Assessing macroeconomic recovery after a natural hazard based on ARIMA—a case study of the 2008 Wenchuan earthquake in China

Abstract

In this research the autoregressive integrated moving average model (ARIMA) was adopted to estimate GDP growth for assessing macroeconomic recovery from a natural hazard. ARIMA is a powerful tool for predicting future macroeconomic situations based on macroeconomic data and trends before a disaster. This research examined the economic recovery of severely affected counties 6 years after the Wenchuan Earthquake by comparing the simulated regional GDP values from 2008 to 2014 with actual regional GDP data following the disaster. A macroeconomic recovery ratio model was built to assess economic resilience of the affected counties. Although the GDP of the 10 most severely affected counties grew rapidly after the earthquake, in only one county—Pengzhou City—it recovered to the pre-disaster level under a no hazard scenario. The gaps in economic recovery between the severely affected counties were significant. Areas with competitive industries and locational advantage exhibited the highest rates of recovery. Therefore, industrial structure and relative location of the affected areas to traffic nodes and economic centers should be considered in pre-disaster assistance decisions and development plans in the future.