Residential loan debt dynamics: Phase analysis of cyclicity

• Main Author: Ilyasov, R. Kh
• Format: Conference Proceeding
• Language: English
• Subjects: Data analysis; Debt restructuring; Decision making; Dynamics; Economic analysis; Economic conditions; Economic models; Efficiency; Indicators; Interpolation; Model accuracy; Modelling
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0075699

Accuracy in the model description of the debt burden indicators dynamics is an important condition of crisis prevention in economy. Cyclical nature, being the form of economy crisis nature, can be frequently manifested as relative growth rate reductions or accelerations, in the form of growth cycles. Identifying growth rate reductions or accelerations in presence of a prevailing trend is possible by modelling methods, sensitive to economic activity minor changes. At this, the transfer from the analysis of generalized data on discrete conditions of the economical system to the analysis of precise data on continuous changes becomes essential. Elements of economical dynamic systems, describing conditions and condition changes, are stock and flows. It is known that the stock determine conditions for the specific time moments, and the flows determine changes in the economical system conditions for time intervals. The flows, being dynamic indicators of changes in economical systems, appear to be the source of more reliable information for decision making, than the stock. In this paper, we suggest to assess the efficiency of econometric modelling of cyclical nature with methods, abstracting from real data distortion. This allows taking into account even minor changes of conditions in the system, that are indicators of growth cycles manifestation. The paper deals with the efficiency of spline interpolation modelling of state dynamics in the growth cycle analysis. It is proposed to reveal growth cycles with the phase analysis, using the example of residential loan debt dynamics. It is proposed to transform the discrete debt dynamics into the flow of continuous changes by differentiation. According to the analysis, spline interpolations shows its efficiency for the purposes of cyclical nature phase analysis. In the dynamics of residential loan debt growth rate accelerations and reductions in 2008-2011 and 2014-2018, it possible to reveal growth cycles.