Farmers agronomic management responses to extreme drought and rice yields in Bihar, India - Mkondiwa, Maxwell; Kishore, Avinash; Veettil, Prakashan Chellattan; Sherpa, Sonam; Saxena, Satyam; Pinjarla, Bhavani; Urfels, Anton; Poonia, Shishpal; Ajay, Anurag; Craufurd, Peter; Malik, Ram K.; McDonald, Andrew J. (SSRN, 2024)
In 2022, the Indian state of Bihar experienced its sixth driest year in over a century. To document the consequences and farmer responses to drought, we collected real-time survey data across 11 districts of Bihar. We then developed a causal machine learning model to quantify the impacts of this drought and how access to affordable irrigation (through electric pumps) affected agronomic behavioural responses to the drought and ultimately determined rice yield losses. Our model addresses the empirical challenge of identifying a credible control group and conducting a counterfactual causal analysis when a factor like drought is widespread and affects nearly all sampled farmers. We find that droughts led to rice acreage reduction, transplanting delays, nursery losses, and more irrigation. For fields that were planted, we also document substantial yield losses from water stress averaging 0.94 t/ha (about 23% yield loss) with partial adaptation (0.3 t/ha) achieved through owned electric tubewell irrigation. Complementary behavioural agronomic management responses to a drought like early transplanting would have improved adaptation effectiveness of the affordable irrigation. To be effective against droughts, the huge investments in electric irrigation infrastructure appear to require complementary agricultural extension support to encourage farmers to make economically rational use of available water resources to maintain yield and profitability.