Подходы к построению трейсера бизнес-циклов на примере обрабатывающей промышленности России

Abstract

The importance of studying business cycles is determined by the scale of their impact on the economy and society, which leads to the need to develop methods to counteract their negative impact. Given the complexity of the topic and the many theories and debates in the field, there is a need for a simple tool to present business cycle information in an intuitive way for a wide audience. Such a tool is a business cycle tracer. This article is devoted to testing the possibility of using three approaches for its construction: the first (trend approach) is based on information whether the cycle is above or below the long-term trend, and whether it is increasing or decreasing; the second (growth rate approach) is whether the growth rates are above zero, and they are growing or decreasing compared to the neighboring time period; the third (fact-expectation approach) is whether estimates of the current situation and expectations are above or below zero (trend, long–term average, etc.). The work used data on the dynamics of output, the volume of future orders and the results of surveys of the manufacturing industry. The article shows that the first approach works best and allows you to clearly define the phases and turning points of the business cycle. The second approach makes it possible to identify phases of the business cycle, but has some disadvantages: jumps in the series from one quadrant to another and back near the boundary values occur, which complicates the analysis. The third approach is not acceptable for constructing a tracer, since it does not allow us to fully identify all phases of the business cycle and may have dynamics that do not correspond to the general logic of business cycles. The article also demonstrates the high relationship between the business cycles of the manufacturing industry and the business climate indicator of the Bank of Russia (data from business surveys of enterprises), indicating a change in the dynamics of the business cycle with 1-3 months ahead of statistics. Given the faster publication of survey results than statistical data, it can be used as a leading indicator.