Abstract
The extreme volatility that has characterized the real estate market in recent years constitutes an important issue for researchers and experts, stimulating the development and the test of evaluation models able to predict future trends and to monitor the consequences of scenario evolutions that are different from those initially expected. With reference to the metropolitan area of Barcelona (Spain), the methodology implemented in this paper has allowed to make explicit the functional relationships between the residential properties prices and the socio-economic variables selected by the model (number of loans, unemployment level, market rent). The analysis carried out is “dynamic”, i.e. it refers to a quarterly time series database covering a period of sixty-seven periods (1st quarter 2001-3rd quarter of 2017). The results obtained have shown the forecasted potentialities of the tool used, as support (i) for the investment decisions of private operators, (ii) for the fiscal decisions of central governments, (iii) for the selection of the most convenient urban transformation initiatives from local administrations.
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Morano, P., Tajani, F., Guarini, M.R., Di Liddo, F., Anelli, D. (2019). A Multivariate Econometric Analysis for the Forecasting of the Interdependences Between the Housing Prices and the Socio-economic Factors in the City of Barcelona (Spain). In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11622. Springer, Cham. https://doi.org/10.1007/978-3-030-24305-0_2
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