Applying Interval Clustering to Quantile Estimates: Empirical Distributions of Fertilizer Cost Estimates for European Countries

Application de la classification par intervalles aux quantiles estimés: distributions empiriques des estimations du coût des engrais pour les pays européens

Dominique Desbois ()

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Abstract: The decision to adopt one or another of the sustainable land management alternatives should not be based solely on their respective benefits in terms of climate change mitigation but also based on the performances of the productive systems used by farm holdings, assessing their environmental impacts through the cost of specific resources used. This communication uses the symbolic clustering tools in order to analyse the conditional quantile estimates of the fertilizer costs of specific productions in agriculture, as a replacement proxy for internal soil erosion costs. After recalling the conceptual framework of the estimation of agricultural production costs, we present the empirical data model, the quantile regression approach and the symbolic clustering tools used to obtain typologies of European countries on the basis of the conditional quantile distributions of fertilizer cost empirical estimates. The comparative analysis of econometric results for main products between European countries illustrates the relevance of the typologies obtained for international comparisons based on their input specific productivity.

Keywords: interval estimates; symbolic clustering; specific cost; empirical distributions; quantile regression; European countries; agricultural product; principal component analysis; hierarchic clustering; input-output model; symbolic data analysis; agricultural production cost; fertilizer; yearly crops; micro-economics; régression quantile; produit agricole : pays européens; coût spécifique; distributions empiriques; classification symbolique; intervalles d'estimation (search for similar items in EconPapers)
Date: 2020-06-02
New Economics Papers: this item is included in nep-agr, nep-eff and nep-env
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Published in SMTDA2020 & Demographics2020, ASMDA International, Jun 2020, Barcelona, Spain. pp.40

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