Human Capital in Africa: Technical Change, Efficiency and Productivity
Vishal Chandr Jaunky
Faculty of Social Studies and Humanities
Department of Economics and Statistics
University of Mauritius
Réduit
Mauritius
Email:
August 2008
Abstract
Human capital remains a critical issue facing the African people. Education which epitomizes investment in human capital is a key determinant of a country’s long term economic success. Yet, the illiteracy rate in Africa is one of the highest rates of any continent. The low access to education coupled with low schooling levels, hinders economic reforms. In 2000, the United Nations adopted the Millennium Development Goals, a set of quantifiable targets which is meant to improve education, together with health care, gender equality, the environment and reducing by half the number of people living in extreme poverty by 2015 across the world. The importance of human capital as a prime engine for productivity growth has been extensively studied. The traditional way of measuring total factor productivity (TFP) relies on the growth accounting methodology. Various parametric production functions which account for contribution of factor inputs to a country’s output are estimated using conventional ordinary least squares (OLS) regressions. TFP growth can be measured by the residual part of the growth of output. Alternatively, TFP can also be computed by means of non-parametric the Malmquist productivity growth index. Such approach will be considered in this study. As a preliminary study, the importance of human capital on overall production is assessed. As such, a stochastic frontier analysis (SFA) is conducted. The basic model is based on regression analysis. OLS regression implicitly assumes that the entire of the residual is the consequence of solely inefficiency. In opposition, SFA models decompose the error term into inefficiency and random error which is aimed to depict a more accurate picture of the true efficiency level. The early SFA models in the literature focus on cross-sectional data. When panel data are available, the most common approach in the data envelopment analysis (DEA) literature is to apply the Malmquist TFP index. The DEA makes use of the notion of distance function and does not require the imposition of any functional form nor distributional assumptions on the data. An index of annual productivity change can thus be estimated by using such non-parametric frontier model. One of the most notable features of this method is that the Malmquist index is decomposable into two components namely, technical change (technology innovation) and efficiency change (catching-up to technology). However, a drawback of the DEA is its inability to deal with noisy data in a satisfactory manner. DEA may not be the appropriate technique in a dataset with several outliers. However, DEA is still regarded as a suitable tool for studying productivity growth at country level. To sum up, the aim of this paper is to analyze the importance of human capital on productivity growth for 26 African countries over the period 1976-1996. To estimate productivity change, the Malmquist TFP growth index is computed. This productivity change index is then decomposed into technical change and efficiency change. In general, human capital is found to exert a positive effect on technical change and productivity change while efficiency change is left unaffected. Additionally, higher levels of technical inefficiency tend to lead to lower rate of innovation.
Keywords:Africa, human capital, Malmquist productivity growth index, stochastic frontier analysis
JEL: N27, O40