Misperceiving and misreporting input quality: Implications for input use and productivity
利用尼日利亚作物品种识别数据，分析农民误判或误报投入品质量的原因及其对投入品使用和生产力的影响，发现误判会导致互补投入品配置不当，纠正误判可改善投资选择和生产力。
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.