Abstract

Recent economic dynamics in southern Europe have been influenced by multifaceted processes with important spatial outcomes. Construction industry has been one of the productive sectors with the most relevant crisis-driven changes in Greece, probably the most affected country in Europe. With the aim to provide a quantitative analysis offering a comprehensive knowledge of regional-scale dynamics in construction industry during expansion and recession times, the present study investigates spatial variations over 2003-2015 in the value of new dwellings, supplemented with other indicators of building activity (number of permits, average building surface, number of floors), at the scale of Greek prefectures. A data mining framework based on principal component analysis and non-parametric correlations with background socioeconomic indicators was developed to identify spatial patterns in building activity during economic expansion (2003-2009) and crisis (2009-2015). According to building permit data, the average value of new dwellings' per surface area increased in a spatially-heterogeneous fashion across the country, with a substantial difference in growth rates between the two investigated time intervals. During expansion, new dwellings' value increased across the country with a slight decline in two regions and a considerable growth in one region. During recession, new dwellings' value decreased in one region and increased markedly in four regions, being relatively stable in the rest of the country. In 2003, the highest values of new dwellings were spatially associated with economically-dynamic districts characterized by agglomeration economies, upper urban functions, and transport accessibility. With crisis, the spatial distribution of dwellings' value was more heterogeneous and not associated to specific background factors, with the highest increase observed in accessible rural districts and coastal areas with tourism specialization. Further investigation on the role of economic cycles in house value spatial trends is particularly required for designing effective post-crisis development measures.

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