The paper presents the newly developed dynamic spatial general equilibrium model of European Commission, RHOMOLO, and proposes its future extensions. The model incorporates several elements from economic geography in a novel and theoretically consistent way. It describes the location choice of different types of agents and captures the interplay between agglomeration and dispersion forces in determining the spatial equilibrium. The model is also dynamic as it allows for the accumulation of factors of production, human capital and technology. This makes RHOMOLO particularly suited for simulating policy scenario related to the EU cohesion policy and for the analysis of its impact on the regions and the Member States of the union. JEL classification: C63, C68, D58, F12, H41, O31, O40, R13, R30, R40
In spatial econometric models, autocorrelation among error terms is usually incorporated by means of the so-called contiguity matrix W, determining the interdependence between the spatial observations on the dependent variable. In this paper, the analysis is generalized by introducing two contiguity matrices, related to two autocorrelation parameters. This may be useful when dealing with variables representing flows between regions, where both the origin and the destination regions have a different impact on the autocorrelation scheme. It is shown analytically and illustrated empirically that the presence of such autocorrelation can be tested with the likelihood-ratio test, whereas the parameters can be estimated by the maximum-likelihood approach.1 Introduction In test procedures for autocorrelation among spatial data, the alternative hypothesis is mostly restricted to the first-order spatial Markov scheme. Thereby the spatial units are linked by a so-called contiguity matrix, which contains weights indicating the degree of interaction between the spatial units with respect to the phenomenon that is studied, for example, income in or flows between regions. Estimation and testing methods based on such a scheme were studied among others by Cliff and Ord (1973), Hepple (1976), andBrandsma andKetellapper (1979). Alternative approaches based on less prior information concerning interactional weights were proposed by Arora and Brown (1977) and Kooyman (1976).These latter two argued that ambiguity in specifying the contiguity matrix W on a priori considerations prevents successful application of this concept of autocorrelation. In fact, Arora and Brown suggested the use of econometric techniques like joint generalized least squares in case the errors of the model display autocorrelation, whereas Kooyman constructed a test statistic for autocorrelation by maximizing the Moran statistic as a function of its weight coefficients under certain constraints. Both papers start from the assumption that only very vague knowledge about possible alternative hypotheses of autocorrelation is available. However, we are of the opinion that testing and estimation based on a specification of W which is theoretically well founded may still be appropriate since it gives the analyst insight into how to respecify his model in order to incorporate the factors that caused the autocorrelation explicitly (for example, the introduction of spatially lagged variables when W represents the Markov scheme-cf Haining, 1978b); the approaches useful for exploratory rather than explanatory analysis. In addition, it is virtually impossible to estimate all elements of W from the data, unless W is postulated to depend only on a few parameters, for example, by means of a distance function. More on this approach follows in section 4.A more general approach to the problem of spatial dependence was followed by Haining (1978b), who (1) defined two-dimensional moving-average schemes, (2) discussed a specification technique based on spatial autocorrelation coeffic...
The paper describes the dynamic spatial general equilibrium model, Regional Holistic MOdeL(RHOMOLO), developed by the European Commission, where the labour market equilibrium is determined by firms' labour demand, unemployment and interregional labour migration. We carry out simulations on the effects of transportation costs on regional labour markets. Our results confirm that wages and unemployment are by far the most important channels of labour market adjustment in the EU. In contrast, labour migration is found to play a secondary role. Also, the complexity and spatially inter-dependent relationship among market access, labour demand, and labour supply is found. It underlines the significance of dynamic spatial general equilibrium approach.
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