A1002
Title: Forecasting agricultural land-use in England by using spatially highly resolution data
Authors: Namhyun Kim - University of Exeter (United Kingdom) [presenting]
Abstract: The aim is to introduce a new analytical framework for conducting an empirical analysis of agricultural land-use shares. The framework includes a nonparametric method of modelling the spatial patterns in the land-use shares, which capture an agglomeration and complementary effect across land grids in the most general way. This enables a more effective analysis of the interplay between land-use and its important determinants, for example, climate and environment policies, than those often used in existing works. The method is a semiparametric generalization of the well-known spatial lag dependence model in spatial econometrics. Furthermore, allowing the data to speak for themselves leads to a more accurate measure of the importance of spatial-physical environment, e.g. soil characteristics, textures, altitude and slope, and therefore helps to re-focus environmental policies.
