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

• Autorzy: Pompigna Andrea , Mauro Raffaele

Identyfikatory

DOI

10.5604/01.3001.0014.5512

• Języki publikacji: EN

Abstrakty

EN

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 references for their application in the freight transport field, the paper proposes the application of the SDA in the perspective 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 trans-ported 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 decomposition 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.

Słowa kluczowe

EN

freight traffic; input-output model; freight corridor; structural decomposition analysis

PL

ruch towarowy; model przepływów międzygałęziowych; korytarz towarowy; analiza rozkładu strukturalnego

• Wydawca: Warsaw University of Technology, Faculty of Transport
• Czasopismo: Archives of Transport
• Rocznik: 2020
• Tom: Vol. 56, iss. 4
• Strony: 19--31
• Opis fizyczny: Bibliogr. 40 poz., rys., tab., wykr.

Twórcy

autor

Pompigna Andrea

• DICAM, University of Trento, Trento, Italy

autor

Mauro Raffaele

• DICAM, University of Trento, Trento, Italy

Bibliografia

• [1] ALISES, A., VASSALLO, J. M., 2015. Comparison of road freight transport trends in Europe. Coupling and decoupling factors from an Input-Output structural decomposition analysis. Transportation Research Part A: Policy and Practice, 82, 141-157.
• [2] ALISES, A., VASSALLO, J. M., 2016. The impact of the structure of the economy on the evolution of road freight transport: a macro analysis from an Input-Output approach. Transportation Research Procedia, 14, 2870-2879.
• [3] ALISES, A., VASSALLO, J. M., GUZMÁN, A. F., 2014. Road freight transport decoupling: A comparative analysis between the UK and Spain. Transport Policy, 32, 186-193.
• [4] BACHMANN, C., KENNEDY, C., ROORDA, M. J., 2014. Applications of random-utility based multiregion input–output models of transport and the spatial economy. Transport Reviews, 34(4), 418–440.
• [5] BRUNEL, J., 2005. Freight transport and economic Growth: an empirical explanation of the coupling in the EU Using Panel Data. Transport Economics Laboratory (UMR-CNRS 5593). Université Lumière Lyon 2.
• [6] BURFISHER, M. E., 2017. Introduction to computable general equilibrium models. Cambridge University Press.
• [7] CASCETTA, E., MARZANO, V., PAPOLA, A., VITILLO, R., 2013. A multimodal elastic trade coefficients MRIO model for freight demand in Europe. In Freight Transport Modelling (pp. 45-68). Emerald Group Publishing Limited.
• [8] CHENERY, H., 1953. The structure and growth of the Italian economy. Regional Analysis (Chenery H., Clark P., eds.), United States Mutual Security Agency, Rome.
• [9] DE BOER, P., RODRIGUES, J. F., 2020. Decomposition analysis: when to use which method? Economic Systems Research, 32(1), 1-28.
• [10] DE LA BARRA, T., 1989. Integrated Land Use and Transport Modelling. Cambridge University Press.
• [11] DIETZENBACHER, E., LOS, B., 1998. Structural decomposition techniques: sense and sensitivity. Economic Systems Research, 10, 307-323.
• [12] DIXON, P. B., and JORGENSON, D. (Eds.), 2012. Handbook of computable general equilibrium modelling (Vol. 1). Newnes.
• [13] ISARD, W., 1951. Interregional and regional input-output analysis: a model of a space-economy. The review of Economics and Statistics, 318-328.
• [14] IC, 2019. ISTAT COEWEB, 2019. International Trade Statistics.
• [15] JIN, L., KOCKELMAN, K., ZHAO, Y., 2003. Tracking Land Use, Transport, and Industrial Production using Random-Utility based Multizonal Input-Output Models: Applications for Texas Trade. Proceedings of the 82nd TRB Meeting, Washington.
• [16] KOPPÁNY, K., 2017. Estimating growth contributions by structural decomposition of input-output tables. Acta Oeconomica, 67(4), 605-642.
• [17] KVEIBORG, O., FOSGERAU, M., 2007. Decomposing the Decoupling of Freight Traffic Growth and Economic Growth 1 Introduction. Transport Policy 14: 39-48.
• [18] LAKSHMANAN, T. R., HAN, X., 1997. Factors underlying transportation CO2 emissions in the USA: a decomposition analysis. Transportation Research Part D: Transport and Environment, 2(1), 1-15.
• [19] LU, I. J., LIN, S. J., LEWIS, C., 2007. Decomposition and decoupling effects of carbon dioxide emission from highway transportation in Taiwan, Germany, Japan and South Korea. Energy policy, 35(6), 3226-3235.
• [20] MAURO R., CATTANI, S., 2018. Freight traffic forecasts at the Brenner pass. Ingegneria Ferroviaria, (10), 1-24.
• [21] MAURO, R., POMPIGNA A., 2019. Dynamic aggregate models for forecasting of freight demand and road/railway modal split at the Brenner. Ingegneria Ferroviaria, (7-8), 555-589.
• [22] MAURO, R., POMPIGNA, A., 2020. Input-Output Models for freight transport demand forecasting. Ingegneria Ferroviaria (3), 181-203.
• [23] MCKINNON, A.C., 2007. The Decoupling of Road Freight Transport and Economic Growth Trends in the UK: An Exploratory Analysis. Transport Reviews 2006.
• [24] MILLER, R. E., BLAIR, P. D., 2009. Input-output analysis: foundations and extensions. Cambridge: Cambridge University Press.
• [25] MIN, Y., KOCKELMAN, K. M., ZHAO, Y., JIN, L., 2001. Models of location, trade and travel: an application of random utility based interzonal input-output models. In Proceedings of the 48th Annual North American Meetings of the Regional Science Association International.
• [26] MT, 2018. MONITRAF!, 2018. Annual Report 2018 Innovative technologies and the future of iMONITRAF!.
• [27] MOSES, L.N., 1955. The stability of interregional trading patterns and input-output analysis. American Economic Review, 45, 803-832.
• [28] NOCERA, S., CAVALLARO, F., GALATI, O. I., 2018. Options for reducing external costs from freight transport along the Brenner corridor. European Transport Research Review, 10(2), 53.
• [29] POMPIGNA, A., RUPI, F., 2018. Comparing practice-ready forecast models for weekly and monthly fluctuations of average daily traffic and enhancing accuracy by weighting methods. Journal of Traffic and Transportation Engineering (English Edition), 5(4), 239-253.
• [30] POMPIGNA, A., MAURO, R., 2020. In-put/Output models for freight transport demand: a macro approach to traffic analysis for a freight corridor. Archives of Transport, 54(2), 21-42. DOI: https://doi.org/10.5604/01.3001.0014.
• [31] ROSE, A., CASLER, S., 1996. Input–output structural decomposition analysis: a critical appraisal. Economic Systems Research, 8(1), 33-62. Lakshmanan, T. R., and Han, X. (1997).
• [32] SCHAFFER, W. A., 1999. Regional impact models. Regional Research Institute, West Virginia University.
• [33] SU, B., ANG, B. W., 2012. Structural decomposition analysis applied to energy and emissions: some methodological developments. Energy Economics, 34(1), 177-188.
• [34] TAVASSZY, L., DE JONG, G., 2014. Model-ling freight transport. Amsterdam: Elsevier. Leontief, W., 1986. Input–Output Economics. New York: Oxford University Press.
• [35] TIMILSINA, G. R., SHRESTHA, A., 2009. Factors affecting transport sector CO2 emissions growth in Latin American and Caribbean countries: an LMDI decomposition analysis. International Journal of Energy Research, 33(4), 396-414.
• [36] TIMMER, M. P., DIETZENBACHER, E., LOS, B., STEHRER, R., DE VRIES, G. J., 2015. An illustrated user guide to the world input-output database: the case of global automotive production. Review of International Economics, 23(3), 575-605.
• [37] TIMMERMANS, H. J., 2003. The saga of integrated land use-transport modeling: how many more dreams before we wake up? In Proceedings of the International Association of Traveler Behavior Conference.
• [38] UNEC, 2004. UNITED NATIONS. Economic Commission for Europe (unece), 2004. Producer Price Index Manual: Theory and Practice. International Monetary Fund.
• [39] YU, H., 2018. A review of input-output models on multisectoral modelling of transportation–economic linkages. Transport Reviews, 38(5), 654-677.
• [40] ZHANG, M., LI, H., ZHOU, M., MU, H., 2011. Decomposition analysis of energy consumption in Chinese transportation sector. Applied Energy, 88(6), 2279-2285.