Department of Agricultural Economics and Agribusiness

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    Ghana
    (Beyond Food Production: The Role of Agriculture in Poverty Reduction, 2007) Al-Hassan, R.M.; Jatoe, J.B.D.
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    Impact of Bioenergy Crop Adoption on Total Crop Incomes of Farmers in Northern Ghana: The Case of Jatropha Curcas
    (Building a Resilient and Sustainable Agriculture in Sub-Saharan Africa, 2018-06) Kemeze, L.S.; Mensah-Bonsu, A.; Egyir, I.S.; Amegashie, D.P.K.; Nlom, J.H.
    The present study examines the adoption of Jatropha Curcas as a bioenergy crop in West Mamprusi and Mion districts of Northern Ghana. A gender analysis is also undertaken. Using data from 400 farmers, the study employs a propensity score matching method to analyze the impact of the adoption of Jatropha Curcas on total crop incomes of farmers. The study concludes that Jatropha adoption significantly reduces the level of crop income per hectare of farmers. The reduction is worse for women-headed households compared to men. Specifically, the Average Treatment effect on the Treated (ATT) estimate is GHC −385.23 per hectare for the whole sample. The study recommends the development of appropriate strategies and a regulatory framework to harness the potential economic opportunities from Jatropha cultivation.
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    Spatial Price Transmission and Market Integration Analysis: The Case of Maize Market in Ghana
    (University of Ghana, 2014-07) Ayeduvor, S.; University of Ghana, College of Humanities , School of Arts , Department of Philosophy and Classics; University of Ghana, College of Humanities , School of Arts , Department of Philosophy and Classics
    This study presents an analysis of spatial price transmission and market integration of major maize markets in Ghana over the period 1995-2013. Monthly wholesale maize prices for the various markets were used for the analysis. The Augmented-Dickey Fuller test was used to test for the stationarity of individual price series and was confirmed by the KPSS test. All the price series data that were used tested for Unit Root. They were found to be non-stationary at levels but stationary after first difference at 1%, 5% and 10% significant levels. Johansen Maximum likelihood cointegration test was used to test the cointegration between the market pairs. It was found that all five market pairs were cointegrated. The proof of cointegration is also evidence for a common domestic maize market in Ghana, where inter-market prices adjust to achieve long-run, market equilibrium. The speed of adjustment and half lives from the vector error correction model shows that averagely, 8.2% of any disequilibrium was corrected within a month by the producer markets, while 12.4% of such shocks were corrected within a month by consumer markets. The net producer markets will return to equilibrium in 10 months while net consumer markets will return to equilibrium by 5 months after a shock. This means that shocks are quickly corrected by consumer market than by producer markets. Also adjustment to shock was characterized by asymmetry in that adjustments to price increases are corrected faster than price decreases. Two out of five market pairs exhibited asymmetry in price transmission while the remaining three were statistically not significant. The inventory and stock holding behavior of traders was the cause of asymmetry in price transmission. The evidence of price causation and leadership by Granger causality test shows Techiman as price leaders. In all, the findings indicate that major maize markets in Ghana are well integrated. It is therefore recommended that policy initiatives be directed towards ensuring efficient transportation of agricultural commodities across markets. These include investment in new transporting vehicles, rail/road construction and maintenance. These may contribute to reducing transaction costs and subsequently improving market integration and the imperfection observed in the maize market in Ghana. Also it is recommended that inventory and stock behaviour of traders be improved through investment in storage facilities by the government given the seasonal nature of the commodity. This can ensure even flow of maize throughout the season and enhance traders’ response to both positive and negative shocks.