SOURCES OF ECONOMIC GROWTH AND TECHNOLOGY TRANSFER IN SUB‐SAHARAN AFRICA1

This paper provides some empirical evidence on the sources of growth in sub‐Saharan Africa (SSA). Within the classical convergence framework, several macroeconomic, socio and political factors are identified as affecting the steady state growth paths of the SSA countries. The rejection of the constant technology growth rate assumption implied by the linearised Solow‐Swan growth specification suggests differences in the economies' technology growth rates. An endogenous technology growth model is estimated to measure contributions of diminishing returns and technology transfer to the rate of conditional convergence in the region. The results carry important policy implications for improving the standard of living and economic growth rate of African countries.     

INFRASTRUCTURE QUALITY AND MANUFACTURING EXPORTS IN AFRICA: A FIRM‐LEVEL ANALYSIS

Using bilateral trade flow models, a body of empirical work has documented how geography and infrastructure variables affect trade performance. However, in this paper, we apply censored regression models like the Tobit and Probit on firm‐level manufacturing data from 10 African countries, and results suggest that inadequate infrastructure in the form of customs, transport, electricity and water negatively affects export intensity and participation. Owning a generator and private water source also appear to have a significant impact on exports. This, therefore, means that firms can minimise the impact of power and water disruption on production, and hence trade by installing these alternative energy and water sources.     

THE PREDICTABILITY OF STOCK MARKET RETURNS IN SOUTH AFRICA: PARAMETRIC VS. NON‐PARAMETRIC METHODS

This paper compares the forecasting performance of a sub‐class of univariate parametric and non‐parametric models in predicting stock market returns in South Africa. To account for conditional heteroskedasticity in stock returns data, the non‐parametric model is generated by the conditional heteroskedastic non‐linear autoregressive (NAR) model, while the parametric model is produced by the generalised autoregressive conditional heteroskedastic in mean (GARCH‐M) model. The results of the paper show that the NAR as a non‐parametric model performs better than the GARCH‐M model in short‐term forecasting horizon, and this indicates the importance of a distribution‐free model in predicting stock returns in South Africa.     

RISK–RETURN TRADE‐OFF AND BEHAVIOUR OF VOLATILITY ON THE SOUTH AFRICAN STOCK MARKET: EVIDENCE FROM BOTH AGGREGATE AND DISAGGREGATE DATA

The study analyses the nature and behaviour of volatility, the risk–return relationship and the long‐term trend of volatility on the South African equity markets using aggregate level, industrial level and sectoral level daily data for the period 1995‐2009. By employing dummy variables for the Asian and the sub‐prime financial crises and the 11 September political shock, the study further examines whether the long‐term trend of volatility structurally breaks during financial crises and major political shocks. Three time‐varying generalised autoregressive conditional heteroskedasticity models were employed: one of them symmetric, and the other two asymmetric. Each of these models was estimated based on three error distributional assumptions. The findings of the study are as follows: First, volatility is largely persistent and asymmetric. Second, risk at both aggregate and disaggregate level is generally not a priced factor on the South Africa (SA) stock market. Third, the threshold autoregressive conditional heteroscedasticity (TARCH) model under the generalised error distribution is the most appropriate model for conditional volatility of the SA stock market. Fourth, volatility generally increases over time, and its trend structurally breaks during financial crises and major global shocks. The policy and investment implications of the findings are outlined.     

HIV/AIDS AND POVERTY IN SOUTH AFRICA: A BAYESIAN ESTIMATION OF SELECTION MODELS WITH CORRELATED FIXED‐EFFECTS

In this paper, we estimate the causal impact of human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS) on monetary poverty using a panel database from South Africa. We treat endogeneity and selection problems associated with HIV/AIDS by a selection model that includes correlated fixed effects both in the level and in the participation equations, which are estimated simultaneously via original Bayesian methods. We model the consequences of the illness on both labour income and income transfers, and disentangle between urban and rural households. While no significant impact of HIV/AIDS on labour income is found because of households' recomposition, we find a substantial fall in received transfers among rural population and a dramatic increase in chronic poverty.     

VALUE CONTENT AND PRODUCTION NETWORKS IN SOUTHEAST ASIA: APPLICATION OF AFTA AND ASEAN‐PLUS‐ONE FTA FORMULAS

Rules of origin are an integral part of all trade rules. To be eligible for Common Effective Preferential Tariffs under the ASEAN Free Trade Area (AFTA) agreement, a product must satisfy the conditions relative to value content. The present paper seeks to calculate value content of industries in Southeast Asia, using the formula specified by the rules of origin in AFTA, the ASEAN–China FTA, the ASEAN–Korea FTA, and the ASEAN–Japan FTA. Moreover, the paper attempts to calculate true value content of industries by applying a simple technique of input–output analysis, and to estimate error margins (i.e., overestimates) in calculating value content. The paper also examines the relationship between value content and production networks. The paper finds that many industries exhibited declines in local content during the period 1990–2000, but that the geographical spread of production networks raised the proportion of inputs supplied by the neighboring ASEAN countries, so that the contribution of the cumulative rule of origin increased.