Detecting and predicting turning points in growth cycle using business survey data
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The aim of this paper is to present the possibility of analyzing cyclical changes in economic activity using business tendency survey data collected by Research Institute of Economic Development (RIED). The delta cumulation concept was presented. It is a new method of aggregation of business survey data, which enables building new time series with inbuilt trends. Therefore they can be decomposed on cycle and trend component using Hodrick-Prescott filter. The cyclical components of these cumulated time series which were highly correlated with GDP cyclical component were used to estimate probit models. The aim of this part of the analysis was to find the probabilities of turning points in Polish economy. The two best models signalled all turning points in Polish growth cycle with an accuracy of two quarters. The out-of-sample turning point was signalled with two quarters lead.The research confirmed the usefulness of RIED business tendency survey data in analysis of waves in economic activity and in predicting turning points in growth cycle in Poland during transition period.
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