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Innovation, Dynamic Regions and Regional Dynamics

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Part of the book series: Advances in Spatial Science ((ADVSPATIAL))

Abstract

The development of economic theory after World War II has focused on clarifying the necessary and sufficient conditions for the existence of an idealized general equilibrium. Debreu (1956), Arrow and Hahn (1971), and Scarf and Hansen (1973) established these conditions, building on earlier attempts by Cassel (1917) and Wald (1933–34, 1934–35). A key assumption in the formulation and proofs of the existence of a general equilibrium of a competitive economy is a large (or even infinite) number of buyers and sellers (Aumann 1964), which ensures anonymous markets and mutual independence of agents. Another assumption is the convexity of preference and production technology sets (Uzawa 1962). A third assumption is flexible pricing of goods and production factors.

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Notes

  1. 1.

    Since people and firms are highly concentrated in space of course we would not expect innovation to be randomly distributed across space. The problem is that we need a priori to formulate a null hypothesis about, what would constitute an “even distribution” (see Glaeser and Ellison 1997; Duranton and Overman 2005).

  2. 2.

    The same is true of new scientific knowledge.

  3. 3.

    This implies that product innovations in one industry often show up as process innovations in one or several other industries. What is a product or a process innovation depends upon the perspective taken in the analysis. In the case of consumer goods there is normally no need to make this type of distinction.

  4. 4.

    In Johansson (1993c), a quasi-dynamic model is applied to estimate how the economic milieu in municipalities influences the production in different manufacturing industries (see also, Johansson et al. 1991; Johansson and Karlsson 1994; Forslund and Johansson 1995).

  5. 5.

    The study by Holmberg and Johansson (1992) indicates, for example, that service sectors, such as wholesale, transportation, consulting and financial services are concentrated in municipalities in which the infrastructure facilitates interpersonal contacts and mobility.

  6. 6.

    A number of recent empirical studies illustrate the importance of “economic density” in functional regions (Ciccone and Hall 1996; Johansson 1996; Johansson et al. 1998; Karlsson and Pettersson 2005).

  7. 7.

    However, there are factors, which limit the growth of cities. Otherwise, cities would grow continuously. There are costs which rise with city size, most obviously prices (space in particular), and some external costs like congestion and pollution. Also probably, crime rises with city size.

  8. 8.

    The continual self-reorganizing and evolution of the global spatial economy at a macro scale can also be analyzed by applying the “new economic geography approach” (Fujita and Mori 1998).

  9. 9.

    For example, the “flying geese model” proposed by Fujita and Mori (1998) can be considered as a special case of the more general lead–lag model.

  10. 10.

    The lead–lag model does not apply to activities, which have to be harvested in the region where they are located. The location of such production is analysed by standard location advantage models, where the comparative advantages are of Ricardo type.

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Karlsson, C., Andersson, Å.E., Cheshire, P., Stough, R.R. (2009). Innovation, Dynamic Regions and Regional Dynamics. In: Karlsson, C., Andersson, A., Cheshire, P., Stough, R. (eds) New Directions in Regional Economic Development. Advances in Spatial Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01017-0_1

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