] +
[b.sub.3p][I.sub.t-1] + [b.sub.4p] [DELTA]E + [b.sub.5p] [DELTA]I ...
... ... (22)
[[alpha].sub.E] = [b.sub.1E][P.sub.t-1] + [b.sub.2E] [E.sub.t-1] +
[b.sub.3E][I.sub.t-1] + [b.sub.4E] [DELTA]P + [b.sub.5E] [DELTA]I ...
... ... (23)
[[alpha].sub.I] = [b.sub.1I][P.sub.t-1] + [b.sub.2i] [E.sub.t-1] +
[b.sub.3i][I.sub.t-1] + [b.sub.4I] [DELTA]E + [b.sub.5I] [DELTA]P ...
... ... (24)
4. DATA AND ESTIMATION TECHNIQUE
The variables used in this study are explained in annexure. We used
the panel data for eight Asian countries for the period of 2005-2011.
The sample economies have been segregated into upper middle income
($1,006 to $3,975) and lower middle income ($1,005 or below it) grouped
by World Bank Gross National Income (GNI) 2011 (1) calculated by World
Bank Atlas Method. Upper middle income economies include China,
Thailand, Turkey and Malaysia. And the lower middle income economies
include India, Indonesia, Pakistan and Philippine.
The variables used in the study have been collected by different
sources such as different types of entrepreneurial activities (Necessity
Driven, Opportunity/Improvement Driven and Growth Oriented), GDP growth,
per capita income, population growth, R&D Secondary Education,
Employment rate, Govt. Consumption Expenditures, Research and
Development Expenditure have been taken from World Development
Indicators (WD1) 2012 whereas Investment Profile and Government
Stability have been taken from International Country Risk Guide (ICRG).
Global Entrepreneurship Monitor, GEM has captured three types of
entrepreneurial activities/self-employment in the market such as
necessity driven, opportunity and growth oriented. These are the
entrepreneurs of small, medium and large level enterprises. The
necessity driven entrepreneurs are not by choice but by necessity based
due to lack of wage employment. The opportunity driven self-employment
is by choice, in order to make use of some perceived market opportunity.
We have employed the panel step-wise least square forward selection
method for the estimation of Equations 5, 6, 7 and 8 and employed pooled
least square method to estimate the Equations 19, 20 and 21.
5. RESULTS AND DISCUSSION
As shown in Table 1, population growth, government stability and
R&D expenditures explain significantly the variation in total
entrepreneurial activity while the impact of socio-economic conditions,
govt, consumption expenditures, secondary education and investment
profile come out to be insignificant. The impact factor of government
stability is the highest. The economic rationale of it is that the
government stability ensures the secured opportunities for investment
and to start new ventures where the R&D expenditures play its role
in garnish the potential faculty of entrepreneurship. Population growth
is an important determinant of the demand side of the economy. Capital
rush to the country where demand and ultimately market for the product
is available. Government stability has significant and encouraging
effect on institutional quality that ultimately give boost to
entrepreneurial activities Qureshi, et al. (2010) and
Khan and Saqib (2011) Adnan, et al. (2011) where government
stability means government is not in crises and there are less cabinet
changes. Furthermore government expenditures have externalities that
enter as a direct input in production function. If government is giving
importance to more productivity enhancing expenditures it will give
boost to entrepreneurial activities [Tumovsky (2004)].
As shown in Table 2, the variables like population growth,
government stability, R&D expenditures, government consumption
expenditures, secondary education and investment profile explain
significantly the variation in Necessity Driven Entrepreneurship. The
point to be noted here that along with other variables, the government
consumption expenditures drive Necessity Based Entrepreneurship through
meso type economic policies. While at secondary level education, most of
the students involve starting their own business or involve themselves
in family business at small scale. This gives the generation and
spreading of household business, cottage industries and small scale
enterprises--the glaring feature of upper middle and lower middle income
economies.
As shown in Table 3, the variables like population growth,
government stability, socio-economics conditions, govt, consumption
expenditures and secondary education explain significantly the variation
in Improvement Driven Entrepreneurship while the impact factors of
government stability, govt, consumption expenditures and secondary
education are the highest respectively. This phenomenon explain that if
these three crucial factors remain playing their role then it changes
the necessity based entrepreneurship into improvement driven
entrepreneurship which is more sustainable and plays important role in
long run economic growth and stability. As shown in Table 4, the
variables like socio-economic conditions and govt, stability still play
their significant role to transform improvement entrepreneurship into
growth oriented and employment led entrepreneurship.
As shown in Table 5, the variables like explained entrepreneurial
activity, R&D expenditures, socio-economic conditions explain
significantly the variation in change in per capita income, where the
impact factor of R &D is the highest. The results explain that
R&D activities affect economic growth both by building up
entrepreneurial potentials and skills and by having direct impact by
increasing the value added of economic activities on large scale (i.e.
large scale industries, firms etc.)
As shown in Table 6, explained necessity based entrepreneurship
along with R&D expenditures and socio-economic conditions explain
variation in change in per capita income. The impact of improvement
driven and growth oriented entrepreneurship activities have
insignificant impact on change in per capita income. It explains the
fact that the major economic activities in upper middle and lower middle
income countries are based on necessity based entrepreneurship
activities and skills, with the first objective of wining the bread for
survival.
As shown in Table 7, the variables like explained entrepreneurship,
and population growth affect change in employment, where the impact
factor of the earlier independent variable is significantly high. While
other variables like secondary education, R&D expenditures, govt,
stability, per capita growth have indirect impact on change in
employment through explained entrepreneurship activities.
As shown in Table 8, the variable unexplained growth
entrepreneurship significantly explains the variation in change in
employment; while the other variables like necessity based and
improvement driven entrepreneurship activities have insignificant impact
on change in employment.
As shown in Table 9, the variables like explained entrepreneurial
activity and govt, stability have significant impact on change in
population, while in Table 10, it is shown that only explained necessity
based entrepreneurship have significant impact on change in population.
This fact is also backed by the general phenomenon in lower middle
income and occasionally in upper middle income countries that in low
paid or low earned families, the number of children is high than
average.
6. CONCLUSION AND POLICY RECOMMENDATIONS
On the basis of analysis made in this study, the drivers of
entrepreneurship in descending order in terms of their importance are
shown in Table 11. As shown in the table, Government stability plays
crucial role at all stages of entrepreneurial activity: total, need
based, improvement led and growth oriented: Any country should take
measures to ensure government stability because this factor builds up
the confidence among the general public about the continuity of policies
especially relating to small scale or large scale economic (business)
activities. These policies include investment policy, tax policy, and
the policy of establishment of industrial cities etc.
[TABLE 11 OMITTED]
Government consumption expenditures turn out to be the second
important driver of entrepreneurial activities. This factor again plays
a key role at all stages of entrepreneurial activities. The government
should initiate such policies which increases govt, consumption
expenditures. These policies include meso economic policies, youth
entrepreneurship programme initiated recently in Pakistan, loan scheme
with small amounts to encourage household business, cottage industries
and small scale industries. The impact of government consumption
expenditure increases, if it is used through micro-finance schemes.
In upper middle and lower middle income countries, the R&D
expenditures help in searching new avenues of establishing new
businesses with small amount in shortest span of time and help in
generating employment level. Secondary education helps both in
generating need based entrepreneurial activities and then still plays
pivotal role in transforming need based entrepreneurial activities into
improvement led activities. Socioeconomic conditions help to generate in
improvement led entrepreneurial activities and then to transform them
into growth oriented entrepreneurial activities.
Taking from the aspects of generating and continuing of
entrepreneurial activities, to generate need based entrepreneurial
activities and then to transform those into improvement led activities,
the drivers include government stability, government consumption
expenditures and secondary education and investment profile. To generate
improvement led activities and then to transform them into growth
oriented entrepreneurial activities, the drivers include government
stability, government consumption secondary education and socio-economic
activities. While to generate and continue growth led entrepreneurial
activities, the drivers include government stability, government
expenditures and socio-economic activities.
Further, it is found in this study that the variables like
explained entrepreneurial activity, explained necessity based
entrepreneurial activates, R&D expenditures, socioeconomic
conditions explain significantly the variation in change in per capita
income, where the impact factor of R&D is the highest. The results
explain that R&D activities affect economic growth both by building
up entrepreneurial potentials and skills and by having direct impact by
increasing the value added of economic activities on large scale (i.e.
large scale industries, firms etc.). The impact of improvement driven
and growth oriented entrepreneurship activities have insignificant
impact on change in per capita income. It explains the fact that the
major economic activities in upper middle and lower middle income
countries are based on necessity based entrepreneurship activities and
skills, with the first objective of wining the bread for survival.
It is also found that the variables like explained
entrepreneurship, and population growth affect change in employment,
where the impact factor of the earlier independent variable is
significantly high. While other variables like secondary education,
R&D expenditures, govt, stability, per capita growth have indirect
impact on change in employment through explained entrepreneurship
activities. The unexplained growth entrepreneurship significantly
explains the variation in change in employment; while the other
variables like necessity based and improvement driven entrepreneurship
activities have insignificant impact on change in employment.
Further investigation deduced that the variables like explained
entrepreneurial activity, necessity based entrepreneurial activities and
govt, stability have significant impact on change in population. This
fact is also backed by the general phenomenon in lower middle income and
occasionally in upper middle income countries that in low paid or low
earned families, the number of children is high than average.
APPENDIX
Variables Definitions
(1) Entrepreneurship
We develop a list of possible support to entrepreneurship
initiatives and variation that address the particular constraints to
entrepreneurship based on literature review. This list is intended to be
illustrative of the types of interventions that can be used to address
context specific constraints, rather than being an exhaustive collection
of all types of possible entrepreneurship support initiatives and
adaptations.
Recognising the importance of entrepreneurship initiatives that
have been adapted to the specific needs of the (potential)
entrepreneurs, we further disaggregate by entrepreneurial profile
focusing on three types of entrepreneurs based on their enthusiasm for
entering into entrepreneurial activity.
* Necessity Driven Entrepreneurs: entrepreneurs who have few or no
other income generation or employment opportunities, and thus become
entrepreneurs to sustain their livelihood by necessity rather than
choice;
* Opportunity Driven Entrepreneurs: entrepreneurs who pursue a
perceived market opportunity and choose to start their own business,
despite having the option of generating an income through employment
elsewhere at the time of starting a business.
* Growth Oriented Entrepreneurs: entrepreneurs who have a
relatively higher job creation potential (which may also be an
indication of greater international market reach and/or a higher degree
of innovation in products and services offered).
* Total Early-stage Entrepreneurial Activity Rates: Percentage of
18-64 population who are either a nascent entrepreneur or owner-manager
of a new business.
(2) GDP Growth (Annual %)
The Annual percentage growth rate of GDP at market prices is based
on constant local currency. Aggregates are based on constant 2000 U.S.
dollars.
(3) Secondary Education, Pupils
Secondary education pupils are the total number of pupils enrolled
at secondary level in public and private schools.
(4) Secondary Education, General Pupils
Secondary general pupils are the number of secondary students
enrolled in general education programmes, including teacher training.
(5) Self-employed, Total (% of Total Employed)
Patent applications are worldwide patent applications filed through
the Patent Cooperation Treaty procedure or with a national patent office
for exclusive rights for an invention--a product or process that
provides a new way of doing something or offers a new technical solution
to a problem. A patent provides protection for the invention to the
owner of the patent for a limited period, generally 20 years.
(6) Expense (% of GDP)
Expense is cash payments for operating activities of the government
in providing goods and services. It includes compensation of employees
(such as wages and salaries), interest and subsidies, grants, social
benefits, and other expenses such as rent and dividends.
(7) Research and Development Expenditure (% of GDP)
Expenditures for research and development are current and capital
expenditures (both public and private) on creative work undertaken
systematically to increase knowledge, including knowledge of humanity,
culture, and society, and the use of knowledge for new applications.
R&D covers basic research, applied research, and experimental
development.
(8) Population Growth (Annual %)
Annual population growth rate for year t is the exponential rate of
growth of midyear population from year t-1 to t, expressed as a
percentage. Population is based on the de facto definition of
population, which counts all residents regardless of legal status or
citizenship--except for refugees not permanently settled in the country
of asylum, which are generally considered part of the population of the
country of origin.
(9) Government Stability
A measure of the government's ability to stay in office and
carry out its declared programme(s), depending upon such factors as the
type of governance, cohesion of the government and governing parties,
approach of an election, and command of the legislature.
(10) Socio-economics Conditions
An estimate of the general public's satisfaction or
dissatisfaction with the government's economic policies, covering a
broad spectrum of factors ranging from
infant mortality and medical provision to housing and interest
rates. Different weights are applied in different societies, depending
upon the relative political impact.
(11) Investment Profile
A measure of the government's attitude toward inward
investment as determined by four components: the risk to operations,
taxation, repatriation, and labour costs.
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Comments
The authors identify those factors along with the role of
education, research and development activities which significantly
explain the entrepreneurial potential and skills. In addition, they
examine the impact of those entrepreneurial skills on economic growth
and employment. They used panel data which includes the observation on
eight upper middle and lower middle income countries over the period
ranging from 2005-2011.
My comments on the paper are outlined below:
* First of all, what selection criteria the authors have used for
selecting the eight upper middle and lower middle income countries for
their analysis? Why have not they used developed countries sample, as
entrepreneurial activities are mostly present in these countries.
* The authors have used stepwise least square with forward
selection method and pooled least square without random and fixed
effects, but have not given any plausible justification for using these
techniques.
* The authors need to give policy recommendations based on their
own study's findings.
Lubna Shahnaz Planning Commission, Islamabad.
(1) http://data.worldbank.org/about/country-classifications.
Farhat Rasool <farhat.rasool2001@gmail.com> is PhD Fellow at
Pakistan Institute of Development Economics, Islamabad. Ahmed Gulzar
<ahmed_g2008@live.com> is Research Officer at National Transport
Research Centre (NTRC), Ministry of Communications and Research Scholar
at Pakistan Institute of Development Economics (PIDE), Islamabad.
Shaheen Naseer <shaheenrana87@yahoo.com> is Research Scholar at
Pakistan Institute of Development Economics (P1DE), Islamabad.
Authors' Note: The views in this paper are those of the
author(s) and not those of the institutions, they attached with. Authors
are responsible for any error and emission. Finally feedback/comments
are strongly welcomed. Authors would like to thank Dr Musleh ud Din,
Joint Director, PIDE and Dr Ejaz Ghani on their kind support and various
policy group discussions especially on relationship among
entrepreneurship, economic growth and employment generation.
Table 1
Dependent Variable: Total Entrepreneurial Activity
Std. t-
Variable Coefficient Error Statistic Prob.*
Constant 57.071 13.199 4.324 0.000
Population Growth 1.605 0.707 2.270 0.000
Government Stability 10.652 2.387 4.462 0.006
R&D exp. (% of GDP) 1.255 0.315 3.988 0.005
Socio-economics Conditions 1.000 0.000 1.989 0.119
Govt. Consumption Exp. 0.956 0.718 1.331 0.250
Secondary edu. Pupil 0.842 0.969 0.869 0.634
Investment Profile 0.225 0.330 0.683 0.742
R-squared 0.514087 Mean dependent var 8.557
Adjusted R-squared 0.4385 S.D. dependent var 5.740
Table 2
Dependent Variable: Necessity Driven Entrepreneurship Activity
Std. t-
Variable Coefficient Error Statistic Prob.*
Constant 30.316 7.827 3.873 0.000
Population Growth 9.402 1.539 6.109 0.000
Government Stability 1.332 0.471 2.828 0.007
R&D exp. (% of GDP) 1.813 0.608 2.981 0.005
Socio-economics Conditions 0.785 0.630 1.247 0.219
Govt. Consumption Exp. 0.565 0.184 3.063 0.004
Secondary Edu. Pupil 1.000 0.000 3.073 0.004
Investment Profile 1.228 0.587 2.092 0.042
R-squared 0.668 Mean dependent var 8.557
Adjusted R-squared 0.616 S.D. dependent var 5.740
Table 3
Dependent Variable: Improvement Driven Entrepreneurship Activity
Std. t-
Variable Coefficient Error Statistic Prob.*
Constant 108.123 18.061 5.987 0.000
Population Growth 0.000 0.000 3.984 0.000
Government Stability 18.342 4.125 4.447 0.000
R & Dexp. (% of GDP) 1.611 1.394 1.156 0.254
Socio-economics Conditions 1.343 0.490 2.742 0.009
Govt. Consumption Exp. 5.079 1.577 3.221 0.002
Secondary Edu. Pupil 4.065 1.413 2.878 0.006
Investment Profile 0.286 0.490 0.584 0.562
R-squared 0.419842 Mean dependent var 45.01852
Adjusted R-squared 0.331557 S.D. dependent var 11.72723
Table 4
Dependent Variable: Growth Oriented Entrepreneurship Activity
Std. t-
Variable Coefficient Error Statistic Prob. *
Govt. Consumption 0.855 0.200 4.277 0.000
Socio-economics Conditions 1.714 0.755 2.270 0.028
Govt. Stability 1.006 0.540 1.862 0.068
R & exp (% of GDP) 0.893 0.793 1.125 0.266
GDP Growth 2.478 1.541 1.608 0.114
R-squared 0.29006 Mean dependent var 9.636364
Adjusted R-squared 0.233265 S.D. dependent var 6.337319
Table 5
Dependent Variable: Change in Per Capita Income
Std. t-
Variable Coefficient Error Statistic Prob.
Constant 6893.919 11433.95 0.602934 0.55
Explained Entrepreneurial 91.19462 46.13344 1.976758 0.055
Activity Rate
Unexplained Entrepreneurial -37.8073 74.76522 -0.50568 0.6159
Activity Rate
Secondary Education Pupil 1.16E-05 8.11E-06 1.426223 0.1616
R&D Exp. 1389.393 302.3845 4.594789 0
Socio-economics Conditions 813.9676 301.0349 2.703897 0.01
Population Growth 112.0886 766.1413 0.146303 0.8844
Employment Rate -85.9998 100.1598 -0.85863 0.3957
Government Stability -316.667 243.3225 -1.30143 0.2006
Investment Profile 103.6366 308.1218 0.33635 0.7384
R-squared 0.385882 Mean dependent var -144.834
Adjusted R-squared 0.247706 S.D. dependent var 1915.183
Table 6
Dependent Variable: Change in Per Capita Income
Std. t-
Variable Coefficient Error Statistic Prob.
Constant 7191.83 11285.07 0.637287 0.5276
Explained Necessity Based 127.2231 59.02128 2.155547 0.0372
Entre.
Unexplained Necessity Based -89.6379 159.7353 -0.56117 0.5778
Entre
Secondary Education Pupil 7.89E-06 8.07E-06 0.977165 0.3344
R&D Exp. 1447.226 315.5883 4.585806 0
Socio-economics Conditions 817.8054 299.0224 2.734931 0.0093
Population Growth 229.186 804.7749 0.284783 0.7773
Employment Rate -89.0467 97.76737 -0.9108 0.3679
Government Stability -274.453 236.3555 -1.16119 0.2524
Investment Profile 29.28781 320.5133 0.091378 0.9276
R-squared 0.40441 Mean dependent var -144.834
Adjusted R-squared 0.270402 S.D. dependent var 1915.183
Table 7
Dependent Variable: Change in Employment
Std. t-
Variable Coefficient Error Statistic Prob.
Constant -7.24038 2.646284 -2.73605 0.0089
Explained Entre. Activity 0.114165 0.055037 2.074348 0.0438
Unxplained Entre. Activity 0.118377 0.09468 1.250286 0.2177
Secondary Education, Pupil 8.97E-09 1.15E-08 0.777134 0.4411
R & D Exp. 0.013378 0.362329 0.036922 0.9707
Govt. Stability 0.342108 0.306915 1.114667 0.2709
Population Growth 1.673903 0.833021 2.009436 0.0505
Per capita Growth 0.015095 0.134503 0.11223 0.9111
R-squared 0.218566 Mean dependent var -0.18491
Adjusted R-squared 0.09701 S.D. dependent var 2.2428
Table 8
Dependent Variable: Change in Employment
Std. t-
Variable Coefficient Error Statistic Prob.
Constant -7.52558 3.371695 -2.23199 0.0304
Explained Growth Entre. 0.049292 0.103707 0.475306 0.6368
Unexplained Growth Entre. 0.189776 0.108965 1.741619 0.0881
Secondary Education, Pupil 1.70E-08 1.15E-08 1.480515 0.1454
R & D Exp. -0.18713 0.353052 -0.53004 0.5986
Govt. Stability 0.421205 0.319056 1.32016 0.1932
Population Growth 2.502124 0.974723 2.567009 0.0135
Per Capita Growth -0.04365 0.113066 -0.38607 0.7012
R-squared 0.156902 Mean dependent var -0.12364
Adjusted R-squared 0.031334 S.D. dependent var 2.22677
Table 9
Dependent Variable: Change in Population
Std. t-
Variable Coefficient Error Statistic Prob.
Constant 5.80E-13 8.85E-14 6.551954 0
Explained Entre. Activity 7.93E-16 4.16E-16 1.905551 0.0633
unexplained Entre. Activity 3.45E-16 6.89E-16 0.501154 0.6188
Secondary Education Pupil 1.36E-22 8.67E-23 1.574212 0.1226
R & D Exp. -6.47E-16 2.64E-15 -0.24457 0.8079
Govt. Stability 3.92E-15 2.27E-15 1.728271 0.091
Per Capita Growth -1.10E-15 9.90E-16 -1.10638 0.2746
Employment Rate 5.73E-15 8.69E-16 6.600376 0
R-squared 0.6 Mean dependent var 1.292925
Adjusted R-squared 0.57 S.D. dependent var 0.473767
Table 10
Dependent Variable: Change in Population
Std. t-
Variable Coefficient Error Statistic Prob.
Constant 2.99E-13 4.55E-14 6.576773 0
Explained Necessity Entre. 4.96E-16 2.87E-16 1.725536 0.0914
Unexplained Necessity Entre 5.65E-16 7.20E-16 0.784072 0.4372
Secondary Education Pupil 7.93E-23 4.54E-23 1.748056 0.0874
R & D Exp. 7.12E-16 1.44E-15 0.494135 0.6237
Govt. Stability 2.98E-15 1.20E-15 2.489074 0.0167
Per capita Growth -5.46E-16 4.98E-16 -1.09585 0.2791
Employment Rate 2.87E-15 4.46E-16 6.44645 0
R-squared 0.65 Mean dependent var 1.292925
Adjusted R-squared 0.6 S.D. dependent var 0.473767
