Handling uncertainty in Multi Regional Input-Output models by entropy maximization and fuzzy programming

• We propose a method for Multi Regional Input-Output model for freight demand estimation.
• Uncertain, imprecise, spot information can be used.
• The method is based on entropy maximization principle and fuzzy optimization.
• The application shows the methods allow to consider uncertainty in available data with good estimation performances.
• It can be used not only in the case of freight demand estimation but in every problem involving MRIO model.

Recently, great attention has been paid to the uncertainties associated with Multi Regional Input-Output (MRIO) models related to the available data sources. We propose a new method based on the entropy maximization principle and fuzzy optimization, which takes explicitly into account the uncertainty embedded in available information. It allows to estimate jointly the values of production level, the trade coefficients and the final demand values assuming the availability of incomplete and/or approximate data on some elements of trade coefficients and of final demand of goods. The model, applied to real scale problem, shows good estimation performances and robustness in different scenario.