Research was conducted to find out the effects of exchange rate variability, terms of trade, competitiveness and gross domestic product on the dominant export crop of Ethiopia, coffee. This study employs annual time series data (1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) and uses the autoregressive distributive lag (ARDL) model augmented by the Wald test. The results reveal that exchange rate variability has a negative effect on the export of coffee in the short run, but is insignificant in the long run. This implies that, over time, exchange rate changes in the country have been favouring the export performance of coffee. Regardless of exchange rate variability, the competitiveness of the country, explained by real effective exchange rates, improved, but the price of coffee did not increase relative to the price of imports, which has resulted in deteriorating terms of trade. To improve the worsening terms of trade and benefit from policy changes, export diversification and value addition are possible solutions the country should focus on.

Given that fish and fishery products are ranked among the most traded food commodities globally, with developing countries accounting for the bulk of the world’s fish exports, the analysis of fish trade flows is of key importance for any policy measure in the fisheries sector. This study evaluates the determinants of fish trade flows by applying the generalized gravity model. Using panel data covering a period of 14 years for 54 African countries, the gravity model is estimated using the Tobit regression to overcome estimation challenges in the presence of zero trade observations. The results suggest that a 1% increase in exporters’ GDP, importers’ GDP, population, exporters’ fish production, and countries sharing a common border increased fish trade flows by 8%, 14 %, 4%, 36% and 60%, respectively. On the other hand, importers’ fish production, and distance reduced fish trade flows by 5% and 17%, respectively. The results further shows that the belonging to ECOWAS, EAC, SADC and AMU has significantly enhanced intra-fish trade flows thereby contributing to gross trade creation for fish. The results indicate that the current demand for fish is very high such that current production is unable to meet the consumption needs. This calls for consolidated efforts in investment and development of the aquaculture sector as an alternative to the dwindling fish supplies from the wild environment. The findings also demonstrate the need for regional blocs to improve the transport networks on the continent by, among others, adopting a regional cooperation strategy centered on infrastructure development.

BACKGROUND: Incidence is a better measure than prevalence for monitoring AIDS, but it is not often used because longitudinal HIV data from which incidence can be computed is scarce. Our objective was to estimate the force of infection and incidence of HIV in Malawi using cross-sectional HIV sero-prevalence data from the Malawi Demographic and Health Survey conducted in 2004. METHODS: We formulated a recurrence relation of population prevalence as a function of a piecewise-constant force of HIV infection. The relation adjusts for natural and HIV-induced mortality. The parameters of the recurrence relation were estimated using maximum likelihood, and confidence intervals of parameter estimates were constructed by bootstrapping. We assessed the fit of the model using the Pearson Chi-square goodness of fit test. We estimated population incidence from the force of infection by accounting for the prevalence, as the force of infection applies only to the HIV-negative part of the population. RESULTS: The estimated HIV population incidence per 100,000 person-years among men is 610 for the 15-24 year age range, 2700 for the 25-34 group and 1320 for 35-49 year olds. For females, the estimates are 2030 for 15-24 year olds, 1710 for 25-34 year olds and 1730 for 35-49 year olds. CONCLUSIONS: Our method provides a simple way of simultaneously estimating the incidence rate of HIV and the age-specific population prevalence for single ages using population-based cross-sectional sero-prevalence data. The estimated incidence rates depend on the HIV and natural mortalities used in the estimation process.

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