SPATIAL HEDONIC PRICING MODELS FOR THE VALUATION OF IRRIGATION WATER

摘要

In this paper two spatial hedonic pricing models and a conventional one are presented and used in order to estimate the value of agricultural water, in the Municipality of Moudania, a rural area in Chalkidiki, Greece. The primary objective of this work is to apply the hedonic pricing method using the spatial econometrics methodology in conjunction with conventional econometrics in order to reveal the value of irrigation water from the agricultural land parcel value. A key feature of the proposed approach is that a GIS analysis of land parcels is a basic component. Hedonic pricing method is an indirect econometric method that estimates the individual values of the characteristics that constitute a good. In this work the good is the agricultural land parcel and the individual characteristics are the property and neighbor characteristics of the land as well as the irrigation water availability. Most of the times the neighbor attributes have spatial character in the hedonic model. Contrary to the variables that form the value of the land parcels, the hedonic pricing model is based on the assumption of spatial stationarity. Thus, spatial regression models are implemented to perform the analysis of spatial characteristics.To achieve the primary objective, i.e. to formulate the spatial hedonic pricing model, the spatial effects of the data are taken into account. The spatial effect, and in particular the spatial dependence, is a determinant of the efficiency and consistency of the hedonic model. In the standard linear regression, spatial dependence is usually incorporated in two ways: a) by including a spatially lagged depended variable and b) by including the spatial dependence of the error term. The first is the spatial lag model and the latter is the spatial error model.In this work, the application of spatial econometric models is presented together with the conventional model of multiple regression. Thus, using each one of the above approaches, the hedonic pricing function is formulated. Results show that the spatial methods increase the efficiency and consistency and reduce the bias of the parameter estimates. As expected, the spatial error model provides better results and it is, therefore, used to estimate the value of the irrigation water availability.