Abstract
AbstractWe explore the relationship between precision agriculture (PA) technology adoption and technical efficiency using the 2016 USDA Agricultural Resource Management Survey (ARMS). Efficiency gains from PA are likely cumulative, that is, the true impact of precision farming depends on the integration of complementary tools. To examine the efficiency benefits of different PA bundles, we perform a two‐step analysis. First, we use cluster analysis to identify distinct producer groups based on patterns in PA technology adoption. These producer groups map naturally onto the classic technology adoption curve (laggards, late majority, early majority, innovators). Second, we use stochastic frontier analysis (SFA) and stochastic meta‐frontier analysis (SMFA) to estimate differences in technical efficiency between PA adoption groups. We find that farms with advanced PA technology bundles are significantly more technically efficient than non‐adopters. Differences in technical efficiency are not found to be driven by heterogeneous production technologies, but rather inefficiencies in input usage at the farm level. Our results have strong implications for farm consolidation in US agriculture.
Highlights
Precision agriculture (PA) uses inter- and intra-field variation to optimize input application and increase profitability
We assess the ability of PA to improve output-oriented technical efficiency using previously unanalyzed data from the 2016 Agricultural Resource Management Survey (ARMS) survey based on observed adoption paths
We first sort farms into groups according to their level and mix of PA technology adoption using hierarchical clustering
Summary
Precision agriculture (PA) uses inter- and intra-field variation to optimize input application and increase profitability. PA promises to enhance efficiency by reducing input costs without sacrificing yield, or by shifting the production frontier outward for a constant level of inputs. Technologies such as automated guidance systems, variable rate technology (VRT), and yield mapping have grown in popularity since their introduction in the 1990s, while newer technologies, including unmanned aerial vehicles (UAVs) and multi-spectral sensors, are being adopted more widely. Despite the promise of PA technology, its impact on efficiency is not well understood. Much of the research on PA adoption evaluates technologies independently without considering how producers often pool complementary tools to create overarching PA systems. Failure to examine PA collectively provides an incomplete picture regarding the benefits of PA adoption
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