Information Technology and Farm Households in Niger
Information technology has transformed markets in developing countries faster than ever imagined. This is particularly dramatic in the rural areas of sub-Saharan Africa, where mobile phone infrastructure often represents the first modern infrastructure of any kind. It is estimated that over 60 percent of the population in sub-Saharan Africa has access to mobile phone service, with over 400 million subscribers.This technology has greatly reduced communication and search costs for rural households, especially compared with traditional methods of searching for information. High search costs are more than a theoretical concern, as they can have important welfare implications for rural households in sub-Saharan Africa. High search costs make it difficult for farmers to engage in optimal arbitrage; without information on the spatial distribution of prices, farmers might sell their commodities at lower than average prices in nearby markets. While policymakers have attempted to address these information constraints by providing price information via market information services (MIS), there is little evidence of their impact on farmers’ behavior and welfare, perhaps because they do not provide timely information on applicable markets.
As a result, mobile phone technology offers an important opportunity to overcome information constraints. A key challenge in measuring the impact of mobile phone coverage or ownership on rural households’ search costs, access to information and welfare is causal attribution. Simple correlations between mobile phone ownership and higher farm-gate prices or incomes does not imply a causal relationship. Rather, it is possible that more active and motivated farmers own mobile phones and therefore have better outcomes. This technical report therefore exploits a randomized experiment in Niger, which provided access to group mobile phones and taught farmers how to use them (Project ABC). By exploiting the exogenous variation in mobile phone access across farmers, we are able to causally identify the impact of mobile phone usage on agricultural outcomes.