Using Synthetic Farm Data to Estimate Individual Nitrate Leaching Levels

Konstantinos Mattas, Michail Tsagris and Vangelis Tzouvelekas

No 2401, Working Papers from University of Crete, Department of Economics

Abstract: he paper develops a novel synthetic population generation scheme to deal with the NPS pollution problem of nitrate leaching from agricultural farms. The scheme relies upon estimation of the joint distribution of the variables using Bayesian network learning which, coupled with the use of non-parametric regression models facilitate the generation of realistic synthetic populations. Then building upon the sequential GME model suggested by Kaplan et al., (2003) in line with the multiple production relations model suggested by Murty et al., (2012) we obtain econometric estimates of both the production technology and nature's residual generating mechanism for the synthetic population of farms. These estimates are used to proxy a reliable optimal taxation scheme that corresponds to local environmental and economic conditions. The methodology is applied to the Greek FADN dataset for the Greek NUTS II region of Thessaly during the 2017-18 cropping year.

Keywords: nitrate leaching; multiple production relations; Generalized Maximum Entropy; synthetic population generation; Bayesian network learning (search for similar items in EconPapers)
JEL-codes: C40 Q24 Q25 Q53 (search for similar items in EconPapers)
Pages: 37 pages
Date: 2024-02-06
New Economics Papers: this item is included in nep-agr
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