Rural Finance and Commitment Mechanisms in Agricultural Input Decisions


Evidence suggests that farmers may be more likely to buy fertilizer right after the harvest than at the beginning of planting season, when fertilizer is used. There are at least two possible explanations for this: farmers may lack credit access during planting season, or it may be that they are more willing to pay for fertilizer right after the harvest. In Mali, researchers are working with Innovations for Poverty Action, Soro Yiriwaso (a microfinance institution), and UNRIA (the national network of agriculture input dealers), to evaluate the relative importance of these two factors in farmers’ fertilizer-purchasing decisions.

Researchers are working with IPA to evaluate how the design and timing of commitment mechanisms, as well as access to credit, affects farmers’ decisions to buy fertilizer. To compare the impact of improved access to inputs and credit, researchers will randomly assign 140 villages to one of seven groups, comprising 20 villages each. These groups vary by the timing of agricultural input fairs and by the up-front payment required to take up credit.

In villages in six groups, UNRIA and Soro Yiriwaso are organizing an input fair. The remaining group serves as a comparison group and will not host at input fair. At the input fairs, farmers can buy agricultural inputs such as fertilizer from dealers at a central location. The timing of the input fairs varies, either right after the harvest (“early” input fairs) or at the start of the planting season (“late” input fairs). The agro-dealer then delivers the purchased inputs to farmers at the beginning of the planting season.

Of these six groups, farmers in three will be offered credit by Soro Yiriwaso while at the input fair while the other three groups will not. These financial products aim to encourage fertilizer purchases and require some up-front payment, which acts as a commitment mechanism. Some farmers are asked to make a 5 percent deposit on their purchase, a “soft” commitment mechanism, and other farmers are asked to make a 50 percent deposit, a “hard” commitment mechanism. Farmers must start repaying the remaining balance on the loan after the fertilizer is delivered. If farmers renege on their purchase, the deposit is given to the agro-dealer who sold the fertilizer.

The full breakdown is as follows:

Groups receiving access to credit at input fairs, where farmers will have the deposit made to the dealers by Soro Yiriwaso:

  • Group 1: Input fair right after harvest + 5 percent deposit
  • Group 2: Input fair right after harvest + 50 percent deposit
  • Group 3: Input fair at the beginning of planting season.

Groups not receiving access to credit, where farmers will pay dealers the deposit directly:

  • Group 4: Input fair right after harvest + 5 percent deposit
  • Group 5: Input fair right after harvest + 50 percent deposit
  • Group 6: Input fair at the beginning of planting season
  • Group 7: Comparison group

Through surveys and administrative data, researchers will measure the effect of commitment devices and offers of credit on input purchases, area of land cultivated, labor, and harvest values. Soro Yiriwaso will provide administrative data on credit history, the credit contract, repayments and default rates. UNRIA will provide administrative data on purchase orders and delivery of agricultural inputs. Researchers will also examine whether impacts differ for women and men.

Demand and Supply Constraints to Sorghum Adoption in Burkina Faso (with Isabelle Diabire (INERA Burkina Faso), Estelle Plat (Innovations for Poverty Action), Maria Porter (Michigan State), Melinda Smale (Michigan State), Nicolo Tomaselli (Innovations for Poverty Action), Adama Traore (INERA Burkina Faso))

Supply and demand constraints reduce adoption of improved sorghum technology in the West African Sahel. We will work with sorghum breeders and agro-input suppliers in Burkina Faso to compare alternative mechanisms to encourage adoption of improved seed and fertilizer micro-packs. A demand side treatment will be targeted by social network characteristics to understand the information effects of farmer take-up and spillover based on social network characteristics from a randomized distribution of micro-packs.  A social network census will reveal the extent to which villagers insure one another against idiosyncratic risk specifically through exchange of seed, use of complementary inputs, intahousehold labor substitution and assets. The supply side of the randomized control trial will test whether consistent market supply, credit constraints and farmer commitment explain low adoption and potential supply side marketing mechanisms to increase adoption. Comparisons of the effects of demand and supply side interventions will inform the development of index insurance to insure farmers against risk. Finally, we will examine the gender dimensions of adoption. If technology adoption diverts women’s labor from their fields to sorghum fields, the household’s dietary diversity and women’s income may decline, as well as induce intrahousehold labor substitution among women and children.