Using synthetic farm data to estimate individual nitrate leaching levels

A-Tier
Journal: American Journal of Agricultural Economics
Year: 2026
Volume: 108
Issue: 1
Pages: 336-362

Authors (3)

Konstantinos Mattas (not in RePEc) Michail Tsagris (not in RePEc) Vangelis Tzouvelekas (University of Crete)

Score contribution per author:

1.341 = (α=2.01 / 3 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

This article delineates a synthetic population generation scheme in an attempt to estimate individual nitrate leaching rates among Greek farms in the region of Thessaly. The proposed scheme relies upon the construction of a Bayesian network describing farming activities in the region, which, coupled with the use of nonparametric regression models, facilitate the consistent generation of synthetic farm data. Then, building upon the sequential generalized maximum entropy approach suggested by Kaplan et al., enhanced with the multiple production relations model proposed by Murty et al., we obtain econometric estimates of the unified farm production and nitrate leaching technology for the synthetic population of farms. The estimation of individual nitrate emissions leads, thus, to the formulation of an optimal taxation scheme aiming to mitigate the negative externality created by chemical fertilization in agricultural activities.

Technical Details

RePEc Handle
repec:wly:ajagec:v:108:y:2026:i:1:p:336-362
Journal Field
Agricultural
Author Count
3
Added to Database
2026-01-29