CONCLUSIONS 133
was implemented (NAADSNON-2) or those based elsewhere (NAADSNON-3). The estimated indirect effects of the program, which were obtained based on
comparison between the direct participants (NAADSDIR) and indirect partici- pants (NAADSNON-1), were surprising: they were consistently negative for the different outcomes analyzed, suggesting that the impacts of the program on
direct participants were not as great as the change observed among indirect participants. Because farmers in the group defined as indirect participants are not very familiar with the NAADS program, they may have confused NAADS service providers with agents of other programs, leading to an over- estimation of NAADS program effects for this group.
As expected, the impacts of the program were distributed differently across different groups of farmers in terms of gender, age, education, owner- ship of assets, and location. Furthermore, we find that different factors have contributed differently to enhancing or mitigating the effects of the program. The most striking result, one that is seemingly counterintuitive at first glance, is that the estimated average impact of the program was greater among households located relatively farther away from credit services and markets. This suggests that the NAADS program, by bringing farmers advisory services and grants for acquiring necessary technologies in addition to creat- ing market linkages, has been more effective in areas with poor access to the services and infrastructure needed to support technology adoption and increased commercialization of agricultural production. Where access to such services and infrastructure is good (including in areas closer to all-weather roads), farmers are able to acquire on their own the improved technologies being promoted by the NAADS program as well as related advisory services. In sum, the evidence, starting with the analysis of whether the NAADS program adequately induced participants to establish new enterprises or to adopt technologies and improved practices more frequently than their non- participating counterparts, seems patchy, with tenuous links, in terms of con- sistent sign and statistical significance across the different methods and model specifications, to increased productivity and commercialization of agriculture. Our underlying assumption is that participation in the NAADS program confers benefits via material inputs (seeds, livestock, fertilizers, etc.) that will lead to subsequent outcomes. But this assumption is not consistently validated in the results obtained. It is thus difficult to draw definitive conclusions regard- ing the direct impact of the NAADS program and, particularly, its indirect impact. This applies to our earlier results published in Benin et al. (2011). Although we have tried to account for several important issues that are critical for a reliable program evaluation study, a major limitation here is our inability to capture in our estimations the separate effect of access to other or non-NAADS extension services. Basically, the government’s regular exten-
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