EPISTEMOLOGICAL BASIS OF DATA MINING IN MACROECONOMICS - E. V. Kondratova (Финансы: теория и практика)
In this article issues of macroeconomic cognition methodology are being considered accenting the problem of unification fundamental possibilities based on common principles of philosophy of science. When interpreting Karl Popper’s postulates on demarcation and science progress author comes to a conclusion that there is no fundamental difference between gnoseological basis of all the sciences in possession of theoretical level. Furtherelaboration of mentioned postulates within macroeconomic context points out the effectiveness of using data mining for connecting theoretical and empirical cognition levels while either generating theoretical hypotheses or estimating their correspondence to the reality. Non-hypothetical character of data mining tools, especially neural networks of supervised learning, gives all the opportunities to show up to falsificationism which according Popper is the basis of science cognition progress. Nevertheless, the true implementation of all the data mining potential towards macroeconomics needs providing data of the highest quality. Identification of statistical indicators that match theoretical variables is based on their fundamental comparison considering also all the suppositions of country statistics which are stipulated by its specificity. It was done after thorough studying of National Economic Accounting; its authors pointed out all the problems connected with that suppositions so researchers could take into account all the distortions of statistic materials.This article reflects gnoseological possibility and effectiveness of applying data mining tools to macroeconomic problems, first of all estimation of correspondence between theoretical constructions and reality necessary for improving prognostic capabilities of macroeconomics.