Modeling The Resilience Conditions Of National Economy And Its Policy Implication

Recently,industrial ecosystems are highly complex and can collapse when subjected to local and global uncertainties.Similarly,unsuitable topology structures(network structures)and exchange rate volatility drop the economic resilience.These two factors are necessary for the industrial sectors and organizations to withstand and remain operational during economic shocks.This study investigates the conditions that shape the robust structure of industrial ecosystems.The effective topology structure will thus have a capacity of absorbing and withstanding disruptive economic events.Each country has a different strategic approach to combat the risks.This study raised the question of why be some economies much better in resilience than others during a crisis? To find answers,this study investigates the ecosystem’s resilience and the impact of mutualistic industrial networks on it.The work has to answer three questions.One is to develop a robust industrial ecosystem structure that withstands economic risks.Secondly,the study investigates the industrial collapse and the contributing factors.Finally,this work suggests strategies to avoid the collapse.Quantifying and analyzing industrial ecosystem resilience is essential in strategically locating critical facilities as network operations strategies.In support of this,this study develops a mathematical model based on the Lotka-Volterra approach.The interactive space’s high dimensionality issue is addressed using the reduction method.We transform the multi-dimensional model into a one-dimensional model without losing the model’s ability to describe the resilience of the industrial ecosystem.Second,we adopt the stochastic model system approach together with the resilience triangle to quantify the degree of industrial resilience.Third,we apply the variance decomposition(AR(1)-VECHMGARCH)method to yield the volatility-spillover index for systemic shock investigation.Finally,to suggest ecosystem collapse mitigation strategies,the study adopted the Ordinary Least Squares(OLS)to examine the statistical significance between industrial diversification and resilience.Moreover,the adoption of the Dyanamic Conditional Correlation(DCC)model robustly discussed the hedge ratio as the best option for industrial collapse mitigation.This study divided the period from 1995 to 2018 into 5 phases to observe the impact of mutualistic interaction of 33 industries,FDI,and exchange rate volatility on the economic resilience of 62 OECD countries.In our study,first,we investigate the conditions for the resilience of the national economy.This is achieved by observing the cases of seven developed and emerging economies and a global perspective for the robustness of the outcome.Secondly,we observe the role of those conditions(industrial topology)towards the collapse of industrial ecosystems.Finally,we suggest hedging and diversification strategies as the optimal control for improving industrial resilience,thereby avoiding the collapse of the industrial ecosystem.The simulated numerical results unveil that network characteristics and industrial diversification can enhance resilience and helps in avoiding economic collapse.Furthermore,the upsurge of FDI,interaction strength,and trade openness enhanced economic resilience.At the same time,exchange rate volatility impeded industrial growth and suppressed system resilience.Optimal hedge ratio and industrial diversification strategies are the problem-solving strategies for resilience enhancement.This study’s results-based implications will help strengthen the system’s resilience against local and global perturbations.