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Add To Calendar 28/04/2016 13:50:0028/04/2016 14:10:00America/Los_AngelesAsian-Pacific Aquaculture 2016PRICE VOLATILITY IN THE AFRICAN CATFISH RESELLER MARKETS IN UGANDA Diamond 2The World Aquaculture Societyjohnc@was.orgfalseanrl65yqlzh3g1q0dme13067DD/MM/YYYY


James O. Bukenya
Department of Finance, Agribusiness and Economics
Alabama A&M University, Normal, AL 35762

The paper examines price volatility in the African catfish (Clarias gariepinus) markets in Uganda. An understanding of the structure of price volatility is of great interest since this is a major contributor to economic risk in the fisheries industry. Well-functioning markets transmit price signals, which allow changes in demand to be met by supply. When demand is greater than supply, producers increase production in response to price signals, and this increased production, in turn, helps to stabilize prices. By transmitting information in this way, markets help to reduce price volatility. The volatility process in catfish prices was analyzed based on monthly data from January 2006 to August 2013.

The analysis draws on price data for ex-vessel, wholesale and retail market channels. The ex-vessel prices were collected at different landing sites along Lake Victoria while corresponding retail and wholesale prices were gathered from fish markets in the central region. The GARCH model, which is widely used in various branches of econometrics, is used to estimate the volatility parameters. The model can be represented as  where  is a white noise term and defines the conditional variance. The model is estimated with a one-month lag in the ARCH and GARCH terms.

Figure 1 presents a plot of the series indicating increasing trends over the study period. Descriptive statistics reveal that ex-vessel and wholesale prices are moderately skewed to the right, indicating that the series have longer right tails than left tails while retail price are approximately symmetric. All series have kurtosis values lower than 3, and the Jarque-Bera statistics shows non-normal distribution for all series.

In a GARCH (1,1) model, the sum () measures the degree of volatility persistence in the market. Thus it reveals the degree of efficiency in the market, where the intuition is that if a market is completely efficient it should immediately correct to any shock. The results reveal evidence for volatility persistence estimated to 0.91, 0.62 and 0.90 for ex-vessel, wholesale and retail markets, respectively. The results suggest that the wholesale market displays a larger degree of efficiency than the ex-vessel and retail markets. Similar findings have been reported is previous fisheries studies. For instance, Buguk et al. (2003) found volatility persistence value for catfish equal to 0.98 while Oglend (2008) reported persistence value for salmon equal to 0.81.

The estimated degree of persistence in the respective markets was used to estimate the half-life of a volatility shock. The half-life estimates [] measures the time it takes for a shock to fall to half of its initial value. In this study, the results show half-life time of 7 months for the ex-vessel market, 1.4 months for the wholesale market and 6.5 months for the retail market. Based on the overall findings, catfish prices in Uganda exhibit substantial volatility.

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