
Conference publicationsAbstractsXXIX conferenceIdentification of long waves in the analysis of some macro indicatorsFinancial University under the Government of the Russian Federation, Moscow, tel. 8 (926) 4994736, kontsevaya07@list.ru 1 pp. (accepted)The rate of change in economic processes has been dramatically increasing in recent decades. The existing generally accepted approaches to the quantitative analysis of both dynamic changes and the assessment of causeandeffect relationships are working worse in the case of assessing the future state of economic indicators and trends. The hope of maintaining the prevailing trends creates a field for maneuvering based on econometric approaches, but this hope is becoming more and more illusory, while the probabilities of shock events in both politics and economics are becoming more and more likely. The structure of the time series of observations of economic indicators assumes the presence of several possible components, and the cyclicity in the observed process can be noticeable only at sufficiently large intervals for observations (in several decades). The problem of detecting cyclicity is reduced to choosing the best specification of the trendseasonal model, after removing which it becomes possible to assess the presence of cyclical fluctuations in the economic indicator of interest. Thus, the cycle allocation procedure is a stepbystep procedure for removing deterministic components of the time series structure, which allows, as a result of reduction, to obtain the latent component of interest, demonstrating the wave nature of the process. In the work, different types of modeling of time series dynamics were used to build trendseasonal models – based on additive and multiplicative models. The best results were obtained based on the inclusion of dummy variables in the parabolic model. The number of fictitious variables was assumed to be equal to the number of observations within one oscillation cycle (quarterly observations) minus one. As a result, the study of the dynamics of some Russian macro indicators revealed the presence of a cyclic component with a long period (about 2025 years). Long waves in the economy are a generally recognized phenomenon, we are discussing the question of the wavelength. This approach in modeling the dynamics of per capita incomes of the population allowed us to confirm the existence of long cycles in the Russian economy.
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