Farmers in developing countries routinely misperceive or misreport input quality for various reasons, which introduces substantial measurement error in farm survey data. In this paper, we motivate and illustrate, both analytically and empirically, the inferential and behavioral implications of misperception and misreporting using a unique crop variety identification data from Nigeria. Using a non-parametric framework for testing the presence of measurement error, we show that crop variety misclassification in our data is mostly driven by misperception. We then demonstrate the inferential challenges of treating misperception as misreporting and vice versa. Finally, we show that misperception induces crowding-in(out) of complementary agricultural inputs but these misperception-driven input allocations may not necessarily be yield-enhancing. As such, rectifying misperception by addressing agricultural input market imperfections may improve farmers’ investment choices and productivity outcomes.

https://dx.doi.org/10.1016/j.jdeveco.2022.102869

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Tesfamicheal Wossen Assfawhttps://orcid.org/0000-0002-3672-2676

Tahirou Abdoulayehttps://orcid.org/0000-0002-8072-1363

https://dx.doi.org/10.1016/j.jdeveco.2022.102869

Social Science and Agribusiness

Agribusiness; Agronomy; Farm Management; Farming Systems; Impact Assessment; Smallholder Farmers

Farm Inputs; Nigeria; Smallholders

Africa; West Africa

Nigeria

Eastern Africa Hub; Headquarters and Western Africa Hub

Journal of Development Economics