Cluster analysis of the bias in the SMB subsidy recipients selection

Abstract

Abstract. This paper is discussing the applicability of cluster analysis techniques to studying bias in the selection process of government SMB subsidy recipients using data from Moscow city SMB administration. Ward's Hierarchical Agglomerative Clustering Method is used to study 812 SMBs, which received subsidies in 2012-2013 from the Moscow City SMB administration. This analysis strongly demonstrates that clustering mechanisms can be used to reduce selection irregularities in government subsidy distribution.

Study of The Correlation Between World Patenting Trends and The University Admission Rate in Russia Based on Open Data

“…Further study is required to find the reason why ICT field shows invers correlation while biotechnological field demonstrates a direct one. This study is important part of the treatment effect study of the government programs on innovation economy conducted by authors [7].…”