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Determinants of Credit Cycles and Their Forecasts

Student: Kareva Yulia

Supervisor: Alexander M. Karminsky

Faculty: International College of Economics and Finance

Educational Programme: Double degree programme in Economics of the NRU HSE and the University of London (Bachelor)

Year of Graduation: 2018

For the insurance of stability of banking system in a country and to minimize losses incurred by financial institutions during crises, Basel Committee proposes to impose a countercyclical buffer corresponding phases of credit cycle. The research is aimed to provide a contribution into the understanding of the nature of credit cycles in countries with developing economy. The novelty that is introduced in the research affects both the independent variable and the explanatory variables. There is proposed an alternative method to evaluate the Credit-to-GDP gap. The method of weighted historical simulation provides clear view of crises caused by political, economical and social sources. The method provides explicit results; however, it is simpler for practical application than the classic approach of Hodrick-Prescott filter. Also a new view on explanatory variables is presented. There is proposed a cluster point of view. Three clusters are evaluated: Banking, Macro country and Macro world. For the countries with emerging economy (namely, countries of BRICS union) models including simultaneously Banking and Macro country clusters have the best explanatory and forecasting power. According to the results obtained in the research the countries are distinct and different sets of factors appeared to be significant for determination of credit cycles. Therefore, in future researches the results may be improved by investigation of the countries separately and also by enlargement of sample of observations in time. The research provides a view on the constituents of credit cycle. However, for the construction of proper forecasts of future changes of credit cycle and occurrence of crises there should be conducted further research for threshold values of the parameters, and their impact on credit cycle to be evaluated.

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