Economic Cycle and Credit Volume Interaction: Case of Lithuania

Abstract

Economic (sometimes called "business") cycle research is one of the most popular topics of scientific literature discussions over the last years encompassing global economy long-term grow and recession starting from 2007. Such cycles can also be observed in banking activities-decreasing crediting volumes can be noticed in the majority of countries. However, the interaction between financial and business cycles is not fully revealed and differs in different countries. In the case of Lithuania credit volume and business activeness cyclic interaction can be also named as specific, reflected in gross domestic product (GDP) and credit volume fluctuations. Based on various economic cycle stages identification methodologies, not every single fluctuations can be assigned as an economic cycle stage: some of them are not identified as significant and are not recognised as economic cycles, the others match an economic cycle stage and time criterions and can be recognized as economic cycles. In the current situation, when global economy and the situation in Lithuania show recovery signs from recession to growth, credit market reacts respectively. Though the question of business and credit volume cycles is very actual, because knowing credit market dynamics indications and synchronization level between credit and economic cycles different financial stability implementation politics measures can be developed. The importance of business and credit volume cycles interaction research is also evident from the number of theoretic studies, however, to investigate interaction between an economic cycle and crediting activities in Lithuania banks there was adopted methodology developed by Kress (2004) and Avouyi-Dovi et al. (2006), including these main stages: 1) identification of turning points according to Avouyi-Dovi et al. (2006) adopted Harding and Pagan methodology, identifying peaks and troughs when two different economic cycle indicators are selected (Industrial production (Lt) and GDP (Lt)) with three credit cycle indicators (Total loans (Lt); Household loans (Lt); Loans to non-financial corporations (Lt)); 2) Calculation of concordance index between economic cycle and banks provided credit volume using business and credit cycle indicators; 3) Valuation of dependence between economic indicators and banks credit activities ratios using correlation function; 4) Conclusions delivering. Research methodology consists of separate independent stages, what makes possible to compare the results in separate stages and deliver more comprehensive conclusions. Obtained results revealed that peak in Total loans indicator converge with the peak in economic cycle indicators, but the peak in Household loans is accessed earlier than the peak in economic cycle indicators. These tendencies were also approved by the correlation analysis and calculation of a conformity indicator. The results allow to deliver significant conclusions about government monetary political decisions influencing the country's economic cycle fluctuations and determining fi...

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