SUMMARY xxi
As expected, we found that not all enterprises were promoted by the NAADS program everywhere. The major crops promoted in terms of the number of subcounties in which they were promoted, the number of technology develop- ment sites (TDSs) established for them, or the number of farmer groups directly benefiting from the TDSs included bananas, groundnuts, and rice, followed by vanilla and maize. The major livestock and related enterprises involved goats, poultry, and bees, followed by cattle and pigs. Comparing the different types of enterprises, those involving livestock seemed to be more widely favored.
Participation in the NAADS Program
Although the NAADS program is a public investment intervention, farmers first have to decide whether or not to participate directly in the program through membership in a NAADS-participating farmer group through which individual farmers access grants to procure technologies and advisory services from private-sector service providers. In our sample, 9 percent were classified
as direct participants in the program (NAADSDIR); 36 percent were those in the same area where the program was implemented and claimed to have bene-
fited indirectly from the program (NAADSNON-1); 39 percent were those in the area where the program was implemented but did not claim any benefits
(NAADSNON-2); and the remaining 16 percent were those in areas where the program had never been implemented (NAADSNON-3). Regardless of the model specification or control group used in the analysis, we find that household
size has a statistically significant negative association with participation, sug- gesting that the NAADS program may be seen to offer immediate labor-saving technologies, such as pesticides, which reduce the labor needed for weeding, for example. Other factors with consistent sign across different specifications and control groups include sources of income (positive for livestock and non- farm activities and negative for other agriculture) and amount of land owned (negative). Most of the other covariates had different types of influence (sign, magnitude, and statistical significance) across different subgroups, reflecting different behavior of households based on their different endow- ments and resources to take advantage of the NAADS programs vis-à-vis their different levels of exposure or nonexposure to the program. Interestingly, we find that the longer the NAADS program has been in a subcounty, the lower the likelihood that farmers participate directly in the program, suggesting that farmers may be giving up direct participation with time. This reflects a declin- ing net gain from direct participation. Farmers may be dropping out due to lack of receipt of grants, increasing cost of participation relative to benefits from any grants, or failure of their preferred enterprise(s) to be selected among the three promoted in the subcounty.
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