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You reap what (you think) you sow? Evidence on farmers’behavioral adjustments in the case of correct crop varietal identification
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You reap what (you think) you sow? Evidence on farmers’behavioral adjustments in the case of correct crop varietal identification

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  • Paola Mallia

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

Adoption of improved seed varieties has the potential to lead to substantial pro ductivity increases in agriculture. However, only 36 percent of the farmers that grow an improved maize variety report doing so in Ethiopia. This paper provides the first causal evidence of the impact of misperception in improved maize varieties on farm ers' production decisions, productivity and profitability. We employ an Instrumental Variable approach that takes advantage of the roll-out of a governmental program that increases transparency in the seed sector. We find that farmers who correctly classify the improved maize variety grown experience large increases in inputs usage (urea, NPS, labor) and yields, but no statistically significant changes in other agricul tural practices or profits. Using machine learning techniques, we develop a model of interpolation to predict objectively measured varietal identification from farmers' self reported data which provides proof-of-concept towards scalable approaches to obtain reliable measures of crop varieties and allows us to extend the analysis to the nationally representative sample.

Suggested Citation

  • Paola Mallia, 2022. "You reap what (you think) you sow? Evidence on farmers’behavioral adjustments in the case of correct crop varietal identification," PSE Working Papers hal-03597332, HAL.
    • Handle: RePEc:hal:psewpa:hal-03597332
    Note: View the original document on HAL open archive server: https://pse.hal.science/hal-03597332v2
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