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Low-rise housing revitalization as a factor of regional innovation development

Rozhkov V.L. cand.econ.sci., assistant, chair of economics and entrepreneurship in construction industry, Kazan State University of Architecture and Engineering

Saifullina F.M. applicant, chair of economics and entrepreneurship in construction industry, Kazan State University of architecture and engineering ( dkmff@mail.ru )

Journal: Regional Economics: Theory and Practice, #24, 2010

Now the format of the low-rise habitation allows being reoriented quickly and mobile on innovative products in building branch. In clause are allocated factors which interfering low-rise constructions in Russia and offered the complex of measures for stimulation of the given segment of housing construction by the active participation of the state government and development of industrial wooden housing construction.


Improving the methodology for rating counterparties

Abdukhanova N.G. Kazan State University of Architecture and Engineering (KSUAE), Kazan, Republic of Tatarstan, Russian Federation ( ab-natali@yandex.ru )

Saifullina F.M. Kazan State University of Architecture and Engineering (KSUAE), Kazan, Republic of Tatarstan, Russian Federation ( ufk22@bk.ru )

Kleshcheva O.A. Kazan State University of Architecture and Engineering (KSUAE), Kazan, Republic of Tatarstan, Russian Federation ( Olga_albertovna@bk.ru )

Zeinetdinova G.R. Kazan State University of Architecture and Engineering (KSUAE), Kazan, Republic of Tatarstan, Russian Federation ( z_guzeliya@mail.ru )

Sharafieva A.E. Kazan State University of Architecture and Engineering (KSUAE), Kazan, Republic of Tatarstan, Russian Federation ( alina_mardanova@mail.ru )

Journal: Finance and Credit, #10, 2019

Subject This article discusses the methodology of using rating in receivables management.
Objectives The article aims to determine whether there is a need to manage receivables and payment discipline of counterparties through the rating assessment of debtors.
Methods For the study, we used the methods of analysis and synthesis, comparison, classification, generalization, and some empirical methods. To collect source qualitative and quantitative information, we used interviews and surveys of representatives of the companies under study.
Results The article presents a developed original method of counterparty rating rapid assessment according to the financial results report data for the previous and reporting years in terms of six indicators and the results of payment discipline.
Conclusions Rating is a condition for effective receivables management. The developed approach can be used by rating agencies in assessing the creditworthiness of issuers.


What model predicts bankruptcy of Russian enterprises better?

Fedorova E.A. Financial University under Government of Russian Federation, Moscow, Russian Federation ( ecolena@mail.ru )

Dovzhenko S.E. Saint Petersburg State University, St. Petersburg, Russian Federation ( serg.dovzhenko@gmail.com )

Timofeev Ya.V. Financial University under Government of Russian Federation, Moscow, Russian Federation ( timofeo@bk.ru )

Journal: Economic Analysis: Theory and Practice, #41, 2014

The purpose of the study is to offer a model with the highest forecast power to predict bankruptcy of Russian enterprises. To test the forecasting abilities of existing foreign and domestic models, we obtained the financial statements of 3,487 Russian enterprises from the SPARK and RUSLANA databases. Out of foreign models, the Fulmer model demonstrated the best results. Correct predictions (for transport) totaled 80.4%, for sound enterprises this indicator was 88.7%, and for bankrupts it was 72.1%. The Fulmer model uses a large number of factors (nine), therefore, it is more stable than other techniques. The Altman model is not completely applicable for predicting the bankruptcy sound enterprises in Russian environment. Under this the model true prediction totaled 71.3%. The domestic models of Zaitseva and Saifullina predict bankruptcy of enterprises (in agriculture) only in 58.6% and 62.6% of cases respectively. The model of the Irkutsk University showed the overall result of predicting bankruptcy of 65.1% (in transport). In general, we point out the asymmetry of results in assessing the likelihood bankruptcy. All models (except the Fulmer model) have a slight shift to sampling that consists of bankrupt enterprises. That is, these models are better applicable for predicting bankrupt enterprises, rather than sound ones.


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