P o l i c i e s a n d I n s t i t u t i o n s t h a t D i s t o r t R e s o u r c e A ll o ca t i o n i n S u b - Sa h a r a n A f r i ca
cost to access knowledge and information can potentially raise rural incomes. Mobilephone coverage is strongly associated with greater market efficiency because it lowers the price dispersion of agricultural goods. For instance, mobile phones helped reduce grain price dispersion across markets in Niger by at least 6.5 percent and intra-annual price variation by 10 percent (Aker 2008). Specifically, the largest decline in price dispersion across Niger’s grain markets occurred in the first four months after getting mobilephone coverage, and the marginal impact has decreased over time (figure 4.5). The lower price dispersion is partly attributed to reduced search costs because grain traders with mobile-phone coverage had information about and access to more markets (Aker 2008, 2010). Mobile-phone coverage is more likely to lower the spatial price dispersion of agricultural products that are more perishable (for example, cowpeas), and this reduction is the largest for remote markets in certain periods of the year. In contrast, it has no significant
impact on (producer) price dispersion of products that are typically stored by farmers, such as millet and sorghum (Aker and Fafchamps 2015). Mobile-phone coverage can also help increase the market participation of farmers who are in remote areas and producing perishable goods. After the expansion of mobile-phone coverage, the share of Ugandan farmers selling bananas increased in the communities located more than 20 miles from district centers (Muto and Yamano 2009). Lower price dispersion was also observed among sardine fishers and wholesalers in the Indian state of Kerala because of greater mobile-phone coverage (Jensen 2007), as well as among smallholder Ghanaian farmers who used multiple data sources including open government data provided by Esoko18 (Schalkwyk, Young, and Verhulst 2017). In addition, access to digital technologies enables farmers to connect with agents and traders to estimate market demand and the selling price of their products, but the impact on farm gate prices is not conclusive.
FIGURE 4.5 Changes in Price Dispersion before and after Mobile-Phone Coverage in Niger’s Grain Markets 4 Monthly difference, CFAF per kilogram
3 2 1 0 –1 –2 –3 –4 –5 –6 –7 –8 –9 –5
–4
–3
–2
–1
0
1
2
3
4
5
6
Months pre- and post-mobile-phone coverage With year trend
Lower confidence interval
Upper confidence interval
Source: Aker 2008. Note: Price dispersion is regressed on a series of dummy variables pre- and post-mobile-phone coverage. Upper and lower confidence intervals are shown. CFAF = CFA franc.
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