poverty reduction research paper

REVIEW article

Poverty reduction of sustainable development goals in the 21st century: a bibliometric analysis.

• Institute of Blue and Green Development, Shandong University, Weihai, China

No Poverty is the top priority among 17 Sustainable Development Goals (SDGs). The research perspectives, methods, and subject integration of studies on poverty reduction have been greatly developed with the advance of practice in the 21st century. This paper analyses 2,459 papers on poverty reduction since 2000 using VOSviewer software and R language. Our conclusions show that (1) the 21st century has seen a sharp increase in publications of poverty reduction, especially the period from 2015 to date. (2) The divergence in research quantity and quality between China and Kenya is great. (3) Economic studies focus on inequality and growth, while environmental studies focus on protection and management mechanisms. (4) International cooperation is usually related to geographical location and conducted by developed countries with developing countries together. (5) Research on poverty reduction in different regions has specific sub-themes. Our findings provide an overview of the state of the research and suggest that there is a need to strengthen the integration of disciplines and pay attention to the contribution of marginal disciplines to poverty reduction research in the future.

Introduction

Global sustainable development is the common target of human society. “No Poverty” and “Zero Hunger” are two primary goals of the 2030 Agenda for Sustainable Development (SDGs) , along with important premises in the completion of the goals of “Decent Work and Economic Growth Industry” and “Innovation and Infrastructure.” China has made great efforts in meeting its No Poverty targets. To achieve the goal of eliminating extreme poverty in the rural areas by the end of2020 1 , China has been carrying out a basic strategy of targeted approach named Jingzhunfupin 2 , which refers to implementing accurate poverty identification, accurate support, accurate management and tracking. By 2021, China accomplished its poverty alleviation target for the new era on schedule and achieved a significant victory 3 .

However, the worldwide challenges are still arduous. On the one hand, the recent global poverty eradication process has been further hindered by the COVID-19 pandemic. The World Bank shows that global extreme poverty rose in 2020 for the first time in over 20 years, with the total expected to rise to about 150 million by the end of 2021 4 . People “return to poverty” are emerging around the world. On the other hand, people who got out of income poverty may still be trapped in deprivations in health or education. About 1.3 billion people (22%) still live in multidimensional poverty among 107 developing countries, according to the Global Multidimensional Poverty Index report released by the United Nations 5 . Meanwhile, the issue of inequality became more prominent, reflected by the number of people who are in relative poverty 6 .

In line with the dynamic poverty realities, the focusing of poverty research moved forward as well. Research frameworks have evolved from single dimension poverty to multidimensional poverty ( Bourguignon et al., 2019 ) and from income poverty to capacity poverty ( Zhou et al., 2021 ). Research perspectives concentrate on the macroscopic view, but have now turned to microscopic individual behavior analysis. Cross-integration of sociology, psychology, public management, and other disciplines also helps to expand and deepen the research ( Addison et al., 2008 ). Some cutting-edge researchers are making effort to shed light on the relationships between “No Poverty” and other SDGs. For example, Hubacek et al. (2017) verified the coherence of climate targets and achieving poverty eradication from a global perspective 7 . Li et al. (2021) discussed the impacts and synergies of achieving different poverty eradication goals on air pollutants in China. These novel papers give us insightful inspiration on combining poverty reduction with the resource or environmental problem including aspects like energy inequity, carbon emission. Hence, summarizing the research on different poverty realities and academic backgrounds should provide theoretical and empirical guidance for speeding up the elimination of poverty in the world ( Chen and Ravallion, 2013 ).

Previous review literature on poverty reduction all directed certain sub-themes. For example, Chamhuri et al. (2012) , Kwan et al. (2018) , Mahembe et al. (2019a) reviewed urban poverty, foreign aid, microfinance, and other topics, identifying the objects, causes, policies, and mechanisms of poverty and poverty reduction. Another feature of the review literature is that scholars often synthesize the articles and map the knowledge network manually, which constrains the amount of literature to be analyzed, leading to an inadequate understanding of poverty research. Manually literature review on specific fields of poverty reduction results in a research gap. Analysis delineating the general academic knowledge of poverty reduction is somewhat limited despite the abundance of research. Yet, following the trend toward scientific specialization and interdisciplinary viewpoints, the core and the periphery research fields and their connections have not been clearly described. Different studies are in a certain degree of segmentation because scholars have separately conducted studies based on their countries’ unique poverty background or their subdivision direction. Possibly, lacking communication and interaction will affect the overall development of poverty reduction research especially in the context of globalization. Less than 10 years are left to accomplish the UN sustainable development goals by 2030. It is urgent to view the previous literature from a united perspective in this turbulent and uncertain age.

Encouragingly, with advances in analytical technology, bibliometrics has become increasingly popular for developing representative summaries of the leading results ( Merediz-Solà and Bariviera, 2019 ). It has been widely applied in a variety of fields. In the domain of poverty study, Amarante et al. (2019) adopted the bibliometric method and reviewed thousands of papers on poverty and inequality in Latin America. Given above issues, we expand the scope of the literature and conduct a systematic bibliometric analysis to make a preliminary description of the research agenda on poverty reduction.

This paper presents an analysis of publications, keywords, citations, and the networks of co-authors, co-words, and co-citations, displaying the research status of the field, the hot spots, and evolution through time. We use R language and VOSviewer software to process and visualize data. Our contributions may be as follows. Firstly, we used the bibliometric method and reviewed thousands of papers together, helping keep pace with research advances in poverty alleviation with the rapid growth in the literature. Secondly, we clarified the core and periphery research areas, and their connections. These may be beneficial to handle the trend toward scientific specialization, as well as fostering communication and cooperation between disciplines, mitigating segmentation between the individual studies. Thirdly, we also provided insightful implications for future research directions. Discipline integration, intergenerational poverty, heterogeneous research are the directions that should be paid attention to.

The structure of this article is as follows. Methodology and Initial Statistics provides the methodology and initial statistics. Bibliometric Analysis and Network Analysis offer the bibliometric analysis and network visualization. The remaining sections offer discussions and conclusions.

Methodology and Initial Statistics

Bibliometrics, a library and information science, was first proposed by intelligence scientist Pritchard in 1969 ( Pritchard, 1969 ). It exploits information about the literature such as authors, keywords, citations, and institutions in the publication database. Bibliometric analyses can systematically and quantitatively analyze a large number of documents simultaneously. They can highlight research hotspots and detects research trends by exploring the time, source, and regional distribution of literature. Thus, bibliometric analyses have been widely used to help new researchers in a discipline quickly understand the extent of a topic ( Merediz-Solà and Bariviera, 2019 ).

Research tools such as Bibexcel, Histcite, Citespace, and Gephi have been created for bibliometric analysis. In this paper, R language and VOSviewer software are adopted. R language provides a convenient bibliometric analysis package for Web of Science, Scopus, and PubMed databases, by which mathematical statistics were performed on authors, journals, countries, and keywords. VOSviewer software provides a convenient tool for co-occurrence network visualization, helping map the knowledge structure of a scientific field ( Van Eck and Waltman, 2010 ).

Data Collection

The bibliometric data was selected and downloaded from the Web of Science database ( www.webofknowledge.com ). We choose the WoS Core Collection, which contained SCI-EXPANDED, SSCI, and A&HCI papers to focus on high-quality papers. The data was collected on March 19, 2021.

To identify the documents, we used verb phrases and noun phrases with the meaning of poverty reduction, such as “reduce poverty” and “poverty reduction,” as search terms, because there are several different expressions of “poverty reduction.” We also considered the combinations of “no poverty” and SDGs, “zero hungry” and “SDGs.” Because the search engine will pick up articles that have nothing to do with “poverty alleviation” depending on what words are used in the abstract, we employed keyword matching. Meanwhile, to prevent missing essential work that does not require author keywords, we also searched the title. Specifically, a retrieval formula can be written as [AK = (“search term”) OR TI = (“search term”)] in the advanced search box, where AK means author keywords and TI means title. Finally, we restricted the document types to “article” to obtain clear data. Thus, papers containing search phrases in headings or author keywords were marked and were guaranteed to be close to the desired topic.

A total of 2,551 studies were obtained, with 2,464 articles retained after removing duplicates. Table 1 presents the results for each search term. The phrasing of “poverty alleviation” and “poverty reduction” are written preferences.

TABLE 1 . Information of data collection.

Descriptive Analysis

Figure 1 gives details of each year’s publications during the period 2000–2021. The cut-off points of 2006 and 2015 divide the publication trends into three stages. The first period is 2000–2006, with approximately 40 publications per year. The second period is 2007–2014, in which production is between 80 and 130 papers annually. The third period is 2015–2021, with an 18.31% annual growth rate, indicating a growing interest in this field among scholars. Perhaps this is because 2006 was the last year of the first decade for the International Eradication of Poverty, and 2015 is the year that eliminating all forms of poverty worldwide was formally adopted as the first goal in the United Nations Summit on Sustainable Development. Greater access to poverty reduction plan materials and data is a vital reason for the growth in papers as well.

FIGURE 1 . Annual scientific production.

We can notice that the milestone year is 1995 when we examine the time trend with broader horizons ( Figure 2 ). Before 1995, scant literature touches upon the topic of “poverty alleviation.” This confirms that in the time range we check the majority of the development of academic interest in this issue takes place. Thus, the 21st century has become a period of booming research on poverty reduction.

FIGURE 2 . Annual scientific production in a longer period.

Bibliometric Analysis

In this section, we offer the bibliometric analysis including the affiliation statistics, citation analysis and keywords analysis. Author analysis is not included because some authors’ abbreviations have led to statistical errors.

Affiliation Statistics

From 2000 to 2021, a total of 2,459 articles were published in 979 journals, a wide range. Table 2 lists the top ten journals, which together account for 439 (17.86%) of the articles in our data set. Development in Practice and World Development have the most publications, respectively 121 (4.92%) and 107 (4.35%), followed by Sustainability at 44 (1.8%). The top 10 journals mostly involve development or social issues, with some having high impact factors, including Food Policy (4.189) and Journal of Business Ethics (4.141).

TABLE 2 . Top 10 sources of publications.

Figure 3 presents the geographic distribution of the published articles on poverty reduction. As indicated in the legend, the white part on the map shows regions with zero published articles recorded in WoS. Darker shades indicate a greater number of articles published in the country or region. The US region is darkest on the map, with 593 articles published, followed by England, with 412 papers, and China, with 348 articles. Ranking fourth is South Africa, perhaps because South Africa is a pilot site for many poverty reduction projects. India, for the same reason, is similarly shaded.

FIGURE 3 . Spatial distribution of publication in all countries. Note: the data of all countries is from Web of Science.

Citation Analysis

The number of citations evaluates the influence and contribution of individual papers, authors, and nations. The top 10 countries in total citations are displayed in Table 3 . Consistent with the publication distribution, the leader is the United States (11,861), with the United Kingdom (8,735) and China (1,666) following. However, there is a broad gap between China and England in total citations. The average article citation ranks are quite different from the total citation list. Notably, Kenya takes first place based on its average citations per paper, though its total citations rank seventh, showing that Kenya’s poverty reduction practices and research are of great interest to a large number of scholars. By contrast, China’s average article citation is just roughly one-sixth of Kenya’s. The different pattern of the number of Chinese publications and citations shows that the quality of Chinese research must be improved even as it raises its publication quantity.

TABLE 3 . Top ten countries by total citations.

Table 4 lists the top 10 most cited articles with their first author, year, source, total citations, and total citations per year. Highly cited articles can be used as a benchmark for future research, and in some way signal the scientific excellence of each sub-field. For example, Wilson et al. (2006) reminded the importance of informal sector recycling to poverty alleviation. Daw et al. (2011) discussed the poverty alleviation benefits from ecosystem services (ES) with examples in developing countries. Pagiola et al. (2005) found that Payments for Environmental Services (PES) can alleviate poverty, and explored the key factors of this poverty mitigation effect using evidence from Latin America 8 . These three papers combined the environmental ecosystem with poverty alleviation. Beck et al. (2007) , Karnani (2007) explored the relationships between the SME sector and poverty alleviation and the private sector and poverty alleviation, respectively. Grindle (2004) discussed the necessary what, when, and how for good governance of poverty reduction. Cornwall and Brock (2005) took a critical look at how the three terms of “participation,” “empowerment” and “poverty reduction” have come to be used in international development policy. Adams and Page (2005) examined the impact of international migration and remittances on poverty. In the theory domain, Collier and Dollar (2002) derived a poverty-efficient allocation of aid. Hulme and Shepherd (2003) provided meaning for the term chronic poverty. Even from the present point of view, these scholars’ studies remain innovative and significant.

TABLE 4 . Top 10 papers with the highest total citations.

Keywords Analysis

The keywords clarify the main direction of the research and are regarded as a fine indicator for revealing the literature’s content ( Su et al., 2020 ). Two different types of keywords are provided by Web of Science. One is the author keywords, offered by the original authors, and another is the keywords plus, contrived by extracting from the cited reference. The frequency of both types of keywords in 2,459 papers is examined respectively in the whole sample and the sub-sample hereinafter for concentration and coverage.

Whole Sample

Table 5 lists the Top 10 most frequently used keywords and keyword-plus of total papers. Clearly author keywords are often repetitive, with “poverty,” “poverty reduction,” and “reduction” chosen as keywords for the same paper, but these do not dominate the keywords-plus. Hence, the keywords-plus may be more precise at identifying relevant content. However, we used author keywords for the literature screening.

TABLE 5 . Top 10 author keywords and keywords-plus with the highest frequency.

In addition to the terms “poverty” or “poverty reduction or alleviation,” we note that “China” and “Africa” occur frequently, with “India” and “Bangladesh” following when we expand the list from the Top 10 to Top 20 ( Supplementary Figure S1 ). The appearance of these places coincides with our speculation that the research was often conducted in Africa, East Asia, or South Asia once again, whereas the larger compositions are from developing countries or less developed countries.

The cumulative trend of TOP20 author keywords and keywords-plus is shown in Supplementary Figure S1 . The diagram also gives some information about other concerns bound up with anti-poverty programs, including “microfinance,” “food security,” “livelihoods,” “health,” “Economic-growth” and “income,” as numerous papers are focused on these aspects of poverty reduction.

Further, policy study and impact evaluation may be the core objectives of these papers. Vital evidence can be found in countless documents. Researchers measured the effect of policies or programs from various perspectives. In the study of Jalana and Ravallion (2003) , they indicated that ignoring foregone incomes overstated the benefits of the project when they estimated net gain from the Argentine workfare scheme. Meng (2013) found that the 8–7 plan increased rural income in China’s target counties by about 38% in 1994–2000, but had only a short-term impact 9 . Galiani and McEwan (2013) studied the heterogeneous influences of the Programa de Asignación Familiar (PRAF) program, in which implemented education cash transfer and health cash transfer to people of varying degrees of poverty in Honduran. Maulu et al. (2021) concluded that rural extension programs can provide a sustainable solution to poverty. Some studies also have drawn relatively fresh conclusions or advice on poverty reduction projects. Mahembe et al. (2019a) found that aid disbursed in production sectors, infrastructure and economic development was more effective in reducing poverty through retrospecting empirical studies of official development assistance (ODA) or foreign aid on poverty reduction. Meinzen-Dick et al. (2019) reviewed the literature on women’s land rights (WLR) and poverty reduction, but found no papers that directly investigate the link between WLR and poverty. Huang and Ying (2018) constructed a literature review that included the necessity and the ways of introducing a market mechanism to government poverty alleviation. Mbuyisa and Leonard (2017) demonstrated that information and communication technology (ICT) can be used as a tool for poverty reduction by Small and Medium Enterprises.

Web of Science provides the publications of each journal category ( Figure 4 ). Economics is the largest type of journal, followed by development studies and environmental studies. Education should be regarded as an important way to address the intergenerational poverty trap. However, we note that journals in education are only a fraction of the total number of journals. Psychology journals are in a similar position, though endogenous drivers of poverty reduction have been increasingly emphasized in recent research. The detailed data can be found in the supplementary documents. To investigate the differences between the subdivisions of the research, we chose economic and environmental journals as sub-samples for further analysis.

FIGURE 4 . Visualization of journal category from the web of science.

As Supplementary Figure S2 shows, the TOP10 author keywords in economic sample are similar to the whole sample. We note that microfinance is a real heated research domain both in economic and whole sample. The poor usually have multiple occupations or self-employment in very small businesses ( Banerjee and Duflo, 2007 ). The poor often have less access to formal credit. Karlan and Zinman (2011) examined a microcredit program in the Philippines and found that microcredit does expand access to informal credit and increase the ability against risk. Banerjee et al. (2015a) reported the results of an assessment of a random microcredit scheme in India, which increased the investment and profits of small-scale enterprises managed by the poor.

Several new keywords enter the TOP20 list in the economic field, including “targeting,” “income distribution,” “productivity,” “employment,” “rural poverty,” “access,” and “program.” “Targeting” is an essential topic in the economic field. It concerns the effectiveness of poverty reduction program and social fairness. Hence, an abundance of literature reviews the definitions of poverty that allow individuals to apply for poverty alleviation programs. Park et al. (2002) , Bibi and Duclos (2007) , Kleven and Kopczuk (2011) , discussed the inclusion error and exclusion error in programs’ targeting and identification under the criterion of poverty lines or specific tangible asset poverty agency indicators (e.g., whether households have color televisions, pumps or flooring, and so forth). In practice, Niehaus et al. (2013) tested the accuracy of different agency indicators to allocate Below Poverty Line (BPL) cards in India and found that using a greater number of poverty indicators led to a deterioration in targeting effectiveness while creating widespread violations in the implementation because less qualified families are more likely to pay bribes to investigators. Bardhan and Mookherjee (2005) explored the targeting effectiveness of decentralization in the implementation of anti-poverty projects. He and Wang (2017) assessed the targeting accuracy of the College Graduate Village Officials (CGVOs) project, a unique human capital redistribution policy in China, on poverty alleviation 10 .

The terms “inequality” and “growth” are first and second in the keywords-plus. This may be because inequality and growth are two of the major components in poverty changes in the economic field, which are stressed in the studies of Datt and Ravallion (1992) , Beck et al. (2007) . The ranking may also imply that the economics of the 21st century is more concerned with human welfare than the pursuit of rapid economic growth. Since a growing number of organizations are trying to build human capital to improve the livelihoods of their clients and further their mission of lifting themselves out of poverty. McKernan (2002) showed that social development programs are important components of microfinance program success. Similarly, Karlan and Valdivia (2006) argued that increasing business training can factually improve business knowledge, practice effectiveness, and revenue. Besides, cash transfers are widely adopted to reduce income inequality and improve education and the health status of poor groups ( Banerjee et al., 2015b ; Sedlmayr et al., 2020 ). Benhassine et al. (2015) noted that the Tayssir Project in Morocco, a cash transfer project, achieved an increasing improvement of school enrolment rate in the treatment group, especially for girls 11 .

We combine the journal types of “Environmental Studies” and “Environmental Sciences” into one unit for analysis ( Supplementary Figure S3 ). In the environmental field, the terms “conservation” and “management” are ranked first and second. This field also involves “ecosystem services,” “climate change,” “biodiversity conservation,” and “deforestation,” with rapid growth in recent years. These themes were discussed by Alix-Garcia et al. (2013) , Alix-Garcia et al. (2015) , Sims and Alix-Garcia (2017) in their investigations of the effect of conditional cash transfers on environmental degradation, the poverty alleviation benefits of the ecosystem service payment project, and comparison of the effects in protected areas and of ecosystem service payment on poverty reduction in Mexico. The differences in economic research in poverty reduction and environmental field show the necessity of strengthening cooperation between disciplines.

Network Analysis

Network relationship is established by the co-occurrence of two types of information. It enables mapping of the knowledge nodes with a joint perspective, instead of viewing scientific ideas in isolation. The data is imported into VOSviewer software after removing duplicates by R package. We then provide the co-authorship analysis, co-citation analysis, and co-keywords analysis.

Co-Authorship Analysis

Co-authorship may reflect international cooperation as shown by the country distribution ( Figure 5 ). When the authors of two countries have a cooperative relationship, a line is generated to connect the corresponding countries. The size of nodes reflects the number of countries of origin of the authors. The width of the line represents the cooperative frequency between them, and the different colors mark the partition of the countries.

FIGURE 5 . International networks of co-authorship.

The network includes a total of 1,449 countries, of which 92 meet the threshold of at least five instances of cooperation. The United States, United Kingdom, China, and South Africa have the strongest interlinkage with other countries or regions. Whether countries in each cluster demonstrate international academic cooperation on poverty reduction is sometimes based on geographic location. For example, the red cluster includes the United States, Mexico, Brazil, Chile, and Ecuador. These countries mainly lie in the Americas. The United Kingdom, Kenya, Uganda, and South Africa are in the yellow group, located in Europe and Africa. The green cluster includes China, Malaysia, and Bangladesh, all Asian countries. The distribution of countries on each cluster and the map as a whole show that research on poverty alleviation is usually conducted by developed and developing nations together. This may be due to anti-poverty programs in developed countries usually being subsidized by international non-governmental organizations, as shown by the branch literature devoted to foreign aid and poverty reduction ( Mahembe et al., 2019b ).

Co-Citation Analysis

Co-citation analysis can locate the core classical literature efficiently ( Zhang et al., 2020 ). Pioneering studies of co-citation analysis were performed by Small (1973) . When an article cited two other articles, a relationship of co-citation will be established between these two “cited” articles ( González-Alcaide et al., 2016 ). Since co-citation aims at reference, it targets the knowledge base for the past.

Figure 6 displays the co-citation network of the cited references. The functions of the sizes and colors are the same as in Figure 5 . The most cited papers in the co-citation relationship are the studies of Foster et al. (1984) , Sen et al. (1999) , Dollar and Kraay (2002) , which respectively explore poverty measures, globalization and development, and the growth impact for the poor.

FIGURE 6 . Cited reference network of co-citation.

Figure 7 gives the co-citation heat map of sources, based on their density. We set the threshold at 20, and 78 cited sources remained on the map. Different colors signify different clusters of co-citation. The lighter the color, the more frequently the journals are cited. There are four major categories. World development and the Journal of Development Economics have the largest influence on the red cluster, which mainly contains development and economic studies. The second cluster is green and includes the fields of energy, environment, and ecology, with Ecology Economics as its brightest star. The Journal of Business Ethics and Annals of Tourism Research are the most-cited journals in the third and fourth cluster, which represents the fields of business and tourism. Some psychology studies exist in transitional spaces between business studies and economic studies, suggesting a trend of interdisciplinary work. In the past 10 years, we checked manually that psychology and other interdisciplinary research performed well. Many papers were published in Science or Nature. In the research of Mani et al. (2013) , there was a causal relationship between poverty and psychological function. Poverty reduced the cognitive performance of the poor, because poverty consumes spiritual resources, leaving fewer cognitive resources to guide choices and actions. Another psychology-based experiment in Togo showed that personal proactive training increased the profits of poor businesses by 30%, while traditional training influence was not significant ( Campos et al., 2017 ). In the study of Ludwig et al. (2012) , they revealed that the shift from high-poverty to low-poverty communities resulted in significant long-term improvements in physical and mental health and subjective well-being and had a continuing impact on collective efficacy and neighborhood security.

FIGURE 7 . Cited source density network of co-citation.

Co-Words Analysis

The analysis of co-words was performed after the co-citation analysis. Since it is hard to explain the changes in cluster from year to another in a co-citation map, Callon et al. (1983) proposed co-word analysis to identify and visualize scientific networks and their evolution. Based on our keyword analysis and following the arguments of Zhang et al. (2016) , the knowledge structures of author keywords and keywords plus are similar, but keywords plus can mirror a large proportion of the author keywords when the threshold of the number of instances of a word exceeds 10. The merger of two types of keywords will inflate the total number of words, leaving unique words representing the latest hot spot with little chance to be selected. Therefore, we conduct the co-word analysis using keywords plus to map the structure.

We set the minimum number of occurrences to 15, and 100 words with the greatest link strength are selected from the total of 2,774. As shown in Figure 8 , keywords plus generates 4 clusters. To our delight, each cluster does reflect the research priorities of each region.

FIGURE 8 . Keywords-plus co-occurrence cluster map.

The first cluster (red) reveals studies concerning livelihood, conservation, management, climate change and agriculture. These topics have strong interlinkage to Africa, suggesting that poverty reduction in Africa is often related to basic livelihood and ecology. The poor in Africa rely on the ecological conditions heavily as they are facing a more disadvantaged climate and resources. Therefore, their poverty reduction process is sometimes highly unstable and subject to considerable internal and external constraints. Stevenson and Irz (2009) concluded that the numerous studies presented almost no evidence of aquaculture reducing poverty directly.

The second cluster (green) represents studies focused on economic growth and income inequality, common in China and India. This pattern may imply that papers of this cluster focus on the economic conditions of the poor. Other studies in this cluster are related to migration, health, and welfare. The third cluster (blue) is the poverty reduction strategies on microfinance and empowerment, which are associated with Bangladesh where the Grameen Bank, one of the most notable and intensely researched microcredit programs, was founded ( McKernan, 2002 ). This cluster’s studies are interested in approaches such as business, markets, and education, to help the poor rise from poverty. The fourth cluster (yellow) contains studies of poverty reduction programs on environmental services in Latin America, where the environmental problem is intertwined with poverty traps.

Figure 9 shows the time trend of keywords-plus co-occurrence. Because the keywords plus are extracted from the cited references, they can reflect the changes in hotspots from relatively early to the most recent years. As can be seen, education, technology, and environmental services are the latest keywords in research on poverty reduction.

FIGURE 9 . Keywords-plus co-occurrence time trend map.

There are several limitations to our bibliometric analysis, though we undertake an extensive review of the literature. First, we inevitably lose a fraction of the literature. keywords and title are chosen as the criteria for helping precisely concentrate the search results on our subject. However, the Web of Science core collection on which our study relied is weak in the coverage of literature to some degree. Hence, there is a trade-off between the quantity and the quality of literature. We choose the latter, leading to an unclear restriction of the comprehensiveness of research. Second, we can identify recent research status but are not able to locate the Frontier accurately. Network mapping requires selecting a minimum occurrence threshold for including corresponding authors, keywords, and citations into the network. Because a certain number of citations or new hotspots take several years to be widely used and studied, this threshold may neglect these important data ( Linnenluecke et al., 2020 ). One possible solution is to manually examine the latest published papers in high-quality journals. Third, the mining of subfields is not deep enough. In other words, bibliometrics cannot sort out the main conclusions of literature on poverty reduction. For instance, we do not know whether the conclusion of different studies are consistent for the same poverty alleviation project. Neither do we know the exact mechanism of the anti-poverty program through bibliometric analysis, which limits the possibility of finding research points from controversial conclusions or mechanisms.

However, several points are worth taking into consideration for the future. To start with, poverty reduction is a natural interdisciplinary social science problem. Interdisciplinary has become a major research trend. Except applying cash transfer to ecological programs, associations are raised. We may discuss whether the combination of finance and ecology will bring positive benefits to financial stability, ecological protection, and poverty reduction by the means of capitalization of ecological resources or establishing the ecological bank. Our analysis suggests that some unheeded branch disciplines like human ethology are contributing to poverty reduction research as well. Thus, we need to investigate the interdisciplinary integration and the contribution of marginal disciplines on poverty reduction.

Then, more attention should be paid the intergenerational poverty. It requires researchers to extend the time span of observation and questionnaire investigation. Some work has been done. One example is the research of Hussain and Hanjra (2004) . They reviewed literature and clarified that advances in irrigation technologies, such as micro-irrigation systems, have strong anti-poverty potential, alleviating both temporary and chronic poverty. Another example is the research of Jones (2016) , which indicated that conditional cash transfers (CCTs) could indeed interrupt the intergenerational cycle of poverty through human capital investments. However, there remains a lot of work to be done for preventing the next generation from returning to poverty in this turbulent period. In a related matter, the role of education in isolating intergenerational poverty or returning to the poverty trap should be highlighted. What kind of education would more effectively help families out of poverty, quality education or vocational skill education? How to allocate educational resources effectively? For poor students, what kind of psychological intervention in education is needed to mitigate the impact of native families and help them grow up confidently? Lots of questions waiting for empirical answering, yet we note that the educational journal only took a little fraction of the total journals in Section 4.3.2.

Next, poverty does exist in prosperous conurbations though the focal point obtained from keywords analysis is “rural area”. Nevertheless, both the slums in the center of big cities and circulative flowing refugees are experiencing more relative deprivation, representing a state of instability. Chamhuri et al. (2012) reviewed the objects, causes, and policies of urban poverty. Exploring how to lift a particular small economic low-lying area out of poverty is also of great significance. Follow-up researches should keep up.

Moreover, poverty alleviation needs to be based on individual or group-specific characteristics to some degree. It is not feasible to implement a unified poverty alleviation policy on a large scale. Exquisitely designed randomized controlled trials are used to reveal the heterogeneous influence of poverty alleviation programs. Haushofer and Shapiro (2016) compared the difference between monthly transfers and one-time lump-sum transfers. The subdivision research on the effect of poverty reduction programs should be strengthened. We imagine that a model may be formed to predict the total poverty reduction effects of different policies in the various region to obtain an optimized strategy of “No Poverty” in the future.

Lastly, exploring whether poverty reduction will be contradictory or coordinate with other SDGs might be a popular direction. About the literature review, two aspects can be improved. The first is merging with other databases to compare the loss of the trade-off between quality and quantity. Next, subsequent literature reviews need to explore how to better combine manual literature collation and bibliometrics, especially when the subject is a large topic.

Poverty reduction is one of the objectives of welfare economics and development economics. It is a classic and lasting topic and has recently come into the limelight. Poverty reduction studies in the 21st century are usually based on specific poverty alleviation projects or policies in developing countries. Researchers examine numerous topics, including whether the target audience has been precisely identified and covered in the design and implementation process, whether poverty reduction projects have been proved effective, what mechanisms have contributed to the success of poverty reduction projects, and what caused their failure. The aim of this paper is to summarize the amount, growth trajectory, citation, and geographic distribution of the poverty reduction literature, map the intellectual structure, and highlight emerging key areas in the research domain using the bibliometric method. We use the VOSviewer software and the R language as tools to analyze 2,459 articles published since 2000.

We have several conclusions. First, the 21st century is a period of booming research on poverty reduction, and the number of publications has increased sharply since 2015. Second, in affiliation analysis, Development in Practice and World Development are the top publications. The most frequently cited source of co-citations are World Development , Ecology Economics, Journal of Business Ethics, and Annals of Tourism Research , respectively the centers of the fields of economics, energy, the environment, and ecology, business, and tourism. Third, there are differences in the national and regional distribution of literature, based on the number of publications and citations. The United States led both the publication list and the total citation list, followed by the United Kingdom, China, and South Africa. Yet, there is a huge variation in the number of citations, with the United States and the United Kingdom having almost 5 to 6 times more citations than China and South Africa. In terms of average citations, Kenya is the best performer. The average citation amount in China is low, implying that Chinese scholars need to improve the quality of their literature. Fourth, in the keyword analysis, policy discussion and impact estimation are the two major themes. The keywords related to poverty reduction are different among different disciplines. Economics pays more attention to inequality and growth, while environmental disciplines pay more attention to protection and management. This may suggest that strengthening the cooperation between disciplines will lead to more diversified research perspectives. Fifth, in the co-author analysis, international cooperation is usually related to geographical location. For example, there is a large amount of cooperation between Europe and Africa, within Asia, and between North and South America. At the same time, poverty reduction research often shows the cooperative patterns of developed and developing countries. Last, in the co-keyword analysis, four clusters reflect the research priorities of each region. Poverty reduction in Africa is often related to basic livelihood and ecology. The economic conditions of the poor are the concerns of research in China and India. The South Asia region is also the location of microcredit program experiments. Poverty traps are intertwined with environmental problems in Latin America’s literature.

Our findings also offer inspiration for the future. There may be a need to investigate the interdisciplinary integration. Intergenerational and urban poverty deserve attention. The heterogeneous design of poverty alleviation strategies needs to be further deepened. It might be a popular direction to figure out whether poverty reduction will be contradictory with other SDGs and conduct scenario simulation. We identify shortcomings as well. Finally, precisely identifying research frontiers requires further exploration.

Author Contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

This work is supported by National Natural Science Foundation of China (NSFC) (grant number 72022009).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fcomm.2021.754181/full#supplementary-material

1 The extreme poverty criterion set by World Bank is 1.9$ a day in purchasing power parties (PPP), https://www.worldbank.org/en/research/brief/policy-research-note-03-ending-extreme-poverty-and-sharing-prosperity-progress-and-policies . The China poverty alleviation target in 2020 is to eliminate absolute poverty, which is defined as living less than 2,300 yuan per person per day at 2010 constant prices. In addition to living above the absolute poverty line, people who must reached other five qualitative criteria can be calculated getting rid of absolute poverty, which is no worries about food, clothing, basic medical care, compulsory education and housing safety

2 Jingzhunfupin is a general term of Chinese targeted poverty alleviation work model. Opposite to the haploid poverty alleviation, different assistance policies will be formulated according to the different category of poverty, distinctive causes, dissimilar background of poor households and their divergent living environment

3 https://enapp.chinadaily.com.cn/a/202102/26/AP60382a17a310f03332f97555.html . https://www.bbc.com/news/56213271

4 https://www.worldbank.org/en/topic/poverty/overview

5 The global Multidimensional Poverty Index (MPI) is developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) since 2010. It has been published annually by OPHI and in the Human Development Reports (HDRs) ever since. https://ophi.org.uk/multidimensional-poverty-index/

6 Relative poverty is another poverty measurement to reflect the underlying economic gradient. It is induced from the relative deprivation theory. Countries set the relative poverty line at a constant proportion of the country or year-specific mean (or median) income in practice ( https://doi.org/10.1162/REST_a_00127 )

7 This paper mainly found that eradicating extreme poverty, i.e., moving people to an income above $1.9 purchasing power parity (PPP) a day, does not jeopardize the climate target. That is to say, the climate target and no poverty goal is consistent and coordinated

8 This paper indicated that Payments for Environmental Services may reduce poverty mainly by making payments to poor natural resource managers in upper watersheds. The effects depend on how many participants are poor, the poor’s ability to participate, and the amounts paid

9 8–7 plan is the second wave of China’s poverty alleviation program. The Leading Group renewed poverty line and the National Poor Counties list in 1993. Targeted counties received three major interventions: credit assistance, budgetary grants for investment and public employed projects (i.e., Food-for-Work).

10 In the College Graduate Village Officials (CGVOs) program, the government hire outstanding graduates to work in the rural areas, for example as the village committee secretary, to help rural development and alleviate poverty. In this paper, the College Graduate Village Officials assisted eligible poor households to understand and apply for relevant subsidies, which reduced elite capture of pro-poor programs and move forward poverty alleviation process

11 The Tayssir Project was labeled the Education Support Program, sending a positive signal of its educative value

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Keywords: poverty reduction, bibliometric analysis, VOSviewer, sustainable development goals, 21st century

Citation: Yu Y and Huang J (2021) Poverty Reduction of Sustainable Development Goals in the 21st Century: A Bibliometric Analysis. Front. Commun. 6:754181. doi: 10.3389/fcomm.2021.754181

Received: 06 August 2021; Accepted: 01 October 2021; Published: 18 October 2021.

Reviewed by:

Copyright © 2021 Yu and Huang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Yanni Yu, [email protected] ; Jinghong Huang, [email protected]

† These authors have contributed equally to this work

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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The Impact of Education and Culture on Poverty Reduction: Evidence from Panel Data of European Countries

1 Department of Economics, University of Foggia, 71121 Foggia, Italy

2 Department of Agricultural, Food and Forest Sciences, University of Palermo, Viale Delle Scienze, 90128 Palermo, Italy

The 2030 Agenda has among its key objectives the poverty eradication through increasing the level of education. A good level of education and investment in culture of a country is in fact necessary to guarantee a sustainable economy, in which coexists satisfactory levels of quality of life and an equitable distribution of income. There is a lack of studies in particular on the relations between some significant dimensions, such as education, culture and poverty, considering time lags for the measurement of impacts. Therefore, this study aims to fill this gap by focusing on the relationship between education, culture and poverty based on a panel of data from 34 European countries, over a 5-year period, 2015–2019. For this purpose, after applying principal component analysis to avoid multicollinearity problems, the authors applied three different approaches: pooled-ordinary least squares model, fixed effect model and random effect model. Fixed-effects estimator was selected as the optimal and most appropriate model. The results highlight that increasing education and culture levels in these countries reduce poverty. This opens space to new research paths and policy strategies that can start from this connection to implement concrete actions aimed at widening and improving educational and cultural offer.

Introduction

Poverty eradication has been the key objective for spans in many countries since that has been recognized as the greatest hostile issues ‘jeopardising balanced society socio-economic development’ (Balvociute, 2020 ). Poverty can be considered one of the core features of unsustainable socio-economic development and as a persistent phenomenon that can have upsetting effect on peoples’ lives (Bossert et al., 2022 ). For this reason, the extreme poverty removal, as well as the fight against inequalities and injustices, have been placed at the center, with climate change, of the 2030 Sustainable Development Goals. The nature of poverty is multidimensional and inequalities within and among countries is an obstinate origin for concern (Fund, 2015 ; Alvaredo et al., 2017 ; Alkire & Seth, 2015 ; Kwadzo, 2015 ). For its interpretation and measurement, the literature has added to the monetary approach of material deprivation, the social and subjective dimension of the human being (Bellani & D’Ambrosio, 2014 ; Maggino, 2015 ). As stated by Kwadzo ( 2015 ), it is possible to define three poverty measurements: monetary poverty, social exclusion, and capability poverty. Similarly, there are a lot of indicators measuring well-being and quality of life: Index of Happiness, Human Poverty Index and Human Development Index (Senasu et al., 2019 ; Spada et al., 2020 ; UNDP, 1990 ; Veenhoven, 2012 ; Watkins, 2007 ). All these indicators focus and start from education. For example, the Human Poverty Index (HPI) was introduced by the United Nations to complement the Human Development Index (HDI) and used, for the first time, in the 1997 Human Development Report. In 2010, it was replaced by the Multidimensional Poverty Index. The HPI focuses on the deprivation of three essential parameters of human life, already taken into account by the Human Development Index: life expectancy, education and standard of living (Alkire et al., 2015 ; UNDP, 1990 ).

Previous studies shown that education indicators have a large impact on a country’s poverty (Bakhtiari & Meisami, 2010 ; UNDP, 1990 ; Watkins, 2007 ) and that investing in health and education is a way to reduce income inequality and poverty. In addition, studies highlight that increasing equality and the quality of education is essential to combat economic and gender inequality within society (Walker et al., 2019 ). However, few studies provide empirical evidence on how education impacts on income inequality (Liu et al., 2021 ; Santos, 2011 ; Walker et al., 2019 ) and most of these studies analyses the poverty phenomenon neglecting the combined effect of various variables. Different dimensions of poverty have also empirically demonstrated a high degree of correlation (Kwadzo, 2015 ). In addition, the literature review analysis highlighted a gap in quantitative studies, especially on the paths between some relevant dimensions, such as education, culture and poverty, considering time lags for the measurement of impacts. In light of this, the main objectives of this study are: (i) To identify over the five-year period considered (2015–2019), with what delay and with what magnitude and sign, the poverty is influenced by some indicators representative of the educational and cultural dimension; and (ii) Consequently, better calibrate education policies in European countries, in order to achieve a reduction in the poverty rate in the short term, in compliance with the objectives of the 2030 Agenda.

The rest of the paper is organized as follows. A literature review regarding the relation between poverty, education and inequalities is presented in Sect.  2 . The Sect.  3 enlightens research gaps linked to the aims of this study and hypothesis to corroborate. Section  4 defines data and summarizes the methodological approach used to reach the work’s aims. Results are presented and discussed in Sect.  5 . Finally, the last section sets out our main conclusions by highlighting limitations of the study and future directions.

Theoretical Framework

The core role of education.

Over the last decades it is possible to individuate in the EU-28 a quickly growing portion of the population having income below 60% of the median disposable income. In addition, there is a share of the population has been becoming more impoverished (Balvociute, 2020 ; EUROSTAT Statistic Explained, 2019 ). In same way, it is possible to speak about “poverty trap”, a mechanisms whereby countries are poor and persist poor: existing poverty appears a straight cause of poverty in the future (Knight et al., 2009 ; Kraay & McKenzie, 2014 ). Aspects such as accommodation, education, medical and material services are considered essential. In particular, an increasing number of empirical studies have supported the positive effects of education on the creation of wealth by individuals and on promoting economic effective and fair development (UNESCO & Global Education Monitoring Report, 2017 ; Walker et al., 2019 ; Xu, 2016 ; Zhang, 2020 ). A research note by European Commission ( 2015 ) shows that individuals with primary education remain the most vulnerable in all EU countries (with a risk of poverty ranging from 13%—Netherlands—to 56% Romania). Even the Millennium Development Goals (MDGs), the Poverty Reduction Strategy Papers (PRSP) endorsed by the World Bank and ‘Education for All’ program (UNESCO, 2007 ) emphases the significant role of education (Awan et al., 2011 ). A diverse balance can be possible and policy efforts to interrupt the poverty trap might have long-term effects. In this framework, the model proposed by Santos ( 2011 ) shows that a policy oriented towards aligning the quality of education would reduce initial inequalities. In light of this, Shi & Qamruzzaman, ( 2022 ) in a recent work, study, by means of numerous econometrical methods, the tie between investments in education, financial inclusion, and poverty decrease for the period 1995–2018 in 68 nations, underlining the role of education-backed poverty mitigation public policies that need to be more targeted. Several studies demonstrate that level of poverty and education are strictly related. For instance, Bossert et al. ( 2022 ) by focusing on Atkinson-Kolm-Sen index, that measures the percentage income gap of the poor that can be attributed to inequality among the poor (Sen, 1973 , 1976 ), emphasized the close relation between poverty and inequality. Consistent with previous studies, Lenzi and Perruca ( 2022 ) demonstrate that tertiary educated people report higher ranks of life satisfaction. This link is even more marked in rural territories where education is recognised as an important tool for reducing poverty as it allows the acquisition of skills and productive knowledges which increase people’s productivity and their earnings (Tilak, 2002 ). A recent report of the United Nations ( 2021 ) underlines how the reduced access to educational and health services in rural areas becomes a barrier, determining the difficulty of people living in these areas to found employment in well-paid professions contributing to economic growth (Chmelewska and Zegar, 2018 ). However, as Liu and colleagues ( 2021 ) find, different levels of education have distinct effects on poverty in rural areas of China and that the latter is driven not only by factors within the region but also by the level of poverty in the surrounding regions. In addition, numerous empirical evidences reveal a link between educational level and income inequalities in several geopolitical contexts. Bakhtiari and Meisami ( 2010 ), in a work of over 10 years ago, makes use of a panel data set of 37 Islamic countries (eight time periods) to study income inequality along with a model of poverty, with the main variables as income level, health status, education and savings. Findings show that enhancing the health and education can reduce income inequality and poverty. Likewise, as Arafat and Khan ( 2022 ) underline the high level of education not only contributes to reducing the degree of poverty but improves the conditions of mental, social and emotional well-being compared to poorly educated families. After about 10 years, similar works by Wani and Dhami ( 2021 ) and Sabir and Aziz ( 2018 ) reach the same results investigating the SAARC (South Asian Association for Regional Cooperation) countries and 31 developing countries (by employing the System Generalized Method of Moments). In several cases, and especially in rural areas, poverty is linked to the lower level of household income compared to urban areas, resulting in differences in access to basic goods and services to meet personal needs (Chmelewska and Zegar, 2018 ). In this territories household income level is directly associated with food security, in fact, an increase in the level of income reduces food insecurity (Chegini et al., 2021 ). However, as evidenced by other authors (Kirkpatrick et al., 2020 ; Kusio & Fiore, 2022 ), access to education can help to overcome the migration of young people and geographical isolation and inaccessibility that characterize the poor areas (Kvedaraite et al., 2011 ). In turn, young, educated people affect entrepreneurial attitudes. Walker et al. ( 2019 ) in the recent report ‘ The Power of Education to Fight Inequality. How increasing educational equality and quality is crucial to fighting economic and gender inequality ’ show how education can be emancipating for individuals, and it can play the role of a ‘leveler and equalizer within society’. Education interrupts obstinate and rising inequality by promoting the development of more decent work, rising incomes for the poorest people: it can aid to endorse long-lasting, wide-ranging economic growth and social cohesion.

Gradstein and Justman ( 2002 ) underlined the role of education in shaping the social cohesion that can assure equality between individuals. Universal free education enhances people’s earning power, and can bring them out of poverty. Low levels of education hamper economic growth, which in turn slows down poverty reduction (UNESCO, 2017 ; Global Education Monitoring Report, 2019 ) estimates that each year of schooling raises earnings by around 10%;53 this figure is even higher for women. In Tanzania, having a secondary education reduces the chances of being poor as a working adult by almost 60%. According to a study by UNESCO and the Global Education Monitoring Report ( 2019 ), if all adults finished secondary school, 420 million individuals would be lifted out of poverty. The convergence of crises deriving first from COVID-19 then from climate change, and conflicts, are generating extra impacts above all on poverty, nutrition, health and education affecting all the Sustainable Development Goals (SDGs).

Equilience, a synchratic neologism composed of Equity + Resilience, that is resilient systems in respect of equity as a balancing of the different interests of the parties. Recent research (Berbés-Blázquez et al., 2021 ; Williams et al., 2020 ; Contò and Fiore, 2020 ) highlight the crucial importance to promote the ‘marriage’ between equity and resilience.

Aims of Study and Hypothesis

This research is potentially the first study to investigate the relationship between educational, cultural factors and poverty in European countries.

The main research directions are as follows: (i) To assess the impact of education and culture (expressed by the following indicators: Cultural employment, Total educational expenditure, Graduates in tertiary education, Number of enterprises in the cultural sectors, Tertiary educational attainment ) upon poverty (indicated by Persons at risk of poverty or social ); (ii) To compare the strength and direction of the relationships between the variables considered in two temporal situations, i.e. with zero lag, and with lag equal to one year. The data cover the period 2015–2019 and were extracted from the Eurostat database.

In the light of the above discussion, of the literature review analysis, and of the theoretical frameworks examined this study explores the following research hypotheses with regard to the European context:

Education and culture have an inverse impact on the levels of poverty.

Our second hypothesis states:

The association between cultural, educational variables and poverty, in the short term is more intense if we consider a delay of one-year.

The dataset is a balanced panel of annual observations for 34 European countries and covers the period from 2015 to 2019. On the basis of literature findings, our analysis focused on the following dimensions: education, income inequality and poverty.

Thereby, the variables considered for our investigation are as follows:

• Poverty indicator: Persons at risk of poverty or social exclusion (% of population, thousand persons; hereinafter labelled with PRP);
• Education and cultural indicators: Cultural employment (thousand persons); Total educational expenditure (million euros); Graduates in tertiary education (‰ of population;); Number of enterprises in the cultural sectors (number) Tertiary educational attainment (‰ of population). Respectively, hereinafter they will be labelled with CE, TEE, GTE, NEC and TEA.

The indicators have been extracted from the Eurostat database. The summary statistics are reported in Table ​ Table1. 1 . In the selected time period, Iceland is the country that shows the lowest values with respect PRP (12.08%). Instead, the country showing the worst performance is Romania (PRP = 41.60%). With regard to the education indicators, Germany holds the highest values for both CE (81,661.48 thousand persons) and TEE (30.588.86 million euros), highlighting great attention to education issues. Instead, in Eastern Europe (Montenegro, Romania, and Hungary) the indicators pertaining to the education area take on more penalized values. Italy is the country that boasts the largest number of enterprises in the cultural sector (NEC = 179,136.8), thanks also to the artistic beauties of which this country is rich. As far as the tertiary education level is concerned, the highest value of is held by Cyprus while the lowest by Romania (respectively TEA = 57.34 and TEA = 25.26). For subsequent processing, since the variables considered are both in the form of ratios and counts, all data were converted to natural logarithms.

Summary statistics for the Eurostat datasets, 2015–2019

Methodology

The methodological approach used is based on linear panel data models including the simple Pooled Ordinary Least Square (pooled OLS) model, the Fixed Effects (FE) model and the Random Effects (RE) model. Before proceeding with the application of the linear models, the correlation matrix between the variables taken into consideration was performed and subsequently, to avoid multicollinearity problems and distorted estimates, the study, based on the principal component analysis (PCA), used two indicators related to education and culture. According to Jolliffe and Cadima ( 2016 ), through PCA starting from a set of correlated variables, a set of uncorrelated variables is obtained, known as Principal Components (PC). In PCA, only common factors that have an eigenvalue greater than one or greater than the mean should be kept (Jolliffe, 2002 ; Kaiser, 1974 ). In this study PCA allowed to obtain the following indicators: EDU1, which includes CE, NEC, TEE, and EDU2, composed of TEA and GTE. These indicators have been incorporated into the panel data models, replacing the original variables.

The first linear panel data model adopted is the pooled OLS, which assumes no heterogeneity between countries, whose equation is as follows:

where ln PRP is the natural logarithm of the poverty indicator, α is the intercept, EDU is composed of the principal components extracted, ε is the error term, i denotes statistical units, in this case countries, and t denotes the time index.

The second model adopted is FE which controls for cross-country heterogeneity and is expressed as:

where α i is the regional specific parameter denoting the fixed effect. The basic intuition of the FE model is that α i does not change over time.

Finally, the third model is RE denoted as;

In the RE model, variations between units are assumed to be random and uncorrelated with the independent variables in the model.

To verify the two research hypotheses, for each of the three models (pooled OLS, FE and RE) two versions were calculated, with lag 0 and lag 1 year. In the model at lag 0 the variables are synchronous, while in the model at lag 1 principal components enter the equation with a one-year lag compared to PRP. The choice of the reference model between pooled OLS, FE and RE is based on several tests. In choosing between FE and pooled OLS, the study applies the F-test. A p-value of less than 5% indicates that there are important country effects that OLS fails to detect, and that thus neglecting unobserved heterogeneity in the model can lead to estimation errors and inconsistencies. The study also tests which is better between the OLS and RE model using the Breusch-Pagan (BP)-Langragian Multiplier (LM) test. The null hypothesis of the BP-LM test is that there is no substantial variance between regions. A probability value of less than 5% for the BP-LM test indicates that the RE model is appropriate and the OLS pool is not. Finally, the Hausman test χ 2 is also performed to compare the FE model and the RE model. According to Algieri and Mannarino ( 2013 ), the Hausman test χ 2 aims to identify a violation of the RE modelling hypothesis. In this test, the alternative hypothesis is that the FE model is preferable to the RE model, while the null hypothesis is that both models produce similar coefficients. A p-value greater than 5% denotes that both FE and RE are reliable, but the RE model is more efficient because it uses a lower degree of freedom. We also test for heteroskedasticity in the FE model using the modified Wald test developed by Lasker and King ( 1997 ). The null hypothesis of this test is that the variance of the error is similar for all countries (Amaz et al., 2012 ). All statistical analyses were conducted in Stata 17.0 (Stata Corp LP, College Station, Texas, USA). A critical value of p  < 0.05 was specified a priori as the threshold of statistical significance for all analyses.

The relationships between the variables, measured by Pearson’s linear correlation coefficient, is shown in Table ​ Table2. 2 . It is noted that the PRP variable is negatively correlated with all the other panel variables, albeit with modest correlations. Instead, TEE shows a high positive correlation with NEC ( r  = 0.963 and r  = 0.903, respectively). There is also a high correlation between NEC and TEE ( r  = 0.857). Therefore, in the light of the results, to exclude the problem of multicollinearity between the covariates, we proceeded to analyse the principal components.

Pearson correlation coefficient

* p  < 0.05, ** p  < 0.01, *** p  < 0.001

Table ​ Table3 3 shows the results of principal component analysis. On the basis of these results, the need to maintain the first two principal components is highlighted, since their eigenvalues are greater or very close to 1 and cumulatively represent the 84% of the information. They will be labelled as EDU1 and EDU2 respectively. EDU1 refers to TEE, CE and NEC, i.e. it refers to a cultural dimension of the country and therefore, even if not strictly connected to the school environment, with an important educational role, while the EDU2 component referring to GTE and TEA, is more closely related to the school.

Principal component analysis: factor loading, eigen value and variance explained

Table ​ Table4 4 shows the results of the three econometric models (pooled OLS, FE, RE) on the link between education, culture and poverty. It is observed that all models converge in showing that poverty decreases with increasing education and culture. In particular, the EDU1 indicator always shows a negative coefficient, and this relationship is statistically significant in the model fixed at lag 0 and lag 1 (respectively b  = − 0.3804, p  < 0.001; b  = − 0.3925, p  < 0.001). Furthermore, for EDU1, in all three econometric models it can be noted that the coefficients are higher in absolute value passing from lag 0 to lag 1, highlighting that the impact between cultural and educational tools and poverty reduction occurs with a delay, perhaps necessary to have positive results. Also, the EDU2 indicator always shows a negative coefficient and this relationship is statistically significant in all three models, both at lag 0 and at lag 1 (for all p  < 0.001). To discern the econometric model that best fits the data, as a first step the F-test allows you to choose between the OLS and FE models. The value F = 80.09 for lag 0 and F = 109.61for lag = 1, (for all p -value < 0.001), indicates in both cases that the FE model is more suitable than the pooled OLS. This demonstrates that in the relationships examined time plays an important role, which a simple OLS model may fail to capture, i.e. EDU1 and EDU2 have an effect on poverty decrease that changes over time. The choice between the RE model and the pooled OLS was instead based on the BP LM test, which suggests that the RE model is more suitable than the pooled OLS. Finally, the Hausman test χ 2 allows to identify which between FE and RE is more suitable: The value χ 2  = 15.95 at lag 0 and χ 2  = 13.40 at lag = 1, (for all p -value < 0.001) suggests that the FE model is more suitable than the RE model, indicating the presence of non-random differences between countries or over time. The model that best fits the examined panel of data is therefore the FE model.

Pooled OLS, Fixed Model, Random Model, at lag 0 and at lag 1

** p  < 0.01, *** p  < 0.001

In light of these results, as supposed in hypothesis H 1 , it is evident that education and culture play a significant role in poverty reduction. Furthermore, as supposed by hypothesis H 2  and based on the FE model which was found to be the most suitable, this impact is more intense if one considers a year of delay, above all for cultural and educational variables relating to a dimension that is not strictly scholastic.

Discussions and Conclusions

The present study analysed the relationship between education, culture and poverty for 34 countries, over the period 2015–2019. The findings indicate that rising education and culture levels in these nations reduce poverty. The model also highlighted that this relationship is weaker if we consider a contemporaneity of the values of the variables (at lag 0), while it is strengthened if we consider a time interval of one year.

As policy-makers regularly disclose the consequences of unfair development by identifying problems requiring solutions built on evidence-based guidelines, these results can have interesting and fruitful implications. By concluding, education appears, in line with other studies (Sabir & Aziz, 2018 ; Xu, 2016 ), one of the best effective methods to eradicate poverty. In line with the work by Walker et al., ( 2019 ), investing in universal-free-public education for all the persons can close different circles: the gap between rich and poor people, between women and men, between poor and rich areas within a country and among countries. In addition, education appears crucial to fight inequalities across the world. The results appear also consistent with the UN report ( 2021 ) that emphasizes the importance of the access to educational and health services in marginal poor areas to improve and contribute equal economic growth and reduce poverty (Chmelewska and Zegar, 2018 ; Bakhtiari & Meisami, 2010 ; Wani & Dhami, 2021 ). The same findings come from the work by Peng ( 2019 ) based on data from poor Chinese provinces showing that education has steady and positive impacts on farmers’ income, and the outcome of growing income in poor zones is higher than in other areas.

All in all, as evidenced by the European Commission ( 2015 ), the means to diminish the risk of poverty appears ‘straight-forward: go to school, get a job’. Clearly, these implications have to consider conditions and country environment. In line with previous research (Noper Ardi & Isnayanti, 2020 ; Walker et al., 2019 ), these results highlight that education can have an immediate impact on income inequalities and poverty; on the other hand, education (and public spending on it) has a longer-term impact on inequality through its effects in enhancing future salaries and chances. Indeed, as stated by some notable researchers (Kraay & McKenzie, 2014 ), the ‘more-likely poverty traps’ need action in less-traditional policy areas. The scholars have to further perfect the theoretical concepts and policy standards of poverty alleviation through education (Shi & Qamruzzaman, 2022 ).

This paper reinforces the conclusions deriving from other research (Mou and Xu, 2020 ; Assari et al., 2018 ; Batool and Batool, 2018 ) that are to give evidence of how education can forecast coming ‘Emotional Well-Being’ thus decreasing the inequalities by means of more generous policies and strategies. The latter can support international experience-based education (Xu, 2016 ).

In the following research phases, other variables can be inserted to improve the specifications of the model and also verify the existence of homogeneous groups of countries. In addition, a distinction between urban and rural areas to highlight the link between income, education and poverty and differences could enrich the literature and provide useful information to guide national policies in a targeted way. Regarding possible limitations of the paper, it is possible to notice a time period limited for missing data and health variables are missing.

The ‘dark’ side of this conclusions is considering the effects of the COVID19 pandemic that has increased on one hand the online teaching and training: on the other hand, education has become more difficult in remote, rural and/or marginal areas due to connections and hardware limitations.

Therefore, nowadays strategies, models and polices focusing on equi-lience (equity and resilience) processes can promote the creation of a different balance between the needs of sustainable growth and those of social, fair and environmental development (Fiore, 2022 ). Therefore, developing a strategy to convey a trained, skilled and well-supported workforce, investing in relevant and fair teaching resources, ensuring funds and building better liability mechanisms from national to local levels can be significant and fair paths to reduce poverty and inequalities. These strategies have to be aimed at developing national education plans that try to identify pre-education existing inequalities in order to arrange actions in poorer rural and marginalized districts or regions.

Open access funding provided by Università di Foggia within the CRUI-CARE Agreement.

Declarations

Authors disclose financial or non-financial interests directly or indirectly related to the work submitted for publication.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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• Published: 13 June 2024

From poverty to prosperity: assessing of sustainable poverty reduction effect of “welfare-to-work” in Chinese counties

• Feng Lan 1 , 2 ,
• Weichao Xu 1 ,
• Weizeng Sun 3 &
• Xiaonan Zhao 1  

Humanities and Social Sciences Communications volume  11 , Article number:  758 ( 2024 ) Cite this article

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• Development studies
• Social policy

The “welfare-to-work” program is a comprehensive supportive policy in the 14th five-year plan period in China. In this paper, a systematical assessment of the long-run effectiveness of the welfare-to-work policy on poverty reduction is of great significance to stimulate the internal impetus of people who are lifted out of poverty to achieve income growth and prosperity and promote regional economic development. Based on the data at the county (city) level in China from 2000 to 2019 and the sustainable development theory, in this paper, a county-relative poverty evaluation system was constructed. Besides, the double difference method was employed to evaluate the effect of the welfare-to-work policy on poverty reduction and test its action mechanism. The findings are as follows: (1) the welfare-to-work policy has a significant poverty reduction effect and presents an inverted “U” shape. In addition, significant achievements have been made in “maintaining employment stability, ensuring income, strengthening skills, and supporting the economy” ; (2) the welfare-to-work policy boosts poverty reduction in counties through infrastructure construction, fiscal intervention, and financial tools; however, the financial tools play a positive role in poverty reduction in the northwest region and suppressed role in the southwest region, and has an insignificant effect in the central region; and (3) there are differences in the effect of poverty alleviation policies of the counties with different sustainable development levels, and the regions with higher development level have a stronger driving effect.

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Introduction.

In 2021, China has scored a competitive victory in the fight against poverty. The final 98.99 million impoverished rural residents living under the current poverty line have all been lifted out of poverty. All 832 impoverished counties across the country and 128,000 impoverished villages have been removed from the poverty list Footnote 1 . Regional overall poverty has been resolved, which marks that China’s poverty governance has entered a new stage from absolute poverty to relative poverty, and from income poverty to multidimensional poverty. Relative poverty and multidimensional poverty have become new forms of poverty in China (Xu et al. 2021 ).

China’s anti-poverty focus has shifted from targeted poverty alleviation in absolute poor areas to comprehensive measures to promote high-quality development in relatively poor areas. The limited ability of the relatively poor population to obtain various livelihood capital also reduces the range of livelihood activities, and aggravates the livelihood risk and vulnerability. These factors will affect the economic development of relatively poor areas and the ability of rural populations to increase their income, and the long-term and complexity of this external environment also determine the long-term sustainability of consolidating and expanding the achievements of poverty alleviation.

Since ancient times, China has had the practice of “providing employment as a form of relief”. Since 1984, welfare-to-work, as a social and economic policy, has played an important role in poverty alleviation and development. Nowadays, with the transformation of China’s anti-poverty focus from the governance of absolute poverty to the high-quality development of relatively poor areas. The welfare-to-work policy not only has the attribute of poverty alleviation, but also has the overlapping role of social welfare and economic development, maximizing the release of the effects of the policy and activating the endogenous power of county economic development. On the one hand, it can be used to resist the impact of unfavorable factors and emergencies such as the COVID-19 pandemic, earthquakes, and tsunamis. Welfare-to-work policy can effectively play the role of “relief” in the process of flood control and post-disaster recovery. Compared with direct subsidies, welfare-to-work further mobilizes the enthusiasm of the broad masses of peasants to participate in the construction of rural public infrastructure and give full play to the investment of government for supporting agriculture. On the other hand, aiming at the employment needs of low-income groups, it provided timely payment of labor remuneration, and employment skills training. With compulsory and welfare means, it enhanced the capacity and subjective motivation of poverty-stricken people and low-income groups, thus encouraging them to participate in the competition.

Through data analysis, it was found that since the implementation of the “Welfare-to-work” policy in different regions, the effects have not been the same. For instance, during the implementation process, the phenomenon of emphasizing construction while neglecting relief has come into existence. Besides, influenced by the factors in regional development level, geographical restrictions, and population flow, the current labor force has lower quality and insufficient skills and thus achieves an unsatisfactory effect on employment and income growth. Although these areas have all been lifted out of poverty under the country’s targeted poverty alleviation policy, once impacted by external uncertainties, the obtained achievements in poverty alleviation will be irrevocably lost.

Therefore, what kind of impact does the sustainability of poverty reduction performance of the welfare-to-work policy have? Is there heterogeneity in the poverty reduction effect of the welfare-to-work policy in different districts and counties? What is the role of a welfare-to-work policy in poverty reduction?

In this paper, a multi-dimensional relative poverty evaluation index system was constructed and the poverty reduction effect of the “welfare-to-work” policy was evaluated by the method of double difference (DID). In addition, the panel regression model was constructed to explore the mechanism of poverty reduction, and the Shapley method was used to quantify the contribution of mechanism variables to the poverty reduction effect. The study has several important findings. First of all, the cash-for-work policy effectively promotes poverty reduction in counties, and the higher the level of local development, the more significant the poverty reduction effect. The results are still valid after robustness testing. Second, policies promote poverty reduction at the county level through infrastructure construction, fiscal intervention, and financial instruments, but the contribution of different variables in different regions is different.

The remainder of this study is arranged as follows. Section 2 “Literature review and research hyptothesis” provides a literature review and research hypothesis. Section 3 “Research design” describes our empirical design. Section 4 “Analysis of empirical results” reports our empirical results and robustness tests. Section 5 “Test of action mechanism” reports the quantitative results of the mechanism of action. Finally, we provide a summary.

Literature review and research hypothesis

Evolution of welfare-to-work policy.

(1) From 1949 to 1983: the stage with a focus on disaster relief. At the First and Second National Civil Affairs work conference, it was emphasized that in disaster relief work, the principles of overcoming adversity through greater production, saving grain to tide over a lean year, holding on to mutual assistance, work relief, and supplementary necessary government relief should be encouraged. However, in accordance with the statement of the National Civil Affairs Conference in 1953, as the following continuous various projects in economic construction in China would inevitably attract the participation of victims, so the Welfare-to-work policy was removed from the disaster relief policy. At this stage, the planned economy system not only strengthened the government’s ability to organize disaster victims to carry out self-rescue action but also endowed the welfare-to-work policy and other policies with distinctive epochal features (Zhu, 2021 ). Specifically, the Welfare-to-work policy mainly focuses on the unemployed population and disaster relief. In addition, with efforts of supply optimization manpower allocation, and material and financial resources supply, the government organized victims in the form of mutual assistance and cooperation and built some engineering facilities in flood control, drainage, irrigation, and power generation, which have promoted the recovery of production and reconstruction of homes while providing disaster relief.

(2) From 1984 to 2000: the early stage of poverty alleviation and development. With the economic reform, poverty has been included as an important part of social and economic development. In 1984, China began to regard welfare-to-work as a means of alleviating poverty, and successively implemented six large-scale welfare-to-work programs, namely “grain and cotton cloth related welfare-to-work program”, “medium-and low-grade industrial products related welfare-to-work program”, “industrial products related welfare-to-work program”, “grain related welfare-to-work program”, “river control related welfare-to-work program” and “state-owned poor farms related welfare-to-work program”. In other words, since 1984, China has organized the impoverished people to carry out infrastructure construction in the fields, roads, rivers, houses, and toilets and has paid for grain, cotton, cotton cloth and industrial products to workers as labor remuneration. This measure not only provides employment opportunities and achieves income growth for poor workers but also improves infrastructure and public services in poor areas. In 1990, the State Council issued the Opinions on the Arrangement of Industrial Products for Welfare to Work from 1990 to 1992. According to the Opinions, 1.5 billion yuan of industrial products were used for the labor remuneration for workers in the construction of the welfare-to-work program; during the eighth five-year plan period, the Chinese government invested 1 billion kilograms of grain or equivalent industrial products per year in the Welfare-to-work program in poor areas; and in 1996, the welfare-to-work program was supported by financial funds instead of the form of in-kind cash conversion. In 1998, in the context of the financial crisis, the National Development and Reform Commission (NDRC) issued measures to support the welfare-to-work program with treasury bonds, which solved the problem of expanding domestic demand. As an important part of the central poverty alleviation fund, the proportion of welfare-to-work funds increased from 15.38% to 37.04% in the ten years from 1986 to 1996, during which the acceleration of infrastructure construction in poor areas became the main operation mode of the welfare-to-work policy. At this time, the Welfare-to-work system not only had the function of disaster relief but also promoted the construction of local infrastructure.

(3) From 2000 to 2020: the special-purpose poverty alleviation policy stage. In the 21st century, the welfare-to-work program gradually has developed with “fine, small and deep” characteristics, with a focus on the implementation in a certain region or in-depth research on the analysis of welfare-to-work on the system (Shen, 2018 ). In December 2005, the NDRC issued the National Administrative Measures for welfare-to-work Policy, which highlighted the funds' management, project implementation, and organizational management of the welfare-to-work program, thereby improving the implementation performance of the policy. In 2011, to improve the quality of cultivated land, strengthen infrastructure construction, enhance the ability to withstand natural disasters, and consolidate the foundation of economic development in poor areas, the Chinese government issued the Outline for Poverty Alleviation and Development in China’s Rural Areas (2011–2020), in which the welfare-to-work program was included as a special-purpose poverty alleviation policy measure. In December 2014, to meet the requirements of rural poverty alleviation under the new situation, the NDRC launched the revision of the administrative measures for welfare-to-work policy. In 2016, the NDRC issued the National “13th five-year plan” for the welfare-to-work program, taking small and medium-sized infrastructure in rural areas the focus of the welfare-to-work program. According to the work plan, the welfare-to-work program should be transformed from “adopting a deluge of strong stimulus policies” to “precision regulation policies”, and a new model of poverty alleviation with asset income featuring “changing assets into equity, poor households into shareholders” should be innovated. In June 2019, the NDRC issued guiding opinions on further leveraging the role of welfare-to-work policies to help win the battle against poverty, which called for the continuous focus on supporting deeply impoverished areas such as the “three regions and three prefectures” to win the battle against poverty as scheduled and consolidate poverty alleviation achievements in poor areas. In July 2019, the NDRC issued Opinions on further adhering to the original purpose of “Relief” and giving full play to the function of the welfare-to-work policy, which underscored the importance of comprehensively expanding a variety of relief modes, relying on welfare-to-work projects to extensively carry out employment skills training and public welfare position development, and exploring the implementation of quantitative dividends through asset share conversion. In November 2020, the NDRC and nine other departments issued opinions on actively promoting welfare-to-work policy in the field of agricultural and rural infrastructure construction, requiring that the welfare-to-work policy should be actively promoted in the fields of rural production and life, transportation, water conservancy infrastructure, cultural tourism infrastructure, forestry, and grassland infrastructure construction, so as to improve rural production and living conditions, which has played an important role in consolidating the achievements of poverty alleviation.

(4) From 2021 to present: multifunctional comprehensive stage. In July 2021, the NDRC issued the National “14th Five-Year Plan” for the welfare-to-work program, which comprehensively expands the implementation areas, implementation functions, beneficiary groups, construction areas, and relief modes of the policy in the next five years. In July 2022, the NDRC issued a work plan on vigorously implementing welfare-to-work policy in key engineering projects to promote employment and income growth of local people. In the work plan, the NDRC emphasized that vigorously implementing the Welfare-to-work policy in key engineering projects is an important measure to promote effective investment, ensure employment stability and people’s well-being, stimulate county consumption, and stabilize the economic market, which will drive the people to share in the fruits of reform and development. In January 2023, in the context of a new journey and new requirements in the new era, the NDRC revised the National Administrative Measures for welfare-to-work policy. The NDRC stressed that on the one hand, we should stick to the original purpose of “Relief”, insist on helping people who have talent and poverty problems, and adhere to the principles of earning more from more work and getting rich through hard work to enhance the internal impetus of income growth and prosperity. On the other hand, we should strengthen the employment assistance for the people in difficulty, and promote common prosperity.

In summary, different from the “blood transfusion” poverty alleviation policy, “the welfare-to-work policy”, as an effective tool of the national “hematopoietic poverty reduction” policy, has a comprehensive poverty alleviation function and profound poverty alleviation connotation in solving the “two no worries, three guarantees”(no worries for basic food and clothing, and guarantees for compulsory education, basic medical services, and safe housing and drinking water), optimizing redundant resources, and improving the supply of public services and infrastructure. As the focus of China’s poverty reduction strategy has shifted from “extensive poverty reduction” to “targeted poverty reduction” and then to “consolidating the achievements of poverty alleviation”, the welfare-to-work policy has transformed from “adopting a deluge of strong stimulus policies” to “precision regulation policies”. However, the policy target always focuses on boosting employment and income growth, enhancing self-development and internal impetus to become rich, and promoting regional development; the scope of implementation has changed from the national key impoverished counties to the less developed areas with poverty alleviation as the focus; the construction field has expanded from the small and medium-sized rural infrastructure field to “one key area” and “seven major areas”; the relief mode has been expanded from the single mode of participating in the construction of welfare-to-work projects to obtain labor remuneration to the various relief modes such as conducting the quantitative dividends through asset share conversion, and carrying out employment skills training and public welfare position development; and the policy function has changed from the single relief type to the comprehensive type integrating the functions of promoting employment, ensuring people’s well being, carrying out emergency disaster relief, and boosting regional development of infrastructure (Table 1 ).

Literature review on the welfare-to-work policy on poverty reduction

The relationship between welfare-to-work and sustainable poverty alleviation of relative poverty.

In the early studies on poverty, poverty alleviation policy is an important influencing factor, and related theories involve human capital theory, poverty cycle theory and sustainable livelihood theory, etc. This paper will combine these theories to analyze the relationship between welfare-to-work policy and relative poverty and put forward a research hypothesis.

Long-term governance of relative poverty is the basic goal of poverty governance in China’s post-poverty alleviation era. The exploration of the transformation of government poverty alleviation ability should not only take this as starting point of the research, but also take solid theoretical achievements as theoretical support (Wang and Wang, 2021 ). Therefore, the governance of relative poverty should start from the perspective of sustainable development. On the one hand, it promotes the sustainability of the livelihood of local low-income people, including the continuous improvement of living standards and the continuous improvement of their livelihood self-improvement ability, that is, they are endowed with development power, create development opportunities, strengthen development ability and share development achievements at the individual level (Luo et al. 2021 ), and then realize the transformation from “blood transfusion” governance to “hematopoiesis” governance. On the other hand, relatively poor areas are an important type of area to promote the formulation of sustainable development policies in underdeveloped areas in China (Zhou et al. 2020 ). In 2020, Fan’s research team introduced the concept of relative poverty into the research of regional sustainable development for the first time, and expanded the micro-sustainable livelihood model into a macro analysis framework of sustainable development in underdeveloped areas–relatively poor areas (Fan et al. 2020 ). From the regional poverty-causing factors, the poverty types were divided and the classified poverty alleviation strategies were discussed. Through 20 consecutive years of follow-up research, this paper reveals the changing process of poverty-relative poverty and explores the poverty alleviation effect and its impact on the natural ecological environment and social progress. According to scholars Li and He ( 2022 ), endogenous motivation is an important foundation for sustainable poverty alleviation, and incentive policies such as “replacing compensation with awards” and “welfare-to-work” should be adopted to promote the transformation of poverty alleviation mode from blood transfusion to hematopoiesis.

According to the cycle of poverty, the development of poverty-stricken areas and the growth of residents’ living standards are subject to the lack of capital, which is the fundamental cause of the vicious circle of poverty (Nurkse, 1957 ). However, a basic feature of underdeveloped areas is that the infrastructure is relatively backward and the production conditions are relatively poor. The welfare-to-work policy is that the state injects construction capital from the outside, provides local infrastructure construction, improves farming conditions, and provides job opportunities for local low-income groups (Xiao and Yan, 2023 ). Foreign scholars can define the welfare-to-work program as a public intervention measure to provide employment opportunities for poor families and individuals with relatively low wages. However, according to sustainable poverty alleviation, the welfare-to-work policy studied in this paper refers to a poverty alleviation policy in which the government invests in the construction of public infrastructure policy, and the recipients participate in the policy construction to obtain labor remuneration instead of direct relief. For low-income people, the welfare-to-work policy has dual value: one is to reduce poverty and vulnerability (Gehrke and Hartwig, 2018 ), and the other is to create public goods through the work done by participants. It can also contribute to a third value if the participants acquire new skills. In addition, the implementation of the welfare-to-work policy strengthens the poor groups’ resistance to external risks by promoting social cohesion and strengthening economic ties between groups (Beierl and Dodlova, 2022 ). On the other hand, based on the local resource endowment, the implementation of the welfare-to-work policy is suitable for the local environment and promotes the sustainable development of underdeveloped areas by improving infrastructure and promoting industrial development (Si, 2011 ). Therefore, this paper puts forward the following assumption:

H1: welfare-to-work policy actively promotes sustainable poverty alleviation.

The mediating effect of infrastructures

According to the analysis of the welfare-to-work policy above, it can be seen that the main methods to implement the welfare-to-work policy are to carry out infrastructure construction in the fields of transportation, water conservancy, energy, agriculture and rural areas, urban construction, ecological environment, and post-disaster recovery and reconstruction. Many scholars have paid attention to the economic growth effect of infrastructure. But to govern poverty, the government should emphasize infrastructure investment, especially agricultural infrastructure investment (Xie et al. 2018 ). Firstly, the construction and improvement of rural infrastructure have created employment opportunities for low-income groups. The more opportunities local farmers have to obtain secondary and tertiary industries, the stronger the employment income-increasing effect of local farmers will be (Gibson and Olivia, 2010 ). In addition, rural infrastructure directly and significantly improves agricultural production efficiency, increases agricultural production efficiency, and reduces agricultural production costs. Secondly, infrastructure interconnection catalyzes the “market scale effect” and improves the market potential of poor areas. The accessibility of infrastructure guarantees the expectation of investment income, leading to expanded investment in poverty-stricken areas and increased innovation support received by producers in poverty-stricken areas (Zhang et al. 2018 ). Thus, his paper puts forward the following assumptions:

H2a: welfare-to-work policy achieves sustainable poverty alleviation effect through infrastructure.

There are two opposite views on the effect of financial poverty alleviation in academic circles. Some scholars such as Skoufias and Di Maro ( 2008 ), Imai ( 2011 ), and Xie ( 2018 ) believe that special financial transfer payment is an effective fiscal policy tool to reduce income inequality and poverty. According to Ma et al. ( 2016 ) and Huang ( 2018 ), financial transfer payment stimulates economic growth in poverty-stricken areas, reduces the incidence of poverty, and promotes the equalization of regional basic public services and financial resources. In addition, it has good policy effects in improving human capital, preventing future poverty, and improving income distribution according to Liu and Qi ( 2019 ). However, other scholars believe that financial transfer payments is not effective in reducing poverty. Presbitero ( 2016 ) pointed out that the large-scale increase of public expenditure in low-income developing countries did not significantly promote economic growth, and Chen et al. ( 2018 ) used the data from China Family Panel Studies to think that financial transfer payment did not play a good role in reducing extreme multidimensional poverty. According to Musgrave’s ( 1959 ) definition of the financial function, public finance should play three basic functions: resource allocation, economic stability, and income distribution. Welfare-to-work policy mainly means that the government provides capital supply and sufficient human capital guarantee for economic development in backward areas by issuing special poverty alleviation funds from the central government. It creates development opportunities for low-income people, consolidates the foundation of individual income growth, and then enhances the ability to resist risk shocks. In addition, increasing the income of such income groups or reducing their expenditure obligations can improve the production and living conditions of poor people and strengthen their economic self-reliance. Therefore, this paper puts forward the following hypothesis:

H2b: welfare-to-work policy achieves sustainable poverty alleviation effect through fiscal intervention.

The analysis method of combining welfare economics with poverty lays a foundation for multidimensional relative poverty theory and empirical research. Amartya Sen’s sustainable livelihoods theory ( 2005 ), attributes individual endowment and welfare sources to the substantive freedom of acquisition. It emphasizes the superposition of external risk impact and internal risk resistance, which easily causes rural families out of poverty to suffer the impact of poverty again and the emergence of poverty vulnerability. All of these hinder poverty alleviation, sustainability, and common prosperity to a certain extent. Finance is an important external influencing factor for the comprehensive development of counties, and financial poverty alleviation mainly provides poor households with “two exemptions one subsidy” micro-credit funds for productive poverty alleviation, which can better meet the capital needs of poor households for industrial development. At the same time, poor households are usually required to have a supporting production and operation policy when obtaining poverty alleviation microfinance, which can ensure that credit funds are effectively used for production and operation to a certain extent. In the long run, it is conducive to improving the self-development ability of poor households (Weng et al. 2023 ). In addition, there is an obvious synergy between rural financial poverty alleviation and financial poverty alleviation measures. Rural finance can often play a greater role in poverty alleviation on the basis of financial poverty alleviation measures (Xia, 2023 ), which can drive economic and industrial development, and then have a significant effect on poverty alleviation (Liu and Liu, 2020 ). Therefore, this paper defines financial instruments as financial measures to accelerate production by improving the ability of beneficiary individuals to resist risks and promoting the flow of local production factors. In the practice of the welfare-to-work policy, the implementation area is weak in resisting risk shocks, while the local people’s savings level can effectively improve the level of resisting risk shocks. On the other hand, because of welfare-to-work projects’ characteristics of long construction periods and poor capital demand, the transmission mechanism of monetary policy is used to better match the scale and structure of bank deposits and loans. By doing so, the circulation of production factors such as manpower, capital, and materials in underdeveloped areas can be accelerated, thus realizing the comprehensive effects of expanding effective investment, driving employment, and promoting consumption. In addition, financial institutions are guided to increase financing support, attract private capital to participate, and form a more physical workload. Therefore, the research hypothesis is as follows:

H2c: welfare-to-work policy achieves sustainable poverty alleviation through financial instruments.

Currently, there are abundant studies on sustainable poverty reduction and policy assessment in academic circles, which provide good theoretical support and research perspective for this paper. But there are still several limitations: first, the current types of policy in poverty reduction mainly focus on the combination type or emphasis on the impact of poverty reduction policies implemented in a certain district, but there is room for research in the performance evaluation of a single welfare-to-work poverty reduction policy. Second, prior studies on quantifying their poverty reduction performance and action mechanism of the welfare-to-work policy by combining the policy with regional sustainable poverty reduction effects are relatively limited. Therefore, the theoretical analysis of this article is based on the theory of “welfare-to-work” and relative poverty. It summarizes the causes of relative poverty in underdeveloped areas, and on this basis, combines the characteristics of welfare-to-work to construct the theoretical analysis of poverty alleviation with welfare-to-work policy. As shown in Fig. 1 , firstly, according to the poverty cycle theory (Nurkse, 1957 ), the lack of capital formation and the contradiction between supply and demand in underdeveloped areas lead to low income and persistent poverty in underdeveloped areas. Secondly, according to the human capital theory (Schultz, 1949 ), human capital is the main factor of national economic growth. The loss of human capital caused by the difficulty of regional development has seriously affected the growth of the local national economy. In order to break this vicious circle, according to the capability approach (Amartya Sen, 2005 ), if a region wants to get rid of poverty and become rich, it must have the natural, economic, and social conditions to support its sustainable development. The welfare-to-work policy is the government’s financial investment in infrastructure to attract local people to work nearby. It is implemented in the form of government public investment to provide more employment opportunities for local people, and thus increases the opportunity cost of labor. On the other hand, stimulated by the market economy, the local labor force can have the opportunity to transfer from agricultural production to infrastructure construction conditionally, which improves the marginal income of the labor force. Firstly, they obtain skills training and increased stock of human capital; Secondly, they obtain broader horizons and more external economic information. In addition, according to development economics, the main constraint force to poverty alleviation comes from capital accumulation in which finance plays an important role. Through the intermediary function, finance can integrate social idle funds to realize the transformation from savings to investment, and promote poverty alleviation and economic growth at a higher level of equilibrium by improving the rate of capital accumulation.

Logical analysis of the impact of Welfare-to-work policy on poverty reduction.

There are several potential contributions in this paper: firstly, the difference with other articles lies in the different research perspectives. Relative poverty will exist for a long time in a certain historical period, in specific areas, and in specific conditions. These characteristics of relative poverty are the key factors that constrain the objectives, contents, and methods of poverty governance. Therefore, sustainable development is introduced into the welfare-to-work policy to alleviate relative poverty and strengthen the sustainable poverty alleviation effect of the policy. On the other hand, it lies in the comprehensiveness of the research subject. According to the 2030 Agenda for Sustainable Development promulgated by the United Nations, the sustainable development of poverty-stricken areas should also require people’s equal rights to access economic resources and inclusive and sustainable economic growth of the region. However, the relevant research on sustainable poverty alleviation directly or indirectly revolves around endogenous motivation stimulation and external resource assistance, and rarely analyzes and integrates these two themes within a unified framework (Ma et al. 2023 ). Therefore, this article takes individual and regional sustainable development as the main body, and takes the concept of sustainable development and the welfare-to-work policy as the donor, promoting the realization of sustainable governance of welfare-to-work policy in relatively poor areas. The third is to quantify the mechanism of action, because the policy will be affected by the local objective environment and show different effects in the implementation process as the regional scope of China’s welfare-to-work policy covering the central and western parts of China. This article adopts Shapley value to quantify the contribution of the action mechanism to poverty alleviation in different regions, and then provides policy reference for local governments to consolidate their poverty alleviation achievements and solve relative poverty problems.

Research design

Model construction.

The National Administrative Measures for welfare-to-work policy (2005) was first formulated by the Chinese government with the aims of standardizing and strengthening the management of the welfare-to-work policy and improving the use efficiency of welfare-to-work funds so as to improve the production and living conditions and development environment of impoverished rural areas, and to help poor residents get rid of poverty and become rich Footnote 2 . Then, it was implemented in specific regions in 2006, and subsequently amended twice and respectively, named the National Administrative Measures for welfare-to-work policy (2014) and the National Administrative Measures for welfare-to-work Policy (2023), but the starting points are to give full play to the role of welfare-to-work policy in poverty reduction.

Therefore, the author regards the welfare-to-work program as a quasi-natural experiment and takes 2006 as the processing point of welfare-to-work policy evaluation. The year before 2006 refers to before the policy implementation, which was denoted as time = 0; and the year after 2006 refers to after the policy implementation, which was denoted as time = 1. In addition, considering that the implementation areas of three revisions of the welfare-to-work policy are mainly less developed areas and ensure continuity of policy implementation, the regions that have been implementing the welfare-to-work policy since 2006 were selected as the treatment group whose dummy variable was set as treat = 1; and to ensure the net effect of the implementation of the welfare-to-work policy every year, the samples added to the implementation after 2006 were deleted, and the remaining regions without conducting the implementation of the welfare-to-work policy were defined as the control group whose dummy variable was set as treat = 0.

Drawing on the modeling practice of Yao et al. ( 2023 ), the author conducted tests on the net effect of the welfare-to-work policy on poverty reduction by studying the increment over time and non-time-varying heterogeneity among individuals through DID elimination. The model settings are as follows:

Where the explained variable is the county multidimensional development index (CMDI), the core explanatory variable is the welfare-to-work policy interaction term (did = treat × time), \({\beta }_{1}\) represents the net effect of welfare-to-work policy on poverty reduction; \({{\rm{\nu }}}_{{\rm{i}}}\) indicates individual fixed effects, which control the individual factors that affect CMDI but do not change with time; \({{\rm{\tau }}}_{{\rm{t}}}\) denotes the period effect, which controls the time factors that affect all individuals over time; and \({\varepsilon }_{{it}}\) indicates the error term.

As the selection of the implementation area of the welfare-to-work policy is subject to national regulation and coupled with imperceptible factors, to avoid selectivity bias and endogenous problems and ensure the robustness of results, the PSM-DID method was employed to conduct a robustness test, and the following model was constructed. The variables are defined as Eq. ( 2 ):

Dynamic effect model

Besides, to test the dynamic effect of the welfare-to-work policy on poverty reduction, on the basis of Eq. ( 1 ), a dynamic effect model was constructed as follows:

In the model, \({{\rm{treat}}}_{i,t}\,\times\,{{\rm{time}}}_{i,t}\) represents the dummy variable of the dynamic poverty reduction effect of the welfare-to-work policy. When the welfare-to-work policy is set at period t, its value is 1.

Test model of action mechanism

To further investigate the impact of the welfare-to-work policy on poverty reduction, the author took the modeling ideas of scholars Li and Zhang ( 2021 ) as a reference to interact with the independent variable did, so as to test the differences in sustainable poverty reduction in counties with different levels. The specific model settings are as follows:

Where M is the variable of the action mechanism, which is considered from infrastructure construction, government finance and financial poverty reduction. \({Y}_{{it}}\) is the explained variable, representing the relative poverty parameter of the county (CMDI) and a series of outcome variables about the multidimensional development of the county; \({\beta }_{1}\) represents the influence of the welfare-to-work policy on the dependent variable \({Y}_{{it}}\) through the action mechanism variables, while \({\beta }_{1}\) is significantly positive, the incentive variable \({Y}_{{it}}\) through the action mechanism variable M , M is the mechanism variable of the welfare-to-work policy; other parameters have the same meaning and benchmark model parameters.

Variable selection

Explained variable: cmdi.

The academic research on regional multi-dimensional relative poverty index systems mostly draws on the theory of man-land relationships and sustainable livelihood theory. British international development institutions based on a multidimensional perspective established a sustainable livelihood model, from the economic, natural, human, material, and social five aspects of comprehensive indicators, and the Chinese Social Science Research Institute of sustainable development strategy group combined with domestic actual situation, established to involve “government regulation, social development, scientific and technological innovation, human resources, survival, safety and environmental protection” and so on six big ability as the core of sustainable ability analysis framework.

Based on the research of the sustainable livelihood model by scholars Zhou et al. ( 2020 ) and Xu et al. ( 2021 ), this article builds a bridge between micro-main economic activities and regional high-quality development, draws lessons from the poverty alleviation requirements and tasks specified in the relevant policy documents of Welfare-to-work, and follows the principles of data availability, dynamics, and relevance.

As shown in Fig. 2 , “opinions on actively promoting welfare-to-work in the field of rural infrastructure construction” emphasizes that giving full play to the multiple functions of welfare-to-work policy, such as employment, disaster relief, investment, and income, it is combined with making up the shortcomings of infrastructure in the fields of agriculture, rural areas, and farmers to consolidate the construction of agricultural production capacity (Lan, 2021 ). Drawing lessons from the research of Liu and Zhao ( 2015 ) and Yang et al. ( 2023 ), the output efficiency of agricultural land is used to measure the agricultural production efficiency, that is, the output of crops per unit area is used. The ratio of rural employment number to the total population under the county is used to measure rural employment opportunities. The logarithmic value of Real GDP per capita (ln PGDP) is used to measure the level of county economic development the logarithmic value of rural per capita disposable income is used to measure the county living standard, and the ratio of fixed assets investment to GDP is used to to measure the level of fixed investment.

Framework of indicators for CMDI.

The identification of multidimensional relative poverty depends on CMDI. This article mainly draws lessons from the calculation ideas of Xu et al. ( 2021 ), and makes improvements on this basis. Specific calculation methods are as follows: firstly, the calculation idea is as follows: the entropy weight method is used to calculate the index weights of each dimension, and the scores of each dimension are calculated on this basis. Then, the polygon area method is used to calculate the CMDI. The reason why the area method is chosen instead of the simple weighting method is that the pentagon constitutes a stable structure and develops in a balanced way, and the five livelihood capitals influence each other, which can not only characterize the multi-dimensional relative poverty degree of the county, but also characterize its sustainability and anti-risk degree. The calculation formula is as follows:

Assuming that the scores of county i in five dimensions are a , b , c , d , and e respectively, and the angle between any two dimensions is α (α = 360°/5).

In addition, in order to avoid the difference of area caused by different sorting methods of five dimensions, the final algorithm is to calculate the average of various possible results. The larger the development index, the higher the comprehensive development potential of the county, the stronger its sustainability and anti-risk ability, and the lower the multidimensional relative poverty level. On the contrary, the higher the degree.

Control variables

In addition to the impact of the welfare-to-work policy on the sustainable development of the county, there are other influencing factors. Therefore, to eliminate interference, these exogenous factors need to be controlled. Drawing on the research ideas of Zhang et al. ( 2019 ), this paper selected the following control variables: the county-level population density was employed to control the impact of economic agglomeration on its economic development; the logarithm of the total output value of large-scale industry was employed to reflect the industrial scale level, and the social consumption level was measured by the total retail sales/total population of household registration; the ratio of the number of rural households to the total number of households in the county was selected to measure the urban-rural structure; and local telephone users were chosen to evaluate the level of regional information, and the ratio of the number of students in primary and secondary schools to the total population was used for the measurement of the educational level of the county.

Data description

The data used in this paper were sourced from the county-level Statistical Yearbook and China Regional Database. The data from 2000 to 2019 at the county (city) level in China were collected, and the counties with incomplete main variables were screened and processed, including 1687 county-level units, among which 456 counties with the implementation of welfare-to-work policy were set as the treatment group. In addition, due to the gap between the development of the eastern and western parts of China, the economically developed areas of the eastern coastal area were excluded from the control group, and the 1231 counties failing to implement the welfare-to-work policy were set as the control group. Other data come from the Statistical Yearbooks and statistical announcements of counties (districts) and cities across the country, and the data that cannot be obtained by each county (district) and city were supplemented by searching for the government data of the corresponding distract. To reduce the impact of heteroscedasticity on the results, all variables were processed by CPI index (with 2020 as the base period) and conducted logarithmic processing. The descriptive statistics of variables are shown in Table 2 .

Analysis of empirical results

Benchmark regression analysis.

The benchmark results are shown in Table 3 . The control variables were not included in column (1), resulting in a significantly positive estimated coefficient of poverty reduction through welfare-to-work policy; and the control variables were introduced in column (2) with a result of a still significantly positive coefficient, indicating that welfare-to-work policy significantly promoted the comprehensive development and alleviated the relative poverty level of counties. Different from the previous two columns, both the individual fixed effect and the year fixed effect were controlled in column (3), as a result, the poverty reduction effect of the welfare-to-work policy was still significant.

On this basis, the effectiveness of the welfare-to-work policy on poverty reduction will be further studied to analyze poverty reduction performance in various aspects in detail. The results are shown in Table 4 .

The results from columns (1–5) show that: with the implementation of the welfare-to-work policy, the GDP per capita of counties has significantly increased by 11.1%, the disposable income of rural residents by 1.3%, the level of fixed asset investment by 14.0%, the quality of cultivated land by 73.7%, and the rural employment opportunities by 0.7%. These growth data indicate that the welfare-to-work policy not only can significantly promote development and effectively alleviate the relative poverty of the counties, but also can achieve remarkable results in “stabilizing employment and ensuring income to boost the economy”, especially in the quality of cultivated land. However, although the policy plays a significant role in providing rural employment opportunities, the coefficient is the smallest. According to the relevant literature on China’s welfare-to-work and foreign welfare work policies, the author finds that welfare-to-work emphasizes the employment promotion mechanism in poverty alleviation, which is essentially consistent with the work-for-welfare concept of “work” for “welfare”, but welfare-to-work emphasizes disaster relief and regional economic development, combines government investment with public demand, and the government focuses on agricultural production development and rural infrastructure investment and construction. The implementation area is mainly concentrated in underdeveloped areas to improve the local development environment, improve the living standards of local residents, and increase the output of land by increasing investment to improve production conditions (Xiao and Yan, 2023 ). In addition, the implementation of the Welfare-to-work policy is mainly supported by the government’s financial and monetary support, while the relevant relief policies affect economic development through various transmission mechanisms, and then affect the employment problem. The policy transmission chain is too long, and employment is at the end of policy transmission, which is only a by-product of the strategy of promoting growth, and the efficiency is bound to be deficient (Tcherneva, 2014 ). Therefore, the Welfare-to-work policy has the weakest impact on employment and a greater impact on the quality of cultivated lands.

Robustness test

Parallel trend test and dynamic effect test.

By conducting parallel trend tests, the author can accurately evaluate the net effect of the welfare-to-work policy on poverty reduction by using the DID method. The condition for passing the test was that before the implementation of the welfare-to-work policy, the coefficients of the treatment group and the control group showed a parallel trend on the whole.

As shown in Fig. 3 , there is a same change trend between the treatment group and the control group before the implementation of the welfare-to-work policy, but there was a difference after the policy implementation. Especially after the policy implementation, the annual differentiation increased significantly, indicating that the economic status of the treatment group is significantly better than that of the control group, which provides evidence for the effectiveness of the policy.

Parallel trend of poverty reduction between the treatment group and the control group.

Equation ( 3 ) was employed to test the dynamic effect of welfare-to-work policy on poverty reduction, and the results are shown in Table 5 .

When other variables are controlled, the coefficient of interaction term in 2006 is 0.0063, which shows a significantly positive trend, and there is no hysteresis effect. When the policy time point moves backward year by year, the coefficient of the interaction term is significantly positive and constantly increasing, indicating that the welfare-to-work policy has a sustainable poverty reduction effect.

Placebo test

To ensure the robustness of the regression results, the author refers to the ideas of scholars Qian and Ma ( 2022 ) and adopts a “counterfactual” method. Two hundred fifty counties in all regions were randomly selected as policy implementation areas, and other regions were regarded as control groups. To avoid the influence of interaction terms on the explained variable CMDI, random sampling was set to 200 and 500 times, respectively, and the estimated coefficients of 200 and 500 interaction terms DID could be obtained, respectively.

As shown in Figs. 4 and 5 , the results obtained from the two random sampling show that most of the coefficients and values t are concentrated around 0 and follow a normal distribution. The mean value is far from the true value, and most of the estimated coefficients are not significant, indicating that other unobserved factors have no impact on the poverty reduction effect of the welfare-to-work policy, which is in line with the expectation of the placebo test.

The placebo test-sampling 200 times.

The placebo test-sampling 500 times.

Replacement of evaluation method (PSM-DID method)

First, the propensity score PS values of all samples were estimated, and then the samples with similar PS values to the treatment group were selected. That is, under the constraints of characteristic variables such as urban–rural structure, educational, medical level, and government fiscal intervention degree, the Logit model was utilized to estimate the predicted probability P(Xi) identified as implementing the welfare-to-work policy. Then the nearest neighbor matching, radius matching, and kernel matching methods were used to match the samples of the treatment group with the control group, respectively, and the control group samples with the most similar comprehensive characteristics were employed as the control group. The results are shown in Table 6 . After matching, the mean value of each covariate is not significantly different from 0 in the control group and the treatment group, which satisfies the equilibrium hypothesis test.

Then, the net effect of the welfare-to-work policy on poverty reduction was tested based on the DID method. The regression results are shown in Table 6 . Compared with the benchmark results, the three matching methods are basically consistent in terms of the estimated coefficient, symbol, and significance level, which confirms the robustness of the conclusions in this paper.

Replacement of the measuring method of the explained variable

In this paper, the CMDI which was constructed on the basis of a sustainable livelihood model was used to measure the county multidimensional poverty degree, while the academic community often adopts the A–F double critical value method and FGT method to measure the regional multidimensional poverty degree. Therefore, to ensure the robustness of the results, the author replaced the current measurement method with the A–F double critical value method and FGT method, respectively to test the robustness of the explained variable—relative poverty degree in counties.

The results are shown in Table 7 . The estimated coefficients obtained from the A–F double critical value method and FGT method are 0.01 and 0.009, respectively, with significance at the 1% level. Compared with the result of benchmark regression, the coefficients are slightly lower but still play a positive incentive role, which confirms the robustness of the benchmark regression result.

Heterogeneity analysis

County-level heterogeneity.

To explore the heterogeneity in the effect of poverty alleviation policies in the counties with different development levels, the quantile diff-in-diff method was adopted for analysis. Compared with the OLS method, the overall picture showing the conditional distribution of explained variables was more comprehensive and the outliers were more robust.

The results are shown in Table 8 . The DID coefficients of the interaction term of CMDI at 10%, 30%, 50%, 70%, and 90% quantiles were all significantly positive at the 1% level, with the highest coefficient at 90% quantile and the lowest coefficient at 10% quantile. The results indicate that there is heterogeneity in the effect of poverty alleviation policies in the regions with different sustainable development levels, and the higher the development level, the stronger the driving effect. Therefore, enormous efforts should be made in the implementation of the welfare-to-work policy. The government should take proactive moves to accelerate the construction of infrastructure in areas with low development potential, and make full use of financial tools to drive the flow of production factors. Besides, the government should encourage the cultivation of industries with local features according to local conditions to improve the regional sustainable development level and boost the county economic development, so as to prevent the large-scale poverty-return phenomenon and effectively consolidate the achievements of regional poverty alleviation.

Regional heterogeneity

With the economic development, there are obvious differences in China’s regional development due to geographical location, infrastructure, public services, economic foundation, and other factors. The absolute majority of the people who are lifted out of poverty are located in rural areas in the central and western inland provinces. It is necessary to conduct a regional heterogeneity analysis on the basic regression results. Therefore, the sample size was divided into the central, northwest, and southwest regions, and Eq. ( 1 ) was employed to carry out studies on the effect of the poverty alleviation policies in each region.

The results are shown in Table 9 . The estimated parameter of the poverty reduction effect of the welfare-to-work policy in the central region and northwest region is 0.172 and 0.157, respectively, with significance at the 1% level, while the estimated parameter of the southwest region is 0.035 with no obvious significance. The results indicate that the welfare-to-work policy has a significant effect on poverty reduction only in the central region and the northwest region, but not in the southwest region, with a higher effect in the central region followed by the northwest region. According to the relevant poverty alleviation policies implemented in China since 2005, the paper finds that a large amount of poverty alleviation resources have been invested in the central and western regions, while the central region has a higher level of development in its enterprises, a significant improvement in income level and a better driving effect of social participation compared with the western region. In addition, since the reform and opening up, although the poverty-stricken areas in the west have also developed to some extent, the gap between the eastern and central regions is widening, and the distribution of poor people is further concentrated in the western region according to Liu and Ye ( 2013 ). Moreover, the counties in the southwest region are mostly hilly counties and ethnic counties, which will significantly weaken the positive impact of the national poverty-stricken county policy on county poverty and the income gap between urban and rural (Guan et al. 2023 ). In addition, this is consistent with the conclusion of county heterogeneity mentioned above, and the sustainable poverty reduction effect of cash-for-work policy in areas with weak development degrees is weaker than that with higher development station levels. Therefore, the effect of the welfare-to-work policy in the southwest region is weaker than in other regions.

Test of action mechanism

Test of action mechanism of welfare-to-work policy on poverty reduction.

According to existing literature research, infrastructure is the main impact mechanism of policy poverty reduction, and government finance is the material guarantee for the smooth implementation of the welfare-to-work policy, which has an important impact on the poverty reduction effect of the welfare-to-work policy. In addition, financial poverty alleviation cultivates the mechanism of hematopoietic and promotes financial marketization in rural areas (Wang et al. 2021 ). With reference to the specific methods of employment assistance, the welfare-to-work program provides preferential policies such as social insurance subsidies, tax incentives, and small guaranteed loans to enterprises that recruit poor laborers to participate in project construction or provide basic jobs, so as to reduce the production cost of enterprises, thus promoting a virtuous cycle of social and economic development (Qin, 2022 ). Therefore, the action mechanism variables of infrastructure construction level, government fiscal intervention, and financial tools were added to the model to conduct a test via Eq. ( 4 ).

First, infrastructure construction is the main way to implement the welfare-to-work policy. Through the opinions on actively promoting welfare-to-work in the field of agricultural and rural infrastructure construction, the NDRC and other nine ministries and commissions emphasize that the main areas for the implementation of the welfare-to-work policy should be strengthened in the field of agricultural and rural infrastructure. Through infrastructure construction, the development environment of agriculture and rural areas will be improved, on the other hand, the effect of increasing employment income will be promoted. Referring to Qiu et al. ( 2021 ), this paper selects the logarithmic output value of capital construction to express the level of infrastructure construction. Second, the measures for the management of welfare-to-work emphasize that government investment in infrastructure construction, that is, government finance, is the material guarantee for the implementation of the welfare-to-work policy, which has an important impact on the poverty alleviation effect. More investment benefits will be achieved when government investment is closely combined with public demand, the role of beneficiaries is brought into full play in the construction of investment policy, and the active participation of beneficiaries is actively promoted (Ma, 2023 ). Referring to Zhang et al. ( 2019 ), this paper uses the logarithmic value of general expenditure of the public budget to express the degree of government financial intervention. Third, savings and credit are effective ways to significantly increase risk resistance and reduce household vulnerability to poverty (Urrea and Maldonado, 2011 ). With reference to the specific methods of employment assistance, the welfare-to-work policy gives preferential policies such as social insurance subsidies, tax incentives, and small secured loans to enterprises that recruit poor laborers to participate in engineering construction or provide basic jobs, so as to reduce the production costs of enterprises and promote a virtuous circle of social and economic development (Qin, 2022 ). Referring to Zhang et al. ( 2019 ), this paper uses the logarithm of the loan balance of financial institutions at the end of the year to represent the loan level as an indicator that directly reflects the use level of financial instruments; The balance of urban and rural residents’ savings deposits/total resident population is selected to indicate the local savings level and reflect the local indicators to resist the impact of external risks.

The results are shown in Table 10a–d : (1) the coefficient of the interaction term of infrastructure construction level is significantly positive, indicating that the county-level poverty reduction has gotten a greater degree with the improved infrastructure investment level. With the construction of infrastructure, the welfare-to-work program focuses on infrastructure fields such as “mountains, forests, paddy fields, roads, grass, and sand”, as well as, on infrastructure projects related to rural life and production. The welfare-to-work policy stimulated the development of a non-agricultural economy in impoverished areas and promoted the transformation and upgrading of employment structure to a diversified and high-value level, thus optimizing the spatial layout of infrastructure and improving the efficiency of resource allocation and giving play to the poverty reduction effect of infrastructure (Lin and Lin, 2022 ). On this basis, the author separately conducted an analysis of the target indicators of the welfare-to-work policy. The results show that except for insignificant improvement in labor efficiency, the level of infrastructure construction has played a significantly positive role in the rest of the aspects. The welfare-to-work policy has a significant impact on “boosting economic growth”, “ensuring income” and “maintaining employment stability” through the level of infrastructure construction. (2) Government financial intervention plays a significant role in the poverty reduction effect of the welfare-to-work policy. In other words, the government can effectively improve the degree of poverty reduction in the local region by increasing government financial expenditure on the welfare-to-work program. However, specifically, the government fiscal expenditure can effectively increase the per capital disposable income and fixed asset investment level of local rural people, but inhibit the development of the local economy. The possible reason lies in that the government fiscal expenditure will directly affect the increase of the local GDP. (3) The utilization of financial tools can effectively promote the poverty reduction degree of welfare-to-work policy, especially can significantly boost the local economic growth and income growth of rural residents.

Regional heterogeneity test of action mechanism

To further verify the impact of the welfare-to-work policy on poverty reduction through mechanism variables in different regions, according to the particularity of policy implementation and sample limitations, the samples were divided into three sub-samples in northwest, southwest, and central regions for regional heterogeneity test.

The results are shown in Table 11 . In the northwest and southwest regions, the three action mechanisms of infrastructure construction, government fiscal intervention, and financial tools play a significant role in the impact of the county poverty reduction degree, but there is heterogeneity among regions. Specifically, the financial tools play a positive role in poverty reduction in the northwest region but caused a significantly inhibited effect in the southwest, while the test was invalid in the central region. With regard to the heterogeneity of financial instruments among regions, the author researches the relevant theories and literature, and finds that the mitigation effect of finance on rural poverty is unbalanced among regions. However, due to the imbalance of resource endowments and economic development in central and western China, there is a gap in the level of financial development in different regions, leading to different effects of poverty alleviation (Zeng and Hu, 2023 ). Thus, the effect of financial poverty alleviation is also affected by the regional relative poverty level. When the income gap between urban and rural areas is large, the relative poverty level is high, and the downward trend is gentle, the poverty alleviation effect is more significant. The relative poverty level in the western region is higher than that in the central region, so the poverty alleviation effect in the central region is weaker than that in the western region. In addition, economically backward areas have less financial support for finance, imperfect financial infrastructure construction, and unbalanced allocation of financial resources, which restrict the availability of financial services for economic entities in economically backward areas. The shortage of financial service supply often forms a “crowding out effect” on rural low-income groups, while the development level of Southwest China is lower than that of Northwest China (Gong and Chen, 2018 ). The availability of financial services in southwest China is weak, which forms service barriers and inhibits the integration of funds.

Analysis of the contribution of the action mechanism variables

The above tests proved that the welfare-to-work policy has an impact on county-level poverty reduction performance through the infrastructure level, government fiscal intervention, and financial tools. However, there is a heterogeneity in the poverty reduction effect between regions. In order to better combine their own advantages in local counties, timely regulate the infrastructure construction, policy and financial intervention, and financial tools, so as to achieve the sustainability of poverty reduction in counties. With reference to the research of Fu and Tang ( 2022 ), the author adopted the Shapley value decomposition method to figure out the contribution degree of action mechanism variables to the county-level poverty reduction performance in different regions. The principle is to average the marginal effect of a factor by calculating the possible results of all combinations and all other factors, and then obtain the marginal contribution of the factor.

In accordance with Table 12 , the estimation results provide a good explanation of the impact of each variable on county poverty reduction. On the whole, among the three major action mechanism variables, infrastructure construction contributes the most with ratios of 58.31%, 51.96%, and 57.33% to the county economic development, the income and the employment opportunities of rural residents, respectively, and it occupies the second place in fixed asset investment, reaching 44.22%, but makes a most minor contribution to the cultivated land quality, only reaching 2.58%. The government financial intervention contributed the most to the fixed asset investment and cultivated land quality with ratios of 45.29% and 66.23%, respectively, the second to the employment opportunities reaching 23.57%, while the least to the county economic development and the rural residents’ income with ratios of 1.71% and 1.05%, respectively. Financial tools take the second place in contribution with ratios of 39.98%, 47.00%, and 2.19% to the county economic development, the rural residents’ income, and the cultivated land quality, but make the least contribution to fixed asset investment and employment opportunities, only reaching 10.49% and 19.10%.

Specifically, in southwest China, infrastructure construction makes the most significant contribution to the promotion of the county economic development, the rural residents’ income and fixed asset investment, fiscal intervention, and financial tools play a decisive role in improving the cultivated land quality with the contribution rate reaching over 40%, and financial tools have a contribution ratio of 68.13% to employment opportunities. In northwest China, infrastructure construction makes the highest contribution to the promotion of county economic development and rural residents’ income, both reaching over 60%; infrastructure construction and fiscal intervention contributed the most in terms of fixed asset investment with ratios of 37.06% and 48.75%, respectively, accounting for more than 85% of the contribution; financial tools make the highest contribution to improving the cultivated land quality, reaching 67.58%, and both the government fiscal intervention and financial tools make the contribution of over 40% to employment opportunities. In central China, infrastructure construction contributes the most to the promotion of the county economic development, rural residents’ income and fixed asset investment, financial tools play the highest role in improving the cultivated land quality, and the government fiscal intervention and financial tools make the contribution of 36.97% and 43.99% to employment opportunities, respectively.

Conclusions and policy suggestions

Conclusions.

The purpose of this study is to assess the effectiveness of cash-for-work policies in reducing poverty and to provide insights on how to improve these policies in the future. On the basis of combining the evolution of the cash-for-work policy, the impact of the welfare-to-work policy on poverty reduction is empirically analyzed by using the DID method. The basic regression results show that the sustainable poverty alleviation effect of the welfare-to-work policy reaches 16.1%, which shows that the welfare-to-work policy significantly promotes the sustainable poverty alleviation effect in county areas. which was mainly reflected in the sustainable poverty reduction effect of regional economic development and the endogenous driving force of people’s livelihood income increase and prosperity, which showed that the poverty reduction effect of the welfare-to-work policy was significant, promoted the accumulation of social capital, effectively increased the development opportunities of the local people, and improved the endogenous motivation of the local people. Furthermore, the heterogeneity of the sustainable poverty reduction effect of the cash-for-work policy verifies the heterogeneity in different regions and different levels of development, and confirms that the strength of the development level in the three regions is consistent in China. From the perspective of mechanism, the cash-for-work policy has promoted the sustainable development capacity of counties and alleviated the relative poverty level of counties through a series of measures such as infrastructure construction, fiscal intervention, and financial instruments. However, due to the differences in resource endowment and development levels among different regions, the effect of different mechanisms on the sustainable poverty reduction of cash-for-work policies is inconsistent in different regions. Among them, the impact of infrastructure construction on county-level sustainable poverty alleviation is the largest, and the impact of financial instruments on county-level sustainable poverty reduction is promoted in the northwest region, but significantly inhibited in the southwest region, while the poverty reduction effect is not significant in the central region.

The main finding of this study is that t the welfare-to-work policy for poverty reduction has achieved great results in regional economic development and people’s livelihood income increase. However, a number of challenges and constraints still need to be addressed to ensure the sustainability of poverty reduction efforts.

Policy suggestions

Based on the above analysis, this paper puts forward the following suggestions for improving the sustainable poverty reduction of cash-for-work policies:

First, sustainable poverty reduction should be achieved through the use of active and differentiated cash-for-work policies. Cash-for-work policy support cannot be simply implemented in all regions, but should be based on its own unique geographical environment and resource advantages, increase the construction of infrastructure suitable for itself, adapt measures to local conditions, develop characteristic industries, realize the upgrading of regional economic quality and efficiency, and focus on employment opportunities for the local people, actively help the local people to broaden the channels for nearby employment and income, and strengthen the self-survival and development ability of local groups.

Second, the government needs to further increase the construction of financial services in the southwest and central regions, further, enhance the internal function and effect of financial services, attract social forces to actively participate in the construction of rural infrastructure region, and give full play to the multiplier effect of the combination of financial services and infrastructure construction to achieve long-term sustainable poverty reduction. Accordingly, in the central region, the government should step up efforts in financial intervention, and all parties should reasonably adjust the critical point of infrastructure construction to improve supply efficiency and poverty reduction efficiency, in the northwest region, the government should focus on taking advantage of financial tools to create good business tools; and in the southwest region, the government should adjust the use pattern of financial tools to promote local high-quality development.

Third, focusing on the specific situation of deeply impoverished areas and special poverty groups, we will increase government financial investment in poverty alleviation, and strive to improve the effectiveness of sustainable poverty reduction. On the one hand, we should give preference to project approval and resource allocation, and improve the allocation of public financial resources to underdeveloped areas and low-income groups from the macro, and micro levels, so as to improve the efficiency of supply and poverty reduction. In addition, the quantitative conclusion of the mechanism of action shows that fiscal intervention has played a positive incentive role, but the effect is not large, especially in indirectly promoting regional economic growth and individual development, so we should pay attention to guiding the supplementary and regulating role of the third distribution on redistribution, and at the same time support the development of industries that meet the needs of poor areas to improve people’s livelihood and well-being.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

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Lan, F., Xu, W., Sun, W. et al. From poverty to prosperity: assessing of sustainable poverty reduction effect of “welfare-to-work” in Chinese counties. Humanit Soc Sci Commun 11 , 758 (2024). https://doi.org/10.1057/s41599-024-03267-z

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Defining the characteristics of poverty and their implications for poverty analysis

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Literature on the characteristics or underlying qualities of the concept of poverty is extensive but fragmented and rarely discusses the influence of these characteristics on poverty analysis. This paper examines the characteristics of poverty and their implications for poverty analysis. It primarily made use of secondary data together with some primary data. Findings are that poverty characteristically has a language and is multidimensional, complex, individual- or context-specific and absolute or relative. The characteristics of poverty have significant implications for, and should therefore be taken into consideration in, poverty analysis. The language of poverty reveals the dimensions and severity of poverty faced by a given community. It also enables poverty analysts to uphold the dignity of people and minimise misconceptions about poverty in a society. Lastly, the language of poverty provides an understanding of the context-sensitive meaning of poverty. The multidimensional and complex nature of poverty guides in the selection of an appropriate poverty worldview for analysing poverty. Moreover, the individual- and context-specific characteristic of poverty reflects the variation in the nature and severity of poverty according to age, gender and context. Knowledge about the absolute or relative nature of poverty, furthermore, is essential for poverty classification. The findings of this paper could allow for a more holistic or effective analysis of poverty, which may contribute to policy building.

• multidimensional
• poverty analysis

PUBLIC INTEREST STATEMENT

World governments and their development partners are working towards achieving the Sustainable Development Goal 1, which calls for the elimination of all forms of poverty in the world. Success in achieving this goal depends on, among other factors, the effective analysis of poverty, which is only possible if one has a clear understanding of the influence of the characteristics of poverty on poverty analysis. However, literature on the characteristics of poverty is fragmented and rarely sheds light on the relationship between the characteristics and analysis of poverty. This article, therefore, pieces together literature on the characteristics of poverty and examines their implications for poverty analysis. Thus, the article provides invaluable insights into the characteristics of poverty and their influence on poverty analysis.

Poverty “is one of the defining challenges of the 21st Century facing the world” (Gweshengwe et al., Citation 2020 , p. 1). In 2019, about 1.3 billion people in 101 countries were living in poverty (United Nations Development Programme and Oxford Poverty and Human Development Initiative, Citation 2019 ). For this reason, the 2030 Global Agenda for Sustainable Development Goals has called for the elimination of all forms of poverty everywhere in the world (Koehler, Citation 2017 ). Success in making a dent in global poverty depends on, among other factors, the effective analysis of poverty, which is only possible if one has an unambiguous understanding of the influence of the characteristics of poverty on poverty analysis. In this paper, the characteristics of poverty are taken to mean the underlying qualities of poverty as a concept. Scholarly work on such characteristics of poverty is extensive but fragmented and rarely sheds light on the relationship between the characteristics and analysis of poverty. This paper, therefore, examines the characteristics of poverty and their implication for poverty analysis.

This paper is significant in that it pieces together fragmented literature on the characteristics of poverty. In so doing, it provides a more holistic picture of the characteristics of poverty. In addition, the paper offers an analysis of the influence that these characteristics have on poverty analysis. The paper therefore enhances poverty analysis, which should ultimately improve the efficacy of poverty eradication efforts.

The paper mainly made use of secondary data together with some primary data. Secondary data were collected from two main sources: textbooks and journal articles that focus on the characteristics and analysis of poverty. In the selection of these sources, the following themes were used as criteria: poverty language, multidimensionality and complexity of poverty, poverty as individual and context-specific, absolute poverty and relative poverty. Poverty characteristics were derived from these themes. Analysis, therefore, focused on what the themes mean and how they influence poverty analysis. Primary data were extracted from a Poverty Class at Great Zimbabwe University. The data collected were on poverty terminologies used by the Shona-speaking community in Zimbabwe.

Poverty characteristically has a language and is multidimensional, complex, individual or context-specific, absolute and relative (Ali-Akpajiak & Pyke, Citation 2003 ; Bantebya-Kyomuhendo, Citation 2015 ; Chambers, Citation 2012 ; Dhongde & Minoiu, Citation 2010 ; Gandolfi & Neck, Citation 2010 ; Ohio-Ethimiaghe, Citation 2012 ; Philip & Rayhan, Citation 2004 ; World Bank, Citation 2001 ). The nature of these traits of poverty and how they influence poverty analysis are examined hereafter.

3.1. Poverty has a language

Table 2. poverty terminologies used by shona communities in zimbabwe, table 1. poverty terminologies used by malay people in brunei darussalam.

Poverty terminologies reflect the forms or dimensions of poverty facing a community ( Citation Ayoola et al., n.d .; Brock, Citation 1999 ; Jutte, Citation 1994 ; Ohio-Ethimiaghe, Citation 2012 ). The poverty terminologies presented in Tables 1 and 2 above, for example, reveal different forms of poverty, which are financial, material, economic and social in nature.

It helps to minimise confusion or misconception in understanding poverty in a society. Within a particular community, different poverty terms can be used for the same subject (Chambers, Citation 2002 ; World Bank, Citation 1999 ), or a term can be used to refer to different forms of poverty. By way of example, the Shona-speaking people of Zimbabwe use kuchoboka, kusauka, kuomerwa and kukamambwa in referring to financial poverty; and kukwangaya and urombo when referring to both financial poverty and the lack of basic necessities. Such case may cause confusion and misconception in analysing poverty, especially for poverty analysts who are foreign to the Shona community’s way of life.

Local poverty terminologies also reveal the severity of the poverty that a person or household experiences. For instance, in Brunei, the term miskin is used to refer to non-severe poverty and fakir to severe poverty. In Zimbabwe, Shona terms: kudyanhoko dzezvironda, kutambura, kushupika, kunhonga masvosve/sunzi nemukanwa and pfumvu are associated with extreme poverty (see also Table 2 ). Meanwhile, Yoruba-speaking people in Nigeria use ise and osi when referring to non-extreme poverty and extreme poverty, respectively (Ohio-Ethimiaghe, Citation 2012 ).

It helps poverty analysts to uphold people’s dignity. According to Gweshengwe et al. ( Citation 2020 ), communities have poverty terms or expressions that they prefer to use when referring to poverty or poor people as some terms can erode people’s self-confidence, esteem or respect. The same authors (Gweshengwe et al., Citation 2020 ) also note, the Malay poverty terms: miskin and fakir , are somewhat sensitive within the Bruneian community. In referring to poverty or poor people, Bruneians prefer to use the following terms, tidak or kurang mampu/kurang kemampuan (living in need/cannot afford basic needs), kesusahan dalam kehidup/hidup susah (hardships/difficulties or difficult life) and orang or keluarga susah (people with difficulties or hardships) (Gweshengwe et al., Citation 2020 ). In Zimbabwe, Shona poverty terms such as nhamo, rombe and kudya nhoko dzezvironda are somewhat frowned upon by people as the terms can make one feel inferior. Researchers therefore need to know local poverty terms or expressions so as to uphold people’s dignity and not to offend them when analysing poverty.

Language of poverty provides an understanding of the context-sensitive meaning of poverty. In Brunei, for example, the terms miskin and fakir denote local definitions of poverty. Miskin refers to “having an income that covers more than half but not all (≥ 50%) of a household’s basic needs and having a few household assets”, while fakir refers to extreme poverty: “having an income that meets at most half (≤ 50% > 100%) of a household’s basic needs or not having an income at all, and lacking household assets” (Gweshengwe et al., Citation n.d. ). These definitions are being used by government welfare agencies. Such definitions are context-sensitive but are somewhat different from the international poverty definition of 1 USD.90 a day. However, they can be used in reference to the international poverty definition.

3.2. Multidimensionality and complexity of poverty

Financial dimension of poverty : refers to a lack or low level of income or having an income below a country’s minimum wage or income-poverty line; lack of access to loans from legal financial institutions, lack of savings, and being in debt (Banerjee, Citation 2016 ; Chambers, Citation 2012 ; Laderchi, Citation 2000 ; Rowntree, Citation 1902 ; Wong, Citation 2012 ; World Bank, Citation 2001 ).

Economic dimension of poverty : refers to a lack of resources needed to lead an acceptable life, have a decent standard of living or meet basic needs (G. F. R. Ellis, Citation 1984 ; SIDA, Citation 2017 ). These resources include natural or environmental capital such as land, clean air and water, forestry products, and fishery stock; physical capital like infrastructure (roads, buildings, markets and communication systems) and production goods such as machinery and tools; and human capital like being educated, skilled and healthy (Brand, Citation 2002 ; F. Ellis, Citation 2000 ; SIDA, Citation 2017 ). Economic deprivation also refers to a lack of employment or having a low-paid, irregular and insecure job (Hulme & McKay, Citation 2007 ). It could also refer to a lack of access to business or entrepreneurial opportunities.

Material dimension of poverty : this dimension of poverty is directly linked to the living conditions of households or individuals (Terraneo, Citation 2017 ). It denotes material deprivation—a lack of or having low-quality consumer goods (household assets) and services such as furniture, radios, televisions, means of transport, clothing, dietary, housing, utilities, and amenities or facilities (Chambers, Citation 2006 , Citation 2012 ; Gordon, Citation 2010 ; Kus et al., Citation 2016 ; Townsend, Citation 1979 , Citation 1987 ).

Social dimension of poverty : refers to a lack of social capital (G. F. R. Ellis, Citation 1984 ). By definition, social capital refers to norms for social control and networks (relationships) for support and securing benefits (Bartkus & Davis, Citation 2009 ; Brand, Citation 2002 ; Ostrom, Citation 2009 ; Portes, Citation 1998 ). It could also refer to the social resources that households depend on for their livelihoods objectives (De Satge et al., Citation 2002 ). Social capital is built on and strengthened by reciprocating favours or assistance, and that involves investing material, cultural and other resources (Ostrom, Citation 2009 ; Portes, Citation 1998 ). Poor people usually struggle to reciprocate as they lack the required resources to do so. The social dimension of poverty also includes limited or no participation in social activities or functions, and an inability to take up responsibilities that are societally encouraged or approved of (Gordon, Citation 2010 ; Raphael, Citation 2011 ; Townsend, Citation 1979 , Citation 1987 ).

Environmental dimension of poverty : focuses on places where poor people live, including the inside and outside home environments (Chambers, Citation 1994 , Citation 2007 ). This includes areas that are: (i) remote or isolated; (ii) lacking infrastructure and communication systems; (iii) vulnerable to disasters such as floods, droughts, and landslides, (iv) lacking clean water and electricity; and (vi) susceptible to crime and drug abuse; etc. (Chambers, Citation 1994 ; Narayan et al., Citation 2000 ; Citation The Chronic Poverty Report, n.d .).

Seasonal dimension of poverty : according to Chambers ( Citation 2012 ), poverty has a seasonal dimension (seasonality), which manifests in all other poverty dimensions and in how they interlink. It includes the realities Footnote 1 that people, especially the poor, experience repeatedly at certain times of the year, which are brought about or aggravated by the changing of seasons, climatic changes in particular (Chambers, Citation 1979 , Citation 1981 , Citation 1995 , Citation 2012 ; Devereux et al., Citation 2012 ). During the wet season in the tropics, for example, poor people experience a combination of realities: lack of food and money; high food prices; indebtedness; debilitating sicknesses such as diarrhoea, malaria and dengue fever; snakebites; isolation when floods cut them off for weeks or months; collapsing and leaking shelter (Chambers, Citation 1979 , Citation 1981 , Citation 1995 , Citation 2012 ; Devereux et al., Citation 2012 ; Narayan et al., Citation 2000 ). For example, the wet season in the Gambia is associated with food shortages, high incidence of infections, lower body weights of mothers, lower birth weights and high levels of child morbidity and mortality (Chambers, Citation 1979 ). In Nepal, meanwhile, the wet season brings about a peak in a combination of realities: hunger, hardships, and diseases such as cholera, diarrhoea or dysentery, hookworm infections and enteric fever (Ono et al., Citation 2001 ; Shively et al., Citation 2011 ). Seasonality also emanates from non-climatic seasons such as back-to-school (determined by school calendar), festival, and human conception seasons (Chambers, Citation 2012 ; Hadley, Citation 2012 ; Lokshin & Radyakin, Citation 2012 ). Thus, seasonality is both climatic and non-climatic in nature.

Health dimension of poverty— refers to ill health (the fact of being in poor health) and lack of access to health care (Chen & Pan, Citation 2019 ; Clarkea & Erreygersa, Citation 2019 ; Combat Poverty Agency, Citation 2004 ; Institute for Research on Poverty, Citation n.d. .) It includes other health realities such as malnutrition, lower life expectancy, vulnerability to diseases, being sick, high level of stress, exclusion from health-care services.

Figure 1. Web of multiple dimensions of poverty

As Figure 1 shows, the relationship between the poverty dimensions is not linear but cyclical in nature. For instance, a lack of income could cause, sustain or strengthen material deprivation, loss of social capital, lack of economic resources and seasonal realities, which could, in turn, fuel the financial deprivation and other dimensions. The interconnectedness and reinforcing nature of the poverty dimensions make poverty complex. Although the health poverty dimension is not included in the diagram, it is also interconnected with and reinforced by other poverty dimensions. In China, for example, ill-health is one of the root causes of other poverty dimensions (Chen & Pan, Citation 2019 ). In America, meanwhile, health poverty is attributed mainly to financial, economic and material poverty ( Citation Institute for Research on Poverty, n.d .).

For poverty analysis, the multidimensionality and complexity of poverty guide in the selection of poverty worldviews. Poverty is conventionally analysed through income, basic needs and capability worldviews, which, according to Gweshengwe and Hassan ( Citation 2019 ), construe poverty differently. These worldviews reflect the multidimensionality and complexity of poverty at a different scale. For poverty analysis, therefore, poverty analysts should select a poverty worldview that satisfactorily reveals all the dimensions of poverty and how the dimensions interlink with and reinforce each other. The choice of a particular poverty worldview is guided by the multidimensionality and complexity of poverty.

3.3. Poverty is individual- and context-specific

In that it is “experienced differently by men and by women and can differ according to a geographical area, social group, and political or economic context” (Ali-Akpajiak & Pyke, Citation 2003 , p. 5). Sen and Begum ( Citation 2008 ) hold the same view in their assertion that poor people may be distinguished according to “sex, region, occupation, land ownership, housing, education, access to infrastructure and even clothing” (p. 4). People living in poverty are, therefore, not a homogenous group (Ali-Akpajiak & Pyke, Citation 2003 ; Citation Ayoola et al., n.d .; Chambers, Citation 1994 ; Sen & Begum, Citation 2008 ). By way of example, in Nepal, women are poorer and more vulnerable than men; indigenous ethnic (Janajaties) and caste (Dalits) groups are more disadvantaged and poor; and poverty is highly concentrated in rural and mountainous areas (Acharya, Citation 2004 ; International Monetary Fund, Citation 2003 ).

The individual- and context-specific nature of poverty also influences the poverty analysis process. It helps poverty analysts to capture variations of the nature and severity of poverty according to age and gender as well as social, cultural, economic, political, environmental and spatial contexts.

3.4. Poverty is either absolute or relative

(Dhongde & Minoiu, Citation 2010 ; Gandolfi & Neck, Citation 2010 ; Zongsheng & Yunbo, Citation 2005 ). Absolute poverty is a condition of acute deprivation in the form of severe food insecurity, premature death, ill-health, illiteracy, homelessness, lack of clothing, etc. (Ikejiaku, Citation 2009 ; Mowafi & Khawaja, Citation 2005 ; United Nations, Citation 1996 ). It is usually measured based on income or nutrition (Gandolfi & Neck, Citation 2010 ; Zongsheng & Yunbo, Citation 2005 ). If a person’s income falls below the international poverty line of 1 USD.90 per day, he or she is in absolute poverty. In nutritional terms, an adult male is considered to be in absolute poverty if he eats less than 2500 calories per day (Gandolfi & Neck, Citation 2010 ). On the other hand, relative poverty is when a person is regarded as poor in comparison to other persons in his or her society (Gandolfi & Neck, Citation 2010 ; Mowafi & Khawaja, Citation 2005 ; Rigg, Citation 2018 ). For example, within the European Union, an individual is considered relatively poor if his or her income is less than 60% of the region’s median income (Belfield et al., Citation 2014 ; Dhongde & Minoiu, Citation 2010 ). In Brunei, relative poverty is described as having a quality of life that is below the expected standard of living in the country, which includes having comfortable housing, being well educated and healthy, owning more than one car and earning sufficient income (Gweshengwe, Citation 2020 ; Gweshengwe et al., Citation 2020 ; Hassan, Citation 2017 ).

Knowledge about the absolute or relative nature of poverty is essential to analysis of poverty. People in poverty are commonly classified as “very poor”, “poor” and “near poor or vulnerable” (Alkire et al., Citation 2014 ; Banerjee et al., Citation 2009 ; Gweshengwe, Citation 2020 ). This classification is based on the level or scale of poverty severity. Thus, the absoluteness of poverty helps poverty analysts to understand the severity of poverty, which is vital for poverty classification. The relativeness of poverty facilitates the understanding of the nature of poverty in a given society since it is construed in the space of “the way of life” of that society.

This paper examined the characteristics of poverty and their implications for poverty analysis. In summary, the paper found that poverty has a characteristic language and is multidimensional, complex, individual- and context-specific, absolute and/or relative in nature. All these traits of poverty influence poverty analysis.

As regards the language of poverty, each culture uses multiple and varied terminologies to refer to poverty or poor people. In analysing poverty, analysts should therefore begin by understanding the poverty terminologies used by the communities being studied. These terminologies reveal the dimensions and severity of poverty faced by a particular community. Moreover, an understanding local poverty terminologies enables poverty analysts to uphold the dignity of people and helps to minimise misconceptions about poverty in a society. Lastly, the terminologies reveal definitions of poverty that are context-sensitive, which allows poverty analysts to balance context-based and international poverty definitions.

Where the multidimensionality and complexity of poverty are concerned, meanwhile, poverty has financial, economic, social, environmental and seasonal dimensions which interlink and reinforce each other. Knowledge of the multidimensionality and complexity of poverty is essential as it guides the selection of a suitable poverty worldview or space for the analysis of poverty.

As to the individual- and context-specific nature of poverty, this shows how poverty varies according to gender, race and age and how it is shaped by context. Poverty analysis should therefore reveal variations in the nature and severity of poverty according to age, gender and context. Lastly, since poverty is either absolute (acute deprivation) or relative (how poor one is in comparison to other people in a society), knowledge about these aspects of poverty is vital for poverty classification.

Notes on contributors

Blessing gweshengwe.

Blessing Gweshengwe is a multi-skilled Development Planner. He holds a PhD in Geography, Universiti Brunei Darussalam; MA in Poverty and Development from the Institute of Development Studies, University of Sussex; and BSc Honours Degree in Rural and Urban Planning, University of Zimbabwe. Blessing is a lecturer in the Department of Rural and Urban Development at Great Zimbabwe University. His research interests include poverty, quality of life, sustainable livelihoods and urban planning.

Noor Hasharina Hassan (PhD) is a lecturer for the Geography, Environment and Development Programme at the Universiti Brunei Darussalam. Her research interests include consumption and identity, urban economies and competitiveness, housing, poverty and quality of life.

1. Realities, in this study, refer to undesirable life conditions or experiences (deprivations) of poor people (Chambers, Citation 1994 , Citation 1995 , Citation 2012 ).

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Poverty Reduction: Concept, Approaches, and Case Studies

• Living reference work entry
• First Online: 10 January 2020
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• Yakubu Aliyu Bununu 7  

Part of the book series: Encyclopedia of the UN Sustainable Development Goals ((ENUNSDG))

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Poverty is universally measured in monetary expenditure terms, and individuals that are considered poor are those living on less than US$1.25 per day. Poverty is however multifaceted as it includes the multitude of lack and deprivations that poor people are subjected to in their lives on a daily basis. These include but are not limited to disease and poor health conditions, illiteracy and lack of access to education, appalling living conditions, lack of access to economic opportunity and disempowerment, underemployment, vulnerability to violence, and exposure to hazardous environmental conditions (OPHI 2019 ). Thus, poverty reduction can be considered as the improvement of an individual’s or group’s monetary expenditure to an amount above the poverty line while improving access to education, healthcare, information, economic opportunities security of land-tenure, and all the other deprivations associated with it.

Introduction

The eradication of poverty is perhaps the only...

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Department of Urban and Regional Planning, Ahmadu Bello University, Zaria, Nigeria

Yakubu Aliyu Bununu

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Bununu, Y.A. (2020). Poverty Reduction: Concept, Approaches, and Case Studies. In: Leal Filho, W., Azul, A., Brandli, L., Özuyar, P., Wall, T. (eds) Decent Work and Economic Growth. Encyclopedia of the UN Sustainable Development Goals. Springer, Cham. https://doi.org/10.1007/978-3-319-71058-7_31-1

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DOI : https://doi.org/10.1007/978-3-319-71058-7_31-1

Received : 23 August 2019

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Published : 10 January 2020

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World Development Perspectives

Research paper global poverty: a first estimation of its uncertainty ☆.

• • The method of derivation of the $1.9/day international Poverty Line introduces substantial uncertainty in global poverty estimates
• • When key uncertainty sources are introduced the dollar-a-day method identifies a 5.19% global poverty reduction instead of the 50% of the MDG1 target (1990–2015).
• • The cost-of-basic-needs method identifies a 35.71% reduction at 95% confidence level in the same period
• • In light of the identified uncertainties, the profile of the global poor and the distribution of poverty around the world may be substantially misleading.
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