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					                Prof. Poh-Kam Wong, National University of Singapore
    Entrepreneurial Firm Formation and Income Equality: A Cross-Country Analysis

1.      Introduction
Wealth distribution is a fundamental concern in economics. Surprisingly, one feature of
economic systems often overlooked when discussing wealth distribution is the role of
entrepreneurship. In the conceptual (Meh, 2005; Cagetti and De Nardi, 2006) and empirical
(Quadrini, 1999) literature, there is support for the conventional wisdom that entrepreneurship is
associated with higher income inequality. However, the empirical evidence on economies
outside the US appears to be ambiguous.
This paper attempts to close this gap by exploring the empirical relationship between
entrepreneurship and income distribution, utilizing cross-national data. The firm formation
attribute of entrepreneurship is emphasized and comparisons are made between different
measures of entrepreneurial activity.
2.      Entrepreneurship and Income Distribution in the Literature
A number of studies in the income distribution literature have sought to examine the association
between entrepreneurship and income inequality. However, the empirical evidence that emerged
from these studies appear to be ambiguous.
By introducing entrepreneurship as an additional dimension in the Kuznets (1955) curve (which
hypothesizes a U-shaped relationship between macroeconomic development and equality),
Deutsch and Silber (2004) implied that rising levels of entrepreneurship are associated with
widening income inequality. This supposition that entrepreneurship causes inequality appears to
be supported by empirical work using Italian and US data (Quadrini, 1999, 2000; Cagetti and De
Nardi, 2003, 2006; Budria et al., 2002; Quintano et al., 2005). However, other studies have
found that the direction of the relationship between inequality and entrepreneurship to be
dependent on moderating factors, such as the tax regime (Meh, 2005; Kanbur, 1982).
A number of economy-specific studies using data from non-OECD economies have postulated
the entrepreneurship should redistribute income more equitably. Berkowitz and Jackson’s (2006)
empirical work on Russian and Polish income distribution indicate that new firm creation is
associated with both larger income and a larger portion of income distributed to the lower
quintiles. Kimhi (2009) found that a uniform increase in entrepreneurial income reduced
household income inequality in southern Ethiopia. However, increasing the number of
entrepreneurs per se did not affect income inequality.
A recent contribution to this discussion is found in a conceptual paper by Spencer et al. (2006),
attempting to link different views of entrepreneurship to their potential wealth distribution
effects. Drawing on illustrative case studies of disruptive technologies that have spawned new
industries, they argue that it is new firms that embody Schumpeter’s (1934) original emphasis on
the wealth distribution function of independent entrepreneurs, a function overlooked by
subsequent theories of entrepreneurship that have moved in divergent directions.
3.      Model, Measures and Data for Empirical Analysis
The contrasting findings from the literature suggest that the relationship between
entrepreneurship and income distribution may not be linear. To verify this, we perform a cross-
country analysis, hypothesizing that there is a non-linear causality effect of entrepreneurship rate
on the degree of income inequality.
The basic analysis model takes the general form:
Inequality = + 1i (Control Variables) + 2 Entrepreneurship + 3 Entrepreneurship 2
We have taken advantage of comprehensive cross-economy databases released by international
organizations to construct our analysis dataset. Data on Income Inequality are taken from the
UNU / WIDER World Income Inequality Database (WIID) version 2.0c. Values for 2005 are
used where available; where 2005 data are not given, the latest available year is used provided
that the year is no earlier than 2001.
The control variables included are:
GDP per capita & GDP per capita squared – Control for the Kuznets (1955) curve effect.
Growth in Real GDP – The literature establishes a relationship between growth and inequality
although there are contrasting findings on the direction of correlation (eg. Li and Zhou, 1998;
Perotti, 1996; Barro, 2000)
Change in Wages – Controls for effect of wages as the price of labour.
Ratio of FDI to GDP and Ratio of FDI:GDP squared – This measure proxies the openness of an
economy. As reviewed by Anderson (2005), time series studies have established a link between
openness and inequality, but the evidence is less conclusive in cross-country studies. A squared
term is included to control for potential non-linearity as found by Calderon and Chong (2001).
Several different measures of entrepreneurship are used, drawing from the World Bank Group
Entrepreneurship Survey (Klapper et al, 2008) and the Global Entrepreneurship Monitor (GEM).
Our primary interest is focused on entrepreneurship as defined by firm formation. From the
World Bank Survey, we extracted the variable New Business Density, which measures the ratio
of total new business registrations to national population, Three GEM measures, all of which are
similarly propensity-based, are examined. Total Early Stage Entrepreneurial Activity (TEA) is
the proportion of adult population involved in early stage entrepreneurship. TEA is divided into
two sub-components: Nascent Entrepreneurship – those involved in attempting to start a
business - and Start-Up Entrepreneurship – those who have started a new business in the last 3.5
4.      Preliminary Results
Preliminary regression results are shown in Table 1. Broadly, there is support for the Kuznets
curve hypothesis. However, the other control variables included were non-significant.
Comparing the World Bank and GEM measures, the squared terms for the GEM propensity
measures were found to be non-significant and have been consequently dropped to improve
model fit. In contrast, the squared terms for the World Bank measure was significant, showing an
inverse U-shaped relationship between new business propensity and inequality. The results for
the GEM measures highlight that it is Start-Up Entrepreneurship that is linked to inequality, with
a positive and significant relationship. The pre-start-up processes of nascent entrepreneurship do
not seem to influence income distribution.
The final version of the paper will include more in-depth analysis of interaction terms between
control variables and entrepreneurship measures to more clearly establish the effects of
entrepreneurship on income distribution in economies of different development levels. Policy
implications and suggestions for further research will be discussed.