Bayesian spatial analysis of US agricultural land values

This study analyses the spatial patterns in agricultural land values using a Bayesian spatial econometrics approach. The model is motivated by land capitalisation theory, which captures the current value of a parcel of farmland as a discounted, future stream of returns associated with its agricultural use and pressures to convert the land. This study extends the land capitalisation model to incorporate variations in neighbouring agricultural lands. The results suggest that farmland prices are subject to spatial connectivities, implying that markets for cropland are highly localised, whereas markets for agricultural commodities are generally global in nature. The estimates imply that changes to neighbouring cropland rental rates and land enrolled in conservation explain about seven percent and eleven percent, respectively, of the variation in local land values.