Harmonization of Economic Cycles: Methods of Statistic Research and Econometric Modeling
Elena Zarova
Samara State University of Economics, Statistics Department, Ulitsa Sovetskoi Armii 141, Samara 443090, Russia

Short-term economic cycles (phase length from several months to half a year) have a more significant impact on the economy on a regional level than on a national level. Thus, there is a demand both in developing the theoretical grounds of studying short-term economic cycles on a regional level and methods of their analysis and modeling as the toolkit for forecasting highly dynamic economic cycles in the region. The object of the research is the economy of Samara region - an industrial and agricultural developed region of the European part of Russia, independent administrative subject of the Russian Federation. According to the data of the recent population census in 2010, the region's population exceeds 3.2 million people. The subject of the research - highly dynamic processes of the region's development having the periodic character with high-frequency time phases and amplitude significant for yearly development results. The scientific novelty of the author's approach is that it suggests and tests evaluation, analysis and forecast methods of short-term cycles in the economy of the region on the basis of leading indices system and the complex of mathematical and statistical methods. The author suggests three variants of calculating composite leading index that differ from each other by sensitivity degree of the final figure to the forthcoming turning points and the change of stages in short-term cycles of the region's economy. The phenomenon of harmonization of economic cycles with different phases (long, medium and short-term) results in multiplication orleveling of their negative economic consequences. The aim of the research was to reveal the leading indices of short-term cycles on a regional level and analyze statistical regularity of Samara and Russia oil production cycling changes impact on the economic indices of European countries. Econometric modeling and forecasting methods were used on the basis of integrating trend and cycling components of different time series. The composite leading index of cycling process in Samara region was designed as a weighted average of trend-cycling magnitudes of leading indices: structure-dynamic indices of Samara region, other regions, Russia in general and other countries.