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Abstract

The interest in promoting food and water security through development projects has evolved to the need for tools that can evaluate the impact of these projects, and to ensure that the projects reach the most vulnerable (Gertler et al., 2011). This study brings together the stochastic frontier model with impact evaluation methodology to measure the impact on farmers’ technical efficiency (TE) within a modern irrigation technology transition framework. In this study, we apply the Heckman (1979) and Greene (2010) models to correct for selectivity bias that arises from unobserved variables, and then we measure and compare technical efficiency scores (TE) resulting from these models. The empirical application will use data covering 56 small-scale greenhouse farms, mainly cultivating vegetables, from the Ierapetra Valley in the Southeast part of the island of Crete (Greece) for the cropping years from 2009 to 2013. The results reveal that the average technical efficiency for farmers who adopted sprinklers is lower than the group of non-adopters when the presence of selectivity bias cannot be rejected. This outcome can be explained by the fact that after the adoption of new technologies, adopters may need more time to learn how to use the technology efficiently.

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