The Future of Smallholder Farming in Eastern Africa - Uganda ...

The variables in the model should first be confirmed to be stationary. Cointegration implies
Granger causality in at least one direction, but this relationship may be violated depending on
the number of missing values in the cointegration model and the error correction model. If
price movements in market j precede price movements in market i, then the ΔΡ i, t-m terms
should have a significant effect on ΔΡ i, t . To verify the existence or otherwise of Granger
causality, an F-test is conducted on the null hypothesis that the coefficients α i 2, and λ i h (h=
1,…,n i ) are jointly equal to zero.
2.3.4 Infrastructure and Government Policy
Data collected from traders using the structured questionnaire were studied to learn how
traders perceive the role of government in influencing maize marketing. Results indicate the
number and proportion of traders (and their characteristics) citing a particular factor as an
impediment to the efficient marketing of maize. The issues considered important in
facilitating or impeding the private sector response to liberalization include infrastructure
(road network, rural feeder roads, storage facilities, and market centers), flow of market
information, capital and credit availability, government rules and regulations, and an
uncertain policy environment.
3.0 RESULTS AND DISCUSSION
3.1 Effects of Liberalization on Prices
Nominal maize prices in surplus and deficit regions exhibited an increasing trend and
substantial fluctuations in both the pre- and postliberalization eras. Real prices, however,
exhibited a slightly declining trend suggesting that liberalization may lead to reduced
consumer prices for maize. Figure 3 presents the trends in nominal maize price series for
Kiritiri and Siakago markets in Mbeere District, Kitale in Trans Nzoia District, Nairobi, and
Migori and Awendo in Migori District. Some summary statistics of the prices are presented
in Table 3. The mean nominal price was significantly higher at the 1 percent level in the
postliberalization period than in the preliberalization period. Real prices showed no
significant differences between the two periods. In addition, prices exhibited higher
variability in the postliberalization period as indicated by the larger ranges and lower
coefficients of variation.
The increase in price volatility after liberalization suggests that traders have not engaged in
effective temporal arbitrage that could stabilize prices. Traders and farmers have failed to
store grain owing to a lack of appropriate storage facilities and technologies and to a
perceived market risk as reported later in this report.
Table 3--Summary statistics of price series (KSh.)
Market Era Maximum Minimum Mean Standard CV a
deviation
Kiritiri Preliberalization 1,120 200 518 282 0.54
Postliberalization 1,800 400 1,052* 389 0.37
Siakago Preliberalization 1,200 200 529 295 0.56
Postliberalization 1,800 480 1,072* 391 0.36
Kitale Preliberalization 941 283 557 201 0.36
Postliberalization 1,840 450 939* 320 0.34
Nairobi Preliberalization 1,200 320 657 280 0.43