Source: https://publications.hse.ru/en/articles/137612662
Timestamp: 2019-04-21 10:52:02+00:00

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Вестник Московского университета. Серия 12: Политические науки. 2013. № 3. С. 42-60.
Юрескул Е. А., Ахременко А. С.
Government efficiency is one of many fuzzy terms in contemporary political science. Due to its multidimensionality, it is not well-defined and, therefore, hard to identify. The idea of the current research is to create an index of government efficiency using data envelopment analysis. Using a sample of 127 countries for the period of 2009-2011 we then mark out the significant institutional factors that could impact government efficiency. Moreover, this study supports the initial hypothesis about the predominance of political factors in the efficiency increase.
Моисеев С. П., Карпов И. А., Мифтахутдинова К. И. и др. Экономическая социология. 2017. Т. 18. № 3. С. 152-159.
A “Network Analysis” section was arranged at the XVIIIth Interna- tional Academic Conference on Economic and Social Development at the Higher School of Economics on 11–12 April 2017. For the third year, this section invited scholars from sociology, political science, management, mathematics, and linguistics who use network analysis in their research projects. During the sessions, speakers discussed the development of mathematical models used in network analysis, studies of collaboration and communication networks, networks’ in- uence on individual attributes, identifcation of latent relationships and regularities, and application of network analysis for the study of concept networks.
The speakers in this section were E. V. Artyukhova (HSE), G. V. Gra- doselskaya (HSE), M. Е. Erofeeva (HSE), D. G. Zaitsev (HSE), S. A. Isaev (Adidas), V. A. Kalyagin (HSE), I. A. Karpov (HSE), A. P. Koldanov (HSE), I. I. Kuznetsov (HSE), S. V. Makrushin (Fi- nancial University), V. D. Matveenko (HSE), A. A. Milekhina (HSE), S. P. Moiseev (HSE), Y. V. Priestley (HSE), A. V. Semenov (HSE), I. B. Smirnov (HSE), D. A. Kharkina (HSE, St. Petersburg), C. F. Fey (Aalto University School of Business), and F. López-Iturriaga (Uni- versity of Valladolid).
Теплова Т. В., Соколова Т. В. Экономика и математические методы. 2017. Т. 53. № 3. С. 110-128.
In this paper for the first time on the base of the non-parametric Data Envelopment Analysis (DEA) method the authors build and test portfolios in the Russian bond market. Using DEA we perform integral evaluation and rank by optimality (efficiency) outstanding ruble corporate bonds from the perspective of a private investor. Our original algorithm for building an optimal bond portfolio includes two analytical procedures: first we identify the determinants of the yield to maturity of ruble corporate bonds for a diversified sample of real sector companies from 2008 to 2015, then we apply the DEA method for this sample in order to find the optimal set of bonds for the portfolio. At the final stage we test (for 2014—2015) an investment strategy based on picking for the portfolio the ruble corporate bonds that reached the efficiency frontier. In order to identify the determinants of ruble corporate bond yields we analyze a set of macroeconomic and firm-level (financial and non-fundamental) factors, characteristics of bond issues using econometric methods. For the first time in the Russian bond market we consider not only current but also expected inflation and GDP growth, risk indicators (the volatility index RTS VIX as a proxy). We identify the optimal bond issues (the bond issues that reached the efficiency frontier) taking into account a set of different factors: yield to maturity, duration and liquidity of bond issues, credit risk indicators of bond issuers. The results of a regression analysis confirm our hypothesis that yield to maturity is significantly influenced by revenue of a bond issuer, the repo eligible factor (inclusion of a bond issue in the Lombard list of the Bank of Russia), the government’s share in the equity, the bond issuer’s debt burden indicators, the level of current and expected inflation. The efficiency (optimality) frontier mainly consists of bond issues of large companies with the government’s participation in the equity. Our hypothesis that investing in the bond issues on the efficiency frontier can beat the bond benchmarks’ returns and “return / volatility” ratios are confirmed in part, for the period of 2014 characterized by a decrease in prices of ruble bonds.
Ким А. В., Филинов Н. Б. Вестник Тверского государственного университета. Серия: Экономика и управление. 2015. № 4. С. 205-218.
DEA-analysis is performed based on publicly available data on 94 world largest fashion retailers. Standard clusterization of coefficients obtained from DEA-analysis gives clusters that are analyzed with respect to homogeneity and fit to the types of strategic behavior outlined in strategic management.
Aleskerov F. T., Petrushchenko S. Математические методы анализа решений в экономике, бизнесе и политике. WP7. Издательский дом ВШЭ, 2013. No. WP7/2013/02.
Data Envelopment Analysis is a well-known non-parametric technique of efficiency evaluation which is actively used in many economic applications. However, DEA is not very well applicable when a sample consists of firms operating under drastically different conditions. Generally, it is difficult to define to what extent the analyzed sample is heterogeneous. We offer a new method of efficiency estimation based on a sequential exclusion of alternatives and standard DEA approach. This allows to assess efficiency in the case of heterogeneous set of firms. We obtain a connection between efficiency scores obtained via standard DEA model and the ones obtained via our algorithm. We also evaluate 29 Russian universities and compare results obtained by two techniques.
Соколова Т. В. В кн.: Модернизация и инновационное развитие экономических систем. М.: Российский университет дружбы народов, 2014. Гл. 2.4. С. 145-164.
The article performs a comparative analysis of the efficiency of G20, BRICS and NIC member countries’ participation in global value chains (GVC) taking into account economic growth, investment activity, global competitiveness and productivity in the period from 2000 to 2009. Efficiency is evaluated by means of the method of data envelopment analysis under constant and variable returns of scale assumptions. The comparison of the efficiency of developed and developing countries participation in GVCs is made, the leaders and outsiders in using the GVCs’ potential are revealed. For the latter the target values of the input and output parameters allowing to reach the efficiency frontier are indicated.
Edited by: A. Emrouznejad, R. Banker, H. Ahn et al. Braunschweig: 2016.
Abankina I., Aleskerov F. T., Belousova V. et al. In bk.: Data Envelopment Analysis and its Applications. Proceedings of the 13th International Conference of DEA. Braunschweig: 2016. P. 25-33.
In recent decades, increased economic pressure and growing societal expectations have led to the introduction of performance-based funding models for universities. In this respect, a great scholarly attention has paid to how to evaluate universities performance correctly. This allows national governments to design and apply various taxonomies to facilitate the development of efficient programmes for the advancement of higher education. The wide spread approach used for that purpose is DEA. This paper provides a review of different approaches how to take into account universities heterogeneity when applying DEA to construct the typologies of university by showing statistically their similarities and differences. The authors use the modified DEA proposed by Aleskerov & Petrushchenko (2013) to evaluate performance scores of Russian technical universities. This proposed typology divides universities into specific groups with a description taking into account their heterogeneity.

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