Research on Natural Disaster Vulnerability and Its Poverty-Causing Effect in Contiguous Poor Rural Areas

doi:10.3969/j.issn.1000-6362.2017.08.007

Abstract

Abstract: In order to explore the natural disaster vulnerability of farmers and its poverty-causing effect in the process of marketization to find the primary point in taking targeted measures in poverty alleviation. Based on the rural survey data of contiguous poor areas in Guangxi and Shaanxi, this paper analyzed farmers’ perception about various disaster risks, evaluated farmers’ vulnerability to natural disaster and market risk. Then the article conducted a comparative study on the poverty-causing effect of natural disaster vulnerability and market risk vulnerability through the Entropy method and Probit model. The results showed that:（1）the farmers’ perception level on the natural disaster is higher than the market risk, which indicates that natural disasters, especially droughts and floods, are the main threats to farmers.（2）Farmers’ natural disaster vulnerability is higher than the market risk vulnerability, which showing that natural disasters are more likely to cause losses than market risks for farmers.（3）The raise of natural disaster vulnerability level will significantly increase the possibility of farmers’ dropping into poverty, its effect to cause poverty is stronger than the market risk vulnerability. But the effect of natural disaster vulnerability is negatively related to market risk vulnerability statistically. Therefore, the poverty caused by natural disasters cannot be ignored, and in order to lift farmers in contiguous poor areas from poverty, it is supposed to take improving the ability of rural disaster mitigation in the first place, and then to promote small farmers participating in big market effectively.

Key words: Farmers, Poverty, Probit, Meteorological disaster, Market risk

YAN Ting-wu, ZHANG Tong-chao, ZHANG Jun-biao. Research on Natural Disaster Vulnerability and Its Poverty-Causing Effect in Contiguous Poor Rural Areas[J]. Chinese Journal of Agrometeorology, 2017, 38(08): 526-536.

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