An Investigation of Industry Associations, Association Loops and Economic Complexity: Application to Canada and the United States
Various methods were proposed to understand the linkages in an input-output system; however, many have focused only on the identification of key sectors in the economy. An alternative approach, identifying analytically the importance of elements and combinations of elements was proposed as a field of influence theory (Sonis et al. , 1996). The purpose of this paper is to offer a complementary approach to the field of influence and the so-called 'Matrioshka principal' (Sonis & Hewings, 1990); the objectives are to identify simple row-column associations (i.e. statistical dependence), seek hierarchical associations between supply and demand in input-output systems and the decomposition of economic complexity into finite stages. For the identification of simple dependencies between rows and columns, we use a log-linear regression and for hierarchical associations and the identification of complexity stages, we use the data analysis technique known as dual scaling. Results of both approaches will be applied to input-output tables of the US and Canada.
Volume (Year): 14 (2002)
Issue (Month): 3 ()
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- Michael Sonis & J. D. Hewings & Jiemin Guo, 2000. "A New Image of Classical Key Sector Analysis: Minimum Information Decomposition of the Leontief Inverse," Economic Systems Research, Taylor & Francis Journals, vol. 12(3), pages 401-423.
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- Cella, Guido, 1984. "The Input-Output Measurement of Interindustry Linkages," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 46(1), pages 73-84, February.
- Sonis, Michael & Hewings, Geoffrey J.D., 1993. "Hierarchies of Regional Sub-Structures and Their Multipliers within Input-output Systems Miyazawa Revisited," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 34(1), pages 33-44, June.
- Clements, Benedict J., 1990. "On the decomposition and normalization of interindustry linkages," Economics Letters, Elsevier, vol. 33(4), pages 337-340, August.
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