Target recovery of the economic system based on the target reinforcement path method

Abstract

An effective and stable operation of an economic system leads to a prosperous society and sustainable world development. Unfortunately, the system faces inevitable perturbations of extreme events and is frequently damaged. To maintain the system's stability, recovering its damaged functionality is essential and is complementary to strengthening its resilience and forecasting extreme events. This paper proposes a target recovery method based on network and economic equilibrium theories to defend the economic system against perturbations characterized as localized attacks. This novel method stimulates a set of economic sectors that mutually reinforce damaged economic sectors and is intuitively named the target reinforcement path (TRP) method. Developing a nonlinear dynamic model that simulates the economic system's operation after being perturbed by a localized attack and recovering based on a target recovery method, we compute the relaxation time for this process to quantify the method's efficiency. Furthermore, we adopt a rank aggregation method to comprehensively measure the method's efficiency by studying the target recovery of three country-level economic systems (China, India, and Japan) for 73 different regional attack scenarios. Through a comparative analysis of the TRP method and three other classic methods, the TRP method is shown to be more effective and less costly. Applicatively, the proposed method exhibits the potential to recover other vital complex systems with spontaneous recovery ability, such as immune, neurological, and ecological systems.

Changes in Air Quality during the Period of COVID-19 in China

“…Previous studies involving air quality prediction used econometric or numerical simulation methods [ 35 , 36 ] or aimed to provide specific air quality estimates or CO 2 for the next few days or weeks. Considering new information makes the system less predictable [ 37 ]. This paper does not intend to estimate the concentration of air pollutants in the future and pays more attention to whether the outbreak of COVID-19 could affect the varying intensity of the AQI.…”