Spatial Econometric Approach to the Economics of Site-Specific Nitrogen Management in Corn Production

The objective of this study is to determine the potential for using spatial econometric analysis of combine yield monitor data to estimate the site-specific crop response functions. The specific case study is for site-specific nitrogen (N) application to corn production in Argentina. Spatial structure of the yield data is modeled with landscape variables, spatially autoregressive error and groupwise heteroskedasticity. Results suggest that N response differs by landscape position, and that site-specific application may be modestly profitable. Profitability depends on the model specification used, with all spatial models consistently indicating profitability, whereas the nonspatial models do not. Key words: Argentina, corn, precision agriculture, site-specific nitrogen management, spatial autocor-relation, spatial econometrics, variable rate. Geographic information systems (GIS) and global positioning systems (GPS) are trans-forming large-scale commercial agriculture throughout the world. This technology is of-ten labeled “precision agriculture ” and has given new life to the old idea of site-specific management (SSM) by reducing the cost of information acquisition and variable rate in-put application. One of the key constraints to adoption has been difficulties in analysis of spatial crop and livestock data (Bullock, Swinton, and Lowenberg-DeBoer). The gap between data analysis and site-specific rec-ommendations makes it difficult to determine how seed, pesticide, fertilizer, and other in-puts should be varied across space to maxi-mize profits, minimize environmental impacts, and achieve other goals. Classical statistics ap