Abstract
Panel models are largely used to analyse different and important topics in agricultural economics. The increasing use of panel data is presumably connected with the growing data set availability. Recently, many contributions have used spatial panel methodologies in agriculture. Spatial panel data consider cross sectional of geo-referenced spatial observations (i.e., countries, regions, and points) repeated across several time periods. This chapter wants to contribute to the literature in the field of spatial panel, highlighting the huge potential of those modelling strategies for agricultural data. In particular, the main aim is to show how spatial panel data models can be estimated in R through the library spml. The chapter presents the main theoretical specifications for spatial panel data models, the description of the panel approach to stochastic frontier analysis with a particular focus on agriculture, and the R codes for the estimation of a spatial stochastic frontier panel model.
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