This paper examines the role of data mining analysis in explaining the Italian regional dualism with the aim of suggesting economic policies to fill the existing socio-economic gaps. We analyze the 2004–2014 period exploiting the capacity of MARS model in finding relationships among data. In Italy, the presence of a North-South divide is well-known for decades and present for several social and economic aspects. Recent studies prove that strong differences exist also in the regional human capital. Thus, we search for the causes of the local differences, also considering the entrepreneurial vitality and the international trade leverage. Among several variables, MARS is useful in showing the actual determinants on which to intervene. This is possible by comparing regions grouped homogeneously into clusters using recent data. MARS results are used for policy suggestions with the aim of filling the income gap.
Advances in Intelligent Systems and Computing, Volume 618, Pages 77-85 14th International Conference on Distributed Computing and Artificial Intelligence, DCAI 2017; Porto; Portugal; 21 June 2017 到 23 June 2017; 代碼 193359