European Regional Growth by Bernard Fingleton (ed.)

By Bernard Fingleton (ed.)

European nearby progress is the results of 3 significant affects. First, the continued integration of the eu local economies and the necessity to comprehend what this suggests for eu monetary and social unity. moment, the advance of geo-economic theories. 3rd, the improvement of suggestions of spatial info research, simulation, information visualization and spatial econometrics. the result is a set of chapters that follow those equipment, inspired by way of a number of theoretical positions. The booklet offers strong and certain analyses of the factors of source of revenue, productiveness and employment adaptations throughout Europe's areas, and insights into their destiny prospects.

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28 52 B. J. (1962) The economic implications of learn ing by doing, Review ofEconomic Studies 29 ,155-173 Barro R. and Sala-i-Martin X. (1995) Economic Growth New York : McGraw Hili Inc Burridge P. (1980) On the Cliff-Ord test for spatial autocorrelation, Journal of the Royal Statistical Society B, 42 , 107-8 Cheshire P. and Carbonaro G. W. W . Vickerrnan (eds) Convergence and Divergence among European Regions European Research in Regional Science, Pion, London, 89-111 Copus A. K. (1997) A new peripherality index for European regions areport for the Highlands and Islands European Partnership Fingleton B.

32 B. Fingleton tirely further widens disparities. 48. This is reinforced visually by the maps of the equilibrium distributions under these two assumptions. 17 is the outcome under the zero spending assurnption . In reality , structural fund spending is unlikely to be eliminated completely in this way, but the simulations remain useful as an indication that structural fund spending is of undoubted importance in limiting income disparities between regions. However, the impact of reducing or eliminating structural fund spending should be seen in the context of removing the effect of human capital differences between regions .

In other words, the prernise is that space, which is absent from the theories outlined above, matters. Regression analysis will produce spatially autocorrelated residuals when there are ornitted variables that are spatial autocorrelated, given that the ornitted variables are relevant ones and the dependent variable is itself spatially autocorrelated. One group that comes into this category consists of those variables that are constant across regions within each country, but differ from country to country.

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