Abstract

AbstractDespite the growing attention to technology adoption in the economics literature, knowledge gaps remain regarding why some valuable technologies are rapidly adopted, while others are not. This paper contributes to our understanding of agricultural technology adoption by showing that a focus on yield gains may, in some contexts, be misguided. We study a technology in Ethiopia that has no impact on yields, but that has nonetheless been widely adopted. Using three waves of panel data, we estimate a correlated random coefficient model and calculate the returns to improved chickpea in terms of yields, costs, and profits. We find that farmers’ comparative advantage does not play a significant role in their adoption decisions and hypothesize that this is due to the overall high economic returns to adoption, despite the limited yield impacts of the technology. Our results suggest economic measures of returns may be more relevant than increases in yields in explaining technology adoption decisions.

Highlights

  • Despite the growing attention to technology adoption in the economics literature, knowledge gaps remain regarding why some valuable technologies are rapidly adopted, while others are not

  • We explore whether the low average returns for yields hide substantial heterogeneity by testing to see if Suri’s (2011) solution to the puzzle for maize in Kenya holds for chickpea in Ethiopia

  • Recent studies of agricultural technology adoption have focused on the physical returns or on the imputed value for these physical returns

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Summary

Introduction

Despite the growing attention to technology adoption in the economics literature, knowledge gaps remain regarding why some valuable technologies are rapidly adopted, while others are not. We find that farmers’ comparative advantage does not play a significant role in their adoption decisions and hypothesize that this is due to the overall high economic returns to adoption, despite the limited yield impacts of the technology. Using a correlated random coefficient model, Suri (2011) confirms this hypothesis for hybrid maize adoption in Kenya According to this result, the empirical puzzle is only a puzzle when researchers fail to adequately control for heterogeneity in returns. Suri (2011) shows that in her data, farmers with low net returns either fail to adopt or disadopt the technology This explanation of the puzzle has gained strong traction in the adoption literature, as evinced by some 449 papers citing her results as of July 2018. In the face of limited sales opportunities due to missing or poorly functioning markets, the assumed equivalence between yields and economic returns may have led the literature astray.

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