Abstract
This paper models inorganic fertilizer and improved maize varieties adoption as joint decisions. Controlling for household, plot-level, institutional and other factors, the study found that household adoption decisions on inorganic fertilizer and improved maize varieties were inter-dependent. Other factors found to influence the adoption of the two technologies were farmer characteristics, plot-level factors and market imperfections such as limited access to credit and input markets, and production risks. Thus, easing market imperfections is a pre-requisite for accelerating farm technology adoption among the smallholders. Inter-dependence of farm technologies must also not be ignored in farm technology adoption promotion initiatives.
Highlights
The Green Revolution which dramatically boosted the yield of cereals in Asia and Latin America is a clear manifestation of the potential of agricultural technologies in improving people’s lives especially in the developing world (Pray, 1981)
The estimated production risk factors were incorporated into the improved maize variety and inorganic fertilizer adoption models (Equations 14 and 15) which were estimated as bivariate probit to deal with simultaneity of technology adoption decisions
Remarkable success has been recorded in adoption of inorganic fertilizers and improved maize varieties wide disparities remain across geographical areas
Summary
The Green Revolution which dramatically boosted the yield of cereals in Asia and Latin America is a clear manifestation of the potential of agricultural technologies in improving people’s lives especially in the developing world (Pray, 1981). Some of the factors that possibly explain the rate of adoption and the long-run equilibrium level of use of new agricultural technology as identified in the economic literature include: credit constraints, risk aversion, the farmer’s landholding size, land tenure system, human capital endowment, quality and quantity of farm equipment, and supply of complementary inputs (Feder et al 1985). Other cross-sectional studies, though focusing on different technologies such as dairy and soil and water conservation, have found similar results (see Nicholson et al, 1999; Ogada et al 2010; Oostendorp and Zaal, 2011) These studies have three main limitations: they are based on cross-sectional data, they cover smaller geographical areas that cannot accurately reflect the diversity among farming communities and they use ordinary binary probit or logit which ignores the inter-dependence of agricultural technologies. The fact that universality of age, education and farm size was confirmed to be weak, one cannot assume that farm households in different locations respond to different technologies in the same way
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