Research

Working papers

Incentivizing Social Learning for the Diffusion of Climate-Smart Agricultural Techniques

With Guigonan Serge Adjognon , Jonas Guthoff , and Daan van Soest
(World Bank Working Paper ; Up to date draft is available here.)

We implemented an RCT in arid Burkina Faso to estimate the impact of financial incentives on the adoption of sustainable land management practices. We did so in the context of a cascade training program, in which some farmers were trained in SLMP implementation, who were subsequently asked to disseminate their newly acquired knowledge and expertise to other farmers in their social networks. This paper reports two important findings. First, we find that offering payments conditional on adoption improves both the transfer of information from the trained to the peer farmers, as well as the peer farmers’ adoption rates. Offering financial incentives thus mitigates two key barriers to SLMP adoption: the (perceived) lack of private benefits, and insufficient diffusion of technical implementation information. Second, reminiscent of the Coase theorem, the effectiveness of the financial incentive in inducing adoption is independent of how the money is initially allocated between the trained farmers and their peers, implying that it is the size of the total surplus that drives both the adoption and information acquisition decision. Combined with the result that the returns to adoption are, in fact, sizeable, our findings suggest that subsequent diffusion of the technologies’ actual profitability will ultimately obviate the need for future adoption payments.

Subsidized Input and Technical Assistance for the Adoption of Sustainable Agriculture: Evidence from a Field experiment in Northern Ghana

With Paul Christian
(draft is available here)

Sustainable land management practices (SLMP) are expected to mitigate land degradation and dwindling agricultural productivity. We implement an RCT to evaluate the effectiveness of a one-time government subsidy and technical assistance program on SLMP take-up and agricultural productivity. The program provides farmers with inputs, labor assistance, and consultation to farmers to overcome input, labor, and informational constraints to adoption, free of charge. We find that the program not only increased SLMP usage of subsidized farmers, but also of farmers whose application for the program was rejected and who then did not receive support. Our results suggest that alleviating informational constrains and the diffusion of these information through social learning from admitted to rejected farmers likely account for the positive impacts on SLMP uptake, while alleviating input and labor constraints have smaller impacts. Despite the increased uptake, the program failed to mitigate (perceived) soil erosion or to increase agricultural productivity in the first two years of the intervention.

Combatting forest fires in the drylands of Sub-Saharan Africa: Quasi-experimental evidence from Burkina Faso

With Guigonan Serge Adjognon and Daan van Soest
(Revise and Resubmit - American Journal of Agricultural Economics; draft is available here)

Forest fires are among the main drivers of deforestation and forest degradation in the drylands of Sub-Saharan Africa. We use remote sensing data on forest fires and remaining tree cover to estimate the effectiveness of a project targeted at reducing fire incidences in twelve protected forests in arid Burkina Faso. The project consisted of two components that were implemented in the villages surrounding the target forests: a campaign aimed at raising community awareness about the detrimental effects of forest fires, and a program to support establishing and maintaining forest fire prevention infrastructures. Using the Synthetic Control Method we find thatthe project resulted in a 35% reduction in forest fire occurrences in the period of the year when they tend to be most prevalent – in November, at the very end of the agricultural season. This impact is, however, short-lived (as the reduction only occurred in the first four years of the program), and the reduction in forest fires did not result in a detectable increase in vegetation cover – because the reduction in the month of November was not sufficiently large to be captured via remote sending, or because the duration of the reduction was too short for the vegetation to recover. We then try to uncover the underlying mechanisms to shed light on which of the project’s components were effective, to also learn how the program can be improved.