Abstract — In the present article we extend our latest studies where we to explored implications in the progression and patterns of Romanian GDP. We employ data mining techniques, such as model trees and linear regression, over data extracted from statistics, socioeconomic indicators tables and reports from the Eurostat, Romanian National Bank (NBR) and Romanian National Institute of Statistics, over the 2001-2010 period. We continue to present our investigation of GDP patterns spaced out from classic ways, through taxes on production, imports, on income and on wealth, employers ’ social contributions from various fields of economy (agriculture, commerce, constructions, industry, services, financial, banking, etc.) as well as salaries level, based on the data mining tasks
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