alleviation of poverty thesis statement

China to assist SA in alleviating poverty 

By Nosihle Shelembe Beijing, China -  As part of ongoing efforts to improve the lives of South Africans, China has committed to assist the country in tackling poverty.  This commitment was revealed in a joint statement by President Cyril Ramaphosa and Chinese President Xi Jinping on the occasion of President Ramaphosa’s State Visit to the People’s Republic of China. “China is committed to sharing with South Africa its experience in poverty alleviation and rural revitalisation; in building poverty alleviation model villages and offering support for South Africa's coordinated urban and rural development,” the statement said on Monday.  During the State Visit, the two countries recommitted to working together towards building a high-quality China-South Africa community, with a shared future.  “To carry forward the friendship, consolidate mutual trust, expand cooperation and enhance coordination, the two Heads of State agreed to elevate the bilateral relationship to an All-round Strategic Cooperative Partnership in a New Era, underpinned by strong political ties and focused on a prosperous future with balanced trade, and accelerated transformative economic growth,” the statement said.  Improving lives China expressed its firm support of national unity and the path of economic and social development that South Africa has chosen. It also said it respects efforts by the South African government to safeguard its national interests to improve the lives of all South Africans.  “The two sides agreed to work on strengthening cooperation and synergy between the Belt and Road Initiative and the Economic Reconstruction and Recovery Plan and to continue implementing the 10 Years Strategic Programme of Cooperation between the People’s Republic of China and the Republic of South Africa (2020-2029), as a blueprint towards more substantive outcomes on priority political and socio-economic issues between the two sides.  “The two sides agreed to fully leverage the role of mechanisms such as the China-South Africa Joint Working Group (JWG) and the Joint Economic and Trade Committee (JETC) to further expand economic and trade ties by improving the current trade structure, increasing market access and the export of value-added goods from South Africa,” the statement said.  Trade and investment China is South Africa's largest trading partner globally, while South Africa is China’s number one trading partner in Africa. Total bilateral trade grew from R614 billion in 2022 to R692 billion in 2023.  “The two sides encouraged the respective business communities to enhance new two-way investments and increase their manufacturing bases within the proximity of the relevant source of raw materials to enable the transfer of skills technology and job creation.  “The two sides committed to providing a stable, fair and enabling business environment for companies from both sides and to ensure the safety and legitimate rights and interests of the relevant personnel, projects and institutions.  “The two sides encouraged mutual visits by economic and trade delegations, including co-hosting the New Energy Investment Conferences with South Africa and holding the Jobs Fair of Chinese-invested Enterprises in South Africa to boost local employment and improve people’s lives,” the statement said. READ | President calls for narrowing of SA, China trade deficit Deepening cooperation  The two sides agreed that promoting modernisation is the joint goal in building a high-level South Africa-China community, with a shared future.  “The two sides will deepen cooperation in traditional fields such as agriculture, health, medical sciences and infrastructure development. However, they will further seize opportunities presented by the new scientific and technological revolution and industrial transformation, focusing on key areas such as the digital economy, new energies and artificial intelligence, boost cooperation on quality productive forces, and further expand mutually beneficial cooperation in renewable energy, energy storage and power transmission and distribution,” the statement said.  The two sides further agreed to continue to strengthen exchanges and cooperation in the areas of culture, women, health, youth, education, sport, media, tourism and other people-to-people cooperation fields.  As part of the State Visit, the two Presidents jointly witnessed the signing of several bilateral cooperation instruments in the following areas:     • Cooperation of the Application of BeiDou Navigation Satellite System;    • Sustainable Housing and Human Settlements Development;     • Deepening Bilateral Trade Cooperation;     • Cultural Heritage;     • Cooperation in Prevention and Control of Foot-and-Mouth Disease;     • Inspection, Quarantine and Sanitary Requirements for Dairy Products Exported from the Republic of South Africa to the People’s Republic of China; and the Protocol on Greasy Wool. - SAnews.gov.za  

Joint statement between China and South Africa on the 2nd State Visit

Joint statement between the people’s republic of china and the republic of south africa on the occasion of the 2nd state visit to china by h.e. president cyril ramaphosa and the establishment of an all-round strategic cooperative partnership in a new era.

At the invitation of H.E President Xi Jinping of the People’s Republic of China, H.E. President Cyril Ramaphosa of the Republic of South Africa paid a State Visit to China on 2 September 2024. During the State Visit, the two heads of state held talks in a cordial and friendly atmosphere and had an in-depth exchange of views on further developing China-South Africa and China-Africa relations, including regional and global issues of mutual interest.

The two sides reaffirmed that they cherish the special and ever-growing friendship between the two countries and recommitted to working together towards building a high-quality China-South Africa community with a shared future. To carry forward the friendship, consolidate mutual trust, expand cooperation and enhance coordination, the two Heads of State agreed to elevate the bilateral relationship to an all-round strategic cooperative partnership in the new era, underpinned by strong political ties and focused on a prosperous future with balanced trade, and accelerated transformative economic growth. The Heads of State reached a series of important common understandings:

Working towards a high-quality China-South Africa community with a shared future

The two sides spoke highly of the leapfrog development of the China-South Africa relationship over the past 26 years since its establishment and commended the growth in many areas of cooperation in the golden era of the bilateral ties heralded by the fourth state visit of President Xi Jinping to South Africa in August 2023. The bilateral relationship boasts growing global significance and strategic influence, setting a fine example of developing countries from the Global South working together in solidarity, for purposes of common development.

China congratulated President Ramaphosa on his reelection as President of the Republic of South Africa, and believes that under his leadership, the South African Government of National Unity will achieve success in building a united, just, equal and prosperous country as espoused in the National Development Plan, including maintaining an independent and non-aligned foreign policy based on the principle of progressive internationalism. South Africa congratulated the People’s Republic of China on the 75th anniversary of its founding, acknowledged the development achievements made by the Chinese people of all ethnic groups under the leadership of the Communist Party of China, and wished China success in realizing its Second Centenary Goal of building itself into a great modern socialist country in all respects.

The two sides agreed to leverage the strategic guiding role of Head-of-State diplomacy based on a common understanding between the two Presidents to foster mutually beneficial cooperation by leveraging further the role of structured bilateral mechanisms held at various levels. The two sides encouraged the deepening of exchanges between government departments, and legislative institutions and agreed to accommodate subnational interactions at multiple levels and across different fields, including intensifying experience sharing and mutual learning on state governance.

China firmly supports national unity and the path of economic and social development that South Africa has chosen, and respects efforts by the South African government to safeguard its national interests to improve the lives of all South Africans. The South African government reaffirmed its commitment to the One-China Policy, recognized that there is but one China in the world, the Government of the People's Republic of China is the sole legal government representing the whole of China, and Taiwan is an inalienable part of China. South Africa supports efforts made by the Chinese government to achieve national reunification.

The two sides agreed on the fundamental need to guarantee and protect universal human rights for all, everywhere, including the right to development, as a common cause for all humanity and expressed readiness to conduct exchanges and cooperation on human rights based on mutual respect, equality and rejection of politicization, polarisation, selective, and double standards concerning all human rights matters. The two sides further agree to oppose all forms of discrimination and to promote and protect the rights of vulnerable persons, particularly women, children and persons with disabilities and ensure their equitable access to resources.

Synergising Belt and Road cooperation with South Africa’s National Development Plan

The two sides agreed to work on strengthening cooperation and synergy between the Belt and Road Initiative and the Economic Reconstruction and Recovery Plan and to continue implementing the 10 Years Strategic Programme of Cooperation between the People’s Republic of China and the Republic of South Africa (2020-2029), as a blueprint towards more substantive outcomes on priority political, socio-economic issues between the two sides.

The two sides agreed to fully leverage the role of such mechanisms as the China-South Africa Joint Working Group (JWG) and the Joint Economic and Trade Committee (JETC) to further expand economic and trade ties by improving the current trade structure, increasing market access and the export of value-added goods from South Africa.

The two sides encouraged the respective business communities to enhance new two-way investments and increase their manufacturing bases within the proximity of the relevant source of raw materials to enable the transfer of skills technology and job creation.

The two sides committed to providing a stable, fair and enabling business environment for companies from both sides and to ensure the safety and legitimate rights and interests of the relevant personnel, projects and institutions. The two sides encouraged mutual visits by economic and trade delegations, including co-hosting the New Energy Investment Conferences by chambers or associations of commerce from both sides, and holding the Jobs Fair of Chinese-Invested Enterprises in South Africa to boost local employment and improve people’s lives.

The two sides agreed that promoting modernisation is the joint goal in building a high-level South Africa-China community with a shared future. The two sides will deepen cooperation in traditional fields such as agriculture, health, medical sciences and infrastructure development, however, they will further seize opportunities presented by the new scientific and technological revolution and industrial transformation, focusing on key areas such as the digital economy, new energies and artificial intelligence, boost cooperation on quality productive forces, and further expand mutually beneficial cooperation in renewable energy, energy storage and power transmission and distribution.

China is committed to sharing with South Africa experience in poverty alleviation and rural revitalization, in building poverty alleviation model villages, and offering support for South Africa’s coordinated urban and rural development. The two sides further agreed to continue to strengthen exchanges and cooperation in the areas of culture, women, health, youth, education, sport, media, tourism, and other people-to-people cooperation fields.

III. Working together to build an equal and orderly multipolar world and universally beneficial and inclusive economic globalization

South Africa welcomed China’s role as a leader on the international stage and acknowledged that China's Global Development Initiative (GDI), Global Security Initiative (GSI) and Global Civilization Initiative (GCI)  are aimed at improving global peace and security, promoting socio-economic development, and contributing to the reform of global governance. South Africa is confident that China will promote these initiatives, noting the primacy of the United Nations (UN) and African Union (AU) and in line with the principles and programs of the UN and the AU, including the 2030 Agenda for Sustainable Development, the Agenda 2063: The Africa We Want, and the principle of subsidiarity. South Africa looks forward to close consultation and cooperation with China on both bilateral and global issues of mutual interest and encourages China to cooperate closely with other major countries in dealing with global challenges such as climate change, conflict prevention and resolution, fair trade, and poverty alleviation. The two sides welcome and support each other in playing an increased role in global affairs, and will work together to uphold fairness and justice, including making global governance more just and equitable.

The two sides applauded the recent 70th Anniversary of China’s “Five Principles of Peaceful Coexistence”, as these were espoused in the buildup to the Asia-Africa Summit of 1955 in Bandung and were later adopted as the main goals and objectives of the Non-Aligned Movement (NAM). The two sides agreed to enhance cooperation on international affairs and multilateral institutions, jointly uphold the UN-centred global system, an equitable international order underpinned by international law, and the basic norms governing international relations based on the purposes and principles of the UN Charter, including to uphold the rights and interests of developing countries jointly and respect for national sovereignty and territorial integrity.

The two sides supported a comprehensive reform of the UN, including its Security Council, with a view to making it more democratic, representative, effective and efficient, and to increase the representation of developing countries in the Council’s memberships so that it can adequately respond to prevailing global challenges and support the legitimate aspirations of emerging and developing countries to play a greater role in international affairs, in particular in the United Nations, including its Security Council.

The two sides agreed to make active efforts to restore development as the centerpiece on the agenda of international cooperation, and to work for the full realisation of the 2030 Agenda for Sustainable Development. China applauded South Africa for contributing to international synergy for common development and congratulated the country on successfully hosting the 15th BRICS Summit in 2023, including its efforts as the chair in achieving a historic BRICS expansion. Both sides agree to continue strengthening coordination and collaboration under the BRICS mechanism and work for more practical outcomes of cooperation of an expanded BRICS.

China expresses its full support for South Africa’s G20 presidency in 2025 and extended felicitations to the African Union on becoming a full member. China called on the international community to attach greater importance to Africa-related priorities in G20 affairs. China expressed its readiness to work with South Africa to increase the influence and voice of emerging markets and developing countries, to focus on major issues such as coordination and macro-economic policies, global poverty reduction, development and reform of international economic and financial institutions, as well as to promote a more balanced and stable global economic and financial architecture.

Both sides undertook to continue to uphold the core values and basic principles of the World Trade Organization, oppose decoupling and disruption of supply chains, resist unilateralism and protectionism, call for reform of the international financial system, and improve development financing for African countries to achieve common prosperity.

The two sides commended each other’s respective roles in terms of resolving the Russia-Ukraine conflict and welcomed the Common Understandings Between China and Brazil on the “Political Settlement of the Ukraine Crisis”, as well as the Peace Mission by the African Union. The two sides agreed that inclusive dialogue and peaceful negotiations are the only viable political ways to find a lasting solution to the crisis. The two sides call on relevant parties to observe the three principles of no expansion of the battlefield, no escalation of fighting and no provocation by any party.

The two sides are deeply concerned about the serious humanitarian disaster in the Gaza Strip caused by the Israeli-Palestinian conflict and its spillover effects. Both called for the earnest implementation of the U.N. Security Council Resolution 2728 and an immediate ceasefire and end to all fighting, and support resuming a process of political settlement of the Palestinian question. China commended the positive role that South Africa has played in activating the role of the international community in the conflict in Gaza and is willing to work together toward a comprehensive, just and lasting settlement at an early date. South Africa expressed its appreciation to China for successfully inviting various Palestinian factions to hold a reconciliation dialogue in China and for signing the Beijing Declaration.

IV. Working to launch a new era of building a high-level China-Africa community with a shared future

The two sides commended the successful China-Africa Leaders’ Dialogue held in South Africa in August 2023 and encouraged the Beijing FOCAC Summit’s full commitment to implementing the Initiative on Supporting Africa’s Industrialization, the Plan for China Supporting Africa’s Agricultural Modernization, and the Plan for China-Africa Cooperation on Talent Development put forth by President Xi Jinping. China commended President Ramaphosa for scheduling to co-host the high level session on “industrialization, agricultural modernization and green development - the path to modernization”.

The two sides agreed to further align the outcomes of the Summit with the African Union Agenda 2063 and the 2030 Agenda for Sustainable Development, as part of opening a new chapter in China-Africa relations. Both Presidents look forward to a fruitful conference that would promote the common interests of both China and Africa.

The two sides applauded the facilitating role that the Forum on China-Africa Cooperation(FOCAC) has played in promoting China-Africa high-quality cooperation during the last 24 years since its establishment. The two Presidents wished the 2024 Beijing Summit of FOCAC all success and expressed the hope that it would open a new chapter of China-Africa solidarity and cooperation.

The two sides call on the international community to support the efforts by African countries in terms of the full implementation of the Africa Continental Free Trade Agreement (AfCFTA) and allow Africa the space to realise the benefits of its integration agenda. The two sides further call on the international community to support efforts by African regional organizations such as the African Union to independently solve African regional problems (i.e. African solutions to African problems) and agree to enhance coordination on hotspot issues in Africa and safeguard peace and security of Africa.

As part of the State Visit, the two Presidents jointly witnessed the signing of several bilateral cooperation instruments in the following areas：Cooperation of the Application of Beidou Navigation System; Sustainable Housing and Human Settlements Development; Deepening Bilateral Trade Cooperation; Cultural Heritage; Cooperation in Prevention an Control of Foot-and-Mouth Disease; Inspection Quarantine and Sanitary Requirements for Dairy Products Exported from the Republic of South Africa to the People’s Republic of China, and the Protocol on Greasy Wool and cooperation in scientific field.

The two sides agreed that President Ramaphosa’s visit to China was successful and carried great significance in terms of promoting China-South Africa relations and building a high-level China-Africa community, with a shared future. President Ramaphosa expressed his heartfelt appreciation to President Xi Jinping and the Chinese Government and People for their warm hospitality during the State Visit to China.

Share this page

Similar categories to explore.

• All Activities
• Sustainable Development Goals
• Conference of the Parties (COP)
• Events and Meetings
• News Portal
• Media Releases
• Latest Publications
• Publication Series
• WMO Bulletin
• Fact Sheets
• Photo Galleries
• WMO Community
• The Secretariat
• Our Mandate
• WMO Members
• Liaison Offices
• Gender Equality
• Partnerships
• Development Partnerships
• History of IMO and WMO
• Finance and Accountability
• World Meteorological Day
• WMO Building

Africa faces disproportionate burden from climate change and adaptation costs

Abidjan, Cote d’Ivoire (WMO) - Africa bears an increasingly heavy burden from climate change and disproportionately high costs for essential climate adaptation, according to a new report from the World Meteorological Organization (WMO).

• Temperature increases in Africa slightly above the global average
• Multi-year droughts continued in northwest Africa in 2023
• Extreme floods caused severe losses and damages
• African countries face increasing climate change bill
• Investment in early warnings will protect lives and economies

On average, African countries are losing 2–5 percent of Gross Domestic Product (GDP) and many are diverting up to 9 percent of their budgets responding to climate extremes. In sub-Saharan Africa, the cost of adaptation is estimated to be between US$ 30-50 billion annually over the next decade, or 2-3 percent of the region's Gross Domestic Product, says the WMO State of the Climate in Africa 2023 report .

By 2030, it is estimated that up to 118 million extremely poor people (living on less than US$ 1.90 per day) will be exposed to drought, floods and extreme heat in Africa, if adequate response measures are not put in place. This will place additional burdens on poverty alleviation efforts and significantly hamper growth, according to figures cited in the report. 

African countries need to prioritize increased investment in National Meteorological and Hydrological Services and accelerate implementation of the Early Warnings For All initiative to save lives and livelihoods. This will help mitigate risks, build adaptive capacity, boost resilience at local, national, and regional levels and guide sustainable development strategies, says the report.

It focuses on climate change indicators and impacts in 2023 – the world’s hottest year on record to date. It supplements the WMO State of the Global Climate report and is one of a series of WMO regional reports which provide the observational basis to help drive action and support decision-making. 

“Over the past 60 years, Africa has observed a warming trend that has become more rapid than the global average. In 2023, the continent experienced deadly heatwaves, heavy rains, floods, tropical cyclones, and prolonged droughts,” said WMO Secretary-General Celeste Saulo. 

“While many countries in the Horn of Africa, southern and North-West Africa continued to suffer exceptional multi-year drought, other countries experienced extreme precipitation events in 2023 leading to flooding with significant casualties. These extreme events led to devastating impacts on communities, with serious economic implications,” said Celeste Saulo.

“This pattern of extreme weather has continued in 2024. Parts of southern Africa have been gripped by damaging drought. Exceptional seasonal rainfall has caused death and devastation in East African countries, most recently in Sudan and South Sudan. This exacerbates an already desperate humanitarian crisis,” she said.  

WMO, the African Union Commission, United Nations Economic Commission for Africa and the African Ministerial Conference on Meteorology will release the report in collaboration with partners at the 12th Climate Change for Development in Africa (CCDA) Conference in Abidjan, Cote d’Ivoire on 2 September 2024.

“The State of Climate in Africa 2023 Report highlights the urgent need for investing in meteorological services and early warning systems to help adapt to climate change and build resilience in Africa. As the impacts of climate change continue to manifest globally, the African continent stands at a critical juncture,” said H.E. Ambassador Josefa Leonel Correia Sacko, Commissioner for Agriculture, Rural Development, Blue Economy and Sustainable Environment at the African Union Commission.

“Africa faces disproportionate burdens and risks arising from climate change related weather events and patterns, which cause massive humanitarian crises with detrimental impacts on agriculture, and food security, education, energy, infrastructure, peace, and security, public health, water resources, and overall socio-economic development,” she said. 

Key messages

Temperatures: In Africa, 2023 was in the top three warmest years in the 124-year record, depending on the dataset used. The mean temperature was 0.61° C higher than the 1991-2020 average and 1.23° C above the 1961-1990 long-term baseline. 

The African continent has been warming at a slightly faster rate than the global average, at about +0.3 °C per decade between 1991 and 2023. The warming has been most rapid in North Africa, around +0.4 °C per decade between 1991 and 2023, compared to +0.2 °C/decade between 1961 and 1990. Southern Africa experienced the lowest warming trend compared to the other sub-regions, around +0.2 °C/decade between 1991 and 2023.

The highest temperature anomalies in 2023 were recorded across northwestern Africa, especially in Morocco, coastal parts of Mauritania and northwest Algeria. 

Several countries including Mali, Morocco, United Republic of Tanzania, and Uganda reported their warmest year on record. Extreme heatwaves in July and August affected northern Africa. Tunis, the capital of Tunisia reached a record of 49.0°C and Agadir, Morocco reached a new maximum temperature of 50.4°C. 

Precipitation

Regions with a marked rainfall deficit included the western part of North and Northwestern Africa, the Horn of Africa, portions of Southern Africa including Zambia, Zimbabwe, Botswana, and most of Namibia. In addition, Madagascar, central Sudan, northern Ethiopia and Uganda suffered from below-normal precipitation.  

West Africa experienced a normal to early onset of its monsoon rainy season Precipitation was notably higher than normal in Angola and coastal areas north of the Gulf of Guinea.

Sea-level rise: The rate of sea-level rise around Africa was close to or slightly higher than the global mean rate of 3.4 mm per year. The largest rate of sea level rise was observed in the Red Sea, reaching 4.1 mm per year.

Extreme climate events

Floods: At least 4 700 confirmed deaths in Libya were attributed to flooding following the Mediterranean cyclone ‘Storm Daniel’ in September, with 8 000 still missing.

Parts of Kenya, Somalia and Ethiopia experienced widespread and severe flooding, with more than 350 deaths and 2.4 million displaced people during the April-June rainy season.

Record-breaking tropical Cyclone Freddy caused extensive flooding during the final landfall, both in Mozambique and Malawi, as extremely heavy rain fell (up to 672 mm during the storm in Mozambique). Malawi was especially hard hit with at least 679 deaths reported. A further 165 deaths were reported in Mozambique. 

Severe flooding with associated landslides affected central Africa in early May on the border between Rwanda and the Democratic Republic of Congo, killing at least 574 people. 

The White Nile in South Sudan reached record high levels in February. Basic needs such as food, clean water, and healthcare were difficult to access and there was a near total collapse of local livelihoods. 

In September and October, approximately 300,000 people were affected by flooding across 10 countries, with Niger, Benin, Ghana and Nigeria most heavily impacted. 

Drought: Parts of Morocco, Algeria, Tunisia, Nigeria, Cameroon, Ethiopia, Madagascar, Angola, Zambia, Zimbabwe and Democratic Republic of Congo experienced severe drought in 2023. Zambia faced its worst drought in the last 40 years, affecting eight out of ten provinces and approximately six million people.

Climate-related impacts to agriculture and food security

Climate extremes including floods and droughts had a major impact on food security.

North Africa’s cereal production in 2023 was about 10 percent below the five‑year average estimated at 33 million tons in 2023, similar to the previous year’s already drought‑stricken harvest. Tunisia was worst hit.

Erratic rainfall and the general situation of insecurity kept cereal production at below-average levels in northern parts of the subregion, including Sudan, South Sudan, the Karamoja region in Uganda, Eritrea, Ethiopia, and central and western Kenya. In Sudan, seasonal rains were below average and temporally erratic, with prolonged dry spells. The production of sorghum and millet was forecast to decrease by about 25% and 50%, respectively, compared to 2022. 

Investment in adaptation and resilience

Climate-resilient development in Africa requires investments in hydrometeorological infrastructure and early warning systems to prepare for escalating high-impact hazardous events. Investments in National Meteorological and Hydrological Services (NMHSs) in Africa are needed to enhance data collection and improve forecasting capabilities in order to strengthen the ability of these institutions to issue early warnings and advisories for extreme events. There is a particular need to invest in cutting-edge technologies and systems to enhance the accuracy and lead time of weather, climate, and hydrological forecasts.

In sub-Saharan Africa, adaptation costs are estimated at US$ 30–50 billion (2–3% of regional gross domestic product (GDP)) each year over the next decade. 

Early Warnings for All

An ambitious Early Warnings for All Action Plan for Africa was launched in September 2023. The primary objective is to make sure that timely and accurate information about natural hazards and impending disasters reaches all segments of African society, particularly the most vulnerable. This answers the call of United Nations Secretary-General António Guterres that every person worldwide must be protected by early warning systems by 2027. A number of African countries have been identified for priority action in the global initiative.

Between 1970 and 2021, Africa accounted for 35% of weather, climate, and water-related fatalities. Yet only 40% of the African population has access to early warning systems – the lowest rate of any region of the world. This new Early Warnings for All Action Plan for Africa seeks to change that.

Notes to Editors

WMO Deputy Secretary-General Ko Barrett will participate in the launch of the report at the 12th Climate Change for Development in Africa Conference. There will also be high-level statements from H.E. Josefa Leonel Correia Sacko (Commissioner for Agriculture, Blue Economy and Sustainable Environment of the African Union Commission); Mr. Claver Gatete (Executive Secretary, United Nations Economic Commission for Africa) and Eng. Collins Nzovu, Minister of Green Economy and Environment, Zambia, Vice President, AMCOMET Bureau. 

The event is in hybrid format. 

The release of the report will be followed by Session 19: Bridging the climate policy, governance and implementation gaps in Africa. This Session will be moderated by H. E. Josefa Sacko, AUC Commissioner and It will set the scene for ministerial and parliamentarians discussions. The idea is to take the climate information provided at the release, especially the key messages into building climate policies in the continent as well as to consider ways of implementing these climate policies through an integrated national policy. 

The World Meteorological Organization (WMO) is a specialized agency of the United Nations responsible for promoting international cooperation in atmospheric science and meteorology.

WMO monitors weather, climate, and water resources and provides support to its Members in forecasting and disaster mitigation. The organization is committed to advancing scientific knowledge and improving public safety and well-being through its work.

For further information, please contact:

• Clare Nullis WMO media officer [email protected] +41 79 709 13 97
• WMO Strategic Communication Office Media Contact [email protected]
• Region I: Africa

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here .

Loading metrics

Open Access

Peer-reviewed

Research Article

Evaluating poverty alleviation strategies in a developing country

Roles Conceptualization, Formal analysis, Funding acquisition, Methodology, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Institute of Rural Management Anand (IRMA), Anand, Gujarat, India

Roles Data curation

• Pramod K. Singh, 
• Harpalsinh Chudasama

• Published: January 13, 2020
• https://doi.org/10.1371/journal.pone.0227176
• Peer Review
• Reader Comments

A slew of participatory and community-demand-driven approaches have emerged in order to address the multi-dimensional nature of poverty in developing nations. The present study identifies critical factors responsible for poverty alleviation in India with the aid of fuzzy cognitive maps (FCMs) deployed for showcasing causal reasoning. It is through FCM-based simulations that the study evaluates the efficacy of existing poverty alleviation approaches, including community organisation based micro-financing, capability and social security, market-based and good governance. Our findings confirm, to some degree, the complementarity of various approaches to poverty alleviation that need to be implemented simultaneously for a comprehensive poverty alleviation drive. FCM-based simulations underscore the need for applying an integrated and multi-dimensional approach incorporating elements of various approaches for eradicating poverty, which happens to be a multi-dimensional phenomenon. Besides, the study offers policy implications for the design, management, and implementation of poverty eradication programmes. On the methodological front, the study enriches FCM literature in the areas of knowledge capture, sample adequacy, and robustness of the dynamic system model.

Citation: Singh PK, Chudasama H (2020) Evaluating poverty alleviation strategies in a developing country. PLoS ONE 15(1): e0227176. https://doi.org/10.1371/journal.pone.0227176

Editor: Stefan Cristian Gherghina, The Bucharest University of Economic Studies, ROMANIA

Received: September 27, 2019; Accepted: December 9, 2019; Published: January 13, 2020

Copyright: © 2020 Singh, Chudasama. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files. The aggregated condensed matrix (social cognitive map) is given in S1 Table . One can replicate the findings of this study by analyzing this weight matrix.

Funding: The World Bank and the Ministry of Rural Development, Government of India

Competing interests: We hereby declare that none of the authors have any conflict of interest on this paper.

1. Introduction

1.1. poverty alleviation strategies.

Although poverty is a multi-dimensional phenomenon, poverty levels are often measured using economic dimensions based on income and consumption [ 1 ]. Amartya Sen’s capability deprivation approach for poverty measurement, on the other hand, defines poverty as not merely a matter of actual income but an inability to acquire certain minimum capabilities [ 2 ]. Contemplating this dissimilarity between individuals’ incomes and their inabilities is significant since the conversion of actual incomes into actual capabilities differs with social settings and individual beliefs [ 2 – 4 ]. The United Nations Development Programme (UNDP) also emphasises the capabilities’ approach for poverty measurement as propounded by Amartya Sen [ 5 ]. “ Ending poverty in all its forms everywhere ” is the first of the 17 sustainable development goals set by the United Nations with a pledge that no one will be left behind [ 6 ]. Development projects and poverty alleviation programmes all over the world are predominantly aimed at reducing poverty of the poor and vulnerable communities through various participatory and community-demand-driven approaches [ 7 , 8 ]. Economic growth is one of the principal instruments for poverty alleviation and for pulling the poor out of poverty through productive employment [ 9 , 10 ]. Studies from Africa, Brazil, China, Costa Rica, and Indonesia show that rapid economic growth lifted a significant number of poor people out of financial poverty between 1970 and 2000 [ 11 ]. According to Bhagwati and Panagariya, economic growth generates revenues required for expanding poverty alleviation programmes while enabling governments to spend on the basic necessities of the poor including healthcare, education, and housing [ 9 ]. Poverty alleviation strategies may be categorised into four types including community organisations based micro-financing, capability and social security, market-based, and good governance.

Micro-finance, aimed at lifting the poor out of poverty, is a predominant poverty alleviation strategy. Having spread rapidly and widely over the last few decades, it is currently operational across several developing countries in Africa, Asia, and Latin America [ 12 – 21 ]. Many researchers and policy-makers believe that access to micro-finance in developing countries empowers the poor (especially women) while supporting income-generating activities, encouraging the entrepreneurial spirit, and reducing vulnerability [ 15 , 21 – 25 ]. There are fewer studies, however, that show conclusive and definite evidence regarding improvements in health, nutrition, and education attributable to micro-finance [ 21 , 22 ]. For micro-finance to be more effective, services like skill development training, technological support, and strategies related to better education, health and sanitation, including livelihood enhancement measures need to be included [ 13 , 17 , 19 ].

Economic growth and micro-finance for the poor might throw some light on the financial aspects of poverty, yet they do not reflect its cultural, social, and psychological dimensions [ 11 , 21 , 26 ]. Although economic growth is vital for enhancing the living conditions of the poor, it does not necessarily help the poor exclusively tilting in favour of the non-poor and privileged sections of society [ 4 ]. Amartya Sen cites social exclusion and capability deprivation as reasons for poverty [ 4 , 27 ]. His capabilities’ approach is intended to enhance people’s well-being and freedom of choices [ 4 , 27 ]. According to Sen, development should focus on maximising the individual’s ability to ensure more freedom of choices [ 27 , 28 ]. The capabilities approach provides a framework for the evaluation and assessment of several aspects of the individual’s well-being and social arrangements. It highlights the difference between means and ends as well as between substantive freedoms and outcomes. An example being the difference between fasting and starving [ 27 – 29 ]. Improving capabilities of the poor is critical for improving their living conditions [ 4 , 10 ]. Improving individuals’ capabilities also helps in the pooling of resources while allowing the poor to engage in activities that benefit them economically [ 4 , 30 ]. Social inclusion of vulnerable communities through the removal of social barriers is as significant as financial inclusion in poverty reduction strategies [ 31 , 32 ]. Social security is a set of public actions designed to reduce levels of vulnerability, risk, and deprivation [ 11 ]. It is an important instrument for addressing the issues of inequality and vulnerability [ 32 ]. It also induces gender parity owing to the equal sovereignty enjoyed by both men and women in the context of economic, social, and political activities [ 33 ].

The World Development Report 1990 endorsed a poverty alleviation strategy that combines enhanced economic growth with provisions of essential social services directed towards the poor while creating financial and social safety nets [ 34 , 35 ]. Numerous social safety net programmes and public spending on social protection, including social insurance schemes and social assistance payments, continue to act as tools of poverty alleviation in many of the developing countries across the world [ 35 – 39 ]. These social safety nets and protection programmes show positive impacts on the reduction of poverty, extent, vulnerability, and on a wide range of social inequalities in developing countries. One major concern dogging these programmes, however, is their long-term sustainability [ 35 ].

Agriculture and allied farm activities have been the focus of poverty alleviation strategies in rural areas. Lately, though, much of the focus has shifted to livelihood diversification on the part of researchers and policy-makers [ 15 , 40 ]. Promoting non-farm livelihoods, along with farm activities, can offer pathways for economic growth and poverty alleviation in developing countries the world over [ 40 – 44 ]. During the early 2000s, the development of comprehensive value chains and market systems emerged as viable alternatives for poverty alleviation in developing countries [ 45 ]. Multi-sectoral micro-enterprises may be deployed for enhancing productivity and profitability through value chains and market systems, they being important for income generation of the rural poor while playing a vital role in inclusive poverty eradication in developing countries [ 46 – 48 ].

Good governance relevant to poverty alleviation has gained top priority in development agendas over the past few decades [ 49 , 50 ]. Being potentially weak in the political and administrative areas of governance, developing countries have to deal with enormous challenges related to social services and security [ 49 , 51 ]. In order to receive financial aid from multinational donor agencies, a good governance approach towards poverty reduction has become a prerequisite for developing countries [ 49 , 50 ]. This calls for strengthening a participatory, transparent, and accountable form of governance if poverty has to be reduced while improving the lives of the poor and vulnerable [ 50 , 51 ]. Despite the importance of this subject, very few studies have explored the direct relationship between good governance and poverty alleviation [ 50 , 52 , 53 ]. Besides, evidence is available, both in India and other developing countries, of information and communication technology (ICT) contributing to poverty alleviation programmes [ 54 ]. Capturing, storing, processing, and transmitting various types of information with the help of ICT empowers the rural poor by increasing access to micro-finance, expanding the use of basic and advance government services, enabling the development of additional livelihood assets, and facilitating pro-poor market development [ 54 – 56 ].

1.2. Proposed contribution of the paper

Several poverty alleviation programmes around the world affirm that socio-political inclusion of the poor and vulnerable, improvement of social security, and livelihood enhancement coupled with activities including promoting opportunities for socio-economic growth, facilitating gender empowerment, improving facilities for better healthcare and education, and stepping up vulnerability reduction are central to reducing the overall poverty of poor and vulnerable communities [ 1 , 11 ]. These poverty alleviation programmes remain instruments of choice for policy-makers and development agencies even as they showcase mixed achievements in different countries and localities attributable to various economic and socio-cultural characteristics, among other things. Several poverty alleviation programmes continue to perform poorly despite significant investments [ 8 ]. The failure rate of the World Bank’s development projects was above 50% in Africa until 2000 [ 57 ]. Hence, identifying context-specific factors critical to the success of poverty alleviation programmes is vital.

Rich literature is available pertinent to the conceptual aspects of poverty alleviation. Extant literature emphasises the importance of enhancing capabilities and providing social safety, arranging high-quality community organisation based micro-financing, working on economic development, and ensuring good governance. However, the literature is scanty with regard to comparative performances of the above approaches. The paper tries to fill this gap. This study, through fuzzy cognitive mapping (FCM)-based simulations, evaluates the efficacy of these approaches while calling for an integrative approach involving actions on all dimensions to eradicate the multi-dimensional nature of poverty. Besides, the paper aims to make a two-fold contribution to the FCM literature: i) knowledge capture and sample adequacy, and ii) robustness of the dynamic system model.

The remainder of the paper proceeds as follows: We describe the methodology adopted in the study in section two. Section three illustrates key features of the FCM system in the context of poverty alleviation, FCM-based causal linkages, and policy scenarios for poverty alleviation with the aid of FCM-based simulations. We present our contribution to the extant literature relating to FCM and poverty alleviation. Finally, we conclude the paper and offer policy implications of the study.

2. Methodology

We conducted the study with the aid of the FCM-based approach introduced by Kosko in 1986 [ 58 ]. The process of data capture in the FCM approach is considered quasi-quantitative because the quantification of concepts and links may be interpreted in relative terms [ 59 ] allowing participants to debate the cause-effect relations between the qualitative concepts while generating quantitative data based on their experiences, knowledge, and perceptions of inter-relationships between concepts [ 60 – 64 , 65 – 68 ]. The FCM approach helps us visualise how interconnected factors/ variables/ concepts affect one another while representing self-loop and feedback within complex systems [ 62 , 63 , 69 ]. A cognitive map is a signed digraph with a series of feedback comprising concepts (nodes) that describe system behavior and links (edges) representing causal relationships between concepts [ 60 – 63 , 65 , 70 – 72 ]. FCMs may be created by individuals as well as by groups [ 60 , 72 , 73 ]. Individual cognitive mapping and group meeting approaches have their advantages and drawbacks [ 72 ]. FCMs allow the analysis of non-linear systems with causal relations, while their recurrent neural network behaviour [ 69 , 70 , 74 ] help in modelling complex and hard-to-model systems [ 61 – 63 ]. The FCM approach also provides the means to build multiple scenarios through system-based modelling [ 60 – 64 , 69 , 74 , 75 ].

The strengths and applications of FCM methodology, focussing on mental models, vary in terms of approach. It is important to remember, though, that (i) the FCM approach is not driven by data unavailability but is responsible for generating data [ 60 , 76 ]. Also that (ii) FCMs can model complex and ambiguous systems revealing hidden and important feedback within the systems [ 58 , 60 , 62 , 69 , 76 ] and (iii) FCMs have the ability to represent, integrate, and compare data–an example being expert opinion vis-à-vis indigenous knowledge–from multiple sources while divulging divergent viewpoints [ 60 ]. (iv) Finally, FCMs enable various policy simulations through an interactive scenario analysis [ 60 , 62 , 69 , 76 ].

The FCM methodology does have its share of weaknesses. To begin with: (i) Respondents’ misconceptions and biases tend to get encoded in the maps [ 60 , 62 ]. (ii) Possibility of susceptibility to group power dynamics in a group model-building setting cannot be ruled out; (iii) FCMs require a large amount of post-processing time [ 67 ]. (iv) The FCM-based simulations are non-real value and relative parameter estimates and lack spatial and temporal representation [ 60 , 77 , 78 ].

These drawbacks notwithstanding, we, along with many researchers, conceded that the strengths and applications of FCM methodology outweighed the former, particularly with regard to integrating data from multiple stakeholders with different viewpoints.

We adopted the multi-step FCM methodology discussed in the following sub-sections. We adopted the multi-step FCM methodology discussed in the following sub-sections. We obtained individual cognitive maps from the participants in two stages: ‘open-concept design’ approach followed by the ‘pre-concept design’ approach. We coded individual cognitive maps into adjacency matrices and aggregated individual cognitive maps to form a social cognitive map. FCM-based simulation was used to build policy scenarios for poverty alleviation using different input vectors.

2.1. Obtaining cognitive maps from the participants

A major proportion of the literature on fuzzy cognitive maps reflects an ‘open-concept design’ approach, while some studies also rely on a ‘pre-designed concept’ approach with regard to data collection.

In the case of the ‘open-concept design’ approach, concepts are determined entirely by participants and are unrestricted [ 59 , 60 , 62 , 63 , 65 – 67 , 79 , 80 ]. While the researcher determines the context of the model by specifying the system being modelled, including the boundaries of the system, participants are allowed to decide what concepts will be included. This approach provides very little restriction in the knowledge capture from participants and can be extremely beneficial especially if there is insufficient knowledge regarding the system being modelled.

In the case of the ‘pre-designed concept’ approach, concepts are pre-determined either by experts or by researchers using available literature [ 64 , 69 , 74 , 81 , 82 ]. In this approach, the researcher is able to exercise a higher degree of control over how the system is defined. The ‘pre-designed concept’ approach is likely to be more efficient compared to the ‘open-concept design’ in the context of time required for model building. However, it restricts the diversity of knowledge captured from participants and is able to influence more heavily the way in which this knowledge is contextualised based on input and interpretation.

We have adopted a ‘mixed-concept design’ approach for this study involving data collection in two stages:

2.1.1. Stage one: ‘Open-concept design’ approach.

During the first stage, we engaged with the experts and national-level policy-makers who designed the Deendayal Antyodaya Yojana -National Rural Livelihoods Mission (DAY-NRLM), a centrally sponsored programme in India. The DAY-NRLM aims at abolishing rural poverty by promoting multiple livelihoods for the rural poor and vulnerable households. The programme is focussed on organising the rural poor and vulnerable communities into self-help groups (SHGs) while equipping them with means of self-employment. The four critical components of the programme viz ., (i) universal social mobilisation and institution building, (ii) financial inclusion, (iii) convergence and social development, and (iv) livelihood enhancement are designed to address the exclusions of these communities, eliminate their poverty, and bring them within the ambit of mainstream economic and social systems. Participants comprising three experts from the World Bank, nine experts from the National Mission Management Unit of the DAY-NRLM, and 25 monitoring and evaluation experts from 25 states of India created 37 FCMs. A sample map of FCMs obtained from these participants is provided in S1 Fig . We demonstrated the construction of fuzzy cognitive maps with the aid of a map from a neutral problem domain referring to direct and consequential impacts of deforestation, which had been approved by the ‘Research Ethics Committee’ of our Institute.

A group discussion was held with the participants regarding the issues under investigation subsumed under the title “critical factors required to ensure that people come out of poverty on a sustainable basis”. It prompted them to identify major concepts pertaining to the above. These were listed down on a whiteboard by the researchers. Once the participants had understood the process of drawing a fuzzy cognitive map and identified major concepts responsible for poverty alleviation, they were asked to draw a fuzzy cognitive map individually. The participants used the concepts listed on the whiteboard to draw fuzzy cognitive maps. Many participants added new concepts while drawing the maps. They then connected all the concepts through various links based on their personal understanding. The links, represented by arrows in between concepts, show the direction of influence between them.

The participants assigned weights to each link on a scale of 1–10 to describe the relationship strength between two concepts [ 60 ]. Ten denoted the highest strength and one the lowest; the numbers 1–3 signified relationships with low strength, 4–6 signified relationships with medium strength, and 7–10 signified relationships with high strength. After constructing the FCMs each participant made a presentation, which was video-recorded, explaining their map to the researchers. The researchers, based on causal relationships between the concepts, assigned positive and negative polarities to the weights of the links [ 59 , 60 , 62 – 64 , 66 – 68 , 72 ].

2.1.2. Stage two: ‘Pre-designed concept’ approach.

During the second stage, an instrument depicting 95 concepts under 22 concept categories was prepared based on the FCMs obtained from participants during the first stage ( S2 Fig ). The instrument also contained links between the 22 concept categories. ‘Research Ethics Committee’ of our Institute approved this instrument as well. We used this instrument during the second stage to obtain FCMs. We obtained 123 additional FCMs, of which 20 FCMs were obtained from the Chief Executive Officers along with experts from livelihood, enterprise, and community development domains belonging to the National Mission Management Unit in the states of Bihar, Jharkhand, Madhya Pradesh, and Maharashtra. The remaining 103 FCMs were obtained from 103 district project coordinators, who had agreed to participate in the study. Unlike most FCM-based studies, which usually rely upon 30 to 50 participants, this study involved 174 experts and project implementers. Most participants produced FCMs individually and some in pairs. The 174 participants produced 160 FCMs.

The participants were given the instrument and were instructed to assign weights to each concept, wherever applicable, and leave other cells blank. These weights were assigned based on the concepts’ significance regarding poverty alleviation in India. The instrument was designed to allow participants to add new concepts and/or remove existing ones from the instrument based on their understanding and perceptions. Later, the participants were asked to assign weights to all pre-established links between the 22 concept categories. The instrument also allowed participants to draw new linkages between the categories and/or discard the existing relationships based on their understanding and perceptions. After constructing the FCMs each participant made a presentation to the researchers, which was video-recorded. During the process, participants added 55 new concepts within the pre-classified 22 concept categories. Five new concepts were added under a new category. The final data comprised 23 concept categories and 155 concepts ( S3 Fig ).

2.2. Coding individual cognitive maps into adjacency matrices

The individual FCMs were coded into separate excel sheets, with concepts listed in vertical and horizontal axes, forming an N x N adjacency matrix. The weights of the links, on a scale of 1−10, were normalised in the −1 to +1 range [ 62 , 63 ]. The values were then coded into a square adjacency matrix whenever a connection existed between any two concepts [ 60 , 62 – 64 , 66 ].

2.3. Aggregation of individual cognitive maps

This aggregation approach has been adopted by many researchers [ 59 , 60 , 63 – 67 , 74 , 79 , 84 – 87 ]. A large number of concepts in an aggregated (social/ group) fuzzy cognitive map with many interconnections and feedback form a complex system. Aggregation of all the 160 individual cognitive maps produced a social cognitive map ( S1 Table ). This shows the cumulative strength of the system.

2.4. Structural analysis of the system

Structural analysis of the final condensed social cognitive map was undertaken using the FCMapper software. The graph theory of a cognitive map provides a way of characterising FCM structures employing several indices in addition to the number of concepts (C) and links (W) such as in-degree, out-degree, centrality, complexity index, and density index [ 60 ].

The degree centrality of a concept is the summation of its in-degree and out-degree. The higher the value, the greater is the importance of a concept in the overall model [ 60 ].

Transmitter concepts (T) depict positive out-degree and zero in-degree. Receiver concepts (R) represent positive in-degree and zero out-degree. Ordinary concepts (O) have both a non-zero in-degree and out-degree [ 60 ].

2.5. Fuzzy cognitive maps-based simulations

The scenarios formed through FCM-based simulations can serve to guide managers and policy-makers during the decision-making process [ 62 – 64 , 66 , 69 , 82 , 88 – 90 ]. An FCM is formed out of the adjacency matrix and a state vector, representing the values of the connections between the concepts and the values of the system concepts [ 62 , 63 , 69 ]. The weighted adjacency matrix of an FCM forms a recurrent neural network, including concepts and interconnections for processing the information and feedback loops [ 88 , 91 ]. These have been used to analyse system behavior by running FCM-based simulations in order to determine possible future scenarios.

In order to understand FCM-based simulations, let us understand the FCM as a quadruple, i.e. M = (C n , W , A , f) , where, n is the set of all concepts ( C ) in the map, W : ( C i , C j ) → w ij is a function which defines the causal weight matrix, W M × M , A : ( C i ) → A ( t ) i is a function that computes the activation degree of each concept C i at the discrete-time step t ( t = 1, 2, …, T ), and f (.) is the transfer function [ 63 , 71 , 92 , 93 ]. Knowledge and experience of stakeholders regarding the system determine the type and number of concepts as well as the weights of the links in FCMs. The value A i of a concept C i , expresses the quantity of its corresponding value. With values assigned to the concepts and weights, the FCM converges to an equilibrium point [ 71 , 91 ]. At each step, the value A i of a concept is calculated, following an activation rule, which computes the influence of other concepts to a specific concept.

Where, n is the total number of concepts, A i ( t +1) is the value of concept C i at simulation step t +1, A i ( t ) is the value of concept C i at simulation step t , A j ( t ) is the value of concept C j at simulation step t , w ji is the weight of the interconnection between concept C j and concept C i , and f is the transformation function [ 64 , 90 ]. The restriction i ≠ j is used when self-causation is assumed to be impossible [ 91 ].

2.5.1. Development of input vectors for policy scenarios.

Identifying pivotal concepts is a traditional approach in scenario planning that helps linking storylines to the quantitative model [ 96 ]. In the FCM-based scenario analysis, recognition of such pivotal concepts, termed as input vectors, mainly relies upon participants’ perceptions along with the characteristics of the model. We identified four input vectors for four poverty alleviation policy scenarios based on existing literature on poverty alleviation strategies. The fifth input vector is based on the concepts with the highest weights identified by the participants. In the sixth input vector, the concept representing entrepreneurship is replaced by the concept representing livelihood diversification considering its importance based on existing literature [ 15 , 40 ]. All six scenarios are explained below:

Scenario 1 : High-quality community organisation based micro-financing —Input vector 1: C2, C3, C4, C5, C11, and C12 (strong institutions of the poor, community heroes driving the programme, capacity building of the community organisations, mainstream financial institutions supporting community organisations, need-based finance, and developing repayment culture). This scenario tries to examine how high-quality community organisation based micro-finance could alleviate poverty.

Scenario 2 : Capabilities and social security —Input vector 2: C19, C20, C21, C22, and C23 (affordable and approachable education and healthcare, social inclusion, building personal assets, adequate knowledge base, and vulnerability reduction). This scenario tries to estimate how improving the capabilities of the poor and providing them social security would help alleviate poverty.

Scenario 3 : Market-based approach —Input vector 3: C13, C14, C15, C16, and C17 (livelihood diversification, entrepreneurship, multi-sectoral collective enterprise, value addition by collectives, and market linkages). This scenario tries to evaluate how a market-based approach could alleviate poverty.

Scenario 4 : Good governance approach —Input vector 4: C6, C7, C8, C9, and C10 (good governance systems and processes, robust monitoring mechanisms, implementation process, linkages/ convergence/ partnerships, and enabling policy & political will). This scenario tries to evaluate how good governance is crucial for poverty alleviation.

Scenario 5 : Integrative approach 1 —Input vector 5: C2, C3, C6, C9, C10, C14, and C19 (strong institutions of the poor, community heroes driving the programme, sound governance systems and processes, enabling policy & political will, linkages/ convergence/ partnerships, entrepreneurship, and affordable and approachable education and healthcare). This scenario tries to assess how the most critical concepts, identified by the participants, are crucial for poverty alleviation.

Scenario 6 : Integrative approach 2 —Input vector 6: C2, C3, C6, C9, C10, C13, and C19 (strong institutions of the poor, community heroes driving the programme, good governance systems and processes, enabling policy & political will, linkages/ convergence/ partnerships, livelihood diversification, and affordable and approachable education and healthcare). This scenario tries to assess how the most important concepts, including livelihood diversification, are critical for the alleviation of poverty. Based on the relative weights, scenarios 4 to 6 also had alternative input vectors incorporating sensitive support structure (C1) without any demonstrable results.

2.5.2. Simulation process.

Each concept in the system has an initial state vector A 0 that varies from 0 to |1|. which is associated with an activation vector, where 0 means ‘non-activated’ and |1| means ‘activated’ [ 65 , 80 ]. A new state of the concepts can be calculated by multiplying the adjacency matrix with the state vector [ 69 ]. When one or more concepts are ‘activated’ this activation spreads through the matrix following the weighted relationships. During the simulation process, each iteration produces a new state vector with ‘activated’ concepts and ‘non-activated’ concepts. Self-loops and feedback cause a repeated activation of concepts, introducing non-linearity to the model [ 61 , 70 , 88 ]. The activation of concepts is iterated, using a ‘squashing function’ to rescale concept values towards |1|, until the vector values stabilise and the model reaches equilibrium or steady-state [ 61 , 65 , 70 ]. The resulting concept values may be used to interpret outcomes of a particular scenario and to study the dynamics of the modeled system [ 61 – 63 , 70 ].

The simulation process is carried out with the initial state vector of the input vectors, identified in each scenario (1 to 6), clamped to 1 ( A 1 ) and the initial state vector of all the other concepts clamped to 0 ( A 0 ). We applied the activation rule proposed by Stylios [ 94 ], to run simulations because of its memory capabilities along with the sigmoid transformation function as the links have only positive values. The sensitivity of the system was analysed by clamping the concepts of each input vector to 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, and 0.9 ( S4 Fig ) to determine whether the system behaves in a similar manner in each simulation [ 62 , 63 , 72 , 89 ].

3. Results and discussions

3.1. key features of the fcm system in the context of poverty alleviation.

The social cognitive map built by combining the individual FCMs comprises 23 concepts and 51 links ( Fig 2 and S1 Table ). This FCM system has a density index of 0.088, which signifies that 8.8% links are actually made of the maximum number of links that could theoretically exist between the 24 concepts. The FCM system has a complexity index of 0.125, which showcases more utility outcomes and less controlling forcing functions. However, unless the density and complexity values of the FCM system are compared to those of other FCM systems representing a similar topic, interpretation of these figures is challenging [ 75 ].

There are some autonomous concepts virtually disengaged from the system. Some dependent concepts although have a relatively low degree of influence, exhibit strong dependence. The contribution of a concept in a cognitive map can be understood by its degree centrality, which is the summation of in-degree and out-degree. Table 1 illustrates the in-degree and out-degree and degree centrality of the FCM system. Concepts have been depicted such as C2: strong institutions of the poor, C15: multi-sectoral collective enterprise development, C13: livelihood diversification and C14: entrepreneurship have higher degree centrality. These concepts should be interpreted as the greatest strength of poverty alleviation strategies. The most influential concepts (i.e., those with the highest out-degree) affecting the poverty alleviation strategies are C6: good governance systems and processes, C19: affordable and approachable education and healthcare, C18: climate-smart production systems, C2: strong institutions of the poor, and C5: mainstream financial institutions supporting CBOs. Scenario analysis results will later help us gain a deeper understanding of the connectivity and influencing concepts of poverty alleviation.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0227176.t001

The participants also provided the state vector values (A) of all the concepts (C) based on their understanding of the relative significance of these concepts regarding poverty alleviation in India ( Fig 1 ).

https://doi.org/10.1371/journal.pone.0227176.g001

The results show that participants assigned greater significance to the following concepts- C3: community heroes driving the programme, C1: quality support structure, C19: affordable and approachable education and healthcare, C6: good governance systems and processes, C2: strong institutions of the poor, C12: developing repayment culture, and C7: robust monitoring mechanisms.

The results acknowledge that building strong institutions of the poor for a community-demand-driven and community-managed poverty alleviation programme is likely to enjoy greater success. They also confirm that developing robust monitoring mechanisms can ensure better functioning of the community-based organisations (CBOs). Robust governance systems and processes are essential for vibrant CBOs. They can empower communities to have better access to affordable education and healthcare facilities. Better access to micro-finance for these CBOs could help alleviate the economic poverty of the poor and vulnerable communities.

The results, however, fail to capture the cultural and social dimensions of poverty.

3.2. Understanding the poverty alleviation strategy

This section summarises the views of participants across the concepts based on the presentations made by them to the researcher during both the stages of knowledge capture. Fig 2 illustrates the cognitive interpretive diagram formed using the social cognitive map. The concepts, represented by each node in the diagram, are connected by several links. These links establish relationships between the concepts representing the basis of degree centrality. The central concept is people coming out of poverty, which is depicted with yellow color in Fig 2 .

Participants indicated that setting up a quality and dedicated support structures at multiple levels (national, state, district, and block) is essential for poverty alleviation ( Fig 2 : C1). The support structures should be staffed with professionally competent and dedicated human resources. The crucial role of these support structures is to build and nurture strong institutions of the poor ( Fig 2 : C2) at multiple levels and evanesce when community heroes start driving the programme. Building and sustaining strong, inclusive, self-managed, and self-reliant institutions of the poor at various levels such as self-help groups (SHGs), village organisations (VOs), and cluster-level federations (CLFs) through training, handholding, and systematic guidance are crucial to the success of a poverty alleviation programme. However, superior CBOs are required to ensure the quality of primary-level institutions and their sustainability. Adherence to the five principles (regular meetings, regular savings, regular inter-loaning, timely repayment of the loans, and up-to-date books of accounts), co-ordination, and cohesiveness between the members would go a long way in building strong institutions of the poor.

https://doi.org/10.1371/journal.pone.0227176.g002

Participants emphasised the importance of community heroes in driving the poverty alleviation programme ( Fig 2 : C3). The poverty eradication programme is likely to meet with greater success if it is entirely operated and managed by the community. Involving experienced community members for social mobilisation, capacity building and scaling-up of various processes within the project will ensure effective functioning and implementation of the programme. Participants believed that the capacity building of the CBOs, community resource persons, community cadres, and community service providers ( Fig 2 : C4) are essential for poverty alleviation. Apart from training in social and financial inclusion, these community members should be provided with knowledge, skills, and tools to improve their existing livelihoods and for managing innovative livelihood collectives and micro-enterprises. Providing access to financial services to society’s most vulnerable group in a cost-effective manner through mainstream financial institutions and allowing the poor to become preferred clients of the banking system is fundamental to the financial inclusion strategy of a poverty alleviation programme ( Fig 2 : C5). The SHG-bank linkage enables an easy access to micro-finance for the SHGs. It also serves to foster their faith towards the banking system.

Good governance systems and processes are crucial to building sensitive support structures and strong institutions of the poor ( Fig 2 : C6). A well-structured process for participatory identification of the poor by the community helps identify very poor, poor, vulnerable, tribal, differently-abled, and other marginalised communities in a village. A robust process for grading the quality of SHGs and their federations could help maintain a high standard for these institutions. Strong, robust, and transparent monitoring mechanisms ( Fig 2 : C7) could ensure good governance systems and processes. The process-oriented approach of the programme needs to undergo continuous review, assessment, and course-correction from the qualitative and quantitative progress achieved at various levels. Hence, participants suggested that a robust ICT-based monitoring and evaluation system remain in place for facilitating informed decision-making at all levels. The participants also indicated the urgency of robust implementation of institutional accountability and a self-monitoring process in institutions of the poor at all levels, including peer internal review mechanisms, external social auditing, public expenditure tracking, and community scorecards, in order to build stronger institutions of the poor ( Fig 2 : C8). Transparency in the functioning of human resources at all levels aided by regular meetings, reviews, and monitoring of progress could ensure effective implementation of the programme. Maintaining equity and transparency in releasing finances and ensuring effective fund utilisation across all eligible groups could also help focus on the most vulnerable groups.

The participants believed that a poverty alleviation programme should have a strong convergence with other welfare programmes ( Fig 2 : C9). Stronger emphasis should be placed on convergence for developing synergies directly and through the institutions of the poor. Participants suggested that the programme recognise the importance of engaging with industries to set up platforms for public-private-partnerships in farm and non-farm sectors while developing various sector-specific value chains to harness the comparative advantage of the micro-enterprise sector. The political will to support and encourage CBOs, enabling policies for smooth and efficient working of the institutions of the poor, diminished political influence in the decision-making of CBOs, and timely and adequate resource allocation on the part of government institutions is critical for poverty alleviation programmes ( Fig 2 : C10).

Participants acknowledged that livelihood augmentation requires customised need-based financing for the poor and vulnerable ( Fig 2 : C11). Access to micro-finance at affordable rates of interest coupled with desired amounts and convenient repayment terms are needed for the poverty reduction of communities. Providing interest subvention for all SHG loans availed from mainstream financial institutions, based on prompt loan repayment, helps develop a healthy loan repayment culture ( Fig 2 : C12).

Participants opined that diversification of livelihoods would ensure steady incomes for households ( Fig 2 : C13). The development of micro-enterprise in farm and non-farm sectors could encourage institutions of the poor in the aggregation of produce, value-addition, and marketing of finished goods. Therefore, it is imperative that more and more sustainable enterprises be created by the poor to improve their livelihood security. The demand-driven entrepreneurship ( Fig 2 : C14) programmes could be taken up through public-private-partnerships. Provisions could be made for incubation funds and start-up funds for the development of multi-sectoral livelihood collectives ( Fig 2 : C15) to foster a collective entrepreneurship spirit. Livelihood activities, in order to be commercially viable, would require economy of scale, enabling the adoption of available technologies while providing better bargaining power, offering a more significant political clout, and influencing public policy over time. Building specialised multi-sectoral collective institutions of the poor, such as producers’ companies and co-operatives could make the latter key players in the market. These livelihood institutions could carry out participatory livelihood mapping and integrated livelihood planning as well as build robust livelihood clusters, supply chains, and value chains. They could also identify gaps in the supply and value chains, create backward and forward linkages, and tap market opportunities for intervention and collectivisation for chosen livelihood activities ( Fig 2 : C16; C17). Developing adequate and productive infrastructure for processing, storage, packaging, and transportation is crucial for value addition ( Fig 2 : C16). The demand-based value chain development is currently evident in micro-investment planning processes. Identifying non-farm activities to support enterprises in a comprehensive way could also be crucial. Adequate market linkages and support services like branding, market research, market knowledge, market infrastructure, and backward linkages would go a long way in deriving optimum returns from the chosen livelihood activities ( Fig 2 : C17).

Several eco-friendly, climate-smart, and innovative approaches in agriculture production systems will ensure the sustainability of production systems even in the context of climate change ( Fig 2 : C18). Contemporary grassroots innovations supplemented by robust scientific analysis, mainly supported by various government programmes, are likely to ensure enhanced and efficient production systems. Focus on developing adequate infrastructure for processing, storing, and transporting for value addition would serve to reduce post-harvest losses.

Participants believed that affordable and approachable quality education up to the secondary level as well as affordable and quality healthcare facilities are crucial for poverty alleviation ( Fig 2 : C19). Convergence with mid-day-meal schemes will not only encourage communities to send their children to schools but also help curb malnutrition. An affordable and approachable healthcare system is likely to help reduce health-related vulnerabilities of the poor. Crucial is an approach that identifies all needy and poor households while primarily focussing on vulnerable sections like scheduled castes, scheduled tribes, particularly vulnerable tribal groups, single women and women-headed households, disabled, landless, migrant labor, isolated communities, and those living in disturbed areas. Equally crucial is including them in institutions of the poor ( Fig 2 : C20). Customised micro-financing coupled with adequate instruments on healthcare and education could aid vulnerability reduction ( Fig 2 : C23). The social, human, and personal assets created by developing institutions of the poor are crucial for sustaining and scaling-up of the poverty alleviation programme ( Fig 2 : C21). This will also allow women to articulate their problems and improve their self-confidence, enhance their respect in society, develop leadership qualities, inspire them to speak and express their feelings unhesitatingly, and empower them economically and socially. Developing an academic understanding of the factors that support community institutions is crucial for the social infrastructure developed to facilitate the social capital building of the poor and vulnerable communities ( Fig 2 : C22).

3.3. FCM-based simulations

In order to evaluate critical factors responsible for poverty alleviation, we used six input vectors for FCM-based simulations. For each scenario, causal propagation occurs in each iteration until the FCM system converges [ 62 – 65 , 67 , 70 , 91 ]. This happens when no change takes place in the values of a concept after a certain point, also known as the system steady-state; the conceptual vector at that point is called the final state vector [ 62 – 65 , 67 , 70 , 91 ]. Values of the final state vectors depend on the structure of the FCM system and concepts considered for input vectors. The larger the value of the final state vectors, the better the selected policies [ 62 – 65 ]. Comparisons between the final state vectors of the alternative simulations are drawn in order to assess the extent of the desired transition by activating each set of input vectors. The initial values and final state vectors of all the concepts for every scenario are presented in Table 2 . The graphical representation of various scenarios for poverty alleviation is provided in the S5 Fig .

https://doi.org/10.1371/journal.pone.0227176.t002

The first scenario highlights the effects of high-quality community organisations based micro-financing approach. If strong institutions of the poor are built and community heroes start driving the poverty alleviation programme, capacity building of the CBOs gets underway. If mainstream financial institutions start supporting CBOs while customised need-based finance and a repayment culture is developed significant efforts would still be required for putting good governance systems and processes in place along with linkages/ convergences/ partnerships along with other schemes while building capabilities of the poor. In the case of successful micro-financing, there will be opportunities for livelihood diversification, entrepreneurship, multi-sectoral collective enterprise development, value addition by collectives, and market linkages.

The second scenario highlights the effects of the capabilities approach and social security. In this case, affordable and approachable education and healthcare, social inclusion, the building of personal assets, adequate knowledge base, and vulnerability reduction are ensured. In this context, ample efforts will be required for mainstream financial institutions supporting CBOs, good governance systems and processes, and linkages/ convergences/ partnerships with other schemes. Efforts will also be required for a quality support structure and customised need-based finance. The capability and social security enhancement could have prospects for strong institutions of the poor, better implementation processes, livelihood diversification, entrepreneurship, value addition by collectives, multi-sectoral collective enterprise development, and vulnerability reduction.

The third scenario highlights the outcomes of the market-based approach. Here, livelihood diversification, entrepreneurship, multi-sectoral collective enterprise development, value addition by collectives, and market linkages are activated. In such a situation, adequate efforts will be required for mainstream financial institutions supporting CBOs, good governance systems and processes, and linkages/ convergences/ partnerships with other schemes. Efforts will also be required for continuous capacity building of the CBOs, customised need-based finance, affordable and approachable education and healthcare, and vulnerability reduction.

The fourth scenario highlights the outcomes of good governance. Here, good governance systems and processes, robust monitoring mechanisms, implementation processes, enabling policies and political will, and linkages/ convergence/ partnership with other governmental schemes are ensured. In such a situation, plentiful efforts will be required for mainstream financial institutions to lend their support to CBOs and for the building of personal assets. Efforts will also be required for developing a repayment culture, climate-smart production systems, and vulnerability reduction. Good governance is likely to ensure strong institutions of the poor, development of collective enterprises, livelihood diversification, entrepreneurship, value addition by collectives, and market linkages.

In the fifth and sixth scenarios, we activated the most important concepts identified by the participants. The sixth scenario is similar to the fifth one except that the concept C14: entrepreneurship has been replaced by the concept C13: livelihood diversification. The simulation results reveal that quality of CBOs, strong institutions of the poor, community heroes driving the programme, good governance systems and processes, convergence with other schemes/ programmes, enabling policies and political will, and livelihood diversification are very critical for poverty alleviation in a developing nation.

The participants judged a relatively higher weight for the concept C1 (sensitive support structure) ( Fig 1 ). This could be attributed to a conflict of interest on the part of the participants. Even after activating the concept C1 across policy scenarios 4 to 6, the outcome does not change. This also justifies the fact that any community-demand-driven and community-managed poverty alleviation programme has to be self-sustainable in the long-term. Therefore, while a poverty alleviation programme may make use of a support structure in its initial phase, it should persist at thriving even after the support structure has been withdrawn.

4. Contributions to FCM and poverty literature and future research directions

This section deals with contributions of the paper to FCM and poverty literature while offering a practical approach to address multi-dimensional poverty. The paper makes a two-fold contribution to FCM literature: i) knowledge capture and sample adequacy and ii) robustness of the dynamic system model. FCM sampling is often extended if additional maps keep adding new dimensions/ insights. The saturation of FCM sampling is formally measured by tracking the number of new concepts introduced in subsequent exercises and estimating an accumulation curve of concepts. When the point of saturation is reached data collection is stopped. In most studies, the saturation of FCM sampling is reported at 30–32 maps [ 60 , 62 , 63 , 66 , 72 ]. This study does demonstrate, however, that in the event of a ‘mixed-concept design’ approach when the participants gain access to concepts already identified by other sets of participant groups the latter participants continue to add new concepts, making the system much more complex and the data richer. Most FCM-based case studies published in scientific journals have taken weights of the causal interactions between the concepts. This study has not only obtained weights of the causal interactions between the concepts but also obtained weights of each concept. Results of the FCM-based simulations, by and large, match with the most critical concepts identified by participants represented by higher relative weights. This demonstrates in-depth understanding of participants of the subject matter and robustness of the system.

Scenarios are defined as ‘a plausible description of how the future may develop based on a coherent and internally consistent set of assumptions’ [ 97 ]. It also represents uncertainty as a range of plausible futures. Hence, in order to establish proper causal pathways of various poverty eradication approaches, it may be necessary to design random control trial experiments along each of the poverty eradication approaches and carry out the efficacy of each approach delineated above using the difference-in-difference micro-econometric model.

5. Conclusions

The results of our FCM-based simulations reveal that in order to eradicate poverty one needs to provide micro-finance through high-quality community organisations, enhance capabilities of the poor while providing social safety nets to the poor and vulnerable, ensure good governance within community organisations and institutions supporting them, continue to diversify livelihood options, and provide market linkages to small producers. Our findings confirm that various approaches to poverty alleviation are rather complementary and need to be implemented simultaneously for a comprehensive poverty alleviation drive. However, in relative terms, factors like good governance within community organisations and supporting institutions, high-quality community organisations based micro-financing, and enhancement of capabilities coupled with social security assurance seem to work better than a market-based approach. There is rich literature available on radical approaches like land reforms, decentralisation and poverty alleviation that have not been evaluated in this study. Nevertheless, findings of the study lead us to conclude that in order to address multi-dimensional poverty an integrated and multi-dimensional poverty alleviation approach is needed. Findings of the study are likely to help improve the design, management, and implementation of poverty eradication programmes in developing countries.

Supporting information

S1 fig. a simple fcm obtained during the workshop conducted in phase 1..

https://doi.org/10.1371/journal.pone.0227176.s001

S2 Fig. The survey instrument used during phase 2 of the data collection.

https://doi.org/10.1371/journal.pone.0227176.s002

S3 Fig. A list of all the concept categories and sub-concepts after data collection.

https://doi.org/10.1371/journal.pone.0227176.s003

S4 Fig. Sensitivity analysis of the system.

https://doi.org/10.1371/journal.pone.0227176.s004

S5 Fig. Various scenarios for poverty alleviation.

https://doi.org/10.1371/journal.pone.0227176.s005

S1 Table. Social cognitive map.

https://doi.org/10.1371/journal.pone.0227176.s006

Acknowledgments

We thank the World Bank team and functionaries of DAY-NRLM at national, state, and district levels for participating in the study. Indrani Talukdar is acknowledged for language editing. We thank the Academic Editor and the two anonymous reviewers for providing insightful comments and constructive suggestions.

• 1. World Bank. The World Bank: Annual Report 2015. The World Bank, Washington, DC, USA. 2015.
• View Article
• Google Scholar
• 4. Sen AK. Social exclusion: concept, application, and scrutiny. Social Development Papers No. 1. 2000. Office of Environment and Social Development, Asian Development Bank. Manila, Philippines. ISBN: 971-561-274-1.
• 5. UNDP. Eradicate extreme poverty and hunger: where do we stand? The United Nations Development Programme (UNDP), New York, USA. 2014.
• 6. United Nations. Transforming our world: the 2030 Agenda for Sustainable Development. The UN General Assembly, A/RES/70/1. 2015. Available at: https://www.refworld.org/docid/57b6e3e44.html
• 9. Bhagwati J, Panagariya A. Reforms and economic transformation in India. Series: Studies in Indian Economic Policies. New York: Oxford University Press. 2012. ISBN:978–0–19–991520–0.
• 11. Bank World. World Development Report 2000/2001: Attacking Poverty. World Development Report. Oxford University Press. New York, Washington, DC, USA. 2001.
• 15. World Bank. Finance for all? Policies and pitfalls in expanding access. World Bank Policy Research Report. The World Bank, Washington, DC, USA. 2007.
• PubMed/NCBI
• 22. Wright GAN. Micro-finance Systems: designing quality financial services for the poor. Zed Books Ltd. London & New York, USA, and The University Press Limited, Dhaka, Bangladesh. 2000.
• 27. Sen AK. Commodities and capabilities. Oxford, Elsevier Science Publishers. Amsterdam, North-Holland. 1985b.
• 28. Sen AK. Capability and well-being. In: Nussbaum MC, Sen AK, editors. The Quality of Life: Oxford, Clarendon Press; 1993. pp. 30–53.
• 34. World Bank. World Development Report 1990: Poverty. Oxford University Press. New York, Washington, DC, USA. 1990.
• 36. World Bank. Safety net programs and poverty reduction: lessons from cross-country experience. The World Bank, Washington, DC, USA. 1997.
• 44. World Bank. Growing the rural non-farm economy to alleviate poverty: an evaluation of the contribution of the World Bank Group. The World Bank, Washington, DC, USA. 2017.
• 52. Khan MH. Governance, economic growth, and development. DESA Working Paper No.75. New York: UN Department of Economic and Social Affairs. 2009.
• 53. Earle L, Scott Z. Assessing the evidence of the impact of governance on development outcomes and poverty reduction. GSDRC Issues Paper. Birmingham: Governance and Social Development Resource Centre, University of Birmingham. 2010.
• 85. Kosko B. Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence/book and disk. Prentice Hall, Upper Saddle River. 1992a.
• 86. Kosko B. Neural networks for signal processing. Prentice Hall, Inc. 1992b.
• 94. Stylios CD, Georgopoulos VC, Groumpos PP, editors. The use of fuzzy cognitive maps in modeling systems. In: Proceedings of 5th IEEE Mediterranean conference on control and systems; 1997; Paphos, Cyprus; pp 21–23. 1997.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List

Evaluating poverty alleviation strategies in a developing country

Pramod k. singh.

Institute of Rural Management Anand (IRMA), Anand, Gujarat, India

Harpalsinh Chudasama

Associated data.

All relevant data are within the manuscript and its Supporting Information files. The aggregated condensed matrix (social cognitive map) is given in S1 Table . One can replicate the findings of this study by analyzing this weight matrix.

A slew of participatory and community-demand-driven approaches have emerged in order to address the multi-dimensional nature of poverty in developing nations. The present study identifies critical factors responsible for poverty alleviation in India with the aid of fuzzy cognitive maps (FCMs) deployed for showcasing causal reasoning. It is through FCM-based simulations that the study evaluates the efficacy of existing poverty alleviation approaches, including community organisation based micro-financing, capability and social security, market-based and good governance. Our findings confirm, to some degree, the complementarity of various approaches to poverty alleviation that need to be implemented simultaneously for a comprehensive poverty alleviation drive. FCM-based simulations underscore the need for applying an integrated and multi-dimensional approach incorporating elements of various approaches for eradicating poverty, which happens to be a multi-dimensional phenomenon. Besides, the study offers policy implications for the design, management, and implementation of poverty eradication programmes. On the methodological front, the study enriches FCM literature in the areas of knowledge capture, sample adequacy, and robustness of the dynamic system model.

1. Introduction

1.1. poverty alleviation strategies.

Although poverty is a multi-dimensional phenomenon, poverty levels are often measured using economic dimensions based on income and consumption [ 1 ]. Amartya Sen’s capability deprivation approach for poverty measurement, on the other hand, defines poverty as not merely a matter of actual income but an inability to acquire certain minimum capabilities [ 2 ]. Contemplating this dissimilarity between individuals’ incomes and their inabilities is significant since the conversion of actual incomes into actual capabilities differs with social settings and individual beliefs [ 2 – 4 ]. The United Nations Development Programme (UNDP) also emphasises the capabilities’ approach for poverty measurement as propounded by Amartya Sen [ 5 ]. “ Ending poverty in all its forms everywhere ” is the first of the 17 sustainable development goals set by the United Nations with a pledge that no one will be left behind [ 6 ]. Development projects and poverty alleviation programmes all over the world are predominantly aimed at reducing poverty of the poor and vulnerable communities through various participatory and community-demand-driven approaches [ 7 , 8 ]. Economic growth is one of the principal instruments for poverty alleviation and for pulling the poor out of poverty through productive employment [ 9 , 10 ]. Studies from Africa, Brazil, China, Costa Rica, and Indonesia show that rapid economic growth lifted a significant number of poor people out of financial poverty between 1970 and 2000 [ 11 ]. According to Bhagwati and Panagariya, economic growth generates revenues required for expanding poverty alleviation programmes while enabling governments to spend on the basic necessities of the poor including healthcare, education, and housing [ 9 ]. Poverty alleviation strategies may be categorised into four types including community organisations based micro-financing, capability and social security, market-based, and good governance.

Micro-finance, aimed at lifting the poor out of poverty, is a predominant poverty alleviation strategy. Having spread rapidly and widely over the last few decades, it is currently operational across several developing countries in Africa, Asia, and Latin America [ 12 – 21 ]. Many researchers and policy-makers believe that access to micro-finance in developing countries empowers the poor (especially women) while supporting income-generating activities, encouraging the entrepreneurial spirit, and reducing vulnerability [ 15 , 21 – 25 ]. There are fewer studies, however, that show conclusive and definite evidence regarding improvements in health, nutrition, and education attributable to micro-finance [ 21 , 22 ]. For micro-finance to be more effective, services like skill development training, technological support, and strategies related to better education, health and sanitation, including livelihood enhancement measures need to be included [ 13 , 17 , 19 ].

Economic growth and micro-finance for the poor might throw some light on the financial aspects of poverty, yet they do not reflect its cultural, social, and psychological dimensions [ 11 , 21 , 26 ]. Although economic growth is vital for enhancing the living conditions of the poor, it does not necessarily help the poor exclusively tilting in favour of the non-poor and privileged sections of society [ 4 ]. Amartya Sen cites social exclusion and capability deprivation as reasons for poverty [ 4 , 27 ]. His capabilities’ approach is intended to enhance people’s well-being and freedom of choices [ 4 , 27 ]. According to Sen, development should focus on maximising the individual’s ability to ensure more freedom of choices [ 27 , 28 ]. The capabilities approach provides a framework for the evaluation and assessment of several aspects of the individual’s well-being and social arrangements. It highlights the difference between means and ends as well as between substantive freedoms and outcomes. An example being the difference between fasting and starving [ 27 – 29 ]. Improving capabilities of the poor is critical for improving their living conditions [ 4 , 10 ]. Improving individuals’ capabilities also helps in the pooling of resources while allowing the poor to engage in activities that benefit them economically [ 4 , 30 ]. Social inclusion of vulnerable communities through the removal of social barriers is as significant as financial inclusion in poverty reduction strategies [ 31 , 32 ]. Social security is a set of public actions designed to reduce levels of vulnerability, risk, and deprivation [ 11 ]. It is an important instrument for addressing the issues of inequality and vulnerability [ 32 ]. It also induces gender parity owing to the equal sovereignty enjoyed by both men and women in the context of economic, social, and political activities [ 33 ].

The World Development Report 1990 endorsed a poverty alleviation strategy that combines enhanced economic growth with provisions of essential social services directed towards the poor while creating financial and social safety nets [ 34 , 35 ]. Numerous social safety net programmes and public spending on social protection, including social insurance schemes and social assistance payments, continue to act as tools of poverty alleviation in many of the developing countries across the world [ 35 – 39 ]. These social safety nets and protection programmes show positive impacts on the reduction of poverty, extent, vulnerability, and on a wide range of social inequalities in developing countries. One major concern dogging these programmes, however, is their long-term sustainability [ 35 ].

Agriculture and allied farm activities have been the focus of poverty alleviation strategies in rural areas. Lately, though, much of the focus has shifted to livelihood diversification on the part of researchers and policy-makers [ 15 , 40 ]. Promoting non-farm livelihoods, along with farm activities, can offer pathways for economic growth and poverty alleviation in developing countries the world over [ 40 – 44 ]. During the early 2000s, the development of comprehensive value chains and market systems emerged as viable alternatives for poverty alleviation in developing countries [ 45 ]. Multi-sectoral micro-enterprises may be deployed for enhancing productivity and profitability through value chains and market systems, they being important for income generation of the rural poor while playing a vital role in inclusive poverty eradication in developing countries [ 46 – 48 ].

Good governance relevant to poverty alleviation has gained top priority in development agendas over the past few decades [ 49 , 50 ]. Being potentially weak in the political and administrative areas of governance, developing countries have to deal with enormous challenges related to social services and security [ 49 , 51 ]. In order to receive financial aid from multinational donor agencies, a good governance approach towards poverty reduction has become a prerequisite for developing countries [ 49 , 50 ]. This calls for strengthening a participatory, transparent, and accountable form of governance if poverty has to be reduced while improving the lives of the poor and vulnerable [ 50 , 51 ]. Despite the importance of this subject, very few studies have explored the direct relationship between good governance and poverty alleviation [ 50 , 52 , 53 ]. Besides, evidence is available, both in India and other developing countries, of information and communication technology (ICT) contributing to poverty alleviation programmes [ 54 ]. Capturing, storing, processing, and transmitting various types of information with the help of ICT empowers the rural poor by increasing access to micro-finance, expanding the use of basic and advance government services, enabling the development of additional livelihood assets, and facilitating pro-poor market development [ 54 – 56 ].

1.2. Proposed contribution of the paper

Several poverty alleviation programmes around the world affirm that socio-political inclusion of the poor and vulnerable, improvement of social security, and livelihood enhancement coupled with activities including promoting opportunities for socio-economic growth, facilitating gender empowerment, improving facilities for better healthcare and education, and stepping up vulnerability reduction are central to reducing the overall poverty of poor and vulnerable communities [ 1 , 11 ]. These poverty alleviation programmes remain instruments of choice for policy-makers and development agencies even as they showcase mixed achievements in different countries and localities attributable to various economic and socio-cultural characteristics, among other things. Several poverty alleviation programmes continue to perform poorly despite significant investments [ 8 ]. The failure rate of the World Bank’s development projects was above 50% in Africa until 2000 [ 57 ]. Hence, identifying context-specific factors critical to the success of poverty alleviation programmes is vital.

Rich literature is available pertinent to the conceptual aspects of poverty alleviation. Extant literature emphasises the importance of enhancing capabilities and providing social safety, arranging high-quality community organisation based micro-financing, working on economic development, and ensuring good governance. However, the literature is scanty with regard to comparative performances of the above approaches. The paper tries to fill this gap. This study, through fuzzy cognitive mapping (FCM)-based simulations, evaluates the efficacy of these approaches while calling for an integrative approach involving actions on all dimensions to eradicate the multi-dimensional nature of poverty. Besides, the paper aims to make a two-fold contribution to the FCM literature: i) knowledge capture and sample adequacy, and ii) robustness of the dynamic system model.

The remainder of the paper proceeds as follows: We describe the methodology adopted in the study in section two. Section three illustrates key features of the FCM system in the context of poverty alleviation, FCM-based causal linkages, and policy scenarios for poverty alleviation with the aid of FCM-based simulations. We present our contribution to the extant literature relating to FCM and poverty alleviation. Finally, we conclude the paper and offer policy implications of the study.

2. Methodology

We conducted the study with the aid of the FCM-based approach introduced by Kosko in 1986 [ 58 ]. The process of data capture in the FCM approach is considered quasi-quantitative because the quantification of concepts and links may be interpreted in relative terms [ 59 ] allowing participants to debate the cause-effect relations between the qualitative concepts while generating quantitative data based on their experiences, knowledge, and perceptions of inter-relationships between concepts [ 60 – 64 , 65 – 68 ]. The FCM approach helps us visualise how interconnected factors/ variables/ concepts affect one another while representing self-loop and feedback within complex systems [ 62 , 63 , 69 ]. A cognitive map is a signed digraph with a series of feedback comprising concepts (nodes) that describe system behavior and links (edges) representing causal relationships between concepts [ 60 – 63 , 65 , 70 – 72 ]. FCMs may be created by individuals as well as by groups [ 60 , 72 , 73 ]. Individual cognitive mapping and group meeting approaches have their advantages and drawbacks [ 72 ]. FCMs allow the analysis of non-linear systems with causal relations, while their recurrent neural network behaviour [ 69 , 70 , 74 ] help in modelling complex and hard-to-model systems [ 61 – 63 ]. The FCM approach also provides the means to build multiple scenarios through system-based modelling [ 60 – 64 , 69 , 74 , 75 ].

The strengths and applications of FCM methodology, focussing on mental models, vary in terms of approach. It is important to remember, though, that (i) the FCM approach is not driven by data unavailability but is responsible for generating data [ 60 , 76 ]. Also that (ii) FCMs can model complex and ambiguous systems revealing hidden and important feedback within the systems [ 58 , 60 , 62 , 69 , 76 ] and (iii) FCMs have the ability to represent, integrate, and compare data–an example being expert opinion vis-à-vis indigenous knowledge–from multiple sources while divulging divergent viewpoints [ 60 ]. (iv) Finally, FCMs enable various policy simulations through an interactive scenario analysis [ 60 , 62 , 69 , 76 ].

The FCM methodology does have its share of weaknesses. To begin with: (i) Respondents’ misconceptions and biases tend to get encoded in the maps [ 60 , 62 ]. (ii) Possibility of susceptibility to group power dynamics in a group model-building setting cannot be ruled out; (iii) FCMs require a large amount of post-processing time [ 67 ]. (iv) The FCM-based simulations are non-real value and relative parameter estimates and lack spatial and temporal representation [ 60 , 77 , 78 ].

These drawbacks notwithstanding, we, along with many researchers, conceded that the strengths and applications of FCM methodology outweighed the former, particularly with regard to integrating data from multiple stakeholders with different viewpoints.

We adopted the multi-step FCM methodology discussed in the following sub-sections. We adopted the multi-step FCM methodology discussed in the following sub-sections. We obtained individual cognitive maps from the participants in two stages: ‘open-concept design’ approach followed by the ‘pre-concept design’ approach. We coded individual cognitive maps into adjacency matrices and aggregated individual cognitive maps to form a social cognitive map. FCM-based simulation was used to build policy scenarios for poverty alleviation using different input vectors.

2.1. Obtaining cognitive maps from the participants

A major proportion of the literature on fuzzy cognitive maps reflects an ‘open-concept design’ approach, while some studies also rely on a ‘pre-designed concept’ approach with regard to data collection.

In the case of the ‘open-concept design’ approach, concepts are determined entirely by participants and are unrestricted [ 59 , 60 , 62 , 63 , 65 – 67 , 79 , 80 ]. While the researcher determines the context of the model by specifying the system being modelled, including the boundaries of the system, participants are allowed to decide what concepts will be included. This approach provides very little restriction in the knowledge capture from participants and can be extremely beneficial especially if there is insufficient knowledge regarding the system being modelled.

In the case of the ‘pre-designed concept’ approach, concepts are pre-determined either by experts or by researchers using available literature [ 64 , 69 , 74 , 81 , 82 ]. In this approach, the researcher is able to exercise a higher degree of control over how the system is defined. The ‘pre-designed concept’ approach is likely to be more efficient compared to the ‘open-concept design’ in the context of time required for model building. However, it restricts the diversity of knowledge captured from participants and is able to influence more heavily the way in which this knowledge is contextualised based on input and interpretation.

We have adopted a ‘mixed-concept design’ approach for this study involving data collection in two stages:

2.1.1. Stage one: ‘Open-concept design’ approach

During the first stage, we engaged with the experts and national-level policy-makers who designed the Deendayal Antyodaya Yojana -National Rural Livelihoods Mission (DAY-NRLM), a centrally sponsored programme in India. The DAY-NRLM aims at abolishing rural poverty by promoting multiple livelihoods for the rural poor and vulnerable households. The programme is focussed on organising the rural poor and vulnerable communities into self-help groups (SHGs) while equipping them with means of self-employment. The four critical components of the programme viz ., (i) universal social mobilisation and institution building, (ii) financial inclusion, (iii) convergence and social development, and (iv) livelihood enhancement are designed to address the exclusions of these communities, eliminate their poverty, and bring them within the ambit of mainstream economic and social systems. Participants comprising three experts from the World Bank, nine experts from the National Mission Management Unit of the DAY-NRLM, and 25 monitoring and evaluation experts from 25 states of India created 37 FCMs. A sample map of FCMs obtained from these participants is provided in S1 Fig . We demonstrated the construction of fuzzy cognitive maps with the aid of a map from a neutral problem domain referring to direct and consequential impacts of deforestation, which had been approved by the ‘Research Ethics Committee’ of our Institute.

A group discussion was held with the participants regarding the issues under investigation subsumed under the title “critical factors required to ensure that people come out of poverty on a sustainable basis”. It prompted them to identify major concepts pertaining to the above. These were listed down on a whiteboard by the researchers. Once the participants had understood the process of drawing a fuzzy cognitive map and identified major concepts responsible for poverty alleviation, they were asked to draw a fuzzy cognitive map individually. The participants used the concepts listed on the whiteboard to draw fuzzy cognitive maps. Many participants added new concepts while drawing the maps. They then connected all the concepts through various links based on their personal understanding. The links, represented by arrows in between concepts, show the direction of influence between them.

The participants assigned weights to each link on a scale of 1–10 to describe the relationship strength between two concepts [ 60 ]. Ten denoted the highest strength and one the lowest; the numbers 1–3 signified relationships with low strength, 4–6 signified relationships with medium strength, and 7–10 signified relationships with high strength. After constructing the FCMs each participant made a presentation, which was video-recorded, explaining their map to the researchers. The researchers, based on causal relationships between the concepts, assigned positive and negative polarities to the weights of the links [ 59 , 60 , 62 – 64 , 66 – 68 , 72 ].

2.1.2. Stage two: ‘Pre-designed concept’ approach

During the second stage, an instrument depicting 95 concepts under 22 concept categories was prepared based on the FCMs obtained from participants during the first stage ( S2 Fig ). The instrument also contained links between the 22 concept categories. ‘Research Ethics Committee’ of our Institute approved this instrument as well. We used this instrument during the second stage to obtain FCMs. We obtained 123 additional FCMs, of which 20 FCMs were obtained from the Chief Executive Officers along with experts from livelihood, enterprise, and community development domains belonging to the National Mission Management Unit in the states of Bihar, Jharkhand, Madhya Pradesh, and Maharashtra. The remaining 103 FCMs were obtained from 103 district project coordinators, who had agreed to participate in the study. Unlike most FCM-based studies, which usually rely upon 30 to 50 participants, this study involved 174 experts and project implementers. Most participants produced FCMs individually and some in pairs. The 174 participants produced 160 FCMs.

The participants were given the instrument and were instructed to assign weights to each concept, wherever applicable, and leave other cells blank. These weights were assigned based on the concepts’ significance regarding poverty alleviation in India. The instrument was designed to allow participants to add new concepts and/or remove existing ones from the instrument based on their understanding and perceptions. Later, the participants were asked to assign weights to all pre-established links between the 22 concept categories. The instrument also allowed participants to draw new linkages between the categories and/or discard the existing relationships based on their understanding and perceptions. After constructing the FCMs each participant made a presentation to the researchers, which was video-recorded. During the process, participants added 55 new concepts within the pre-classified 22 concept categories. Five new concepts were added under a new category. The final data comprised 23 concept categories and 155 concepts ( S3 Fig ).

2.2. Coding individual cognitive maps into adjacency matrices

The individual FCMs were coded into separate excel sheets, with concepts listed in vertical and horizontal axes, forming an N x N adjacency matrix. The weights of the links, on a scale of 1−10, were normalised in the −1 to +1 range [ 62 , 63 ]. The values were then coded into a square adjacency matrix whenever a connection existed between any two concepts [ 60 , 62 – 64 , 66 ].

2.3. Aggregation of individual cognitive maps

There are various methods of aggregating individual FCMs; each method has advantages and disadvantages [ 83 ]. We aggregated individual adjacency matrices obtained by normalising each adjacency matrix element according to its decisional weight, w i , and the number of participants, k , who supported it. The following equation illustrates the augmentation of individual adjacency matrices:

M FCM is the aggregated adjacency matrix, where, k represents the number of participants interviewed; w i is the decisional weight of the expert i , where, ∑ i = 1 k w i = 1 ; and m i is the adjacency matrix written by the participant i .

This aggregation approach has been adopted by many researchers [ 59 , 60 , 63 – 67 , 74 , 79 , 84 – 87 ]. A large number of concepts in an aggregated (social/ group) fuzzy cognitive map with many interconnections and feedback form a complex system. Aggregation of all the 160 individual cognitive maps produced a social cognitive map ( S1 Table ). This shows the cumulative strength of the system.

2.4. Structural analysis of the system

Structural analysis of the final condensed social cognitive map was undertaken using the FCMapper software. The graph theory of a cognitive map provides a way of characterising FCM structures employing several indices in addition to the number of concepts (C) and links (W) such as in-degree, out-degree, centrality, complexity index, and density index [ 60 ].

The in-degree is the column sum of absolute values of a concept in the adjacency matrix. It shows the cumulative strength of links entering the concept ( w ji ). Where n = the total number of concepts:

The out-degree is the row sum of absolute values of a concept in the adjacency matrix. It shows the cumulative strengths of links exiting the concept ( w ij ). Where n = the total number of concepts:

The degree centrality of a concept is the summation of its in-degree and out-degree. The higher the value, the greater is the importance of a concept in the overall model [ 60 ].

Transmitter concepts (T) depict positive out-degree and zero in-degree. Receiver concepts (R) represent positive in-degree and zero out-degree. Ordinary concepts (O) have both a non-zero in-degree and out-degree [ 60 ].

The complexity index of a cognitive map is the ratio of receiver concepts (R) to transmitter concepts (T). Higher complexity indicates more complex systems thinking [ 60 ]:

The density index of a cognitive map is an index of connectivity showing how connected or sparse the maps are. It is a product of the number of concepts (C) and the number of links (W). Here the number of existing links is compared to the number of all possible links. Higher the density, greater the existence of potential management policies [ 60 ]:

2.5. Fuzzy cognitive maps-based simulations

The scenarios formed through FCM-based simulations can serve to guide managers and policy-makers during the decision-making process [ 62 – 64 , 66 , 69 , 82 , 88 – 90 ]. An FCM is formed out of the adjacency matrix and a state vector, representing the values of the connections between the concepts and the values of the system concepts [ 62 , 63 , 69 ]. The weighted adjacency matrix of an FCM forms a recurrent neural network, including concepts and interconnections for processing the information and feedback loops [ 88 , 91 ]. These have been used to analyse system behavior by running FCM-based simulations in order to determine possible future scenarios.

In order to understand FCM-based simulations, let us understand the FCM as a quadruple, i.e. M = (C n , W , A , f) , where, n is the set of all concepts ( C ) in the map, W : ( C i , C j ) → w ij is a function which defines the causal weight matrix, W M × M , A : ( C i ) → A ( t ) i is a function that computes the activation degree of each concept C i at the discrete-time step t ( t = 1, 2, …, T ), and f (.) is the transfer function [ 63 , 71 , 92 , 93 ]. Knowledge and experience of stakeholders regarding the system determine the type and number of concepts as well as the weights of the links in FCMs. The value A i of a concept C i , expresses the quantity of its corresponding value. With values assigned to the concepts and weights, the FCM converges to an equilibrium point [ 71 , 91 ]. At each step, the value A i of a concept is calculated, following an activation rule, which computes the influence of other concepts to a specific concept.

We have used an increasingly popular activation rule [ 61 – 64 , 90 , 91 ] introduced by Stylios [ 94 ], which is as follows:

Where, n is the total number of concepts, A i ( t +1) is the value of concept C i at simulation step t +1, A i ( t ) is the value of concept C i at simulation step t , A j ( t ) is the value of concept C j at simulation step t , w ji is the weight of the interconnection between concept C j and concept C i , and f is the transformation function [ 64 , 90 ]. The restriction i ≠ j is used when self-causation is assumed to be impossible [ 91 ].

The simulation outcomes also depend on the type of transformation function used. The most frequently used transformation functions (ƒ) are sigmoid and hyperbolic tangent functions [ 90 – 93 ]. When the values of concepts can only be positive, i.e. in the range of (0,1), the most common unipolar sigmoid transformation function is used [ 64 , 91 – 93 ]. Following is the mathematical equation of the sigmoid transformation function:

Where, 𝛌 is a real positive number (𝛌 > 0) and a constant value that determines the slope steepness factor, while, x is the value of concept A i ( t ) on the equilibrium point [ 64 , 93 ]. Higher values of 𝛌 increase the steepness and make it more sensitive to the changes of x . Hence, the derivative δ f δ x becomes higher when increasing the activation value [ 95 ].

2.5.1. Development of input vectors for policy scenarios

Identifying pivotal concepts is a traditional approach in scenario planning that helps linking storylines to the quantitative model [ 96 ]. In the FCM-based scenario analysis, recognition of such pivotal concepts, termed as input vectors, mainly relies upon participants’ perceptions along with the characteristics of the model. We identified four input vectors for four poverty alleviation policy scenarios based on existing literature on poverty alleviation strategies. The fifth input vector is based on the concepts with the highest weights identified by the participants. In the sixth input vector, the concept representing entrepreneurship is replaced by the concept representing livelihood diversification considering its importance based on existing literature [ 15 , 40 ]. All six scenarios are explained below:

Scenario 1 : High-quality community organisation based micro-financing —Input vector 1: C2, C3, C4, C5, C11, and C12 (strong institutions of the poor, community heroes driving the programme, capacity building of the community organisations, mainstream financial institutions supporting community organisations, need-based finance, and developing repayment culture). This scenario tries to examine how high-quality community organisation based micro-finance could alleviate poverty.

Scenario 2 : Capabilities and social security —Input vector 2: C19, C20, C21, C22, and C23 (affordable and approachable education and healthcare, social inclusion, building personal assets, adequate knowledge base, and vulnerability reduction). This scenario tries to estimate how improving the capabilities of the poor and providing them social security would help alleviate poverty.

Scenario 3 : Market-based approach —Input vector 3: C13, C14, C15, C16, and C17 (livelihood diversification, entrepreneurship, multi-sectoral collective enterprise, value addition by collectives, and market linkages). This scenario tries to evaluate how a market-based approach could alleviate poverty.

Scenario 4 : Good governance approach —Input vector 4: C6, C7, C8, C9, and C10 (good governance systems and processes, robust monitoring mechanisms, implementation process, linkages/ convergence/ partnerships, and enabling policy & political will). This scenario tries to evaluate how good governance is crucial for poverty alleviation.

Scenario 5 : Integrative approach 1 —Input vector 5: C2, C3, C6, C9, C10, C14, and C19 (strong institutions of the poor, community heroes driving the programme, sound governance systems and processes, enabling policy & political will, linkages/ convergence/ partnerships, entrepreneurship, and affordable and approachable education and healthcare). This scenario tries to assess how the most critical concepts, identified by the participants, are crucial for poverty alleviation.

Scenario 6 : Integrative approach 2 —Input vector 6: C2, C3, C6, C9, C10, C13, and C19 (strong institutions of the poor, community heroes driving the programme, good governance systems and processes, enabling policy & political will, linkages/ convergence/ partnerships, livelihood diversification, and affordable and approachable education and healthcare). This scenario tries to assess how the most important concepts, including livelihood diversification, are critical for the alleviation of poverty. Based on the relative weights, scenarios 4 to 6 also had alternative input vectors incorporating sensitive support structure (C1) without any demonstrable results.

2.5.2. Simulation process

Each concept in the system has an initial state vector A 0 that varies from 0 to |1|. which is associated with an activation vector, where 0 means ‘non-activated’ and |1| means ‘activated’ [ 65 , 80 ]. A new state of the concepts can be calculated by multiplying the adjacency matrix with the state vector [ 69 ]. When one or more concepts are ‘activated’ this activation spreads through the matrix following the weighted relationships. During the simulation process, each iteration produces a new state vector with ‘activated’ concepts and ‘non-activated’ concepts. Self-loops and feedback cause a repeated activation of concepts, introducing non-linearity to the model [ 61 , 70 , 88 ]. The activation of concepts is iterated, using a ‘squashing function’ to rescale concept values towards |1|, until the vector values stabilise and the model reaches equilibrium or steady-state [ 61 , 65 , 70 ]. The resulting concept values may be used to interpret outcomes of a particular scenario and to study the dynamics of the modeled system [ 61 – 63 , 70 ].

The simulation process is carried out with the initial state vector of the input vectors, identified in each scenario (1 to 6), clamped to 1 ( A 1 ) and the initial state vector of all the other concepts clamped to 0 ( A 0 ). We applied the activation rule proposed by Stylios [ 94 ], to run simulations because of its memory capabilities along with the sigmoid transformation function as the links have only positive values. The sensitivity of the system was analysed by clamping the concepts of each input vector to 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, and 0.9 ( S4 Fig ) to determine whether the system behaves in a similar manner in each simulation [ 62 , 63 , 72 , 89 ].

3. Results and discussions

3.1. key features of the fcm system in the context of poverty alleviation.

The social cognitive map built by combining the individual FCMs comprises 23 concepts and 51 links ( Fig 2 and S1 Table ). This FCM system has a density index of 0.088, which signifies that 8.8% links are actually made of the maximum number of links that could theoretically exist between the 24 concepts. The FCM system has a complexity index of 0.125, which showcases more utility outcomes and less controlling forcing functions. However, unless the density and complexity values of the FCM system are compared to those of other FCM systems representing a similar topic, interpretation of these figures is challenging [ 75 ].

There are some autonomous concepts virtually disengaged from the system. Some dependent concepts although have a relatively low degree of influence, exhibit strong dependence. The contribution of a concept in a cognitive map can be understood by its degree centrality, which is the summation of in-degree and out-degree. Table 1 illustrates the in-degree and out-degree and degree centrality of the FCM system. Concepts have been depicted such as C2: strong institutions of the poor, C15: multi-sectoral collective enterprise development, C13: livelihood diversification and C14: entrepreneurship have higher degree centrality. These concepts should be interpreted as the greatest strength of poverty alleviation strategies. The most influential concepts (i.e., those with the highest out-degree) affecting the poverty alleviation strategies are C6: good governance systems and processes, C19: affordable and approachable education and healthcare, C18: climate-smart production systems, C2: strong institutions of the poor, and C5: mainstream financial institutions supporting CBOs. Scenario analysis results will later help us gain a deeper understanding of the connectivity and influencing concepts of poverty alleviation.

The participants also provided the state vector values (A) of all the concepts (C) based on their understanding of the relative significance of these concepts regarding poverty alleviation in India ( Fig 1 ).

The results show that participants assigned greater significance to the following concepts- C3: community heroes driving the programme, C1: quality support structure, C19: affordable and approachable education and healthcare, C6: good governance systems and processes, C2: strong institutions of the poor, C12: developing repayment culture, and C7: robust monitoring mechanisms.

The results acknowledge that building strong institutions of the poor for a community-demand-driven and community-managed poverty alleviation programme is likely to enjoy greater success. They also confirm that developing robust monitoring mechanisms can ensure better functioning of the community-based organisations (CBOs). Robust governance systems and processes are essential for vibrant CBOs. They can empower communities to have better access to affordable education and healthcare facilities. Better access to micro-finance for these CBOs could help alleviate the economic poverty of the poor and vulnerable communities.

The results, however, fail to capture the cultural and social dimensions of poverty.

3.2. Understanding the poverty alleviation strategy

This section summarises the views of participants across the concepts based on the presentations made by them to the researcher during both the stages of knowledge capture. Fig 2 illustrates the cognitive interpretive diagram formed using the social cognitive map. The concepts, represented by each node in the diagram, are connected by several links. These links establish relationships between the concepts representing the basis of degree centrality. The central concept is people coming out of poverty, which is depicted with yellow color in Fig 2 .

Participants indicated that setting up a quality and dedicated support structures at multiple levels (national, state, district, and block) is essential for poverty alleviation ( Fig 2 : C1). The support structures should be staffed with professionally competent and dedicated human resources. The crucial role of these support structures is to build and nurture strong institutions of the poor ( Fig 2 : C2) at multiple levels and evanesce when community heroes start driving the programme. Building and sustaining strong, inclusive, self-managed, and self-reliant institutions of the poor at various levels such as self-help groups (SHGs), village organisations (VOs), and cluster-level federations (CLFs) through training, handholding, and systematic guidance are crucial to the success of a poverty alleviation programme. However, superior CBOs are required to ensure the quality of primary-level institutions and their sustainability. Adherence to the five principles (regular meetings, regular savings, regular inter-loaning, timely repayment of the loans, and up-to-date books of accounts), co-ordination, and cohesiveness between the members would go a long way in building strong institutions of the poor.

Participants emphasised the importance of community heroes in driving the poverty alleviation programme ( Fig 2 : C3). The poverty eradication programme is likely to meet with greater success if it is entirely operated and managed by the community. Involving experienced community members for social mobilisation, capacity building and scaling-up of various processes within the project will ensure effective functioning and implementation of the programme. Participants believed that the capacity building of the CBOs, community resource persons, community cadres, and community service providers ( Fig 2 : C4) are essential for poverty alleviation. Apart from training in social and financial inclusion, these community members should be provided with knowledge, skills, and tools to improve their existing livelihoods and for managing innovative livelihood collectives and micro-enterprises. Providing access to financial services to society’s most vulnerable group in a cost-effective manner through mainstream financial institutions and allowing the poor to become preferred clients of the banking system is fundamental to the financial inclusion strategy of a poverty alleviation programme ( Fig 2 : C5). The SHG-bank linkage enables an easy access to micro-finance for the SHGs. It also serves to foster their faith towards the banking system.

Good governance systems and processes are crucial to building sensitive support structures and strong institutions of the poor ( Fig 2 : C6). A well-structured process for participatory identification of the poor by the community helps identify very poor, poor, vulnerable, tribal, differently-abled, and other marginalised communities in a village. A robust process for grading the quality of SHGs and their federations could help maintain a high standard for these institutions. Strong, robust, and transparent monitoring mechanisms ( Fig 2 : C7) could ensure good governance systems and processes. The process-oriented approach of the programme needs to undergo continuous review, assessment, and course-correction from the qualitative and quantitative progress achieved at various levels. Hence, participants suggested that a robust ICT-based monitoring and evaluation system remain in place for facilitating informed decision-making at all levels. The participants also indicated the urgency of robust implementation of institutional accountability and a self-monitoring process in institutions of the poor at all levels, including peer internal review mechanisms, external social auditing, public expenditure tracking, and community scorecards, in order to build stronger institutions of the poor ( Fig 2 : C8). Transparency in the functioning of human resources at all levels aided by regular meetings, reviews, and monitoring of progress could ensure effective implementation of the programme. Maintaining equity and transparency in releasing finances and ensuring effective fund utilisation across all eligible groups could also help focus on the most vulnerable groups.

The participants believed that a poverty alleviation programme should have a strong convergence with other welfare programmes ( Fig 2 : C9). Stronger emphasis should be placed on convergence for developing synergies directly and through the institutions of the poor. Participants suggested that the programme recognise the importance of engaging with industries to set up platforms for public-private-partnerships in farm and non-farm sectors while developing various sector-specific value chains to harness the comparative advantage of the micro-enterprise sector. The political will to support and encourage CBOs, enabling policies for smooth and efficient working of the institutions of the poor, diminished political influence in the decision-making of CBOs, and timely and adequate resource allocation on the part of government institutions is critical for poverty alleviation programmes ( Fig 2 : C10).

Participants acknowledged that livelihood augmentation requires customised need-based financing for the poor and vulnerable ( Fig 2 : C11). Access to micro-finance at affordable rates of interest coupled with desired amounts and convenient repayment terms are needed for the poverty reduction of communities. Providing interest subvention for all SHG loans availed from mainstream financial institutions, based on prompt loan repayment, helps develop a healthy loan repayment culture ( Fig 2 : C12).

Participants opined that diversification of livelihoods would ensure steady incomes for households ( Fig 2 : C13). The development of micro-enterprise in farm and non-farm sectors could encourage institutions of the poor in the aggregation of produce, value-addition, and marketing of finished goods. Therefore, it is imperative that more and more sustainable enterprises be created by the poor to improve their livelihood security. The demand-driven entrepreneurship ( Fig 2 : C14) programmes could be taken up through public-private-partnerships. Provisions could be made for incubation funds and start-up funds for the development of multi-sectoral livelihood collectives ( Fig 2 : C15) to foster a collective entrepreneurship spirit. Livelihood activities, in order to be commercially viable, would require economy of scale, enabling the adoption of available technologies while providing better bargaining power, offering a more significant political clout, and influencing public policy over time. Building specialised multi-sectoral collective institutions of the poor, such as producers’ companies and co-operatives could make the latter key players in the market. These livelihood institutions could carry out participatory livelihood mapping and integrated livelihood planning as well as build robust livelihood clusters, supply chains, and value chains. They could also identify gaps in the supply and value chains, create backward and forward linkages, and tap market opportunities for intervention and collectivisation for chosen livelihood activities ( Fig 2 : C16; C17). Developing adequate and productive infrastructure for processing, storage, packaging, and transportation is crucial for value addition ( Fig 2 : C16). The demand-based value chain development is currently evident in micro-investment planning processes. Identifying non-farm activities to support enterprises in a comprehensive way could also be crucial. Adequate market linkages and support services like branding, market research, market knowledge, market infrastructure, and backward linkages would go a long way in deriving optimum returns from the chosen livelihood activities ( Fig 2 : C17).

Several eco-friendly, climate-smart, and innovative approaches in agriculture production systems will ensure the sustainability of production systems even in the context of climate change ( Fig 2 : C18). Contemporary grassroots innovations supplemented by robust scientific analysis, mainly supported by various government programmes, are likely to ensure enhanced and efficient production systems. Focus on developing adequate infrastructure for processing, storing, and transporting for value addition would serve to reduce post-harvest losses.

Participants believed that affordable and approachable quality education up to the secondary level as well as affordable and quality healthcare facilities are crucial for poverty alleviation ( Fig 2 : C19). Convergence with mid-day-meal schemes will not only encourage communities to send their children to schools but also help curb malnutrition. An affordable and approachable healthcare system is likely to help reduce health-related vulnerabilities of the poor. Crucial is an approach that identifies all needy and poor households while primarily focussing on vulnerable sections like scheduled castes, scheduled tribes, particularly vulnerable tribal groups, single women and women-headed households, disabled, landless, migrant labor, isolated communities, and those living in disturbed areas. Equally crucial is including them in institutions of the poor ( Fig 2 : C20). Customised micro-financing coupled with adequate instruments on healthcare and education could aid vulnerability reduction ( Fig 2 : C23). The social, human, and personal assets created by developing institutions of the poor are crucial for sustaining and scaling-up of the poverty alleviation programme ( Fig 2 : C21). This will also allow women to articulate their problems and improve their self-confidence, enhance their respect in society, develop leadership qualities, inspire them to speak and express their feelings unhesitatingly, and empower them economically and socially. Developing an academic understanding of the factors that support community institutions is crucial for the social infrastructure developed to facilitate the social capital building of the poor and vulnerable communities ( Fig 2 : C22).

3.3. FCM-based simulations

In order to evaluate critical factors responsible for poverty alleviation, we used six input vectors for FCM-based simulations. For each scenario, causal propagation occurs in each iteration until the FCM system converges [ 62 – 65 , 67 , 70 , 91 ]. This happens when no change takes place in the values of a concept after a certain point, also known as the system steady-state; the conceptual vector at that point is called the final state vector [ 62 – 65 , 67 , 70 , 91 ]. Values of the final state vectors depend on the structure of the FCM system and concepts considered for input vectors. The larger the value of the final state vectors, the better the selected policies [ 62 – 65 ]. Comparisons between the final state vectors of the alternative simulations are drawn in order to assess the extent of the desired transition by activating each set of input vectors. The initial values and final state vectors of all the concepts for every scenario are presented in Table 2 . The graphical representation of various scenarios for poverty alleviation is provided in the S5 Fig .

*O = Ordinary; T = Transmitter; R = Receiver

The first scenario highlights the effects of high-quality community organisations based micro-financing approach. If strong institutions of the poor are built and community heroes start driving the poverty alleviation programme, capacity building of the CBOs gets underway. If mainstream financial institutions start supporting CBOs while customised need-based finance and a repayment culture is developed significant efforts would still be required for putting good governance systems and processes in place along with linkages/ convergences/ partnerships along with other schemes while building capabilities of the poor. In the case of successful micro-financing, there will be opportunities for livelihood diversification, entrepreneurship, multi-sectoral collective enterprise development, value addition by collectives, and market linkages.

The second scenario highlights the effects of the capabilities approach and social security. In this case, affordable and approachable education and healthcare, social inclusion, the building of personal assets, adequate knowledge base, and vulnerability reduction are ensured. In this context, ample efforts will be required for mainstream financial institutions supporting CBOs, good governance systems and processes, and linkages/ convergences/ partnerships with other schemes. Efforts will also be required for a quality support structure and customised need-based finance. The capability and social security enhancement could have prospects for strong institutions of the poor, better implementation processes, livelihood diversification, entrepreneurship, value addition by collectives, multi-sectoral collective enterprise development, and vulnerability reduction.

The third scenario highlights the outcomes of the market-based approach. Here, livelihood diversification, entrepreneurship, multi-sectoral collective enterprise development, value addition by collectives, and market linkages are activated. In such a situation, adequate efforts will be required for mainstream financial institutions supporting CBOs, good governance systems and processes, and linkages/ convergences/ partnerships with other schemes. Efforts will also be required for continuous capacity building of the CBOs, customised need-based finance, affordable and approachable education and healthcare, and vulnerability reduction.

The fourth scenario highlights the outcomes of good governance. Here, good governance systems and processes, robust monitoring mechanisms, implementation processes, enabling policies and political will, and linkages/ convergence/ partnership with other governmental schemes are ensured. In such a situation, plentiful efforts will be required for mainstream financial institutions to lend their support to CBOs and for the building of personal assets. Efforts will also be required for developing a repayment culture, climate-smart production systems, and vulnerability reduction. Good governance is likely to ensure strong institutions of the poor, development of collective enterprises, livelihood diversification, entrepreneurship, value addition by collectives, and market linkages.

In the fifth and sixth scenarios, we activated the most important concepts identified by the participants. The sixth scenario is similar to the fifth one except that the concept C14: entrepreneurship has been replaced by the concept C13: livelihood diversification. The simulation results reveal that quality of CBOs, strong institutions of the poor, community heroes driving the programme, good governance systems and processes, convergence with other schemes/ programmes, enabling policies and political will, and livelihood diversification are very critical for poverty alleviation in a developing nation.

The participants judged a relatively higher weight for the concept C1 (sensitive support structure) ( Fig 1 ). This could be attributed to a conflict of interest on the part of the participants. Even after activating the concept C1 across policy scenarios 4 to 6, the outcome does not change. This also justifies the fact that any community-demand-driven and community-managed poverty alleviation programme has to be self-sustainable in the long-term. Therefore, while a poverty alleviation programme may make use of a support structure in its initial phase, it should persist at thriving even after the support structure has been withdrawn.

4. Contributions to FCM and poverty literature and future research directions

This section deals with contributions of the paper to FCM and poverty literature while offering a practical approach to address multi-dimensional poverty. The paper makes a two-fold contribution to FCM literature: i) knowledge capture and sample adequacy and ii) robustness of the dynamic system model. FCM sampling is often extended if additional maps keep adding new dimensions/ insights. The saturation of FCM sampling is formally measured by tracking the number of new concepts introduced in subsequent exercises and estimating an accumulation curve of concepts. When the point of saturation is reached data collection is stopped. In most studies, the saturation of FCM sampling is reported at 30–32 maps [ 60 , 62 , 63 , 66 , 72 ]. This study does demonstrate, however, that in the event of a ‘mixed-concept design’ approach when the participants gain access to concepts already identified by other sets of participant groups the latter participants continue to add new concepts, making the system much more complex and the data richer. Most FCM-based case studies published in scientific journals have taken weights of the causal interactions between the concepts. This study has not only obtained weights of the causal interactions between the concepts but also obtained weights of each concept. Results of the FCM-based simulations, by and large, match with the most critical concepts identified by participants represented by higher relative weights. This demonstrates in-depth understanding of participants of the subject matter and robustness of the system.

Scenarios are defined as ‘a plausible description of how the future may develop based on a coherent and internally consistent set of assumptions’ [ 97 ]. It also represents uncertainty as a range of plausible futures. Hence, in order to establish proper causal pathways of various poverty eradication approaches, it may be necessary to design random control trial experiments along each of the poverty eradication approaches and carry out the efficacy of each approach delineated above using the difference-in-difference micro-econometric model.

5. Conclusions

The results of our FCM-based simulations reveal that in order to eradicate poverty one needs to provide micro-finance through high-quality community organisations, enhance capabilities of the poor while providing social safety nets to the poor and vulnerable, ensure good governance within community organisations and institutions supporting them, continue to diversify livelihood options, and provide market linkages to small producers. Our findings confirm that various approaches to poverty alleviation are rather complementary and need to be implemented simultaneously for a comprehensive poverty alleviation drive. However, in relative terms, factors like good governance within community organisations and supporting institutions, high-quality community organisations based micro-financing, and enhancement of capabilities coupled with social security assurance seem to work better than a market-based approach. There is rich literature available on radical approaches like land reforms, decentralisation and poverty alleviation that have not been evaluated in this study. Nevertheless, findings of the study lead us to conclude that in order to address multi-dimensional poverty an integrated and multi-dimensional poverty alleviation approach is needed. Findings of the study are likely to help improve the design, management, and implementation of poverty eradication programmes in developing countries.

Supporting information

Acknowledgments.

We thank the World Bank team and functionaries of DAY-NRLM at national, state, and district levels for participating in the study. Indrani Talukdar is acknowledged for language editing. We thank the Academic Editor and the two anonymous reviewers for providing insightful comments and constructive suggestions.

Funding Statement

The World Bank and the Ministry of Rural Development, Government of India

Data Availability

• PLoS One. 2020; 15(1): e0227176.

Decision Letter 0

14 Nov 2019

PONE-D-19-26538

Evaluating Poverty Alleviation Strategies in a Developing Country

Dear Dr. Singh,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

The manuscript requires further revisions are regards the abstract, the contribution to the related literature, literature, research methodology, outcomes’ reporting style. Not least, an extensive English language is required.

We would appreciate receiving your revised manuscript by Dec 22 2019 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Stefan Cristian Gherghina, PhD

Academic Editor

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Thank you for including your ethics statement:  "Research Ethics Committee of our Institute approved the methodology of this paper, including the neutral problem domain— direct and consequential impacts of deforestation.

Collection of plant, animal, or other materials are not involved in this study"

a) Please amend your current ethics statement to include the full name of the ethics committee/institutional review board(s) that approved your specific study.

b) Once you have amended this/these statement(s) in the Methods section of the manuscript, please add the same text to the “Ethics Statement” field of the submission form (via “Edit Submission”).

For additional information about PLOS ONE ethical requirements for human subjects research, please refer to http://journals.plos.org/plosone/s/submission-guidelines#loc-human-subjects-research .

2. In your Data Availability statement, you have not specified where the minimal data set underlying the results described in your manuscript can be found. PLOS defines a study's minimal data set as the underlying data used to reach the conclusions drawn in the manuscript and any additional data required to replicate the reported study findings in their entirety. All PLOS journals require that the minimal data set be made fully available. For more information about our data policy, please see http://journals.plos.org/plosone/s/data-availability .

Upon re-submitting your revised manuscript, please upload your study’s minimal underlying data set as either Supporting Information files or to a stable, public repository and include the relevant URLs, DOIs, or accession numbers within your revised cover letter. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories . Any potentially identifying patient information must be fully anonymized.

Important: If there are ethical or legal restrictions to sharing your data publicly, please explain these restrictions in detail. Please see our guidelines for more information on what we consider unacceptable restrictions to publicly sharing data: http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions . Note that it is not acceptable for the authors to be the sole named individuals responsible for ensuring data access.

We will update your Data Availability statement to reflect the information you provide in your cover letter.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

2. Has the statistical analysis been performed appropriately and rigorously?

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The is an interesting research which identifies the critical factors for poverty alleviation in India with the aid of fuzzy cognitive maps (FCMs). This paper has many strengths and some opportunities for improvement, which I will elaborate below:

Abstract has inappropriate structure. I suggest to answer the following aspects: - general context - novelty of the work - methodology used - main results

Section 1 presents interesting information. However, it fails to set out any specific interest to a broader audience. There is nothing more than a sort of putting forward the topic. However, what about contribution to relevant literature? Which gaps do you want to fill and how?

Methodology is unclear. Initially a short resume can be proposed to explain several steps. The methodology used must be linked to the existing literature on FCM. what is its potential? its limit?

Results must be linked to the methodology. Please define the relationship and relate your finding with the relevant literature.

Finally, an extensive editing of English language and style is required.

Suggested references:

https://doi.org/10.1016/j.techfore.2019.07.012

https://doi.org/10.1016/j.eist.2015.06.006

https://doi.org/10.1016/j.jenvman.2015.10.038

Reviewer #2: The paper is accurate in the description of the methodology; however some steps can be explained better.

In 189-190 you explained that the concepts were elicited asking the participants the “critical 190 factors required to ensure that people come out of poverty on a sustainable basis”. Was this enough to prompt the contribution of the participants or did you give some other information to elicit their contribution. The quantity of information given before the participant tasks is a question that matter in FCMs building since a great quantity of information could lead to bias while very little information can lead to scanty results. How did you reach the correct trade-off?

523-524 “The 524 larger the value of the final state vectors, better the selected policies.” This means that all the concept give a desired and positive contribution to the poverty alleviation. Did all respondent give positive concept or did you declined all in a positive way to make them handy?

The paper aims also at giving a methodological contribution. I suggest some recent paper to enrich this part:

Falcone, P. M., Lopolito, A., & Sica, E. (2019). Instrument mix for energy transition: A method for policy formulation. Technological Forecasting and Social Change, 148, 119706.

Morone, P., Falcone, P. M., & Lopolito, A. (2019). How to promote a new and sustainable food consumption model: A fuzzy cognitive map study. Journal of cleaner production, 208, 563-574.

Falcone, P. M., Lopolito, A., & Sica, E. (2018). The networking dynamics of the Italian biofuel industry in time of crisis: Finding an effective instrument mix for fostering a sustainable energy transition. Energy Policy, 112, 334-348.

Falcone, P. M., Lopolito, A., & Sica, E. (2017). Policy mixes towards sustainability transition in the Italian biofuel sector: Dealing with alternative crisis scenarios. Energy research & social science, 33, 105-114.

ln 192 why do you mention only two concepts?

The diagrams of the various scenarios are hard to read. I suggest bar diagrams showing differences with the steady state values of each variable under each scenario.

6. PLOS authors have the option to publish the peer review history of their article ( what does this mean? ). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy .

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at gro.solp@serugif . Please note that Supporting Information files do not need this step.

Author response to Decision Letter 0

Uploaded as separate file namely, Response to Reviewers

Submitted filename: Response to Reviewers.docx

Decision Letter 1

16 Dec 2019

PONE-D-19-26538R1

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/ , click the "Update My Information" link at the top of the page, and update your user information. If you have any billing related questions, please contact our Author Billing department directly at gro.solp@gnillibrohtua .

If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact gro.solp@sserpeno .

With kind regards,

Additional Editor Comments (optional):

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

2. Is the manuscript technically sound, and do the data support the conclusions?

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: N/A

4. Have the authors made all data underlying the findings in their manuscript fully available?

5. Is the manuscript presented in an intelligible fashion and written in standard English?

6. Review Comments to the Author

Reviewer #1: The authors accurately addressed all my previous comments. I recommend the article for publication in PLOS ONE Journal.

Reviewer #2: The author(s) has/have addressed all the point raised in the review. The paper has been much improved and suits for the publication in the Journal

7. PLOS authors have the option to publish the peer review history of their article ( what does this mean? ). If published, this will include your full peer review and any attached files.

Acceptance letter

20 Dec 2019

Dear Dr. Singh:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact gro.solp@sserpeno .

For any other questions or concerns, please email gro.solp@enosolp .

Thank you for submitting your work to PLOS ONE.

PLOS ONE Editorial Office Staff

on behalf of

Dr. Stefan Cristian Gherghina

Poverty Alleviation and Sustainable Development Essay

• To find inspiration for your paper and overcome writer’s block
• As a source of information (ensure proper referencing)
• As a template for you assignment

Introduction

Causes of poverty, how poverty alleviation may help in achieving sustainable development.

The Millennium Development Goals (MDG), which were set by 189 countries, consisted of global targets aimed at improving livelihoods and eliminating numerous deprivations, among them poverty. In fact, the countries considered poverty as the most serious problem and affirmed their dedication to eradicating extreme poverty and hunger. According to Tagler and Cozzarelli (2013), poverty is an economic condition that is characterized by sustained low levels of income. The status affects access to basic services of education, health, food, and shelter. The research focuses on the causes of poverty and the benefits of poverty alleviation in achieving sustainable development.

Poverty is a long-term consequence of economic, social, and political failures. According to Williams (2013), an author with ‘The Borgen Project (NGO)’, causes of poverty are categorized into four major categories. One of the causes of poverty is discrimination and social inequality. Levels of inequalities in income distribution, access to basic amenities, legal structures, and information lead to serious economic disparities that subject victims to poverty. Additionally, Burton and Development Programme United Nations (2005) consider war and political instability as a leading cause of poverty. Political instabilities and wars affect insecurities and social and legal structures responsible for enhancing equitable distribution of resources and wealth. Ineffective policies expose people to exploitation and corruption. Sociopolitical failures affect literacy levels and access to information, which is vital in promoting self-actualization. Similarly, geopolitical histories and locations are other major causes of poverty. At-risk countries exposed to frequent natural catastrophes experience serious challenges in sustaining infrastructure development, effective information communications, and delivery of communal amenities. Additionally, historical political conflicts led to the depletion of vital resources from colonies of historic superpowers. The last cause of poverty is the national debt accrued from local and international loans. The loans increase financial constraints in the affected countries and deter the implementation of development initiatives that empower citizens.

The Commission on Human Rights considers poverty eradication as an effective strategy for combating social and economic inequalities. There have been different poverty alleviation measures, including food distribution, the building of infrastructures and schools, intervening in politically unstable countries, and providing financial support, among others. Lloyd-Jones and Rakodi (2013) argue that poverty alleviation programs contribute greatly to achieving sustainable development. One of the benefits of poverty alleviation programs in achieving sustainable development is in empowering the poor. Provision of education, electricity, stable political structures and favorable market conditions are some of the poverty alleviation strategies that empower poor people. The other sustainable development target in poverty alleviation is introducing equality and non-discrimination measures. These initiatives ensure that affected persons are self-sufficient. Equality and accountability are also assured in poverty alleviation when funding goes from donors to governments yet to streamline local structures. Additionally, civil and social rights are streamlined through poverty alleviation strategies.

Poverty is one of the most challenging issues among global institutions. The causes of poverty have been associated with political failures, historical implications, and infringed human rights. The research demonstrates the need to address poverty in order to uphold human rights for the welfare of global sustained developments. Whereas human rights are not rigid, poverty needs a flexible platform to integrate affected people while targeting corrupt and compromised officials in the global governments.

Burton, I., & Development Programme United Nations. (2005). Adaptation policy frameworks for climate change: developing strategies, policies and measures. Cambridge, MA: Cambridge University Press.

Lloyd-Jones, T., & Rakodi, C. (2013). Urban livelihoods: A people-centred approach to reducing poverty . Ney York, NY: Routledge.

Tagler, M. J., & Cozzarelli, C. (2013). Feelings toward the poor and beliefs about the causes of poverty: The role of affective-cognitive consistency in help-giving. The Journal of psychology , 147 (6), 517-539.

Williams, D. (2013). What are Causes of Global Poverty? Web.

• Poverty and Disasters in the United States
• Why the Lottery is Useful to Society?
• Poverty, Government and Unequal Distribution of Wealth in Philippines
• Poverty in Urban Areas
• Global Conflict and Poverty Crisis
• Intro to Sociology: Poverty
• Central Outreach and Advocacy Center
• Thesis Statement on Dumpster Diving
• Urban Planning Optimization and Homelessness
• Chad-Cameroon Pipeline Project
• Chicago (A-D)
• Chicago (N-B)

IvyPanda. (2022, January 25). Poverty Alleviation and Sustainable Development. https://ivypanda.com/essays/poverty-alleviation-and-sustainable-development/

"Poverty Alleviation and Sustainable Development." IvyPanda , 25 Jan. 2022, ivypanda.com/essays/poverty-alleviation-and-sustainable-development/.

IvyPanda . (2022) 'Poverty Alleviation and Sustainable Development'. 25 January.

IvyPanda . 2022. "Poverty Alleviation and Sustainable Development." January 25, 2022. https://ivypanda.com/essays/poverty-alleviation-and-sustainable-development/.

1. IvyPanda . "Poverty Alleviation and Sustainable Development." January 25, 2022. https://ivypanda.com/essays/poverty-alleviation-and-sustainable-development/.

Bibliography

IvyPanda . "Poverty Alleviation and Sustainable Development." January 25, 2022. https://ivypanda.com/essays/poverty-alleviation-and-sustainable-development/.

Advertisement

An assessment of the policy of poverty alleviation in continuous poverty-stricken areas: evidence from Yunnan Province, China

• Published: 11 June 2022
• Volume 25 , pages 9757–9777, ( 2023 )

Cite this article

• Jiaxin Wu 1 ,
• Hongjuan Yang   ORCID: orcid.org/0000-0002-1984-5105 1 &
• Tanveer Ahmed 1  

533 Accesses

5 Citations

Explore all metrics

Poverty eradication is the key to sustainable development. China's most principal poverty alleviation policy at present is the policy of poverty alleviation in continuous poverty-stricken areas. According to panel data containing 126 county-level districts of Yunnan Province from 2006 to 2018, assessed the consequence of the poverty alleviation policy in continuous poverty-stricken areas. The combination of the PSM and DID method is pragmatic to right the possible selection partiality as well as resolve the probable endogenic complications, and a series of robustness tests have been carried out to prove the robustness of the research conclusions. The outcomes specify that the policy meaningfully upgraded the GDP thru 11.8% in these areas. Furthermore, the policy endorses economic development through the adjustment of industrial structure, lastly providing three policy suggestions to expand the level and driving force of economic development in impoverished areas.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save.

• Get 10 units per month
• Download Article/Chapter or eBook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

A statistical evaluation of the effectiveness of multidimensional relative poverty alleviation efforts in China

Analysis of China’s policy effect on poverty alleviation: evidence from Chongqing in the Three Gorges Reservoir Region

Government spending and regional poverty alleviation: evidence from Egypt

Ali, A., & Rahut, D. B. (2018). Forest-based livelihoods, income, and poverty: Empirical evidence from the Himalayan region of rural Pakistan. Journal of Rural Studies, 57 , 44–54. https://doi.org/10.1016/j.jrurstud.2017.10.001

Article   Google Scholar  

Arestis, P., Ferreiro, J., & Gomez, C. (2020). Quality of employment and employment protection. Effects of employment protection on temporary and permanent employment. Structural Change and Economic Dynamics, 53 , 180–188. https://doi.org/10.1016/j.strueco.2020.02.008

Becerril, J., & Abdulai, A. (2010). The impact of improved maize varieties on poverty in Mexico: A propensity score-matching approach. World Development, 38 , 1024–1035. https://doi.org/10.1016/j.worlddev.2009.11.017

Del Prete, D., Ghins, L., Magrini, E., & Pauw, K. (2019). Land consolidation, specialization and household diets: Evidence from rwanda. Food Policy, 83 , 139–149. https://doi.org/10.1016/j.foodpol.2018.12.007

Ding, H., Qin, C., & Shi, K. (2018). Development through electrification: Evidence from rural China. China Economic Review . https://doi.org/10.1016/j.chieco.2018.04.007

Friedman, M. (1937). The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American Statistical Association, 32 , 675–701. https://doi.org/10.1080/01621459.1937.10503522

Ge, Y., Hu, S., Ren, Z., Jia, Y., Wang, J., Liu, M., Zhang, D., Zhao, W., Luo, Y., Fu, Y., Bai, H., & Chen, Y. (2019). Mapping annual land use changes in China’s poverty-stricken areas from 2013 to 2018. Remote Sensing of Environment, 232 , 111285. https://doi.org/10.1016/j.rse.2019.111285

Guo, Y., Zhou, Y., & Liu, Y. (2019). Targeted poverty alleviation and its practices in rural China: A case study of fuping county, hebei province. Journal of Rural Studies . https://doi.org/10.1016/j.jrurstud.2019.01.007

Haushofer, J., & Fehr, E. (2014). On the psychology of poverty. Science, 344 , 862–867. https://doi.org/10.1126/science.1232491

Article   CAS   Google Scholar  

Heckman, J. J., Ichimura, H., & Todd, P. E. (1998). Matching as an econometric evaluation estimator. Review of Economic Studies, 65 , 261–294. https://doi.org/10.1111/1467-937x.00044

Holz, C. A. (2006). New capital estimates for China. China Economic Review, 17 , 142–185. https://doi.org/10.1016/j.chieco.2006.02.004

Holz, C. A. (2020). Understanding PRC investment statistics. China Economic Review . https://doi.org/10.2139/ssrn.3532573

Howes, S., & Hussain, A. (1994) Regional growth and inequality in rural China. Working Paper EF 11 London, London School of Economics.

Huang, Z. (2018). Does the establishment of national poverty-stricken counties promote local economic development? an empirical analysis based on psm-did methods. Chinese Rural Economy, 5 , 98–111.

Google Scholar  

Huang, B., Gao, M., Xu, C., & Zhu, Y. (2017). The impact of province-managing-county fiscal reform on primary education in China. China Economic Review, 45 , 45–61. https://doi.org/10.1016/j.chieco.2017.06.001

Kemeny, T., & Osman, T. (2018). The wider impacts of high-technology employment: Evidence from US cities. Research Policy, 47 , 1729–1740. https://doi.org/10.1016/j.respol.2018.06.005

Li, S., Li, F., & Dong, Y. (2018). The impact evaluation of the policy of poverty alleviation in concentrated poverty-stricken areas: An investigation based on PSM-DID method. Reform, 12 , 142–155.

Liu, Z., & Zhang, X. (1999). Poverty alleviation tackling and benefit balance analysis method-take Aba, Ganzi and Liangshan autonomous prefectures in sichuan province as sample points. Economic Research Journal, 7 , 49–56.

Locke, C. M., Butsic, V., & Rissman, A. R. (2017). Zoning effects on housing change vary with income, based on a four-decade panel model after propensity score matching. Land Use Policy, 64 , 353–362. https://doi.org/10.1016/j.landusepol.2017.03.019

Long, H., & Liu, Y. (2016). Rural restructuring in China. Journal of Rural Studies, 47 , 387–391. https://doi.org/10.1016/j.jrurstud.2016.07.028

Lucas, R. (1988). On the mechanics of development planning. Journal of Monetary Economics, 22 , 3–42.

Meng, L. (2013). Evaluating China’s poverty alleviation program: A regression discontinuity approach. Journal of Public Economics, 101 , 1–11. https://doi.org/10.1016/j.jpubeco.2013.02.004

Odhiambo, N. M. (2009). Savings and economic growth in South Africa: A multivariate causality test. Journal of Policy Modeling, 31 , 708–718. https://doi.org/10.1016/j.jpolmod.2009.04.001

Parisi, M. L. (2017). Labor market rigidity, social policies and the labor share: Empirical evidence before and after the big crisis. Economic Systems, 41 , 492–512. https://doi.org/10.1016/j.ecosys.2017.08.003

Park, A., & Wang, S. (2001). China’s poverty statistics. China Economic Review, 12 , 384–398. https://doi.org/10.1016/s1043-951x(01)00066-9

Park, A., & Wang, S. (2010). Community-based development and poverty alleviation: An evaluation of China’s poor village investment program. Journal of Public Economics, 94 , 790–799. https://doi.org/10.1016/j.jpubeco.2010.06.005

Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels. Cambridge Working Papers in Economics, 69 , 1240. https://doi.org/10.1007/s00181-020-01875-7

Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross section dependence. Journal of Applied Econometrics, 22 , 265–312. https://doi.org/10.1002/jae.951

Rahut, D. B., Ali, A., & Behera, B. (2015). Household participation and effects of community forest management on income and poverty levels: Empirical evidence from Bhutan. Forest Policy & Economics, 61 , 20–29. https://doi.org/10.1016/j.forpol.2015.06.006

Romer, P. M. (1986). Increasing returns and long-run growth. Journal of Political Economy, 94 , 1002–1037. https://doi.org/10.1086/261420

Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70 , 41–55. https://doi.org/10.21236/ada114514

Rozelle, S., Park, A., Benziger, V., & Ren, C. (1998). Targeted poverty investments and economic growth in China. World Development, 26 , 2137–2151. https://doi.org/10.1016/s0305-750x(98)00104-1

Shao, S., Wang, Y., Yan, W., Yang, L., & Yin, J. (2020). Administrative decentralization and credit resource reallocation: Evidence from China’s “Enlarging Authority and Strengthening Counties” reform. Cities, 97 , 102530. https://doi.org/10.1016/j.cities.2019.102530

Shi, H., Li, X., Liu, X., Wang, S., Liu, X., Zhang, H., Tang, D., & Li, T. (2020). Global protected areas boost the carbon sequestration capacity: Evidences from econometric causal analysis. The Science of the Total Environment, 715 , 1370011–13700110. https://doi.org/10.1016/j.scitotenv.2020.137001

Shi, K., Chang, Z., Chen, Z., Wu, J., & Yu, B. (2020). Identifying and evaluating poverty using multisource remote sensing and point of interest (POI) data: A case study of Chongqing China. Journal of Cleaner Production, 255 , 120245. https://doi.org/10.1016/j.jclepro.2020.120245

Sunak, Y., & Madlener, R. (2016). The impact of wind farm visibility on property values: A spatial difference-in-differences analysis. Energy Economics, 55 , 79–91. https://doi.org/10.1016/j.eneco.2015.12.025

Tan, R., Tang, D., & Lin, B. (2018). Policy impact of new energy vehicles promotion on air quality in Chinese cities. Energy Policy, 118 , 33–40. https://doi.org/10.1016/j.enpol.2018.03.018

United Nations (UN), (2015). Transforming our World: The 2030 Agenda for Sustainable Development.

Wang, S., Park, A., & Chaudhuri, S. (2007). Rural poverty-reduction and village-level poverty targeting of new period in China. Management World, 1 , 56–64. https://doi.org/10.19744/j.cnki.11-1235/f.2007.01.009

Wu, R., & Gorder, R. V. (2018). Nonlinear dynamics of discrete time multi-level leader–follower games. Applied Mathematics and Computation, 320 , 240–250. https://doi.org/10.1016/j.amc.2017.09.034

Yang, Y., & Zhang, C. (2019). A study on the impact of “replacing business tax with VAT” on the financing revenue of county level land. East China Economic Management, 33 , 91–98.

Yang, X., Lin, S., Li, Y., & He, M. (2019). Can high-speed rail reduce environmental pollution? Evidence from China. Journal of Cleaner Production, 239 , 118135. https://doi.org/10.1016/j.jclepro.2019.118135

Zhang, H., Duan, M., & Deng, Z. (2019). Have China’s pilot emissions trading schemes promoted carbon emission reductions?– The evidence from industrial sub-sectors at the provincial level. Journal of Cleaner Production, 234 , 912–924. https://doi.org/10.1016/j.jclepro.2019.06.247

Zhao, X., Yu, B., Liu, Y., Chen, Z., & Wu, J. (2019). Estimation of poverty using random forest regression with multi-source data: A case study in Bangladesh. Remote Sensing, 11 , 375. https://doi.org/10.3390/rs11040375

Zheng, J., & Jiang, F. (2016). Policy of key counties in national poverty alleviation and development work: Driving growth, narrowing gap or policy failure–Based on PSM-DID method. Inquiry into Economic Issues, 12 , 43–52.

Zhou, Y., Guo, Y., Liu, Y., Wu, W., & Li, Y. (2018). Targeted poverty alleviation and land policy innovation: Some practice and policy implications from China. Land Use Policy, 74 , 53–65. https://doi.org/10.1016/j.landusepol.2017.04.037

Zhu, B., Zhang, M., Huang, L., Wang, P., Su, B., & Wei, Y. (2020). Exploring the effect of carbon trading mechanism on China’s green development efficiency: A novel integrated approach. Energy . https://doi.org/10.1016/j.eneco.2019.104601

Download references

This work was supported by the Natural Science Foundation of China [Grant Number 72064025] and the Ministry of Education Planning Fund [Grant Number 20XJA630002].

Author information

Authors and affiliations.

Faculty of Management and Economics, Kunming University of Science and Technology, 68 Wenchang Road, Yieryi Street, Wuhua District, Kunming, 650093, Yunnan, China

Jiaxin Wu, Hongjuan Yang & Tanveer Ahmed

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Hongjuan Yang .

Ethics declarations

Conflict of interest.

The authors have no financial or proprietary interests in any material discussed in this article.

Additional information

Publisher's note.

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

Rights and permissions

Reprints and permissions

About this article

Wu, J., Yang, H. & Ahmed, T. An assessment of the policy of poverty alleviation in continuous poverty-stricken areas: evidence from Yunnan Province, China. Environ Dev Sustain 25 , 9757–9777 (2023). https://doi.org/10.1007/s10668-022-02459-4

Download citation

Received : 18 October 2021

Accepted : 18 May 2022

Published : 11 June 2022

Issue Date : September 2023

DOI : https://doi.org/10.1007/s10668-022-02459-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Poverty Alleviation
• Continuous Poverty-stricken Areas
• Yunnan Province
• Find a journal
• Publish with us
• Track your research

Bristol Poverty Institute

Poverty-related phd theses.

You can download PhD theses with full abstracts, awarded by Bristol University.  PhD Theses (PDF, 289kB)

You can find a list of PhD theses by date here  list of PhD theses (PDF, 93kB)

You can download the individual abstracts below:

From potential donor to actual donation : how does socioeconomic deprivation affect the recruitment and progression of living kidney donors (2016) Phillippa Kathryn Bailey  Click here to view abstract (PDF, 11kB)

Youth poverty and social inequalities in Mexico (2016) Héctor E. Nájera Catalán  Click here to view abstract (PDF, 10kB)

Widening participation in higher education for students from the low socio-economic status group - a social justice analysis of student loans in Tanzania  (2016) Faustina Martha Msigwa  Click here to view abstract (PDF, 36kB)

To what extent has research been used to inform anti-poverty policy in Ghana ‌ ‌ (2016) Muhammed Williams  Click here to view abstract (PDF, 11kB)

Perspectives and models of community social work - social workers' understanding and practices in social exclusion and citizenship in Chile (2015) Gianinna Ines Munoz Arce  Click here to view abstract (PDF, 35kB)

Who deserves a better life - Social inequality in Chinese higher education access (2015) Yu Chen  Click here to view abstract (PDF, 13kB)

Improving the quality of teaching and learning in Mauritian primary schools - the role of learner-centred pedagogy in current educational reform   (2015) Mindy Lee Colin  Click here to view abstract (PDF, 11kB)

Alcohol patterns through mid-adolescence and socioeconomic position - the ALSPAC birth-cohort  ( 2015) Roberto Melotti‌  Click here to view abstract (PDF, 11kB)

Measuring residential segregation in England and Wales - a model-based approach (2015) Dewi Owen  Click here to view abstract (PDF, 11kB)

Child poverty in urban China (2015) Di Qi  Click here to view abstract (PDF, 9kB)

Pastoral community perspectives on formal education for girls - an ethnographic  study of Monduli District in Tanzania (2015) Adella Raymond  Click here to view abstract (PDF, 39kB)

Being and becoming - youth poverty and labour market transitions in Europe (2015) Alba Lanau Sánchez  Click here to view abstract (PDF, 11kB)

Social citizens - welfare provision and perceptions of citizenship amongst young people in Sri Lanka  (2014) Catherine Mary Agg  Click here to view abstract (PDF, 37kB)

Young people's lives in university - exploring welfare mixes and inequality of young people's experiences in university in England, Italy and Sweden (2014) Lorenza Antonucci  Click here to view abstract (PDF, 35kB)

Low social contact among UK working parents ‌ (2014) Marco Pomati  Click here to view abstract (PDF, 11kB)

Embracing universal access to secondary education in St. Vincent - what are the costs and consequences for parents in beneficiary households (2013) George S. Bristol  Click here to view abstract (PDF, 13kB)

A longitudinal multilevel study of the health outcomes for the elderly in China  (2013) Zhixin Feng ‌ Click here to view abstract (PDF, 11kB)

Dilemmas and dynamics relating to selection for secondary schooling in Trinidad and Tobago (2013) Michele Celine Mills  Click here to view abstract (PDF, 36kB)

Youth poverty reduction in Nigeria - a policy perspective ‌  (2012) Patricia Adaeze Momah  Click here to view abstract (PDF, 36kB)

School level fundraising - exploring equity and governance in Tanzanian secondary schools ‌  (2012) Dorothy Godfrey Phumbwe  Click here to view abstract (PDF, 13kB)

Money, friends and coping day to day - an inclusive research project exploring poverty and social capital in the lives of people with a learning disability  (2012) Liz Tilley  Click here to view abstract (PDF, 11kB)

A woman can starve before she gets any relief - poverty and hardship amongst service families during the Second World War in England   (2011) Helen Vegoda  Click here to view abstract (PDF, 11kB)

Mobility, inequality and polarization (2011) Claudia Vittori  Click here to view abstract (PDF, 38kB)

Gender, work and the new economy (2011) Jackie West  Click here to view abstract (PDF, 36kB)

Community cohesion and ethnic difference (2011) Hannah White  Click here to view abstract (PDF, 36kB)

Policy networks in African poverty reduction - a case study of the policy process for water supply in Lusaka, Zambia (2010) Darren Kirk Hedley  Click here to view abstract (PDF, 11kB)

An analysis of changes in child poverty in the developing world at the end of the 20th century (2010) S Nandy  Click here to view abstract (PDF, 11kB)

Structural adjustment in Mexico - social and economic impacts (2009) Luis Felipe Gorjón Fernández  Click here to view abstract (PDF, 11kB)

The meaning and measurement of poverty (2008) C. Deeming  Click here to view abstract (PDF, 10kB)

Jacob’s Wealth - an examination into the nature and role of material possessions in the Jacob-cycle (Gen 25.19-35.29) (2008) Paul D. Vrolijk  Click here to view abstract (PDF, 10kB)

Governance and policy-making in Thailand : a study of poverty alleviation policy since 1997 (2007) Amornsak Kitthananan  Click here to view abstract (PDF, 36kB)

Dimensions of poverty ( 2007) Stephen McKay  Click here to view abstract (PDF, 10kB)

Social tariffs - a solution to fuel poverty (2006) William Baker  Click here to view abstract (PDF, 11kB)

Macroeconomic determinants of inequality and finance - evidence from Brazil (2006) Manoel F. Meyer Bittencourt  Click here to view abstract (PDF, 13kB)

Health outcomes and income inequality - a multilevel analysis of the Wilkinson hypothesis (2006) Min-Hua Jen  Click here to view abstract (PDF, 37kB)

Taiwans mountain policies and the poverty of the indigenous people  (2005) He-Chium Liou  Click here to view abstract (PDF, 11kB)

How the World Bank perceives education's role in development and poverty reduction - an analysis of educational policy documents in their historical context (2005) Alison Oldfield  Click here to view abstract (PDF, 10kB)

Miscarriages of justice - exception to the rule ‌  (2003) Michael Naughton  Click here to view abstract (PDF, 11kB)

(Net)working out poverty and social exclusion in rural Ireland and Russia  (2003) Sergei Vitalyevich Shubin  Click here to view abstract (PDF, 36kB)

The Child Poverty Action Group 1965-1974 - the origins and effectiveness of a single-issue pressure group (2002) Maria Lesley Meyer-Kelly ‌ Click here to view abstract (PDF, 10kB)

Analysing the distribution of income and taxes in Slovenia with a tax benefit model (2002) Mitja CÌOEok  Click here to view abstract (PDF, 11kB)

The effects of poverty on single mothers living in Hartcliffe (2000) Angela Vowles‌‌  Click here to view abstract (PDF, 8kB)

Structure, agency and power in local authority possession proceedings (1998) Nancy Carlton‌‌  Click here to view abstract (PDF, 11kB)

Working towards gender parity in education in developing countries - issues and challenges (1998) Rose Nassali-Lukwago  Click here to view abstract (PDF, 37kB)

What are the comparative advantages of international non-governmental organisations engaged in the alleviation of poverty in rural Africa (1996) Alistair Gilbert  Click here to view abstract (PDF, 9kB)

Social construction of gender inequality in the housing system in Hong Kong ‌  (1995) Kam Wah Chan‌‌  Click here to view abstract (PDF, 11kB)

Ghana : structural adjustment and its impact on the incidence of mass poverty  (1995) Kwabena Donkor‌‌  Click here to view abstract (PDF, 36kB)

Womens health in urban primary health care (1995) Ingrid Mijlof  Click here to view abstract (PDF, 11kB)

The role of primary health care in the management of diseases of poverty in Northern Lesotho  (1994) Anastasia Ntsoaki Mohlba  Click here to view abstract (PDF, 11kB)

A study of anti-poverty policy in the welfare state - the case of public assistance programmes in the Republic of Korea ( 1994) Gil-Sang Nho  Click here to view abstract (PDF, 11kB)

The link between poverty and ill health - some implications for health education in Zimbabwe (1993) Annah-Maria Regedza Razika-Mangwiro  Click here to view abstract (PDF, 37kB)

Poverty and social security in Malaysia - major themes in economic and social development ‌  (1991) Saaidah Abdul-Rahman  Click here to view abstract (PDF, 36kB)

Social justice and children in care (1990) Morag Christine Owen  Click here to view abstract (PDF, 9kB)

Life-history factors and inequalities in affective disorders - a cohort study ‌  (1990) Bryan Rodgers  Click here to view abstract (PDF, 10kB)

Colour and class inequality in Seychelles (1984) Kathleen Low-Hang  Click here to view abstract (PDF, 12kB)

Studies in the criminalisation of poverty - pauperism, pathology and policing ‌  (1984) P. Squires  Click here to view abstract (PDF, 18kB)

Christians and poverty ‌ ‌ (1983) Richard Norton  Click here to view abstract (PDF, 12kB)

Gender and the mental health of women (1982) J. Williams  Click here to view abstract (PDF, 13kB)

The population, public health and the poor of Leamington Priors 1830 – 51 (1979) Sally A. Brealey  Click here to view abstract (PDF, 14kB)

The relief of the poor in Walton-on-Thames under the Vestry and the Board of Guardians 1800-1850 - a comparison  (1974) Sarah Whiteaway  Click here to view abstract (PDF, 13kB)