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Displaying empirical distributions of conditional quantile estimates: an application of symbolic data analysis to the cost allocation problem in agriculture
[Affichage des distributions empiriques de conditionnel estimations quantiles: une application de l'analyse de données symboliques au problème de l'allocation des coûts en agriculture]

Author

Listed:
  • Dominique Desbois

    (ECO-PUB - Economie Publique - INRA - Institut National de la Recherche Agronomique - AgroParisTech)

Abstract

This paper uses the symbolic data analysis tools in order to display and analyze the conditional quantile estimates, with an application to the cost allocation problem in agriculture. After recalling the conceptual framework of the estimation of agricultural production costs, the first part presents the empirical data model, the quantile regression approach and the interval data techniques used as symbolic data analysis tools. The second part presents the comparative analysis of the econometric results for wheat between twelve European member states, using principal component analysis and hierarchic clustering of estimates and range of estimation intervals, discussing the relevance of the displays obtained for inter-country comparisons based on specific productivity.

Suggested Citation

  • Dominique Desbois, 2017. "Displaying empirical distributions of conditional quantile estimates: an application of symbolic data analysis to the cost allocation problem in agriculture [Affichage des distributions empiriques ," Post-Print hal-02735229, HAL.
    • Handle: RePEc:hal:journl:hal-02735229
    as

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