Abstract
In this paper, we consider the role of inequality-based entry barriers on the formation of female-owned firms in Nigeria. With data from the 2010 World Enterprise Survey, we estimate the parameters of a simple model of female-owned firm entry to determine the role of inequality-based barriers on the number of female-owned firms across city-industry clusters in Nigeria. Parameter estimates from count data specifications of firm entry reveal that access to financing, land, and licenses/permits absolutely deter the entry of female-owned firms, as these entry barriers are proportional to the probability of observing no female-owned firms. In general, barriers to securing land constrain the entry of female-owned firms beyond the process determining absolute entry deterrence. This suggests that the market entry and underrepresentation of female-owned among firm-owners and entrepreneurs in Nigeria is, at least in part, caused by gender inequality in general. As private firm output dominates the gross domestic product of modern economies, our findings suggest that the reduction of gender inequality in Sub-Saharan Africa would result in more female-owned and entrepreneurs which would catalyze economic growth.
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Notes
- 1.
Internationally, Human Development is officially measured by the United Nations Development Program’s Human Development Index (HDI). The HDI is a composite index based on three sub-indexes, one of which is an index for a country’s Gross Domestic Product (Anand and Sen 2000)—which provides a linkage between human development and economic growth.
- 2.
- 3.
WES data are available at: http://www.enterprisesurveys.org/Data
- 4.
A Poisson regression model (Cameron and Trivedi 1998) is formulated by specifying for integer-valued measures of female-owned firms E i in city-industry cluster i, the conditional mean λ i as:
$$ ln{\lambda}_i=\kern0.5em {\beta}^{\prime}\Theta $$where β is a coefficient vector, and Θ is a vector of exogenous expected profit and entry barrier measures that determine the expected value of the number of female-owned firms E i in the i th city-industry cluster. The log-likelihood function L(β) has a gradient and Hessian given by:
$$ \frac{\partial L\left(\beta \right)}{\partial \beta}={\displaystyle \sum}\left[{\Theta}^{\prime}\left({E}_i-{e}^{\beta^{\prime}\Theta}\right)\right]=0 $$$$ \frac{\partial^2 L\left(\beta \right)}{\partial \beta \partial {\beta}^{\prime}={\displaystyle \sum}\left[-\left({E}_i^{\prime }{E}_i\right){e}^{\beta^{\prime}\Theta}\right]<0} $$Equating the gradient to zero solves for β, and the negativity of the Hessian ensures a global maximum of the log-likelihood estimator of the coefficients in β.
As a Poisson specification assumes there is no unobserved heterogeneity, the mean and variance of λ are identical. Given the possibility of unobserved heterogeneity, the Poisson model can be modified as a Negative Binomial (Cameron and Trivedi 1998) where the specification of λ is:
$$ ln{\lambda}_i={\beta}^{\prime}\Theta +{\varepsilon}_i $$where ε i reflects unobserved heterogeneity causing the mean and variance of λ to differ.
- 5.
All estimates are weighted with the cross-product of the size, region and establishment stratum weights, and the standard errors are clustered on city-industry groupings to control for the unobservables associated with localization and agglomeration.
- 6.
In the sample, approximately 74 % of the city-industry clusters have zero female-owned firms. This preponderance of zero counts could mimic overdispersion—different values for the mean and variance of λ i —inducing false selection of a Negative Binomial specification as a result of failing to account for the process determining the zero counts. In a zero-inflated count specification, the realizations come from two regimes. In one regime the outcome is always zero, while in the other it is not always zero. Let ω i be the probability that a realization has a zero outcome, then for a Poisson distribution, the mean is (1−ω i ) β′Θ, where [ω i  = β′Θ d ]/[1 + β′Θ d ], is a Logit specification, and Θ and Θ d could be identical. A Zero-inflated Negative Binomial specification simply adds a stochastic error term to the specification for the conditional mean.
- 7.
The value of the additional net output follows from multiplying average firm profit reported in Table 6.2 by the additional number of female-owned firms that would enter the market as a result of a 50 % reduction in barriers to securing land.
References
Akaike H (1998) Information theory and an extension of the maximum likelihood principle. In: Selected papers of Hirotugu Akaike. Springer, New York, NY, pp 199–213
Anand S, Sen A (2000) The income component of the human development index. J Hum Dev 1:83–106
Arauzo-Carod J-M, Segarra-Blasco A (2005) The determinants of entry are not independent of start-up size: some evidence from Spanish manufacturing. Rev Ind Organ 27:147–165
Asiedu E, Kalonda-Kanyama I, Ndikumana L, Nti-Addae A (2013) Access to credit by firms in Sub-Saharan Africa: how relevant is gender? Am Econ Rev 103:293–97
Audretsch DB (2007) Entrepreneurship capital and economic growth. Oxf Rev Econ Policy 23:63–78
Bain Joe S (1956) Barriers to new competition. Harvard University Press, Cambridge, MA
Baliamoune-Lutz M, McGillivray M (2009) Does gender inequality reduce growth in Sub-Saharan African and Arab countries? Afr Dev Rev 21:224–242
Barbosa N, Guimaraes P, Woodward D (2004) Foreign firm entry in an open economy: the case of Portugal. Appl Econ 36:465–472
Belleflamme P, Picard P, Thisse J-F (2000) An economic theory of regional clusters. J Urban Econ 48:158–184
British Council of Nigeria (2012) Gender in Nigeria report 2012: improving the lives of girls and women in Nigeria, issues, policies, action, 2nd edn. Abuja
Cameron AC, Trivedi PK (1998) Regression analysis of count data. Cambridge University Press, Cambridge, UK
Elu JU (2013) NEA presidential address: gender inequality and human development in Sub-Saharan Africa. Rev Black Polit Econ 40:105–113
Feinberg RM (2010) Price impacts of small-firm entry in US manufacturing. East Econ J 36:58–69
Glaeser EL, Kallal HD, Scheinkman JA, Shleifer A (1992) Growth in cities. J Polit Econ 100:1126–1152
Hallward-Driemeier M (2011) Strengthening women’s entrepreneurship, The Africa competitiveness report. World Bank, Washington DC, pp 67–88
Khemani RS, Shapiro DM (1986) The determinants of new plant entry in Canada. Appl Econ 18:1243–1257
Koellinger PD, Roy Thurik A (2012) Entrepreneurship and the business cycle. Rev Econ Stat 94:1143–1156
Lambert D (1992) Zero-inflated poisson regression with an application to defects in manufacturing. Technometrics 34:1–14
McMillan J, Woodruff C (2002) The central role of entrepreneurs in transition economies. J Econ Perspect 16:153–170
Mullahy J (1986) Specification and testing of some modified count data models. J Econom 33:341–365
Orr D (1974) The determinants of entry: a study of the canadian manufacturing industries. Rev Econ Stat 56:58–66
Price GN (1995) The determinants of entry for black-owned commercial banks. Q Rev Econ Finance 35:289–303
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Bussey, T.R., Elu, J.U., Price, G.N. (2014). Do Inequality-Based Entry Barriers Deter the Formation of Female-Owned Firms in Nigeria?. In: Seck, D. (eds) Private Sector Development in West Africa. Advances in African Economic, Social and Political Development. Springer, Cham. https://doi.org/10.1007/978-3-319-05188-8_6
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