Regional Input–Output with Endogenous Internal and External Network Flows

  • John R. RoyEmail author
  • Geoffrey J.D. Hewings
Part of the Advances in Spatial Science book series (ADVSPATIAL)


Regional I–O analysis has a long history, including seminal works by Chenery (1953) and Leontief and Strout (1963), with the latter analysis seen as a disaggregation of the Leontief–Strout (L–S) approach. Other significant contributors include Isard et al. (1960), Polenske (1980), Hewings (1985), Miller and Blair (1985) and Oosterhaven (1988). An overview is provided in Roy (2004a). As more and more regional survey data became available, such analysis was approached with more confidence. In fact, regional I–O has become one of the most widely practiced techniques in the field of regional science. Before proceeding further, we need to clarify the terminology. For this, we turn to Isard et al. (1998). The first class of regional model which they define is the interregional model where both the flows and the I–O coefficients have four indices, that is, the flow of sector i into sector j from region r to region s. As it is extremely difficult to implement a full interregional model, most developments have concentrated on devising multi-regional models with less stringent data requirements. Although the dimensionality of these approaches reduces from four to three, different indices are absorbed in the flows compared to the I–O coefficients. The flows relate to the total flow of sector i as input to all other sectors between regions r and s, with the aggregation over destination sectors j. These flows are more likely to be available within freight statistics. The I–O coefficients relate to the amount of the sector i product being supplied as intermediate inputs to sector j in region s per unit of output of sector j in region s, aggregated over the different regions r which supply the inputs. It is precisely this different nature of the aggregation of the flows versus that over the I–O coefficients which creates the main challenge to development of sound multi-regional methods.


Transport Cost Base Period Intermediate Input Final Demand Component Flow 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Batten DF (1983) Spatial analysis of interacting economies. Kluwer, BostonGoogle Scholar
  2. Chenery H (1953) Regional analysis. In: Chenery H, Clark P, Pinna V (eds) The structure and growth of the Italian economy. US Mutual Security Agency, RomeGoogle Scholar
  3. Cole S (1997) Closure in Cole’s reformulated Leontief model: a response to R.W. Jackson, M Madden and H. A. Bowman. Pap Reg Sci 76:29–42Google Scholar
  4. Hewings GJD (1985) Regional input–output analysis. Sage, Beverly Hills, CAGoogle Scholar
  5. Hitomi K, Okuyama Y, Hewings GJD, Sonis M (2000) The role of interregional trade in generating change in the interregional Leontief inverse in Japan, 1980–1990. Econ Syst Res 12: 515–537Google Scholar
  6. Hotelling H (1932) Edgeworth’s taxation paradox and the nature of supply and demand functions. J Poli Econ 40:577–616CrossRefGoogle Scholar
  7. Isard W et al. (1960) Interregional and regional input–output techniques. In: Isard W et al. (ed) Methods of regional analysis, chap. 8. Wiley, New YorkGoogle Scholar
  8. Isard W et al. (1998) Methods of interregional and regional analysis. Ashgate, Brookfield, VTGoogle Scholar
  9. Jackson RW, Madden M (1999) Closing the case on closure in Cole’s model. Pap Reg Sci 78: 423–427CrossRefGoogle Scholar
  10. Johansson B (1991) Regional industrial analysis and vintage dynamics. Ann Reg Sci 23:1–18CrossRefGoogle Scholar
  11. Kim E, Hewings GJD, Hong C (2004) An application of an integrated transport network – multiregional CGE Model I: a framework for economic analysis of highway projects. Econ Syst Res 16:235–258CrossRefGoogle Scholar
  12. Leontief W, Strout A (1963) Multi-regional input–output analysis. In: Barna T (ed) Structural interdependence and economic development. Macmillan, LondonGoogle Scholar
  13. Miller RE, Blair PD (1985) Input–output analysis: foundations and extensions. Prentice-Hall, Englewood Cliffs, NJGoogle Scholar
  14. Oosterhaven J (1988) On the plausibility of the supply-driven input–output model. J Reg Sci 28:203–217CrossRefGoogle Scholar
  15. Oosterhaven J (2000) Lessons from the debate on Cole’s model closure. Pap Reg Sci 79:233–242CrossRefGoogle Scholar
  16. Polenske KR (1980) The U.S. multiregional input–output accounts and model. Lexington Books, Lexington, MAGoogle Scholar
  17. Roy JR (1987) An alternative information theory approach for modelling spatial interaction. Environ Plann A 19:385–394CrossRefGoogle Scholar
  18. Roy JR (2004a) Spatial interaction modelling: a regional science context. Advances in spatial science series. Springer, HeidelbergCrossRefGoogle Scholar
  19. Roy JR (2004b) Regional input–output analysis and uncertainty. Ann Reg Sci 38:397–412CrossRefGoogle Scholar
  20. Roy JR, Lesse PF (1985) Entropy models with entropy constraints on aggregated events. Environ Plann A 17:1669–1674CrossRefGoogle Scholar
  21. Smith TE (1990) Most-probable-state analysis: a method for testing probabilistic theories of population behaviour. In: Chatterji M, Kuenne RE (eds) New frontiers in regional science. MacMillan, London, pp 75–94Google Scholar
  22. Snickars F, Weibull J (1977) A minimum information principle: theory and practice. Reg Sci Urban Econ 7:137–168CrossRefGoogle Scholar
  23. Sohn J, Hewings GJD, Kim TJ, Lee JS, Jang SG (2004) Analysis of economic impacts of an earthquake on transportation networks. In: Okuyama Y, Chang S (eds) Modeling spatial and economic impacts of disasters. Springer, HeidelbergGoogle Scholar
  24. Wilson AG (1970) Entropy in urban and regional modelling. Pion, LondonGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  1. 1.ETUDESMallacootaAustralia
  2. 2.REALUniversity of IllinoisUrbanaUSA

Personalised recommendations