36 CHAPTER 3


literature on the issues addressed here, within the limitations of the data. The aim of the NAADS program is to help strengthen the institutional capac- ity and human resource skills of farmers to demand and manage the delivery of agricultural advisory services that meet their local production and market conditions. Thus, assuming that participation in the NAADS program confers these benefits on participating farmers backed by access to program grants that allow them to acquire the necessary technologies, participation should lead to greater agricultural productivity and increased incomes, among other benefits, via greater adoption of profitable enterprises and technologies and related practices and information, all other factors remaining the same. On the other hand, participating farmers may be limited in achieving the expected outcomes of the NAADS program to the extent that participation is not commensurate with the empowerment of farmers to effectively demand advisory services. We did not explicitly capture in the estimation the type and quality of services provided or how participants actually used any ser- vices received. We assume that the effect of service providers is the same across all households within the jurisdiction of their service provision, which is captured by the variables measured at the subcounty level. The fixed- effect time-invariant regional dummies may also capture some of this effect. A finding of a lack of (significant) impact could also derive from the way we capture the enterprise-based nature of the NAADS program with the variable that measures the main income-generating activity (crops, livestock, etc.) of a household. Ideally, matching could be done for specific enterprises. How- ever, households engage in multiple activities and enterprises, and different enterprises are introduced in different subcounties (more on this in the next chapter), so performing the match enterprise by enterprise results in very few valid observations for reliable estimation.


Based on the design features of the NAADS program, too, we acknowl- edge that the participation decision (i.e., determinants) could be different for the direct and indirect participants. We tried different combinations of explanatory variables and their transformations in the estimation of both decisions to examine how they are indeed different in affecting the results. Furthermore, we expect the characteristics of the two groups to be different to the extent that the principles of the program were indeed implemented. For example, if the program’s principle of targeting the economically active poor—those with limited physical and financial assets, skills, and knowledge rather than destitute or large-scale farmers—was upheld, one could expect the direct participants to have been significantly different in terms of these characteristics prior to implementation of the program when compared to nonparticipants or indirect participants in the program. These characteristics are testable, and our findings show that direct participants in 2004 were on


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