nep-afr New Economics Papers
on Africa
Issue of 2007‒02‒10
five papers chosen by
Suzanne McCoskey
Foreign Service Institute, US Department of State

  1. Using the hierarchical linear model to understand school production in South Africa By Martin Gustafsson
  2. Intensity of technology use and per capita real GDP across some African countries By Amavilah, Voxi Heinrich
  3. Africa's Lagging Demographic Transition: Evidence from Exogenous Impacts of Malaria Ecology and Agricultural Technology By Dalton Conley; Gordon C. McCord; Jeffrey D. Sachs
  4. Informal chain-saw timber from Cameroon : the northern trail By Yeboah Alexis Koffi
  5. Explaining the Variation in Tax Structures in the MENA Region By Mehmet Tosun

  1. By: Martin Gustafsson (Research Triangle Insitute, Department of Education (Tswane))
    Abstract: The emphasis placed in the existing South African school production function literature on better skilled teachers and better school management is discussed. Ordinary least squares and hierarchical linear production function models, using 2000 SACMEQ data, for the country and for a sub-set of historically disadvantaged schools, are constructed. Ways of making the results more readable for policymakers are explored. The importance of physical infrastructure, textbook and nutrition budgets is highlighted by the models. Correct allocation of teaching and management time in schools, less learner repetition, and better teaching methodologies stand out as important school and classroom management imperatives.
    Keywords: Educational quality, Education policy, Education resources, SACMEQ, South Africa
    JEL: I21 H52
    Date: 2007
  2. By: Amavilah, Voxi Heinrich
    Abstract: African countries may have fared poorly compared to some countries in other regions, but relative to their own performance history some African countries have done quite well over the past eight years. In particular 2004 and 2005 were especially good years. How can such performance be made to stick and even expand? The answer to that question requires better understanding of the source of good performance. This paper proceeds on the assumption that technology was, at least partially, responsible. The result shows that a feeble technology undercuts per capita real GDP across African countries. However, the impacts of new technologies, measured by the intensities of internet and cell phone use are very strong. The policy implication of the findings speaks to the need for investment in new technologies for which productivity is high and the adoption and diffusion costs seem low. Further research can clarify the findings and policy by expanding and improving the data coverage, and examining effects on income of different kinds of technologies.
    Keywords: technology and per capita income; GDP per capita Africa; African countries’ GDP-technology nexus
    JEL: O55 O47 C21 O14 C51 O41
    Date: 2006–11–18
  3. By: Dalton Conley; Gordon C. McCord; Jeffrey D. Sachs
    Abstract: Much of Africa has not yet gone through a "demographic transition" to reduced mortality and fertility rates. The fact that the continent's countries remain mired in a Malthusian crisis of high mortality, high fertility, and rapid population growth (with an accompanying state of chronic extreme poverty) has been attributed to many factors ranging from the status of women, pro-natalist policies, poverty itself, and social institutions. There remains, however, a large degree of uncertainty among demographers as to the relative importance of these factors on a comparative or historical basis. Moreover, econometric estimation is complicated by endogeneity among fertility and other variables of interest. We attempt to improve estimation (particularly of the effect of the child mortality variable) by deploying exogenous variation in the ecology of malaria transmission and in agricultural productivity through the staggered introduction of Green Revolution, high-yield seed varieties. Results show that child mortality (proxied by infant mortality) is by far the most important factor among those explaining aggregate total fertility rates, followed by farm productivity. Female literacy (or schooling) and aggregate income do not seem to matter as much, comparatively.
    JEL: I1 J11
    Date: 2007–02
  4. By: Yeboah Alexis Koffi
    Abstract: This document presents a synthesis of the unformal trade of timber in Cameroon. It focuses on the informal trade which occurs from tropical forests towards various countries of Africa. This trade, largely ignored by the litterature so far, is surprisingly important, and its geographical extension is very large. The data and figures are extracted from the master thesis of the author : Sciage artisanal, Transformation et commerce du bois d'oeuvre du Cameroun à destination de l'arc Soudano-Sahélien, 2005
    Date: 2005
  5. By: Mehmet Tosun (Department of Economics, University of Nevada, Reno)
    Abstract: This paper examines the tax structures of the Middle East and North Africa (MENA) countries by focusing on the quality of governance and demographic changes as two influential factors in region’s economies. The objective of is to determine whether these factors can explain the variation in the tax structures of these countries. Results from regressions on the MENA countries and the ones based on a larger sample of 61 countries show that these factors affected the level of taxation, measured by the tax ratio, more strongly than they affected the tax composition. While the quality of governance seems to have affected the tax structures in the MENA countries more than in other comparable Non-OECD countries, demographics seems to have played a bigger role in determining the tax structures in other Non-OECD countries. However, neither of these factors explained changes in the income tax share satisfactorily. One key result is that the increase in the quality of governance has decreased the reliance on domestic taxes on goods and services. The paper provides a discussion on the policy implications of these results.
    Keywords: Tax structure, quality of governance, demographics, MENA countries
    JEL: E62 H20 H71 H87
    Date: 2006–12

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