Displaying Empirical Distributions of Conditional Quantile Estimates: An Application of Symbolic Data Analysis to the Cost Allocation Problem in Agriculture

Abstract

This paper introduces some 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 symbolic data analysis techniques used. The second part presents the comparative analysis of the econometric results for wheat between 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.