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Evaluating the efficiency of foreign direct investment: A cross sectoral comparison

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

Fedorov F.Yu. Financial University under Government of Russian Federation, Moscow, Russian Federation ( fedorovfedor92@mail.ru )

Nikolaev A.E. AO Gidromashservis, Moscow, Russian Federation ( alexed.nik@gmail.com )

Afanas'ev D.O. Financial University under Government of Russian Federation, Moscow, Russian Federation ( dmafanasyev@gmail.com )

Journal: Financial Analytics: Science and Experience, #41, 2016

Importance The research evaluates the efficiency of companies having foreign direct investment in line with industry specifics.
Objectives The research pursues ranking the industries that handle foreign direct investment in the most effective way.
Methods The research involves methods of analysis that draws upon performance indicators (profitability) and technological efficiency (DEA analysis). We also used financial statements of the Russian companies that work with foreign direct investment.
Results General profitability decreases over time, with profitability of assets being negative in 2014. It results from anti-Russian sanctions, including the restriction of foreign direct investment.
Conclusions and Relevance Foreign direct investment has a positive effect on the Russian economy, and their restriction caused a reduction in performance indicators of the Russian companies. The average efficiency of the industry confirms that foreign direct investment has a positive effect in each industry, and its restriction will affect industries respectively.


Assessment of the quality of education in Russian regions

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

Musienko S.O. Financial University under Government of Russian Federation, Moscow, Russian Federation ( som090788@yandex.ru )

Fedorov F.Yu. Financial University under Government of Russian Federation, Moscow, Russian Federation ( fedorovfedor92@mail.ru )

Rogov O.Yu. Financial University under Government of Russian Federation, Moscow, Russian Federation ( olegrgv@yandex.ru )

Journal: Regional Economics: Theory and Pactice, #2, 2018

Importance This article discusses the issues of education quality assessment in Russian regions.
Objectives The article aims to compile the rating of education quality in the regions of Russia.
Methods For the study, we used the methods of data envelopment analysis and composite indexes. The quality of education was assessed through dividing all the regions of the Russian Federation by type of economic activity. For consideration, we used the Rosstat data for the period of 2006 to 2015.
Results We found that the quality of education varies depending on the type of region and its economic orientation. The level of education in industrial regions is higher than in export-oriented ones. Our article presents a rating of ten most and ten least effective regions at quality of education.
Conclusions Education policies should be tailored to the regional context. Financial and economic centers and industrial regions demonstrate high levels of quality and efficiency of education as opposed to export-oriented regions. Given the orientation of Russia's economy to exports, special attention should be paid to raising the level of education in export-oriented regions.


Developing the crisis indicators for the Russian financial market

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

Fedorov F.Yu. Financial University under Government of Russian Federation, Moscow, Russian Federation ( fedorovfedor92@mail.ru )

Koshcheeva E.E. Financial University under Government of Russian Federation, Moscow, Russian Federation ( koscheeva8@gmail.com )

Journal: Finance and credit, #47, 2015

Subject The study focuses on the development of crisis indicators for the Russian financial market.
     Objectives The aim is to develop such crisis indicators that can predict a crisis one, three, and six months in advance.
     Methods The methodology includes the use of binary choice models that are often used in such types of studies. To test the significance of coefficients, we apply the Bayesian approach in logit modeling. We determined crisis and non-crisis periods on the basis of the EMP crisis indicator.
     Results The main indicators of crisis, which can be used for the Russian financial market are the money multiplier, M2 to foreign reserves ratio, growth of imports, market conditions, increase in stock prices, growth of M2 to GDP, the ratio of foreign liabilities to assets. The highest predictive capability of the indicators is within 1 to 6-month time-lags.
     Conclusions Significant factors in the logit model were approximately equal when using the Bayesian approach for lags of 1 and 6 months. Thus, they show resistance to selecting the model of the study. Therefore, the offered indicators may be useful to predict crisis situations in Russia.


Environmental effect on mergers and acquisitions efficiency in the telecommunications industry

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

Medvedeva A.A. Financial University under Government of Russian Federation, Moscow, Russian Federation ( bzzz93@mail.ru )

Fedorov F.Yu. Moscow State Technical University of Radio Engineering, Electronics and Automation (MSTU MIREA), Moscow, Russian Federation ( fedorovfedor92@mail.ru )

Journal: Economic Analysis: Theory and Practice, #1, 2016

Importance The article addresses development processes of the Russian M&A market in the telecommunications sector, and the effect of macroeconomic factors on efficiency of M&A transactions.
Objectives The aim is to analyze the impact of macroeconomic factors on mergers and acquisitions efficiency in the telecommunications industry.
Methods The study draws on the analysis of transactions in the Russian telecommunications industry over the period from January 2005 to March 2015. The analysis identified factors of the telecommunications sector and the entire economy, which influence the transactions. We calculated efficiency of transactions using the index of cumulative abnormal return. The analysis is based on econometric models of linear regression, probit regression; the volatility is calculated by using the GARCH model.
Results The analysis leads to the conclusion about the influence of macroeconomic factors on transactions’ efficiency. There is a weak correlation between the yield of the transaction and the condition of financial markets and entire economy, while the level of industry development has a direct impact on the deal.
Conclusions and Relevance The telecommunications sector has become one of main sectors of M&A development. Over the recent year, Russia has been experiencing economic turmoils, and enters a crisis phase. Companies are looking for the most efficient ways of development, therefore, they need to competently analyze deals in the M&A market.


How the sanctions have affected the efficiency of enterprises: The sectoral aspect

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

Nemchaninova D.N. Financial University under Government of Russian Federation, Moscow, Russian Federation ( ndn14@mail.ru )

Fedorov F.Yu. Financial University under Government of Russian Federation, Moscow, Russian Federation ( fedorovfedor92@mail.ru )

Journal: Financial Analytics: Science and Experience, #1, 2018

Importance This paper studies the impact of sanctions on the efficiency of Russian companies.
Objectives The purpose of the study is to analyze the impact of sanctions on the foreign direct investment (FDI) efficiency of domestic companies using the Malmquist Index (MI) and economic and mathematical modeling.
Methods The paper examines the FDI performance of 2,166 companies in order to investigate the impact of the sanctions imposed. The Malmquist Productivity Index, combined with the DEA analysis, is taken as the basis for the comparison.
Results The hypothesis that sanctions from countries with a high level of development have a greater impact on the activities of companies with foreign direct investment than those ones from developing countries, is not refuted in the Russian market. The work tests the hypothesis about the impact of sanctions on the industry. The oil and trade sectors have suffered the most, while the productivity of the banking (financial) sector remains practically unchanged.
Conclusions and Relevance The conducted analysis is relevant for the Russian reality, as it shows which way the Russian economic realities are changing. The conducted research can be applied to study the influence of the sanction package, evaluate political decisions from the economic point of view. In addition, the analysis can be used to investigate foreign direct investment in Russian conditions.


Developing threshold critical values of macroeconomic indicators to predict crisis situations

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

Fedorov F.Yu. Financial University under Government of Russian Federation, Moscow, Russian Federation ( fedorovfedor92@mail.ru )

Lazarev M.P. Financial University under Government of Russian Federation, Moscow, Russian Federation ( mp_laz@mail.ru )

Journal: Finance and credit, #22, 2016

Subject The article considers the calculation of indicators of crisis and their threshold values for the Russian financial market.
Objectives The aim is to develop threshold values of indicators of financial crisis, which may help predict crisis in Russia, Belarus, Kazakhstan and Ukraine at different time periods.
Methods In the study, we applied the model of binary choice (BCT (Binary Classification Tree)). The model is very popular nowadays as it does not require any suppositions about model's basic functional forms, which are considered by regressive models; the correlation between the factors does not play any role; the dependence between variables may not be linear; the model is able to deal with series, where some data are absent.
Results We calculated threshold values of crisis indicators for 1, 3 and 6-month time lags and without any lag. The results are partly confirmed by previous researches on Russia. We developed a new crisis indicator consisting of 3 variables, i.e. a ratio of foreign debt to GDP, the growth of internal dept and inflation.
Conclusions and Relevance The majority of meaningful indicators have 1 and 6-month time lags. The most important indicator for all 4 periods is the ratio of foreign debts to GDP (threshold value is over 4% for 1-month time lag). If internal debt increases or GDP decreases, the likelihood of crisis is strong.


Forecasting the bankruptcy of enterprises: Evidence from the construction, manufacturing, transportation, agricultural and trade industries

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

Fedorov F.Yu. Financial University under Government of Russian Federation, Moscow, Russian Federation ( fedorovfedor92@mail.ru )

Khrustova L.E. Financial University under Government of Russian Federation, Moscow, Russian Federation ( khrustoval@yandex.ru )

Journal: Finance and credit, #43, 2016

Subject The study considers bankruptcy evaluation parameters formalized in the Russian legislation.
Objectives The aim is to provide empirical support to the methodology for bankruptcy evaluation offered by the Russian legislation, and update the parameters of financial performance it establishes.
Methods The study rests on two hypotheses: financial indicators established by Russian laws correctly evaluate the probability of bankruptcy and are better adapted to the realities of modern Russian economy than similar western models; an adequate assessment of the probability of bankruptcy in the Russian legislation is provided not only through financial performance, but also through a set of standards for its evaluation. However, the current standards are obsolete and do not consider the industry specifics of analyzed companies.
Results We built a standard model of logistic regression that enables to assess the accuracy of financial indicators of bankruptcy approved by Russian laws, and to support their correctness empirically based on the data on enterprises operating in construction, manufacturing, transportation, agricultural and trade industries. Similarly, we proved the need for updating the criteria for financial performance evaluation, and offered a new system of standards, which takes into account the industry characteristics of the companies under analysis. Both hypotheses were confirmed and empirically proved.
Conclusions The findings substantiate the need for updating the legal standards, the importance of industry specifics, and show that our developed standards are correct and can be translated into practice for analysis purposes.


A system analysis in the innovation-driven economy

Firstov Yu.P. National Research Nuclear University MEPhI, Moscow, Russian Federation ( firstovyp@mail.ru )

Fedorov P.L. National Research Nuclear University MEPhI, Moscow, Russian Federation ( walgecore@gmail.com )

Khusniyarov M.R. National Research Nuclear University MEPhI, Moscow, Russian Federation ( Khusniyarovmr@gmail.com )

Journal: Economic Analysis: Theory and Practice, #38, 2014

In today's economy, there is a growing trend towards integration and acceleration of development processes. A new technical and economic environment is underway. However, the applied models and forecasting often disregard this factor. Until recently, the practitioners did not have confidence in the system analysis and its derivative disciplines. However, the formation of highly integrated and rapidly changing economy of the new generation (an innovation economy) provides the system analysis with the possibility to become an applied and exact discipline. Addressing the issues related to the consistency of the past, present and future, the uniformity of changes of the system and an element and maintaining the adequacy of models and reality become imperative for the practice. Innovation economy requires creating an analytical tool with movement as its main subject. Apparently, identifying the innovation economy as a specific phase of the world economy development, first of all depends on a fundamental correction of the analytical tool. Its practical meaning implies that in today's world changes occur very rapidly and to ensure the optimality of the dynamics processes is in the limelight. The specifics of task description for a systems analysis and systems engineering are extremely important in the innovation economy. The attempts to solve them without a fundamental correction of analytical tools and management methods are not likely to be effective. The authors emphasize that identifying the conditions that provide ample opportunity for the new mechanisms of technical and economic development, which are created by the next-generation technologies, is the most important task of systems engineering. The article considers the specifics of the strategic analysis methods in the innovation economy.


Interrelation of company capital structure and effectiveness in Russia

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

Rybalkin P.I. Higher School of Economics, Moscow, Russian Federation ( rybalkinpavel93@gmail.com )

Fedorov F.Yu. OOO RedSys, Moscow, Russian Federation ( fedorovfedor92@mail.ru )

Journal: Finance and credit, #48, 2017

Subject The article investigates interrelations between capital structure and effectiveness of 451 Russian manufacturing companies from 2008 to 2015.
Objectives The purpose of the study is to explore the interaction between the capital structure of the companies and their effectiveness in the Russian market.
Methods Annual financials of Russian manufacturing companies from Ruslana database serve as input data. We estimate the companies' effectiveness by building non-parametric DEA models (VRS and FDH modifications). To challenge the main hypotheses, we constructed two linear regression equations under three methods, namely, OLS, 2SLS, and quantile regression.
Results Using the obtained estimates of effectiveness, we tested the agency-cost hypothesis to find out whether an additional debt leads to an increase in company performance in the next period (Jensen & Meckling, 1976). Also, there have been tested two competing efficiency risk and franchise value hypotheses to understand whether more effective companies raise additional debts to achieve their capital structure optimum or they tend to maintain positive cash flow for equity holders and avoid additional debts. Based on the findings, we rejected the agency-cost hypothesis. The effectiveness of Russian companies is not improved if the debt level grows. For a number of companies, the franchise value hypothesis was confirmed – if the major shareholder possesses from over seventy percent of the total share capital, it results in the biggest decline in the debt level in the next period.
Conclusions Raising new debt by more effective companies has an insignificant impact on their performance in the subsequent period.


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