中国灾害风险与贫困互相关效应的理论分析与实证研究

doi:10.12118/j.issn.1000-6060.2021.581

摘要/Abstract

摘要：

在全球自然灾害频发和贫困长期且不均衡展布的背景下,灾害风险与贫困的联结成为学术界和利益相关者关注的焦点。基于自然灾害风险管理和社会-生态韧性评估的基本原理,系统论述了灾害致贫和贫困致险的作用机理与驱动路径,这种互相关效应称为灾害风险-贫困的“羁绊”;基于中国31个省（自治区、市）2010—2019年的面板数据,运用计量经济学回归分析方法,以证实减轻灾害风险和扶贫脱贫在省域尺度上存在双向加持的作用。结果表明：（1）较高的致灾因子危险性、承灾体暴露性和脆弱性及复杂的灾害风险情景引发了人员伤亡、资产破坏和经济损失等多重负面影响,最终导致和加剧了经济、机会、能力和文化的多维度贫困;贫困群体农业生计和家庭资产的高暴露性和低韧性放大和累积了灾害风险。（2）中国在脱贫攻坚和全面建设小康社会的进程中,减灾扶贫和脱贫降险的循环效应显著,籍此带来了乡村振兴、治理现代化等战略的属性加持。（3）贫困致险的机制较为隐性且主要显现于广布型灾害风险情景,对其无视或轻视可能带来投资减灾失效、学科范式陷阱和不可持续发展等诸多后果。研究结果可为中国的减灾和扶贫协同发展提供理论依据和现实证据,并为贯彻落实经济、政治、文化、社会和生态文明建设“五位一体”战略,实现“双碳”目标和应对全球气候变化提供智力支撑。

关键词: 灾害风险, 贫困, 羁绊, 韧性, 广布型灾害风险

Abstract:

In order to clarify the disaster risk-poverty nexus and evaluate the two-way correlation effects related to poverty caused by disasters and risk caused by poverty, this paper takes the “fetter” of disaster risk and poverty as the study object. This work aims to integrate disaster risk reduction (DRR) and poverty alleviation. Using the econometrics hypothesis test, this work uses regression analyses on the data from 31 provinces in China from 2010 to 2019 to identify the positive effects of investment in poverty alleviation on DRR. The research shows that: (1) High disaster risk produces huge casualties and asset destruction, resulting in economic poverty. High disaster risk leads to long term poverty and relative poverty by eroding agricultural livelihoods and destroying development capacity. The high exposure to disaster risk, vulnerability, low resilience, and low adaptive capacity of the poor lead to the continuous amplification and accumulation of disaster risks. (2) The disaster risk-poverty nexus exists on many scales, including the scale of province, city, and family. Such an effect on the scale of the country and continent is not clear. In the process of building a economically well-off society and eradicating poverty, China has undertaken considerable risk control and mitigation. (3) The causal relationship between disaster risk and poverty (closed loop or cyclic relationship between disaster and poverty) is not a “natural phenomenon” but a historical function of the mainstream economic social paradigm. It is a result of the capital economic cycle. If the economic and social operation mode does not change, the connection between disaster risk and poverty will not disappear. At the same time, economic globalization, inequality, disordered urbanization, poor governance, damage to the ecological environment, and climate change have exacerbated the effect of disaster risk-poverty fetters. Faced with this dilemma, a multidisciplinary approach and bold creative thinking are necessary. Ignoring or not sufficiently addressing this topic will weaken the global DRR effort and impose a paradigm trap to disaster risk science. This study intends to provide a theoretical basis and evidence for the coordinated development of DRR and poverty alleviation in China. This work also provides intellectual support for the implementation of the “five in one” strategy for the construction of economic, political, cultural, social, and ecological civilization and the realization of the “double carbon” goal and the response to global climate change.

Key words: disaster risk, poverty, fetters, resilience, extensive disaster risk

何冰晶,刘耀龙,张华明,冯洁瑶. 中国灾害风险与贫困互相关效应的理论分析与实证研究[J]. 干旱区地理, 2022, 45(5): 1649-1658.

HE Bingjing,LIU Yaolong,ZHANG Huaming,FENG Jieyao. Theoretical analysis and empirical study of the nexus of disaster risk and poverty in China[J]. Arid Land Geography, 2022, 45(5): 1649-1658.

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变量类型	变量	测量方式
自变量/因变量	灾害风险指数（R）	省域尺度为直接经济损失和农业受灾面积等权重相加
因变量/自变量	贫困指数（Pov）/%	贫困发生率指的是低于贫困线的人口占全部人口的比例
控制变量	农村居民家庭人均医疗保健消费支出（H）	农村居民家庭人均医疗保险的支出
	农村居民家庭人均教育文娱消费支出（E）	农村居民家庭人均教育文娱的支出
	农村居民人均可支配收入（I）	农村居民人均可用于支配的收入
	农村居民人均消费支出（C）	农村居民人均用于满足家庭生活消费的全部支出

变量	均值	中位数	标准差	最小值	最大值
R	0.1454	0.1201	0.1254	0.0010	0.6908
Pov/%	8.0209	5.3000	9.1632	0.0000	49.2000
H	0.3893	0.3680	0.2004	0.0311	1.0311
E	0.4097	0.4317	0.1945	0.0198	1.0198
I	0.3859	0.3614	0.1749	0.1178	1.1178
C	0.4039	0.3831	0.1751	0.1198	1.0010

变量	被解释变量Pov的回归结果			被解释变量R的回归结果
变量	符号	模型1	模型2	符号	模型3	模型4
常数项	α	19.6723^***	16.9066^***	α	0.2160^***	0.1438^***
控制变量	H	0.0001	-0.0003	I	0.00000582	0.00000136
	E	-0.0155^***	-0.0146^***	C	-0.000015^**	-0.00000463
	I	0.0002	0.0002
自变量	R		12.4275^***	Pov		0.0034^***
F		108.36^***	88.36^***	F	14.00^***	14.12^***
R²		0.5408	0.5624	R²	0.0918	0.1330

被解释变量Pov的回归结果			被解释变量R的回归结果
地区/年份	系数	P值	地区/年份	系数	P值
山东省	6.2403	0.008^***	天津市	-0.0199	0.003^***
海南省	16.3480	0.022^**	吉林省	0.1552	0.078^*
西藏自治区	31.4478	0.069^*	黑龙江省	0.0569	0.009^***
甘肃省	28.6672	0.004^***	浙江省	-0.0481	0.032^**
东部地区	6.4758	0.020^**	山东省	0.1527	0.002^***
中部地区	3.8108	0.064^*	甘肃省	0.0263	0.014^**
中部地区	3.8108	0.064^*	东部地区	0.0055	0.083^*
			中部地区	0.0114	0.042^**
2010	20.9407	0.071^*	2011	0.0017	0.386^**
2010—2014	9.1089	0.025^**	2014	0.0043	0.089^*
2015—2019	3.8593	0.099^*	2017	0.0012	0.007^***
			2010—2014	0.0042	0.032^*