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

Spatial technologies such as GPS and GIS increasingly form the basis for site-specific management in crop production. This paper assesses the contribution of an explicit spatial econometric methodology in the estimation of crop yield functions that are used to optimize fertilizer application. The specific case study is for Nitrogen (N) application to corn production in Argentina, where the implementation of variable rate technology (VRT) requires methods that use inexpensive information and that focus on the inputs and variability common to Argentine growing areas. The objective of the paper is to assess the economic value of the application of spatial regression analysis to yield monitor data as a means to optimize variable rate fertilizer strategies. The data in the case study are from onfarm trials with a uniform N rate along strips and a randomized complete block design to estimate site-specific crop response functions. Spatial autocorrelation and spatial heterogeneity are taken into account in regression estimation of N response functions by landscape position, in the form of both a spatial autoregressive error structure and groupwise heteroskedasticity. Both uniform rate and VRT returns are computed from a partial budget model. The results suggest that N response differs significantly by landscape position, and that VRA for N may be modestly profitable depending on the VRT fee level Profitability depends crucially on the model specification used, with all spatial models consistently suggesting profitability, whereas the non-spatial models do not.