To the problem of turbulence in quantitative easing transmission channels and transactions network channels at quantitative easing policy implementation by central banks

TL;DR

This paper models the turbulence in quantitative easing transmission and transaction channels as nonlinear chaotic flows, using physics-inspired theories to forecast US economic responses to liquidity changes.

Contribution

It introduces a novel approach applying hydrodynamics and nonlinear dynamics theories to analyze and predict financial system behavior under QE policies.

Findings

Capital flows can be characterized by Reynolds numbers.

Transition to chaos occurs via bifurcations in turbulent flows.

Model accurately forecasts US economic performance under different liquidity levels.

Abstract

In agreement with the recent research findings in the econophysics, we propose that the nonlinear dynamic chaos can be generated by the turbulent capital flows in both the quantitative easing transmission channels and the transaction networks channels, when there are the laminar turbulent capital flows transitions in the financial system. We demonstrate that the capital flows in both the quantitative easing transmission channels and the transaction networks channels in the financial system can be accurately characterized by the Reynolds numbers. We explain that the transition to the nonlinear dynamic chaos regime can be realized through the cascade of the Landau, Hopf bifurcations in the turbulent capital flows in both the quantitative easing transmission channels and the transaction networks channels in the financial system. We completed the computer modeling, using both the Nonlinear Dynamic Stochastic General Equilibrium Theory (NDSGET) and the Hydrodynamics Theory (HT), to accurately characterize the US economy in the conditions of the QE policy implementation by the US Federal Reserve. We found that the ability of the US financial system to adjust to the different levels of liquidity depends on the nonlinearities appearance in the QE transmission channels, and is limited by the laminar turbulent capital flows transitions in the QE transmission channels and the transaction networks channels in the US financial system. The proposed computer model allows us to make the accurate forecasts of the US economy performance in the cases, when there are the different levels of liquidity in the US financial system.