Economic Empowerment of Women on Economic Growth in Sub-Saharan Africa 2 nd International Conference on Sustainable Development in Africa Dakar, Senegal; 26 – 27 November 2015 UNU-MERIT Conference Elizabeth N. Appiah, PhD Pentecost University College, Ghana

Background Ratio of female to male labor force participation rate increased from SSA % 84.13% LAC64.55%67.03% South Asia45.54%39.74%

Background Available data on earned income suggests that SSA women earned about 55 cents of each dollar earned by men (ADB, 2014). SSA women account for over 50% of the sub- continent’s population and about 50% of the labor force, and continue to grow even faster than SSA men’s labor force yet inequality in earned income persists. SSA women labor force increased over the past decade with the majority of them involved in the informal agriculture, commerce & service sectors, including cash and non-cash products (World Bank, 2015; ILO, 2002).

Background on GDP IMF projected GDP growth to increase from 4.9% in 2013 to about 5.5% in , annual GDP growth was 4.24% 2004 GDP growth rate was 9.46 ‘Ebola’ crisis; Power outrages; Poor macroeconomic policies 111 million women remained illiterate between 2005 and 2014, about a third of the illiterate men during the same period. Nearly 30 million of these women are between ages (UNESCO Institute for Statistics, 2015).

Objectives Seeks to point out the impediments to women economic empowerment Examine the determinants of economic growth by explicitly incorporating women’s participation in the labor market.

Approach Lucas Production Function where output is produced as a function of inputs of human capital skills resulting from education, (LITADULT) proxy for educational attainment

Model and Data Ordinary Least Square Regression Data (World development Indicators, The World Bank) Dependent Variable: – GDPGROWTH = annual percentage growth in gross domestic product – GDPPC = annual per capita GDP growth Regressors Education Inputs: – LITADULT(F), LITADULT(M) Growth Inputs: – GDPPC, GDI, LF15&UP(F), LF15&UP(M), LEXP(F), LEXP(M), and POPGROWTH

Results Significant VariablesWomenMen GDP per Capita (+)(+) Labor Force 15 & UP (-)(+) Life Expectancy (+)(+) Population Growth(+)(+)

Results Insignificant VariablesWomenMen GDI(+)(-) Literacy Adult(-)(-)

Policy Implications Improve macroeconomic policies that reduce financial costs, and make financial and credit assistance inclusive to both men & women Reduce intermediation costs & other policies that will benefit everyone irrespective of gender, educational attainment than measures that try to increase access to credit directly. For example: improvement in labor force participation (population growth) reduces equilibrium level of GDP per capita if technology is static.

Policy Implications Solow’s model states that investment in capital cannot drive long run growth in GDP per worker. Need technological change to avoid diminishing returns to capital. Not prudent for SSA countries to invest without due regard for technology Need to revive the informal agriculture sector, which is dominated by women, by granting equal rights to land and production tools. Improve the informal commerce sectors