Forecasting Macroeconomical Indices with Machine Learning : Impartial Analysis of the Relation Between Economic Freedom and Quality of Life
Jonathan Staufer and Patricia Brockmann Technische Hochschule Nurnberg, Germany
ABSTRACT
The importance of economic freedom has often been stressed by supporters of liberalism, but can its actu-al effect be observed in a data driven, objective way? To analyze this relation the Economic Freedom of the World (EFW) index and the Human Development Index (HDI) were examined with modern machine learning algorithms and a wide-ranging approach. Considering the EFW index’s preference of a liberal-istic oriented economic policy, an objective recommendation for creating an economic policy that im-proves people’s everyday lives might be derived by the analysis results. It was found that these more ad-vanced algorithms achieve a considerably stronger correlation between both indices than pure statistical means yet leave a small room for interpretation towards a counter-liberalistic implementation of demand-driven economic policy
KEYWORDS Data Mining, Machine Learning, Neural Networks, Economic Freedom of the World Index, Human Devel-opment Index Original Source URL: http://aircconline.com/ijscai/V7N4/7418ijscai02.pdf http://airccse.org/journal/ijscai/current2018.html

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