Land Markets in Agent Based Models of Structural Change

Copyright 2007 by [Konrad Kellermann, Christoph Sahrbacher, Alfons Balmann]. All rights reserved. Readers may make verbatim copies of this document for non-commercial purposes by any means, provided that this copyright notice appears on all such copies. 2 Abstract. Land markets play a crucial role in agricultural structural change. The dynamics on land markets mainly depend on the interactions between individual farms. Agent-based modelling (ABM) provides one way to take the specific characteristics of land transactions into account, as it allows to model interactions between different agents as well as spatial relationships in a straightforward manner. However, reviewing the literature one can find only a few attempts of endogenized land markets in ABM. Furthermore, it seems that the allocation mechanisms of these endogenized land markets are chosen rather arbitrarily and not much attention is given to an intensive discussion of the impact of the respective allocation mechanisms to simulation results. To close this gap the aim of this paper is threefold: First we want to give a brief review of existing ABM with endogenized land allocation mechanisms and we identify a theoretical framework which serves as a guidance to develop a suitable and extendable land market (sub-) model. Second, we derive a number of relevant design considerations necessary to endogenize land transactions in an agent based modelling framework. Based on this we propose three different land market implementations which are based on auction mechanisms. In order to be able to evaluate the different implementations not only in relative but also in absolute terms we furthermore propose an approach to create a global optimal allocation in terms of the resulting economic land rent. For this we use a mathematical programming approach to solve the underlying allocation problem and the concept of average shadow prices to price the allocated plots. In the third part we show the practical implications of different allocation mechanisms. This is done using the spatial and dynamic agent-based simulation model AgriPoliS as experimental laboratory. In that way we can analyse the properties of the respective allocation mechanisms in a realistic framework which is based on a detailed empirical calibration.