Nonclassical measurement error and farmers' response to information treatment

This paper reports on a randomized experiment conducted among Malawian agricultural households to study nonclassical measurement error (NCME) in self-reported plot area, and farmers' responses to new information - the objective plot area measure - subsequently provided to them. Farmers' pre-treatment self-reported plot areas exhibit considerable NCME. Most of the measurement error follows a regression-to-mean pattern with respect to plot area, and another 18 percent arises from asymmetric rounding to half acre increments. Randomized provision of GPS-based measures of true plot area generates four important findings. First, most treated farmers' self-reports exhibit no reduction in NCME after the provision of true plot area measures. Second, farmers update asymmetrically in response to information, with upward corrections being far more common than downward ones even though most plot sizes were initially overestimated. Third, the magnitude of updating varies by true plot area, as well as the magnitude and direction of initial NCME. Fourth, the information treatment affects self-reported information about non-land inputs such as fertilizer and labor, indicating that the effects of measurement error and updating spillover across variables. NCME clearly carries implications for survey data collection methods, econometric inference, and the design of information-based interventions. It might also reflect behavioral anomalies that may matter for farm management practices, input allocation, agricultural productivity, and the design of effective interventions.

Automated summary

This paper reports on a randomized experiment conducted among Malawian agricultural households to study nonclassical measurement error (NCME) in self-reported plot area, and farmers' responses to new information - the objective plot area measure - subsequently provided to them. The experiment shows that most farmers have significant NCME in their self-reported plot areas, and the provision of true plot area measures through GPS has important effects on their self-reported data. This has implications for survey data collection methods, econometric inference, and the design of information-based interventions, as well as potential implications for farm management practices, input allocation, agricultural productivity, and the design of effective interventions.