The poverty dynamics in rural China during 2000–2014: A multi-scale analysis based on the poverty gap index

Ren, Qiang; Huang, Qingxu; He, Chunyang; Tu, Mengzhao; Liang, Xiaoying

doi:10.1007/s11442-018-1554-1

Cited by 25 publications

(10 citation statements)

References 30 publications

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“…The selection of the multidimensional poverty dimension refers to the multidimensional poverty-indicator system proposed by Wang Yanhui et al [6,16,40] and the existing main factors (natural and socioeconomic factors) affecting poverty. Economic, social, and natural factors play a key role in the sustainable development of human and land resources [41], so select three dimensions: economic [18,[42][43][44], social [6,16,42,43], and natural [6,45,46]. In addition, based on the research objectives and data accessibility, three dimensions were combined with regional poverty-reduction policies to construct a multidimensional relative-poverty-index system containing a total of 18 indicators in 8 vectors, as shown in Table 2.…”

Section: Multidimensional Relative-poverty-construction Modulementioning

confidence: 99%

Spatio-Temporal Synergy between Urban Built-Up Areas and Poverty Transformation in Tibet

Wang

et al. 2022

Sustainability

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Understanding the causes of poverty and identifying the transformation characteristics of poverty is the basis for achieving poverty eradication. In order to clarify the availability of construction land for poverty assessment, this paper explores the spatio-temporal synergy between urban built-up areas and poverty transformation in Tibet. The following conclusions are drawn: (1) the built-up areas in Tibetan counties have been growing from 2013 to 2019; (2) the proportion of counties with very low and low levels of relative poverty have decreased significantly, and the overall spatial characteristics of poverty are “high in the center and low in the surroundings”; (3) the overall coupling-coordination level between the built-up areas and the relative poverty level is gradually improving from the initial antagonism, and the relative-poverty index shows a significant negative correlation with coupling coordination (correlation coefficient of −0.63); and (4) the built-up area has a strong explanatory power for the spatial distribution of regional relative-poverty transfer compared to temperature, precipitation, elevation, and slope. The results of the study prove that the built-up area cannot be directly used as an indicator factor when constructing the multidimensional relative-poverty model and, instead, should use urban built-up areas by region to participate in poverty-estimation models based on regional economic development.

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Section: Multidimensional Relative-poverty-construction Modulementioning

confidence: 99%

Spatio-Temporal Synergy between Urban Built-Up Areas and Poverty Transformation in Tibet

Wang

et al. 2022

Sustainability

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“…Numerous theoretical and empirical studies have been conducted on poverty and its alleviation [13][14][15][16][17][18][19]. The literature primarily concentrated on the concept and measurement of poverty, spatial pattern characteristics, influencing factors, and poverty alleviation policies.…”

Section: Of 17mentioning

confidence: 99%

The Nexus between Poverty and the Environment: A Case Study of Lijiang, China

Gao

Liu

et al. 2020

Sustainability

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Highlighting the nexus between poverty and environment is essential to promote poverty alleviation and sustainable development. This study analyzed spatial differences and environmental factors influencing poverty incidence and reduction using spatial statistical methods and GeoDetector tools. It focused on Lijiang in the Hengduan Mountains of western China as the case area. The results indicate a notable decline in poverty incidence in most Lijiang villages during 2014–2018 under China’s poverty alleviation strategy. However, there are distinct spatial differences for both poverty incidence and reduction. The main environmental factors affecting poverty incidence and reduction are available water storage and geological hazard risks. Socioeconomic factors such as administrative unit and distance to city center also play a key role. The anti-poverty policies in various administrative units have the most significant influence. However, existing policy formulation mainly considers elevation factor in mountainous areas. This study suggests that water resources and geological hazards should also be highly considered, and not only elevation. It is imperative to promote the construction of water conservancy facilities and improve the prevention and control of geological disasters. Moreover, targeted poverty alleviation should focus on, not only policy or socioeconomic factors, but also main environmental factors affecting poverty incidence and reduction.

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“…Consequently, these countries have witnessed a decrease in poverty, but to varying extents. The evolution of poverty degree is primarily determined by two types of measures: single income poverty and its derivative measure method (Dang and Lanjouw, 2018;Ren et al, 2018;Purwono et al, 2021), the Multidimensional Poverty Index (Alkire and Santos, 2014). Several studies have analyzed poverty reduction experiences that have taken place in countries along the Belt and Road.…”

Section: Introductionmentioning

confidence: 99%

The poverty evolution of typical countries along the Belt and Road and implications from China’s poverty reduction experiences

2022

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The world is facing a poverty crisis. Despite the great achievements that have been made in poverty alleviation over the past two decades, the extent of poverty in countries along the Belt and Road is still high. Successful poverty reduction in these countries is crucial to meeting the 2030 SDGs. Improving governance to eradicate poverty is a shortcoming that needs to be addressed urgently in poverty reduction pathways along the Belt and Road. In this study, the Standard Deviational Ellipse method was used to study the spatial trajectory of the poverty gravity center. Results showed that the poverty gravity center moved from east to west by 87.60 km annually, while the poverty population decreased by 1211.14 million along the Belt and Road from 2000 to 2020. In addition, the trajectory of the center has shifted due to the different effects of poverty reduction. Among the countries situated along the Belt and Road, China is the most significant contributor to poverty reduction. Accordingly, this study examined the implications of China’s successful poverty reduction strategies in order to understand how other countries can effectively respond to poverty. Ultimately, we propose that sustainable poverty alleviation development strategies should be established with the objectives of promoting social equity and improving the wellbeing of all people.

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The poverty dynamics in rural China during 2000–2014: A multi-scale analysis based on the poverty gap index

Cited by 25 publications

References 30 publications

Spatio-Temporal Synergy between Urban Built-Up Areas and Poverty Transformation in Tibet

Spatio-Temporal Synergy between Urban Built-Up Areas and Poverty Transformation in Tibet

The Nexus between Poverty and the Environment: A Case Study of Lijiang, China

The poverty evolution of typical countries along the Belt and Road and implications from China’s poverty reduction experiences

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