Svetlana Balashova
Candidate of Physics and Mathematics
Associate Professor, Head of the Department , department of Economic and Mathematical Modeling

“Economic and mathematical modeling is an independent scientific and applied direction that serves as a link in the triad “economic theory - economic policy - economic practice” George Kleiner


Graduated from the Peoples’ Friendship University named after Pa-trice Lumumba (now - RUDN University), Faculty of Physics, Mathematics and Natural Sciences, specialty “Physics”.


Candidate thesis on “Intermediate quantum statistics of birth-destruction oper-ators in quantum field theory” was defended. The degree of Candidate of Phys-ics and Mathematics was awarded.

1997 - 2019

Associate professor of the Department of Economic and Mathematical Model-ing of the Faculty of Economics RUDN University.


Retraining in the direction “Economics” at the School of advanced training of academic staff in Economics at the National Research University Higher School of Economics (NRU HSE).


Advanced training at the London School of Economics and Political Science, LSE in the direction “Economics” under the program “Econometrics”.

2013 - present

Permanent participant of the advanced training program “Spring Course on Econometrics” at the University of Coimbra, Portugal.

2016 - present

Executive Director of the International Centre for Emerging Market Studies at the Faculty of Economics RUDN University (ICEMS).

2017 - present

Visiting editor of the International Journal of Economic Policy in Emerging Economies (London, Scopus).


Diploma of Lomonosov Moscow State University on professional retraining in the field of “Economics and enterprise management”. Qualification work on the topic “Business planning of the company’s investment project”.

2019 - present

Head of the Department of Economic and Mathematical Modeling of the Facul-ty of Economics, RUDN University.


Gives lectures to RUDN students of bachelor’s and master’s programs and students of further vocational education programs:

  • “Econometrics”,
  • “Econometrics (advanced level)”,
  • “Macroeconomic modeling”,
  • “Modeling of socio-economic processes in the urban environment”,
  • “Econometrics of financial markets”,
  • “Project financing”,
  • “Applied aspects of investment analysis”.

The author of the study guides:

  1. “Econometrics in tasks and solutions” Study guide Balashova S. A., Lazanyuk I. V. Moscow: RUDN, 2017. - 188 p.
    The study guide analyzes in detail examples of econometric research based on actual empirical material that illustrate the application of certain econometric methods to solving economic problems. The theoretical assumptions of the models under consideration, which follow from the economic theory, and the justification of the applied econometric methods are given. For more detailed explanations, readers are referred to well-established coursebooks on econometrics and economic theory. The use of specialized Eviews 7 software for conducting econometric analysis is illustrated in great detail, the most difficult stages of the solution are provided with step-by-step instructions.
  2. “Fundamentals of econometric modeling by using Eviews” Study guide Matyushok V. M., Balashova S. A., Lazanyuk I. V. M: RUDN, 2015. - 223 p.
    The study guide describes the principles of constructing econometric models in an accessible form. Pair and multiple regression analysis, nonlinear regression, models and using dummy variables, modeling of time series, as well as some problems in the construction of models, in particular, heteroscedasticity, multicollinearity and autocorrelation are studied. The algorithm for evaluating various econometric models is described in detail using the Eviews program
  3. “Introduction to financial mathematics” Study guide Kasimov Yu. F., Balashova S. A. Moscow: RUDN, 2007. - 282 p.
    This study guide is dedicated to the study of deterministic models of financial mathematics and therefore can be considered as an introduction to the discipline. The main attention is paid to the basic concepts, construction and correct interpretation of financial models, and their use in practice. Each topic is provided with examples of problem solving, as well as tasks for individual work.


  • Built an econometric model that allows somebody to determine scenarios for the development of the Russian economy based on the concept of endogenous development.
  • Developed a methodology for assessing energy efficiency at the regional level, taking into account the introduction of smart grid elements.
  • Defined the contribution of renewable energy sources (RES) to improving energy efficiency in the European Union.
  • Developed a system of econometric equations to assess the impact of “pull” and “push” on the capital movement in the form of direct and portfolio investments in developing markets.
  • Studied the linkage between innovative development and economic growth in the transition to the sixth technological order.
  • Developed a set of econometric models to assess the impact of public policy instruments in the field of innovative development on the innovative activity of the business sector and total factor productivity.
  • Defined the impact of the quality of political institutions on cross-border capital movement in emerging markets.

Scientific interests

  • Econometric modeling of socio-economic processes;
  • Endogenous models of economic growth;
  • Innovative development and economic growth in developed and emerging markets;
  • State mechanisms for stimulating innovative development in the EU and Russia;
  • Green economy and sustainable development;
  • Emerging market countries;
  • Econometric tools.
This chapter provides an evaluation of the influence of the most significant external and inter-nal factors on international capital flows in the form of direct and portfolio investments for 24 developing countries during the period 1990–2015. The authors have adopted the partial ad-justment model and the feasible generalized least squares estimator for panel data. Results show that the determinants of capital flow for foreign direct and portfolio investments differ. The impact of political risks on cross-border capital flows has been identified.
The primary motivation of our study is to shed light on the impact of global and local risk factors (including currency risk) on the expected return of the Russian stock market during last dec-ade. This period includes the global financial crisis, a recovering period, and the recent crisis in the Russian economy in the period of 2014-2015. We review the hypothesis that the expected return on the Russian stock market depends on the world market return, as well as on domes-tic risk factors, but this relationship is changing over time.
The paper analyses the prospects of the Russian economy in the ‘new reality’. Under this term, we mean slow down of the global economy, economic and political volatility and low oil. The export-oriented model, driven by high oil prices, providing the growth for the Russian econo-my before the global crisis, has exhausted itself. The growth deceleration of the Russian econ-omy has occurred long before the decline in oil prices and the imposition of sanctions in 2014, which is fully understood by the Russian government and academics. The new strategy of economic growth was declared by President Putin after his election for a new term in 2018. The research aims to estimate the impact of the new initiatives on growth drivers.
In this article, interrelations between the indicators of the innovation performance of European countries are evaluated by methods of multivariate statistical analysis. The modified method of principal components is used to create the summary innovation index, which gives the abil-ity to emphasize the most significant factors, essential for innovation development.
The introduction of smart networks leads to an increase in the reliability and efficiency of production, transmission and use of electricity, reducing power losses and the time of emer-gency shutdown, the introduction of renewable energy sources, reducing carbon dioxide emis-sions, improving the quality of customer relations, identifying theft of electricity, creating a market for high-tech products. The modern development of the energy industry in Russia is also focused on the development of a highly efficient and safe infrastructure with the use of modern efficient equipment with intelligent power systems, on the local implementation of re-newable energy generation. The article discusses external effects and feasibility of smart grids in Russian energy sector on the basis of active-adaptive grid. The targets of smart grid devel-opment are analysed. The authors developed an econometric model of electricity consumption in Russia depending on the influence of indirect factors. Using econometric analysis, authors predicted three scenarios of electricity consumption in Russia depending on the amount of en-ergy losses in the networks, the volume of production of electricity, including energy from re-newable sources.