A Dynamic Model for Measuring Resilient Dividend Including the Levels of Shocks and Resilience Based on Covid-19 Data at the Subnational Level of China

Resilience has been mentioned frequently as an essential component of Sustainable Development and a solution to climate change. However, resilience does not impose an additional burden, but provide dividend on development. After an overview of definitions for resilient dividend, we proposed a dynamic framework to measure the resilient dividend under different levels of shocks and resilience. We did an empirical study in the context of COVID-19 to verify the correlations between resilience and dividend. A bunch of indicators and quantitative data at the subnational level of China were collected to represent the impact of the pandemic, the resilient levels and the dividend gained from resilience for 30 provinces in China. After descending the dataset with PCA (Principal Component Analysis) and maximum variance method, we experimented hierarchical regression which revealed that more dividends could be expected with a higher level of resilience, particularly under severe shocks. The conclusions could provide a better understanding of resilience and a theoretical basis for further discussion on resilient dividends.