Эффективное развитие филиальной сети коммерческого банка
We estimate efficiency scores for Russian universities based on data set of input and output criteria by using Data Envelopment Analysis. In addition, we use a reputation index as another indicator of a university’s productivity. To construct it, 4000 contexts are analyzed and 13 reputation criteria are found. The threshold procedure is used to aggregate them into a reputation indicator. Factors which lead a university to be efficient are studied.
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).
Using the Rosstat panel data for the 2001-2008 period we estimate the gravity model of migration between Russian regions. We show that though the migration flows have been quite stable, their determinants have changed substantially. Special attention is drawn to the role of distance between the regions. So far we have found out that social and economic factors are affecting migration between nearby regions. Yet our attempts to model the flows between distant (>500 km) places have lead to very poor goodness of fit.