Assessing the Behaviour of Non-Survey Methods of Constructing Regional Input-Output Tables through a Monte Carlo Simulation
The paper aims to analyse the tendency of a battery of non-survey techniques of constructing regional I-O tables to over-(under-)estimate impact. The behaviour of the regionalization methods is assessed relatively to the techniques analysed. For this aim, a Monte Carlo simulation has been carried out. Then, a multidimensional scaling procedure has been applied to search for a common and repeated structure of differences among the methods and to give an immediate picture of possible implications, in terms of impact direction, coming from the choice of a given regionalisation method rather than another. Afterwards, the results have been compared to those obtained by applying the same procedure to 2000 I-O tables, which have been mechanically constructed for the 20 Italian regions. The results indicate that the choice of the regionalization method is crucial in estimating multipliers. According to the chosen method, the extent of multipliers could be considerably bigger or lower. This can have serious repercussions in terms of policy choices and, therefore, policy makers and I-O analysts should be aware of it. In addition, the results have confirmed a tendency of the methods to over-(under)-estimate impact both statistically and empirically. However, they have also shown that sectoral aggregation can reverse this tendency. Finally, from an economic point of view, it turned out that the most recent Flegg et al. Location Quotient (Flegg et al., 1995; Flegg and Webber, 1997) is the best to represent regional economies.
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