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We present a complex analysis of business models for large, medium and small Russian commercial banks from 2006 to 2009. The Russian banks are grouped based on homogeneity criteria of their financial and operational outcomes. The banks’ structure of assets and liabilities, profitability and liquidity ratio are taken into account. The results show how the banks are adjusted their business models before and after the financial turmoil taken place in 2008. In addition, the prevailing banking business models observed for the leading banks in Russia are defined. The banks often changing their business models are found and analyzed.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.