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In the era of networking and information technology, ongoing advancement of the new business pattern \"Internet+ \" has enabled the Internet to permeate all facets of rural residents' production and life, with profound effects on their daily choices. Can the Internet continue to help people get out of poverty by making rural households less poor? To test the consequences of the Internet usage on farming people’s relative poverty as well as its internal mechanisms of action, we use data from the China Family Panel Studies in 2016 and 2018, employing the model of probit as well as the mediation impact theories. The results are as follows: (1) In terms of comparison to farmers who refrain from using the Internet, farmers who do use the Internet have lower levels of objective and subjective relative poverty. Regarding the marginal effects, each extra Internet use metric, a farmer’s likelihood of falling into objective and subjective relative poverty is reduced by 3.84% and 2.67%, respectively. (2) Farmers' use of the Internet concerning their business activities has the most prominent effect on their relative poverty alleviation. (3) The poverty alleviation effect of the Internet varies by region, gender, and age. (4) Human capital, social capital, and non-agricultural employment help alleviate the relative poverty of farm households using the Internet. According to these results, the Communist Party of China may be able to minimize relative rural poverty by strongly investing in information infrastructure, offering online training for residents, and stimulating rural human capital. Those findings convey indispensable theoretical suggestions and pragmatic support for generating an everlasting mechanism to lessen relative poverty and accomplish the 2030 Sustainable Development Goals.

Governing relative poverty is an indispensable part of achieving inclusive growth. Using data from the China Household Financial Survey, we scientifically investigate the impact of China's development of digital financial inclusion on household vulnerability to relative poverty. The research results show that the development of digital financial inclusion can significantly alleviate the vulnerability to relative poverty of households, and effectively prevent families from falling into a state of relative poverty in the future. The results of the heterogeneity analysis show that the effect of digital financial inclusion in mitigating vulnerability to relative poverty is greater in households with high population dependency ratios, digital tools, and household head education levels. In parallel, there are also significant regional differences in digital finance in mitigating the relative vulnerability of households. Further mechanism research found that the development of digital finance inclusion mainly reduces the probability of families falling into relative poverty in the future by alleviating income inequality, thereby improving the health status of family members, family development-oriented consumption, and family happiness.

China achieved comprehensive poverty eradication under the current standards in 2020, but eliminating absolute poverty does not mean the end of poverty alleviation and reduction; relative poverty will exist for a long time and has become the subject of poverty study. In this paper, the social poverty line (SPL) index is utilized to establish the relative poverty standard, and CHFS2017 is used to compare the regional distribution of relative poverty in China. The results show that the relative poverty in rural areas is more serious than that in urban areas. The rural relative poverty rate in five provinces and cities including Beijing is over 60%, and the rural relative poverty rate in Qinghai is low. The urban relative poverty rate in many provinces and cities of the central and western regions is below 40%, and the relatively high relative poverty rate in the eastern region has drawn attention to the issue of the income distribution. Moreover, a logit model for binary is employed for the influencing factor analysis of the relative poverty of urban and rural residents. The results show that the education year has a negative effect on the relative poverty of urban and rural residents. Happiness has a positive effect on urban residents, government financial expenditure and financial support for agriculture have different effects on rural residents and urban residents. Therefore, we put forward aiming at relative poverty in the rural areas of the central and western regions to reduce financial pressure and increase the benefits of poverty reduction.

[Purpose/Significance] Consolidating the achievements of targeted poverty alleviation and building a relative poverty reduction mechanism will be the key problem for Chinese government after 2020; information poverty alleviation is expected to play a key role in the future poverty reduction in China. [Method/Process] Based on a systematic literature review and an on-site investigation, this study made an in-depth analysis on the policy documents issued by Chinese government in past decades to shed light on the governance and intervention on information poverty. [Results/Conclusions] Although China's information poverty reduction policy has made remarkable achievements, there are still some problems, including \"to pay too much attention on the information infrastructure construction instead of the how to use them\", \" investment, but not evaluation, is put on the top priority\", \"the content of information poverty reduction project remains vague\", \"compared to social level information resource allocation, individual level information poverty intervention is ignored\", and \" emphasizing too much on the coverage of information sources instead of identification of those vulnerable people in the information society\". Thus, based on an analysis of logic association between information poverty and economically relative poverty, this study puts forward some policy related suggestions and potential research items for future research.

As absolute poverty in China, measured by the current standard, is being eliminated, the focus of future poverty reduction projects will necessarily shift to addressing relative poverty. Contiguous poverty areas have been identified in Hebei province around Beijing and Tianjin (HABT), and this is not conducive to the coordinated development of the Beijing-Tianjin-Hebei region. The dynamic identification of relative poverty at the county level within the region must be the basis for formulating scientific strategies for poverty reduction. Night light (NTL) data can reveal socio-economic information and reflect human activities, and has a wide range of other applications for evaluating and identifying poverty. For this reason, NPP/VIIRS (Visible Infrared Imaging Radiometer Suite equipped on the Suomi National Polar orbiting Partnership satellite) NTL data from 2012 to 2020 were corrected, and NTL data for HABT were obtained. A multidimensional relative poverty index (MRPI) that assesses being “free from worries over food and clothing and having access to compulsory education, basic medical services, and safe housing” using social statistical data was created with the analytic hierarchy process and entropy weight method. A panel regression model with fixed effects was established for MRPI and corrected NPP/VIIRS NTL data. The R2 of fitting was 0.6578 and confirmed a strong correlation between MRPI and corrected NPP/VIIRS NTL data. Based on this, the MRPI estimation model was constructed based on the MRPI and corrected NPP/VIIRS NTL data, and passed the accuracy test. Finally, using the national list of poverty counties, it was verified that, at the county scale, the corrected NPP/VIIRS NTL data could effectively identify areas of relative poverty. This study lays the foundation for the use of NPP/VIIRS NTL data in the identification of areas of relative poverty. It provides a feasible method and data reference for analyzing relative poverty at a smaller scale. The dynamic identification of areas of relative poverty can also provide a basis for formulating scientific poverty reduction strategies.

Prevailing measures of relative poverty are unchanged when all incomes grow or contract by the same proportion. This property stems from seemingly implausible assumptions about the disutility of relative deprivation and the cost of social inclusion. We propose ‘‘weakly relative’’ lines that relax these assumptions. On calibrating our measures to national poverty lines and survey data, we find that half the population of the developing world in 2005 lived in poverty, only half of whom were absolutely poor. The total number of poor rose over 1981 to 2005 despite falling numbers of absolutely poor. With sustained economic growth, the incidence of relative poverty became less responsive to further growth. The number of relatively poor rose, just as the numbers of absolutely poor fell.

Counting the world's poor: problems and possible solutions; by Angus Deaton. Comments on \"counting the world's poor\"; by Martin Ravallion, and T. N. Srinivasan. Ecology, history, and development : a perspective from rural Southeast Asia; by Yujiro Hayami. Productivity growth and sustainability in post-green revolution agriculture: the case of the Indian and Pakistan Punjab; by Rinku Murgai, Mubarik Ali, and Derek Byerlee. The politics of Russian enterprise reform: insiders, local governments, and the obstacles to restructuring; by Raj M. Desai and Itzhak Goldberg.

Poverty lines are typically higher in richer countries, and lower in poorer ones, reflecting the relative nature of national assessments of who is considered poor. In many high-income countries, poverty lines are explicitly relative, set as a share of mean or median income. Despite systematic variation in how countries define poverty, global poverty counts are based on fixed-value lines. To reflect national assessments of poverty in a global headcount of poverty, this paper proposes a societal poverty line. The proposed societal poverty line is derived from 699 harmonized national poverty lines, has an intercept of $1 per day and a relative gradient of 50 percent of median national income or consumption. The societal poverty line is more closely aligned with national definitions of poverty than other proposed relative lines. By this relative measure, societal poverty has fallen steadily since 1990, but at a much slower pace than absolute extreme poverty.

This study examines the effect of digital financial inclusion on relative poverty among urban households in China. Based on the data of the China Family Panel Studies and the Peking University Digital Financial Inclusion Index of China, using the weak relative poverty line to identify relative poverty among urban households, we use a probit model, a mediating effect model, and an instrumental variable method to conduct empirical research. The results reveal that digital financial inclusion helps reduce the probability that urban households will fall into relative poverty. Digital financial inclusion not only promotes entrepreneurship by urban households but also increases their participation in the financial market. The increase in their income flow can be translated into an improvement in the stock of wealth, enabling them to avoid falling into relative poverty. But this effect is heterogeneous. Digital investment and digital credit play more important roles than digital payment. It is also more pronounced in households with higher financial literacy and households in smaller cities. In addition, regardless of how the relative poverty line and digital financial inclusion are calculated, our results are robust. The research in this study is important for a comprehensive understanding of the development of digital financial inclusion and urban relative poverty in developing countries such as China.

To realize efficient and sustainable poverty alleviation, this study firstly investigated the identification of multidimensional poverty and relative poverty, and then explored relevant poverty alleviation pathways. Poverty levels in 31 provinces including the autonomous regions and municipalities of China were identified at the county level using the average nighttime light index (ANLI), county multidimensional development index (CMDI), and a method combining multidimensional poverty index and relative poverty standards. Poverty alleviation pathways for poverty-stricken counties were explored from the aspects of industry, education, tourism and agriculture. The results revealed that nearly 60% of counties in China were primarily under relative poverty, most of which were corresponded to light relative poverty. In terms of ANLI and CMDI, 63% and 79% of the national poverty-stricken counties, as of 2018, could be identified, suggesting that CMDI had a higher performance for identifying poverty at the county level. In terms of poverty alleviation pathways, 414, 172, 442, and 298 poverty-stricken counties were receptive to industry poverty alleviation, education poverty alleviation, tourism poverty alleviation, and agriculture poverty alleviation, and 61% of counties had more poverty-causing factors, implying that multidimensional poverty alleviation is suitable in most of the counties.