Kate Vaiknoras, Catherine Larochelle, Jeffrey Alwang
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引用次数: 0
Abstract
New agricultural technologies, such as stress-tolerant rice varieties (STRVs), that reduce yield risk can modify farmers’ production decisions. This article explores how STRV adoption affects farmer decision-making and productivity in Nepal in a non-drought year. STRVs are bred to be high-yielding and tolerant to climate shocks such as drought. To assess the effect of input measurements on treatment effects, we collected information from 900 households on STRV adoption and input use. We also conducted a survey experiment in which half of sampled households were randomly assigned to answer additional, more detailed questions on agricultural inputs. Farmers apply more total chemical fertilizer, pesticides, early-season chemical fertilizer, and land preparation labor to plots planted with STRVs compared to traditional varieties (TVs). Detailed input data enhances our understanding of how this “crowding-in” effect of STRV adoption on input use compares with other high-yielding varieties. While farmers increase application of a subset of these inputs on other improved variety types such as hybrids, results suggest that crowd-in effects are most consistent for STRVs. In the absence of drought, STRVs also provide a similar yield boost and yield variance reduction over TVs compared to other, non-stress tolerant improved varieties. Results suggest that improved varietal adoption, and STRV adoption in particular, can improve household productivity and modernization of agriculture.
期刊介绍:
Agricultural Economics aims to disseminate the most important research results and policy analyses in our discipline, from all regions of the world. Topical coverage ranges from consumption and nutrition to land use and the environment, at every scale of analysis from households to markets and the macro-economy. Applicable methodologies include econometric estimation and statistical hypothesis testing, optimization and simulation models, descriptive reviews and policy analyses. We particularly encourage submission of empirical work that can be replicated and tested by others.