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Of all publications in the section: 62
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Working paper
Smirnov S. V. Количественный анализ в экономике. WP2. Высшая школа экономики, 2013. No. 01.
  This paper demonstrates that cyclical movements of major industrial market groups (durable and nondurable consumer products, equipment, materials and supplies) have important peculiarities in Russia and in the US. It allows a better understanding of business cycles in national economies determined with their specific structural features. Based on a statistical analysis of monthly indexes of industrial output (for Russia the relevant indexes were specially calculated by the author), one can conclude that in Russia the dynamics of industrial output do not dependent so much on demand but rather on supply of products. This is explained through both weak diversification of the Russian economy as well as its high degree of monopolization and exceptional role of imports in consumer and investment expenditures. 
Added: May 13, 2013
Working paper
Smirnov S. V. Количественный анализ в экономике. WP2. Высшая школа экономики, 2011. No. 03.
The cyclical indicators approach has been used for decades but the last recession has once more rekindled an interest for them throughout the world. Several new techniques and indicators were introduced in recent years but the actual quality of these ‘newcomers‘ was not well established. During the last recession, performance of such ‘veterans’ as indexes by The Conference Board, ECRI, ISM, PhilFed, OECD, etc. has also not been checked in a comprehensive and comparable manner. Another problem with cyclical indicators is that their usage in real time has not yet been fully clarified. Contemporary global economic life is measured in days and hours, but most common economic indicators have inevitable lags of months and sometimes quarters (GDP). Is it possible for a leading indicator (which is monthly in most cases) to be timely? Moreover, the real-time picture of economic dynamics may differ in some sense from the same picture in its historical perspective, because all fluctuations receive their proper weights only in the context of the whole. Therefore, it’s important to understand whether the existing indicators are really capable of providing important information for decision-makers. In other words, could they be useful in real-time? What does the experience of the last recession tell us in this regard? This paper answers these questions for the USA as well as for Russia.
Added: Dec 26, 2012
Working paper
Smirnov S. V. Количественный анализ в экономике. WP2. Высшая школа экономики, 2015. No. 3.
Russia is a country with a unique history. Its economy became strictly planned in 1928; then the turbulent processes of collectivization and industrialization took place; then the arduous years of the war with Nazi Germany came; then the Cold War with its armaments race started; then the USSR crashed and the transition from planned to market economy began in separated Russia; then the Russian economy was attached to the world economy and the world financial system; then came the period of sanctions and isolation of Russia… It’s reasonable to think that all these processes strongly affected the Russian economic trajectory but it’s not known exactly: a lot of the Soviet statistics (especially for the 1930s-1940s) were never published, and some of the indicators had serious distortions because of improper deflators. Hence, our first aim was to construct statistical time-series which might be useful for describing the long-run trajectory of the Russian economy. Using previously unpublished data stored in Russian archives, we tried to make them as long as possible; in fact, most of them begin in the late 1920s. Our second aim was to denote periods of growth and contraction in the Russian economy and to reveal the economic factors which determined the changes in the trajectory. Periods of contractions during the era of the planned economy were of special interest for us. Even now, many think that economic recessions generated for economic reasons are impossible in the planned economy. We checked this idea against the long-run statistical data for Russia and found that cycling does occur, not only in market, but in planned economies as well (of course, with a significant remark that crises in planned economies are much rarer but possibly more destructive).
Added: Apr 9, 2015
Working paper
Karev M. G. Количественный анализ в экономике. WP2. Высшая школа экономики, 2013. No. WP2/2013/05.
One of the fundamental sources of heterogeneity in real-life economies lies in stochastic nature of individual income. However to incorporate this heterogeneity into a tractable general equilibrium model presents a difficult problem since the dynamics of such economies is the type-distribution of agents. For that reason research has been concentrated for the last 20 years on numerical methods. This paper offers an analytical framework that helps to characterize the behavior of economies with idiosyncratic income shocks in close analogy to the standard representative agent model. The first part deals with aggregation issue. The second part develops special models, the so called constant prudence economies, that yield a remarkably high level of approximation (0,05% precision in the calibrated model).
Added: Sep 30, 2013
Working paper
Muradov K. Количественный анализ в экономике. WP2. Высшая школа экономики, 2014. No. 03.
Gross exports accounting is a novel sub-area of research that seeks to allocate the value added in gross trade flows to its true country and sector of origin and country or sector of destination. Various frameworks have been recently proposed to perform such decompositions. This paper reviews and classifies these into two broad categories: gross exports accounting and cumulative value added accounting. While the former was exhaustively explored by Wang, Wei and Zhu (2013), this paper attempts to refine and generalise the latter. The results are mostly identical to those of Koopman, Wang and Wei (2012) and Stehrer (2013), but the generalised framework attains a desired level of computational efficiency and is highly customisable for specific purpose of global value chain analyses. The refined formulations are applied to describe Russia’s export performance from global value chain perspective using the data from the World Input-Output Database (WIOD) for 2000, 2005 and 2010.
Added: Jun 28, 2014
Working paper
Danilin V., Isaev N. I., Kapustin A. K. et al. Количественный анализ в экономике. WP2. Высшая школа экономики, 2015. No. 2.
The authors of the paper suggested an original methodology for measuring social exclusion risks and scope of social exclusion in regions of the Russian Federation. Regional ratings for specific groups of population and dimensions of social exclusion risks presented in this paper may have socialpoli-cyimplications.
Added: Mar 18, 2015
Working paper
Шведов А. С. Количественный анализ в экономике. WP2. Высшая школа экономики, 2010. № 01.
This paper is concerned with matrix variate t-distribution. The degrees of freedom parameter of the t-distribution is a vector. The distribution is applied to multivariate regression models.
Added: Apr 1, 2013
Working paper
Smirnov S., Isaev N. I., Kapustin A. K. et al. Количественный анализ в экономике. WP2. Высшая школа экономики, 2015
Added: Jan 28, 2018
Working paper
Соловьев А. К., Донцова С. А., Кувалкина Е. Количественный анализ в экономике. WP2. Высшая школа экономики, 2003. № 02.
The paper is devoted to methods of an estimation of a financial state of the system of obligatory pension insurance of the Russian Federation on a long-term outlook.
Added: Mar 31, 2013
Working paper
Писляков В. В. Количественный анализ в экономике. WP2. Высшая школа экономики, 2002. № 02.
The paper deals with a comprehensive analysis of the content of electronic databases of foreign periodicals with online and CD-ROM access. Main emphasis lies on social sciences databases (economics, business, sociology, political science, law). A detailed analysis of the quantitative characteristics of the content of leading databases is performed. A procedure for determining professional level and quality of the electronic database content with the impact factor as a principal criterion is proposed. Results of this method used for some of the content providers are presented. Perspectives of applying of the method for collection acquisition management in academic libraries as well as its further enhancing are outlined.
Added: Mar 31, 2013
Working paper
Бессонов В. А. Количественный анализ в экономике. WP2. Высшая школа экономики, 2010. № 05.
Added: Apr 1, 2013
Working paper
Борзых (Зюзина) О. А. Количественный анализ в экономике. WP2. Высшая школа экономики, 2016. № WP2/2016/02.
The aim of this paper is to reveal the main features of the bank lending channel in the Russian economy. Having the answer to this question is important for increasing the efficiency of monetary policy because it will allow to evaluate the extent to which monetary policy impulses affect bank loans that are one of the main source of investments in Russia. The methodology is based on [Kashyap, Stein, 2000]. We analyze monthly data on the individual Russian banks’ balance sheets over the period 2010-2014. In order to take into account considerable differences between different groups of the Russian banks we divide our sample into groups according to their ownership structure, value of net assets, and their main activities. We also address a heterogeneity in the period of time we study. It is shown that there exists a relationship between liquidity level of the Russian banks’ balance sheets, their lending policy and monetary policy impulses depending on the banks’ characteristics and the period of time. We find liquidity “anti-effect” for the big Russian banks during the structural liquidity deficit period: the more liquid their balance sheets, the more these banks substitute corporate loans with liquid assets purchases under conditions of contractionary monetary policy regime. For some groups of medium and small banks that prefer to maintain the volume of corporate loans by selling liquid assets we justify the “classical” Kashyap and Stein liquidity effect. We also find some groups of medium and small banks through which bank lending channel did not work during the period of time we analyze.
Added: Nov 14, 2016
Working paper
Шведов А. С. Количественный анализ в экономике. WP2. Высшая школа экономики, 2009. № 01.
This paper is concerned with a matrix variate beta distribution. Two vector parameters determine the distribution. It is applied to state space models.
Added: Apr 1, 2013
Working paper
Бессонов В. А. Количественный анализ в экономике. WP2. Высшая школа экономики, 2009. № WP2/2009/02.
Added: Jan 28, 2013
Working paper
Карев М. Г. Количественный анализ в экономике. WP2. Высшая школа экономики, 2010. № 02.
Added: Apr 1, 2013
Working paper
Смирнов А. Д. Количественный анализ в экономике. WP2. Высшая школа экономики, 2007. № 03.
Simple debt monetization model is proposed to analyze one of the major consequences of global excess liquidity. Stochastic dynamics of liquidity is decomposed into several regimes to be distinguished due to changes in the standard asset portfolio. Thus, regime of complete market that, as a rule, allows for the debt monetizing in full, is modeled as analogue to the Black-Sholes equation. Further transition into regime of excess liquidity gives rise to severe distortions in relationships between debt and liquidity due to large increases in positive feedbacks speeding up the growth of debt outstanding as well as of notional debt. These outcomes are straightforward consequences of the widespread practice of debt redemption which allows for the usage of new debt obligations, the latter being similar, for example, to the asset-backed commercial paper, ABCP. If the market micro structure continues to evolve towards the fractal cluster of debt buyers as liquidity approaches its critical level, then fi nancial system percolates. At the point of singularity market collapses since infi nite debt cannot be redeemed with fi nite liquidity. The model demonstrates that, unlike the mere “paper losses’ of the 2007 credit crunch, asset securitization and fi nancial innovation processes might under particular conditions produce the total crash of global fi nancial system. Simple site percolation methods make it possible to evaluate the conditional probability of such an outcome as being equal to 27 percent.
Added: Feb 12, 2013
Working paper
Смирнов С. В. Количественный анализ в экономике. WP2. Высшая школа экономики, 2012. № WP2/2012/04.
The trajectory of the industrial output of the Russian empire – the USSR – the Russian Federation for more than 150 years has been carefully investigated through official statistics as well as dozens of alternative estimates made by Russian and foreign experts. Calculation of the aggregated “consensus” industrial production index has made it possible to date the cyclical turning points and to measure the depth and length of the main industrial recessions for the last century and a half. The most important causes of all these recessions are described. The cyclical volatility of Russian industry is compared with the cyclical volatility of American industry.
Added: Apr 12, 2013
Working paper
Дементьев А. В., Бессонов И. О. Количественный анализ в экономике. WP2. Высшая школа экономики, 2011. № 04.
This paper systematically reviews the theoretical rationale for the various core inflation measures and the experience of their implementation. The widely used exclusion-based method, also adopted in Russia for the official ‘core’ consumer price index since 2003, is applied to calculate retrospectively this index back to 1997. A number of alternative core inflation measures for Russia for the period of 1997-2010 are also provided, with the methodology of their construction explained in detail. Formal criteria characterizing the correspondence of different core inflation measures to the theoretical requirements are econometrically tested, showing that the official ‘core’ consumer price index reflects the trend of price dynamics no worse than other measures constructed using exclusion-based and trimmed-mean methods
Added: Dec 21, 2012
Working paper
Шведов А. С. Количественный анализ в экономике. WP2. Высшая школа экономики, 2007. № 02.
The paper approaches portfolio selection by dynamic stochastic programming in a Bayesian framework. Interpolation by spline functions is implemented to avoid the computational burden. A solution for testing of the method to the portfolio selection problem is suggested. Results of the test are presented.
Added: Apr 1, 2013
Working paper
Карев М. Г. Количественный анализ в экономике. WP2. Высшая школа экономики, 2008. № 03.
We consider a model of a small open economy that explains some important features of inflation and real exchange rate dynamics observed in the Russian economy and based on the assumption of low interest rate elasticity of capital flow. We demonstrate efficiency of the model in simulating the medium term dynamics of inflation and real exchange rate including the financial crisis of 1998 and its usefulness in forecasting the variables under given conditions including the current financial crisis. We derive a clear trade-off between inflation and real exchange rate appreciation in the presence of external shocks. We offer a comparative analysis of optimal monetary policy under conditions of low and high interest rate elasticity of capital flow.
Added: Apr 1, 2013
Working paper
Шведов А. С. Количественный анализ в экономике. WP2. Высшая школа экономики, 2015. № WP2/2015/01.
Added: Mar 9, 2015