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The relevance of inter-regional trade data produced by the 2012 Commodity Flow Survey for multi-regional CGE modelling

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  • Glyn Wittwer

Abstract

The objective of this study is to assess the suitability of Commodity Flow Survey (CFS) data released by the US Census Bureau as a check on the estimates of inter-regional trade generated in creating the USAGE-TERM master database. A close inspection of the Census Bureau's CFS data indicate that they record movements to and from transport nodes. In some cases, transport nodes may align with production origins and final use destinations. In other cases, nodes appear to be intermediate points rather than origins or final destinations. This implies that CFS data are often incompatible with the trade flows in a CGE database. Merchandise, that is primary and manufacturing commodities, account for no more than 15% of GDP in the U.S. economy. Therefore, even comprehensive merchandise trade flow data would have limited use in a CGE database. The usefulness of the CFS data is diminished further by its concentration on bulky goods, which account for a small fraction of total trade flows. Bulky trade flows may account for a substantial proportion of the volume of trade but make a small contribution to total economic activity. Mining products excluding oil and gas account for 50.9% of the recorded weight in the survey, but just 3.9% of the value of trades – and only 0.3% of GDP. The CFS data might be useful for examining transport logistics but are of little use in CGE database preparation. There is no evidence that the CFS data supersedes the Horridge gravity method of allocating inter-regional trades. However, CFS data point to the desirability of noting the difference between transport in the Mississippi basin and elsewhere. The basin relies heavily on water transport for moving agricultural, mining and fuel products.

Suggested Citation

  • Glyn Wittwer, 2017. "The relevance of inter-regional trade data produced by the 2012 Commodity Flow Survey for multi-regional CGE modelling," Centre of Policy Studies/IMPACT Centre Working Papers g-275, Victoria University, Centre of Policy Studies/IMPACT Centre.
    • Handle: RePEc:cop:wpaper:g-275
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    References listed on IDEAS

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    1. Peter B. Dixon & Maureen T. Rimmer & Glyn Wittwer, 2011. "Saving the Southern Murray‐Darling Basin: The Economic Effects of a Buyback of Irrigation Water," The Economic Record, The Economic Society of Australia, vol. 87(276), pages 153-168, March.
    2. Glyn Wittwer & Mark Horridge, 2010. "Bringing Regional Detail to a CGE Model using Census Data," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(2), pages 229-255.
    3. Adams, Philip D. & Parmenter, Brian R., 2013. "Computable General Equilibrium Modeling of Environmental Issues in Australia," Handbook of Computable General Equilibrium Modeling, in: Peter B. Dixon & Dale Jorgenson (ed.), Handbook of Computable General Equilibrium Modeling, edition 1, volume 1, chapter 0, pages 553-657, Elsevier.
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    1. Glyn Wittwer, 2022. "Preparing a multi-country, sub-national CGE model: EuroTERM including Ukraine," Centre of Policy Studies/IMPACT Centre Working Papers g-334, Victoria University, Centre of Policy Studies/IMPACT Centre.
    2. Glyn Wittwer & Mark Horridge, 2018. "SinoTERM365, Bottom-up Representation of China at the Prefectural Level," Centre of Policy Studies/IMPACT Centre Working Papers g-285, Victoria University, Centre of Policy Studies/IMPACT Centre.
    3. Standardi, Gabriele & Turdyeva, Natalia, 2019. "Testing a methodology to split a national SAM and compute intra-national trade flows: an application for the Russian regions," Conference papers 333050, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    4. Gabela, Julio Gustavo Fournier, 2020. "On the accuracy of gravity-RAS approaches used for inter-regional trade estimation: evidence using the 2005 inter-regional input–output table of Japan," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 32(4), pages 521-539.

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    More about this item

    Keywords

    Regional CGE modelling; inter-regional trades;

    JEL classification:

    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R13 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General Equilibrium and Welfare Economic Analysis of Regional Economies
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models

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