A structural decomposition analysis for traffic demand assessment on a freight transport corridor

This paper deals with a Structural Decomposition (SDA) applied to the analysis of the freight traffic demand in an Input Output (IO) modelling context. After reviewing the basic definitions of IO models and some methodological refer-ences for their application in the freight transport field, the paper proposes the application of the SDA in the perspec-tive of a freight corridor. This application takes place downstream of an IO model that directly relates the quantities of goods transported along the corridor with the functioning of the reference economic system. Considering the evolution of tons annually transported in a certain time interval, the SDA model allows to isolate the specific effects related to: intensity of freight traffic typical of the corridor; technological structure of the production sectors; characteristics of the final demand in relation to its overall level, sectoral structure and allocation between components. The SDA model is applied to a case study considering the total volumes of goods annually in transit at the Brenner pass between 2000 and 2014. The evaluation of the polar forms of the multiplicative decomposition and their geometric mean allow to quantify the effects of each factor on the variation of the tonnage in terms of indexed value, absolute variation and percentage contribution compared to the base year (2000). The relative influences on freight traffic at the Brenner pass are therefore highlighted, both in terms of total volumes transited and impacts attributable to each of the decomposi-tion factors introduced, with particular evidence also in the event of periods of economic and financial crisis. The SDA specified in the paper and the related case study provide useful elements for studying the traffic demand of goods through a freight corridor, helping in outlining the effects of the different driving forces related to the economic system and affecting freight transport demand trends.