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Regular version of the site
Of all publications in the section: 108
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Article
Уринсон Я. М., Безруков В. Б. Экономика и математические методы. 1980. № 1.
Added: Nov 29, 2010
Article
Котляров И. Д. Экономика и математические методы. 2015. Т. 51. № 2. С. 103-112.

The article provides an economic analysis of a specifi c form of license cooperation when the licensee is allowed to produce and to sell products according to licensor's technology and under his brand. Proposed criteria of a partner selection that takes into account incentives, risks and resources. It is demonstrated that licensor's and licensee's goals should meet each other

Added: Oct 12, 2015
Article
Афанасьев А. А., Баранов Э. Ф. Экономика и математические методы. 2018. Т. 54. № 3. С. 4-12.

From the Guest Scientific Editors / For the 100th Anniversary of Nikolai P. Fedorenko, Founder and First Director of CEMI

Added: Sep 16, 2019
Article
Бессонов В. А. Экономика и математические методы. 2002. Т. 38. № 2. С. 113-127.
Added: Jan 28, 2013
Article
Паламарчук Е. С. Экономика и математические методы. 2013. Т. 49. № 3. С. 99-116.

We consider stochastic linear economic control system with a quadratic cost function taking into account the agents’ negative time preferences that can be represented by increasingdiscount function. We give a definition of average optimality over an infinite time horizon for such a system. Risk of using the obtained optimal control law is being estimated. The results are applied to an eco-logical-economic model.

Added: Mar 26, 2015
Article
Эйсмонт О. А., Катышев П. К., Чернавский С. Я. Экономика и математические методы. 2008. Т. 44. № 2.
Added: Nov 1, 2010
Article
Копнова Е. Д., Розенталь О. Экономика и математические методы. 2009. № 45 (2).
Added: Jun 30, 2011
Article
Пресняков В. Ф. Экономика и математические методы. 2008. Т. 44. № 2.
Added: Nov 8, 2008
Article
Асатуров К. Г., Теплова Т. В. Экономика и математические методы. 2014. Т. 50. № 1. С. 37-54.

In our paper we propose a method for constructing a dynamic hedging strategy based on multivariate GARCH models for the marketable Russian stocks. Hedging instruments include stock futures. The method provides a calculation of dynamic hedge ratios instead of the traditional method of ordinary least squares (OLS), which determines the constant hedge ratio. An analysis of spot and futures Russian markets found that 1) it is the dynamics of the futures market affects the behavior of prices of stocks, 2) for all pairs of stock-futures is no asymmetry in the conditional correlation of returns, 3) there is an asymmetry in the conditional volatility, and 4) GARCH class models allow to construct a method of calculation of hedging ratio for portfolio with the best characteristics of "risk-return profile.

Added: Dec 8, 2014
Article
Пресняков В. Ф., Зотов В., Белова М. Экономика и математические методы. 2013.
Added: Apr 10, 2013
Article
Сластников С. А. Экономика и математические методы. 2014. № 1. С. 117-126.
Added: Mar 4, 2015
Article
Федорова Е. А., Гиленко Е. В. Экономика и математические методы. 2013. Т. 49. № 1. С. 106-118.
Added: Nov 1, 2014
Article
Афанасьев А. А. Экономика и математические методы. 2017. Т. 53. № 2. С. 50-65.

The author proposes a modification of a computable simulation model for money circulation in the Russian economy developed in the Laboratory of social simulation CEMI together with academician V.L. Makarov and researcher A.A. Losev due to disaggregation of a block “Oil and gas industry” agent on the two modified model block – a block “Exploration of oil and gas” and a block “Oil and gas production”. In this article we will explore a model related to the exploration and production of oil and gas condensate leaving development of similar models for natural and associated gas for the next study. For modeling of crude oil and gas condensate production, we decide to divide all the 144 Russian oil fields and oil production centers into five groups according to the level of oil production in 2014. On the basis of the model’s two sub-blocks of exploration and production of oil and gas condensate, designed to computable monetary economy of Russia, we forecast volumes of Russian oil and gas condensate production up to 2035 for five aggregated centers of oil production, the federal districts and Russia as a whole under the inertial scenario of economic development in 2014. Given values of internal oil prices, the rate of tax of oil extraction, price and rental rates for new fixed assets, other fixed costs in the production of oil, given at the 2014 level the calculations show a decrease in volumes of oil and gas condensate production in Russia by 5% for 2035.

Added: Jul 12, 2017
Article
Афанасьев А. А. Экономика и математические методы. 2017. Т. 53. № 4. С. 26-35.

This study is devoted to forecasting the Russian Gazprom natural gas production from the Tyumen region's fields and its production potential under in the context of the Russian economy crises and foreign economic restrictions that has been occurred since 2014, including a reduction in external and domestic demand for all Russian natural gas as well as for gas of Gazprom. On the basis of gas production function estimated for 1985-2008 we make forecasts for 2017 of Gazprom gas production volumes in Tyumen region (where the company extracts more than 90% of its gas) and estimate the under-utilized production potential of PJSC Gazprom in this region for 2014-2016. Basing on the additional econometric study of Gazprom gas production function (with labour) in the Tyumen Region we have empirically proved the growth of the coefficient of the company's neutral technical progress since 2014, one of the consequences of which, according to the author, was a continuous decline since 2014 the unit cost of natural gas production of the Gazprom subsidiary Gazprom dobycha Nadym, which operates the largest Bovanenkovskoye ​​oil and gas condensate field in the Yamal Peninsula which reserves are estimated to be 4.9 trillion cubic metres of gas. It is concluded that under the Russian economy crisis that has been intensified since 2014 as well as the foreign economic and political restrictions that have been started in the same year, in the segment of gas production Russian Gazprom continues to be an effective natural monopoly with increasing coefficient of neutral technical progress, declining average gas production cost in new fields and minimal production costs, the marginal and average values ​​of which coincide and do not depend on the volumes of produced gas.

Added: Aug 31, 2017
Article
Андреева А. В., Т. К. Богданова Экономика и математические методы. 2016. Т. 52. № 1. С. 79-94.

The article represents the information and logical complex model to manage the company’s customer base in order to calculate the index of long-term value of the client. In contrast to the previous issues this model takes into account the peculiarities of consumer behavior and socio–demographic characteristics of the client groups, and the movement of customers within the customer base is represented as a Markov chain. Developed complex dynamic model to manage the company’s customer base makes possible to forecast the cluster frequency and the client base at all on any period, to analyze the population- change-dynamics of client cluster and to highlight the most important stages in the formation and development of the customer base. On each stage highlighted groups of clients are estimated according to future company’s profit and potential for cross selling of products/services. The estimates allow to calculate the budget for marketing activities on retention of given profit level and to compose the most effective plan of address–directed marketing activities.

Added: Apr 14, 2016
Article
Афанасьев А. А., Пономарева О. С. Экономика и математические методы. 2014. Т. 50. № 4. С. 21-33.

Econometric models of the aggregate production function of the Russian economy have been built. These models adequately (from the standpoint of economics and econometrics) describe the expanded reproduction of the Russian economy in 1990–2012. The role of the national economic infrastructure and world oil price fl uctuations on GDP as well as predictive power of econometric models are investigated.

Added: Oct 31, 2014
Article
Афанасьев А. А. Экономика и математические методы. 2010. Т. 46. № 2. С. 35-48.

The subject of this econometric study was the production functions of natural gas production industry in Sakha Republic (Yakutia) for 1968-2008. The production functions can be applied for short-term and medium-term natural gas production forecasting by the Sakha Republic Council of Ministers as well as by regional gas production companies.

Added: Feb 4, 2013
Article
Афанасьев А. А. Экономика и математические методы. 2009. Т. 45. № 2. С. 37-53.
Added: Nov 1, 2011
Article
Замулин О. А., Платонов К. Е. Экономика и математические методы. 2015. Т. 51. № 3. С. 3-18.
Added: Oct 5, 2015
Article
Пересецкий А. А. Экономика и математические методы. 2007. № 43(1). С. 3-15.
Added: Mar 7, 2011