Farmers’ knowledge improves identification of drought impacts: A nationwide statistical analysis in Zambia

Climate adaptation policies rely on accurate estimates of weather-related impacts on community-level food insecurity. These estimates must capture local livelihoods and their varying sensitivity to climate extremes. This paper develops a novel methodology to address this need through incorporating farmer knowledge into robust drought impact assessments.

Using a new dataset of 925 farmer focus groups in Zambia, we investigate whether farmers’ recollection can identify consequential drought events more consistently than crop yields, which are conventionally used for this purpose. Zambia, like many countries, has experienced structural changes in its crop production systems over the last 30 years. Staple crop yields are therefore a weak proxy for food insecurity without wider socio-economic and agricultural context. We posit that in settings like this, farmers’ knowledge can provide the missing context for what constitutes a meaningful climate shock.

We conduct a statistical analysis of the dominant patterns of variability in farmers’ recollected drought years as compared to satellite rainfall. We find that farmers’ recall identifies meteorologically consistent patterns in shocks, going back 40 years. In contrast, conventional methods of regressing weather on maize yields to measure shocks would result in estimates that are biased and overconfident. Our analysis demonstrates, for the first time at a national scale, that farmers’ knowledge of climate shocks is a uniquely reliable source of impact data.