Финансово-экономические кризисы как завершение и начало экономических циклов
Куранов Г. О., Владимиров А. Б.
Edited by: Е. Г. Ясин Кн. 1. М.: Издательский дом ГУ-ВШЭ, 2010.
Берзон Н. И. В кн.: X Международная научная конференция по проблемам развития экономики и общества: В 3 кн.. Кн. 1. М.: Издательский дом ГУ-ВШЭ, 2010.
Added: Sep 27, 2013
Островская Е. П. Мировая экономика и международные отношения. 2010. № 4. С. 52-63.
Added: Oct 2, 2012
Smirnov S. V., Kondrashov N. V., Petronevich A. Economics. EC. Высшая школа экономики, 2016. No. 122.
This paper establishes a reference chronology for the Russian economic cycle from the early 1980s to mid-2015. To detect peaks and troughs, we tested nine monthly indices as reference series, three methods of seasonal adjustments (X-12-ARIMA, TRAMO/SEATS, and CAMPLET), and four methods for dating cyclical turning points (local min/max, Bry-Boschan, Harding-Pagan, and Markov-Switching model). As these more or less formal methods led to different estimates, any sensible choice was possible only on the grounds of informal considerations. The final set of turning points looks plausible and separates expansions and contractions in an explicable manner, but further discussions are needed to establish a consensus between experts.
Added: Jan 22, 2016
Вып. 4. М.: Национальный совет по корпоративному управлению, 2011.
Added: Feb 16, 2013
Воронин Г. Л., Дорофеева З. Е., Киселева И. П. и др. В кн.: Вестник Российского мониторинга экономического положения и здоровья населения НИУ ВШЭ (RLMS-HSE). Вып. 2. М.: Издательский дом НИУ ВШЭ, 2012. С. 6-65.
Added: Jan 29, 2013
Added: Jan 29, 2013
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
Савицкая Е. В. М.: Литтерра, 2015.
Added: Nov 7, 2015
Petronevich A., Billio M. University Ca' Foscari of Venice, Dept. of Economics Research Paper Series. WP/2017. University Ca' Foscari of Venice, 2017
We adopt the Dynamical Influence model from computer science and transform it to study the interaction between business and financial cycles. For this purpose, we merge it with Markov-Switching Dynamic Factor Model (MS-DFM) which is frequently used in economic cycle analysis. The model suggested in this paper, the Dynamical Influence Markov-Switching Dynamic Factor Model (DI-MS-FM), allows to reveal the pattern of interaction between business and financial cycles in addition to their individual characteristics. More specifically, this model allows to describe quantitatively the existing regimes of interaction in a given economy and to identify their timing, as well as to evaluate the effect of the government policy on the duration of each of the regimes. We are also able to determine the direction of causality between the two cycles for each of the regimes. The model estimated on the US data demonstrates reasonable results, identifying the periods of higher interaction between the cycles in the beginning of 1980s and during the Great Recession, while in-between the cycles evolve almost independently. The output of the model can be useful for policymakers since it provides a timely estimate of the current interaction regime, which allows to adjust the timing and the composition of the policy mix.
Added: Oct 20, 2017
Added: Jun 30, 2012