Livelihood Resilience of Rural Residents under Natural Disasters in China

Hang Liu (), Wenli Pan, Fei Su, Jianyi Huang, Jiaqi Luo, Lei Tong, Xi Fang and Jiayi Fu
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Wenli Pan: School of Tourism and Urban-Rural Planning, Zhejiang Gongshang University, Hangzhou 310018, China
Fei Su: School of Tourism and Urban-Rural Planning, Zhejiang Gongshang University, Hangzhou 310018, China
Jianyi Huang: College of Applied Arts and Science, Beijing Union University, Beijing 100191, China
Jiaqi Luo: School of Tourism and Urban-Rural Planning, Zhejiang Gongshang University, Hangzhou 310018, China
Lei Tong: School of Tourism and Urban-Rural Planning, Zhejiang Gongshang University, Hangzhou 310018, China
Xi Fang: School of Tourism and Urban-Rural Planning, Zhejiang Gongshang University, Hangzhou 310018, China
Jiayi Fu: School of Tourism and Urban-Rural Planning, Zhejiang Gongshang University, Hangzhou 310018, China

Sustainability, 2022, vol. 14, issue 14, 1-21

Abstract: The impact of natural disasters on rural areas has recently increased, the question of how to effectively improve the livelihood resilience of rural residents has therefore become an essential issue. In this context, a livelihood resilience evaluation index system for rural residents was constructed in four dimensions: livelihood quality, livelihood promotion, livelihood provision, and disaster stress. A structural dynamics model was used to analyze the changing characteristics of the livelihood resilience of rural residents in China between the years 1980 and 2020, and a livelihood resilience trend from 2021 to 2030 was predicted based on the ARIMA model. The main factors influencing livelihood resilience were explored using ridge regression analysis. The results show that: (1) livelihood resilience of rural residents in China fluctuated significantly between 1980 and 2020, tending generally to increase; (2) livelihood resilience is positively correlated with livelihood quality, livelihood promotion, and livelihood provision, while it is negatively correlated with disaster stress; (3) livelihood quality, livelihood promotion, and livelihood supply will still increase between the years 2021 and 2030, while the increase of livelihood resilience will tend to slow down; and (4) six variables have a significant positive impact on livelihood resilience, and provide a basis for the subsequent enhancement of livelihood resilience.

Keywords: livelihood resilience; ARIMA model; structural dynamics; ridge regression analysis; rural residents (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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