Can Mobile Technologies Enhance Productivity? A Structural Model and Evidence from Benin Food Suppliers

This paper analyzes the drivers of digital technologies adoption and how it affects the productivity of small scale businesses in Africa. We use data collected from two semi-rural markets in Benin, where grains and legumes are key staple foods and one-third of the population has internet access. We develop a structural model to rationalize digital technologies adoption—defined as the use of mobile broadband internet connection through smartphones—as well as usage patterns and outcomes observed in the data. The model’s implications are empirically tested using both reduced-form and structural maximum likelihood estimations. We find that younger, wealthier, more educated grains and legumes suppliers and those closely surrounded by other users are more likely to adopt digital technologies. Adopters perform 4-5 more business transactions each month than non-adopters on average, suggesting that digital technologies adoption could raise the monthly frequency and amounts of trades by up to 50%. Most adopters are women, but their productivity gains are lower than their male counterparts. Counterfactual policy simulations with the estimated model suggest that upgrading the broadband internet quality yields the largest improvement in adoption rate and productivity gains, while reducing its cost for a given connection quality only has a moderate effect. Improving access to credit only increases the adoption rate of constrained suppliers.