Flow Correlations Within Time Intervals Of Variable Length: Spline Analysis

Abstract

The paper presents a new method for studying the mutual correlation of flows within short time intervals. The analysis of local correlations is necessary for the efficient management of flows in the economygoods, transport, financial, labor, etc. It is known that switches can be observed in regressions of economic processes and divide correlation trajectories into temporal segments of various lengths. This causes the problem of quantifying the closeness and analytical representation of the correlation within sequential time intervals of variable length. Solving the problem will contribute to identification of possible regression switches and management of flows with regard to changes in market conditions. The sensitivity of conventional econometric methods to the length of the studied dynamics series does not allow identification of regression switches and estimation of the correlation closeness within short time intervals. Modeling of the dynamics of the investigated processes by cubic splines is effective. It is shown that the minimum curvature of cubic splines eliminates the criticality of the correlation method to the length of the studied dynamics series. Zero error of spline models at nodal points allows for more efficient identification of regression switches. The differentiability of splines allows movement from the study of the flow dynamics to the search for correlations between changes in the flow rate. The study is based on data on oil export flows. The proposed methodology for modeling flows and analyzing their correlation enabled identification of correlations between the rate of oil export flows to non-CIS and CIS countries.