Agriculture Reference
In-Depth Information
combination, reducing uncertainty in the staple food price indices due to missing informa-
tion. The commodity price indices were averaged to form a country price index for each
country, and a similar method was used to create regional indices. The 2004-11 time period
captures more than 75 percent of the price data from 18 of the 35 countries, between 50 and
75 percent of the price data from ten of the countries and between 25 and 50 percent of the
price data from six countries. The FEWS NET price indices reflect the average rate of price
change for a bundle of key staple cereals that are consumed in each food insecure country.
Results from price index analysis
Plate 12 shows results from East, South and West Africa price indices, compared to the FAO
cereals index. The plate shows three series from each region: a regional cereal price index
created from markets in the surplus, minor deficit and major deficit zones. Each zone has a
different time series and shows variability for each period derived from the spread of price
observations among all the markets in each region. The plate shows considerable difference
among the regional cereal price index for these three zones.
The plate shows the differences among the surplus, deficit and major deficit regions, and
how these are only poorly correlated to the FAO cereals index. The major surplus and minor
deficit zones seemed to be more correlated with each other than with the major deficit zones.
Examining the time series for East Africa shows a clear lag between the peak cereal prices
occurring in the FAO index in 2007 and price increases in East Africa, particularly in the
minor deficit zones. West African price indices show much lower variability across markets
than the east and southern regions, particularly in the higher price periods. There were many
more high prices in the surplus markets in all three markets, six months after the FAO price
peak, which were not as pronounced in the major deficit zones. This may be a result of pro-
ducer prices rising due to the influence of the value of commodities in these regions.
Plate 13 shows the time series of the cereals, non-cereals and all food price indices for each
region. In East and West Africa, the cereals and non-cereal prices seem to be very similar. In
Southern Africa, the non-cereal prices are far more variable than the non-cereal time series.
In Central Asia, non-cereal price series (consisting of locally produced wheat flour and pota-
toes) are completely unrelated to the cereals time series, and do not show the price increase
seen in 2007-08 at all (Brown et al ., 2012).
Relationship between FAO cereals and local food price indices
When we take the data shown in Plate 13 and compare it statistically with the FAO cereals
index at the regional scale, we are able to determine if a region as a whole is integrated or not
integrated into the world market. Table 5.4 shows the results of the Granger-causality test,
with local cereal prices in regions that are integrated into the global market shown in grey.
The results of the analysis show that in East Africa, wheat, corn and rice are derived from the
international markets in the capital and non-capital cities. Non-cereals that are often con-
sumed by the poor are not related to international prices. These non-cereals include mixed
teff, sorghum, beans and cassava in East Africa.
The results for Southern and West Africa show that these two regions are not integrated
into the international markets. West Africa in particular shows no relationship at all with the
international markets, indicating its particularly isolated position in the global marketplace.
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