10 datasets found
  1. Number of people living in extreme poverty in Ghana 2016-2026

    • statista.com
    Updated Jun 30, 2024
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    Statista (2024). Number of people living in extreme poverty in Ghana 2016-2026 [Dataset]. https://www.statista.com/statistics/1439971/number-of-individuals-living-in-extreme-poverty-in-ghana/
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    Dataset updated
    Jun 30, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Ghana
    Description

    As of 2024, some 6.9 million people in Ghana lived in extreme poverty, with the poverty threshold at 2.15 U.S. dollars per day. This stood as an increase from the previous year when roughly 6.8 million people lived in the said state of poverty. In 2026, around 6.7 million Ghanaians are expected to live on a maximum of 2.15 U.S. dollars daily.

    Poverty in the country is segregated

    Indeed, poverty figures do not considerably vary when considering men and women apart. In 2024, around 3.5 million men lived in extreme poverty in Ghana, while the count reached roughly 3.3 million for women. On the other hand, in distinguishing the state of extreme poverty among rural and urban dwellers, the difference is striking, even when based on the previously set poverty line of 1.90 U.S. dollars per day. Overall, 1.1 percent of the world's population in extreme poverty lived in Ghana as of 2024.

    Ghana's Private Wealth Position in Africa

    Ghana is one of the African countries with the highest private wealth concentration, ranking 6th after Kenya as of 2021. That year, the country's total private wealth amounted to 59 billion U.S. dollars, corresponding to around 1,900 U.S. dollars per capita. Between 2011 and 2021, the total wealth held by individuals in Ghana increased, representing a higher growth in comparison to other African countries save five. Overall, the nation ranks 9th in Africa in terms of countries with high net-worth individuals.

  2. H

    Data from: Ghana Africa Research in Sustainable Intensification for the Next...

    • dataverse.harvard.edu
    • data.wu.ac.at
    Updated Jan 16, 2024
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    International Food Policy Research Institute (IFPRI) (2024). Ghana Africa Research in Sustainable Intensification for the Next Generation (Africa RISING) Baseline Evaluation Survey [Dataset]. http://doi.org/10.7910/DVN/QUB9UT
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 16, 2024
    Dataset provided by
    Harvard Dataverse
    Authors
    International Food Policy Research Institute (IFPRI)
    License

    https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.7/customlicense?persistentId=doi:10.7910/DVN/QUB9UThttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.7/customlicense?persistentId=doi:10.7910/DVN/QUB9UT

    Time period covered
    2014
    Area covered
    Ghana
    Dataset funded by
    United States Agency for International Development (USAID)
    Description

    As part of the US government’s Feed the Future initiative that aims to address global hunger and food security issues in sub-Saharan Africa, the US Agency for International Development is supporting three multi-stakeholder agricultural research projects under Africa Research In Sustainable Intensification for the Next Generation (Africa RISING - AR) program. The overall aim of the program is to transform agricultural systems through sustainable intensification projects in Ghana, Ethiopia, Tanzania, Malawi, Mali, and (potentially) Zambia. In West Africa, IITA works with multi-disciplinary R4D partners in selected communities located in Northern Ghana and Southern Mali. More particularly, in Northern Ghana three regions were chosen for the study: the Northern, Upper-East and Upper-West regions. These areas cover both maize-based and rice-vegetables-based systems and therefore allow to address the production constraints characterizing both realities7. As IFPRI (2012) highlights, the northern regions of Ghana are characterized by small land holdings and low input - low output farming systems, which adversely impact food security. In particular, they are subject to a seasonal cycle of food insecurity of three to seven months for cereals (i.e., maize, millet and sorghum) and four to seven months for legumes (i.e., groundnuts, cowpeas, and soybeans). These crops in the savannahs are often produced in a continuous monoculture, steadily depleting soil natural resources and causing the yields per unit area to fall to very low levels. The poverty profile of Ghana identifies the three northern regions as the poorest and most hunger-stricken areas in the country. Gender inequalities are also apparent in these regions, since women have limited access to resources and therefore limited capacity to generate income on their own.

  3. T

    GDP PER CAPITA by Country in AFRICA

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 27, 2017
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    TRADING ECONOMICS (2017). GDP PER CAPITA by Country in AFRICA [Dataset]. https://tradingeconomics.com/country-list/gdp-per-capita?continent=africa
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    json, csv, xml, excelAvailable download formats
    Dataset updated
    May 27, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2025
    Area covered
    Africa
    Description

    This dataset provides values for GDP PER CAPITA reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  4. g

    Africa Research in Sustainable Intensification for the Next Generation...

    • gimi9.com
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    Africa Research in Sustainable Intensification for the Next Generation (Africa RISING) Baseline Evaluation Survey - Ghana | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_africa-research-in-sustainable-intensification-for-the-next-generation-africa-rising-basel/
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    License

    Attribution-NoDerivs 4.0 (CC BY-ND 4.0)https://creativecommons.org/licenses/by-nd/4.0/
    License information was derived automatically

    Area covered
    Africa, Ghana
    Description

    In West Africa, IITA works with multi-disciplinary Results for Development (R4D) partners in selected communities located in Northern Ghana and Southern Mali. More particularly, in Northern Ghana three regions were chosen for the study: the Northern, Upper-East and Upper-West regions. These areas cover both maize-based and rice/vegetables-based systems and therefore allow to address the production constraints characterizing both realities. As IFPRI (2012) highlights, the northern regions of Ghana are characterized by small land holdings and low input / low output farming systems, which adversely impact food security. In particular, they are subject to a seasonal cycle of food insecurity of three to seven months for cereals (i.e., maize, millet and sorghum) and four to seven months for legumes (i.e., groundnuts, cowpeas, and soybeans). These crops in the savannahs are often produced in a continuous monoculture, steadily depleting the soil's natural resources and causing the yields per unit area to fall to very low levels. The poverty profile of Ghana identifies the three northern regions as the poorest and most hunger-stricken areas in the country. Gender inequalities are also apparent in these regions, since women have limited access to resources and therefore limited capacity to generate income on their own.

  5. s

    Afrint Village Level Data 2002 and 2008 - Ghana

    • microdata.statsghana.gov.gh
    Updated Sep 12, 2014
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    Lund University (2014). Afrint Village Level Data 2002 and 2008 - Ghana [Dataset]. https://microdata.statsghana.gov.gh/index.php/catalog/66
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    Dataset updated
    Sep 12, 2014
    Dataset authored and provided by
    Lund University
    Time period covered
    2001 - 2008
    Area covered
    Ghana
    Description

    Abstract

    Afrint intensification of food crops agriculture in sub-Saharan Africa Swedish-African Research Network Agricultural development and its relation to food security and poverty alleviation Primary research in nine sub-Saharan African countries. Afrint was in three phases 200I-2016. Afrint I - 2001-2005: The African Food Crisis, the Relevance of Asian Experiences. Afrint II - 2007-2010: The Millennium Development Goals and the African Food Crisis.

    Gender gaps and pro-poor agricultural growth in Malawi and Zambia - (Sida). African Urban Agriculture - Kenya and Ghana (Sida, Formas).

    Geographic coverage

    Sub Saharan Africa, (Ethiopia,Ghana,Kenya,Malawi,Nigeria,Tanzania,Uganda,Zambia) Regions within selected countries

    Analysis unit

    Household

    Universe

    Farming Household

    Kind of data

    Aggregate data [agg]

    Sampling procedure

    Data collection for the first round of the Afrint project was made in 2002. The data collected as part of the second round are referred to as 2008 data, although in some cases collected in late 2007. From the outset the research team selected five case study countries: Ghana, Kenya,Malawi, Nigeria and Tanzania. Outside francophone Africa, these five countries were ideally suited, in the researchers view, to charting progress in intensification, induced from below by farmers themselves, or state induced, as in the Asian Green Revolution. At the insistence of Sida, to the original five countries, four more were added: Ethiopia, Mozambique, Uganda and Zambia. Unlioriginal five, the three last mentioned countries were deemed less constrained with respect to productive resources in agriculture. Ethiopia on the other hand is peculiar in an African context, with its long history of plough agriculture, and feudal-like social formation. In this project, the heterogeneous sample of countries has proved less cumbersome to work with than one might have expected.

    Formally, the Afrint sample was drawn in four stages, of which the country selection described above was the first one. The next stage was regions within countries, followed by selection of villages within regions, and with selection of farm households as the last stage. All stages except the final one have been based on purposive sampling. Data collection was sought to be made at all four levels.

    The households sampled within these countries were selected with respect to the agricultural potential of the areas in which they reside. The intention was to capture the dynamism in the areas that are 'above average' in terms of ecological and market (infrastructure) endowments but excluding the most extreme cases in this regard. For logistical reasons we could not aim for a sample which is representative in a statistical sense. Instead we aimed at a sample which is illustrative of conditions in the maize-cassava belt, excluding both lowpotential dry and remote areas and extreme outliers at the other end of the scale, i.e. privileged high-potential areas.

    Thus we used a four-stage sample design, with purposive sampling at all stages, except the last one, where households were sampled after having made up household lists. When we compare point estimates from the sample with those from other sources, for examples yields for the various crops with FAO statistics, no apparent sample bias has been detected. In addition to household questionnaires we also used village questionnaires. Respondents to village interviews were key persons, like village leaders and extension agents. Investigators were also instructed to conduct focus group interviews with representatives for various segments of the village population, including women farmers.

    When going for a second round and a panel in 2008, we went for a balanced panel design, i.e. constructing the 2008 sample so that in itself it would be representative of village populations in 2008. This also involved sampling descendants when a household had been partitioned since 2002. In case of sizeable in-migration to a village, we also provided for sampling from the newly arrived households. The 2002-2008 panel thus is a subset of the two cross sectional samples. In itself this subset is not statistically representative of the village population in any of the two years.

    Sampling deviation

    20.6 percent

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Scope of Surey Round I (2001-2005)

    Population size and land use Agricultural dynamism: agro-ecology Agricultural dynamism: infrastructure and markets State interventions Markets Farmer organisations Land and land tenure Credit History of intensification (indicators) Labour: Economic constraints and facilitating factors Gender aspects:

    Scope of Survey Round II (2007-2010).

    Section I Village identification Summary on agro-ecological potential Section II General village characteristics Population size and land use Infrastructure land and land tenure Agricultural dynamism: agro-ecology and environmental problems Cattle Section III General village characteristics Credit Contract farming (commercial) Section IV Staple crops: availability and access to varieties Fertilizer Fertilizer access Agricultural techniques Extension Food security indicators

    Section V General village characteristics Population size and land use

    Land and land tenure Rural-urban linkages Gender dynamics in relation to crops Food security indicators

    Cleaning operations

    No editing specification given.

    Response rate

    79.4 percent

    Sampling error estimates

    No sampling error estimates given.

    Data appraisal

    No other forms of appraisal given.

  6. d

    Data from: Impact of Savings Groups on the Lives of the Poor

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 21, 2023
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    Karlan, Dean; Savonitto, Beniamino; Thuysbaert, Bram; Udry, Christopher (2023). Impact of Savings Groups on the Lives of the Poor [Dataset]. http://doi.org/10.7910/DVN/EJTYHC
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    Dataset updated
    Nov 21, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Karlan, Dean; Savonitto, Beniamino; Thuysbaert, Bram; Udry, Christopher
    Description

    Savings-led microfinance programs operate in poor rural communities in developing countries to establish groups that save and then lend out the accumulated savings to each other. Nonprofit organizations train villagers to create and lead these groups. In a clustered randomized evaluation spanning three African countries (Ghana, Malawi, and Uganda), we find that the promotion of these community-based microfinance groups leads to an improvement in household business outcomes and women’s empowerment. However, we do not find evidence of impacts on average consumption or other livelihoods. The data and code for this study are forthcoming.

  7. u

    The Impact of Food Systems Research Network for Africa on Mentors...

    • datacatalogue.ukdataservice.ac.uk
    Updated Jan 3, 2025
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    Swanepoel, F, University of Pretoria; Quinn, C, University of Leeds; Mkandawire, E, University of Pretoria (2025). The Impact of Food Systems Research Network for Africa on Mentors Professional Development, 2023-2024 [Dataset]. http://doi.org/10.5255/UKDA-SN-857096
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    Dataset updated
    Jan 3, 2025
    Authors
    Swanepoel, F, University of Pretoria; Quinn, C, University of Leeds; Mkandawire, E, University of Pretoria
    Area covered
    United Kingdom, Ghana, Tanzania, Malawi, Kenya, South Africa, Zambia
    Description

    A dataset was created from responses to a survey conducted to evaluate whether mentors in an early career researcher development programme enhanced their capabilities by participating in a two-year programme as mentors. The survey specifically targeted mentors of early career researchers from higher education institutions in the United Kingdom and Africa. The objective was to assess the impact of the FSNet-Africa early career researcher development programme on mentors' professional development by determining the effects of being a mentor in the FSNet-Africa early career researcher development programme on mentors' networks and visibility, potential skills development, performance improvement, and personal growth in eight areas of professional development. These areas include conducting integrated research, research data management, integrating gender in research, research ethics, monitoring and evaluation, disseminating research findings, and stakeholder engagement.

    The Food Systems Research Network for Africa (FSNet-Africa) will strengthen food systems research and its translation into implementable interventions in support of interrelated Sustainable Development Goals related to food systems in Africa (focusing on SDG2 - Zero Hunger).

    The network partners - University of Pretoria (UP) (ARUA-CoE in Food Security host), University of Leeds (UoL) (GCRF-AFRICAP host) and the Food, Agriculture and Natural Resources Policy Analysis Network (FANRPAN) (GCRF-AFRICAP partner) have been selected based on their track record of working together, strengths in food systems research and existing partnerships with food systems stakeholders.

    The major contribution of FSNet-Africa to addressing the challenge of SDG2 will be its focus on developing a new understanding of the African food systems through developing the FSNet-Africa Food Systems Framework and utilising systems-based methodologies to conduct research that enhances understanding of the components of the framework, the interactions between these components, and ultimately the leverage points for food system transformation. The latter will be implemented by an interdisciplinary cohort of early career research fellows (ECRF) who are supported in their research to identify (in dialogue with food systems stakeholders) and evaluate climate-smart, nutrition-sensitive, poverty-reducing interventions.

    FSNet-Africa will collaboratively produce context-relevant, interdisciplinary research through creating 2-year long structured opportunities for up to 30 ECRF, majority female, who obtained their PhD's less than 10 years ago to (i) conduct impact-focused, gender sensitive, interdisciplinary research related to African food systems, (ii) build lasting research networks, and (iii) develop their skills to translate their research impactfully. ECRF will be selected from 10 academic partner institutions in six countries - Ghana, Kenya, South Africa, Malawi, Tanzania and Zambia.

    The three formal components of the fellowships (science, mentorship and leadership development) will ensure that the ECRF are positioned in the necessary enabling environment and are provided with the opportunity to develop the necessary skills to produce excellent research, achieve the project objectives and significantly advance their academic careers. During the fellowship, each fellow will be assigned at least two mentors - one from an African university and the other from the UK. These research-triads will be carefully matched to ensure that the triad is an interdisciplinary team, enabling the ECRF to receive the support they need to develop and implement quality interdisciplinary research projects. The Science Component of the fellowship will be comprised of a fellowship orientation workshop, funding for research, participation in a split-site winter/summer school and a write-shop. After attending an Orientation Workshop with their mentors, ECRF will be expected to develop their research proposals that focus on climate-smart, nutrition-sensitive and poverty-reducing food systems solutions. Six months later, a 10-week split-site winter/summer school (at UP's Future Africa Campus and at the University of Leeds) will provide the ECRF with the opportunity to finalise their research proposals for implementation and to participate in various capacity development workshops. The Leadership Component will give ECRF the opportunity to develop skills the skills they need to be future food systems science leaders - such as managing research teams and leadership in science-policy communication.

    As a mechanism to facilitate research uptake and impact, every project undertaken by the ECRF will be co-designed and implemented in partnership with relevant policymakers, private sector role players or grassroots level organisations who will engage directly with the research teams at the Orientation Workshop, during the Winter School and in-country to implement the research.

  8. u

    The Impact of the Food System Research Network for Africa on the Skills and...

    • datacatalogue.ukdataservice.ac.uk
    Updated Jul 7, 2025
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    Swanepoel, F, University of Pretoria; Claire, Q, University of Leeds; Elizabeth, M, University of Pretoria (2025). The Impact of the Food System Research Network for Africa on the Skills and Experience of Researchers at the University of Pretoria, 2022-2024 [Dataset]. http://doi.org/10.5255/UKDA-SN-857169
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    Dataset updated
    Jul 7, 2025
    Authors
    Swanepoel, F, University of Pretoria; Claire, Q, University of Leeds; Elizabeth, M, University of Pretoria
    Area covered
    South Africa
    Description

    A dataset was created by collecting survey responses from University of Pretoria researchers who participated in a two-year FSNet-Africa researcher development programme as hosts (referred to as UP Hosts). The role of the UP Host was to expand fellows network within the University of Pretoria. Some Hosts were invited by research teams to actively participate in the research project. The survey specifically targeted researchers from the University of Pretoria with the aim of evaluating the impact of their participation in the FSNet-Africa development programme on their skills and experience. This evaluation was conducted by assessing the effects of being a host in the FSNet-Africa early career researcher development programme on the hosts' networks and visibility, skills development, performance improvement, and personal growth in eight areas of professional development. These areas included conducting integrated research, research data management, integrating gender in research, research ethics, monitoring and evaluation, and stakeholder engagement.

    The Food Systems Research Network for Africa (FSNet-Africa) will strengthen food systems research and its translation into implementable interventions in support of interrelated Sustainable Development Goals related to food systems in Africa (focusing on SDG2 - Zero Hunger).

    The network partners - University of Pretoria (UP) (ARUA-CoE in Food Security host), University of Leeds (UoL) (GCRF-AFRICAP host) and the Food, Agriculture and Natural Resources Policy Analysis Network (FANRPAN) (GCRF-AFRICAP partner) have been selected based on their track record of working together, strengths in food systems research and existing partnerships with food systems stakeholders.

    The major contribution of FSNet-Africa to addressing the challenge of SDG2 will be its focus on developing a new understanding of the African food systems through developing the FSNet-Africa Food Systems Framework and utilising systems-based methodologies to conduct research that enhances understanding of the components of the framework, the interactions between these components, and ultimately the leverage points for food system transformation. The latter will be implemented by an interdisciplinary cohort of early career research fellows (ECRF) who are supported in their research to identify (in dialogue with food systems stakeholders) and evaluate climate-smart, nutrition-sensitive, poverty-reducing interventions.

    FSNet-Africa will collaboratively produce context-relevant, interdisciplinary research through creating 2-year long structured opportunities for up to 30 ECRF, majority female, who obtained their PhD's less than 10 years ago to (i) conduct impact-focused, gender sensitive, interdisciplinary research related to African food systems, (ii) build lasting research networks, and (iii) develop their skills to translate their research impactfully. ECRF will be selected from 10 academic partner institutions in six countries - Ghana, Kenya, South Africa, Malawi, Tanzania and Zambia.

    The three formal components of the fellowships (science, mentorship and leadership development) will ensure that the ECRF are positioned in the necessary enabling environment and are provided with the opportunity to develop the necessary skills to produce excellent research, achieve the project objectives and significantly advance their academic careers. During the fellowship, each fellow will be assigned at least two mentors - one from an African university and the other from the UK. These research-triads will be carefully matched to ensure that the triad is an interdisciplinary team, enabling the ECRF to receive the support they need to develop and implement quality interdisciplinary research projects. The Science Component of the fellowship will be comprised of a fellowship orientation workshop, funding for research, participation in a split-site winter/summer school and a write-shop. After attending an Orientation Workshop with their mentors, ECRF will be expected to develop their research proposals that focus on climate-smart, nutrition-sensitive and poverty-reducing food systems solutions. Six months later, a 10-week split-site winter/summer school (at UP's Future Africa Campus and at the University of Leeds) will provide the ECRF with the opportunity to finalise their research proposals for implementation and to participate in various capacity development workshops. The Leadership Component will give ECRF the opportunity to develop skills the skills they need to be future food systems science leaders - such as managing research teams and leadership in science-policy communication.

    As a mechanism to facilitate research uptake and impact, every project undertaken by the ECRF will be co-designed and implemented in partnership with relevant policymakers, private sector role players or grassroots level organisations who will engage directly with the research teams at the Orientation Workshop, during the Winter School and in-country to implement the research.

  9. u

    SAMSET - Model

    • zivahub.uct.ac.za
    • resodate.org
    zip
    Updated May 31, 2023
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    Bryce McCall (2023). SAMSET - Model [Dataset]. http://doi.org/10.25375/uct.7239968.v1
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    zipAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    University of Cape Town
    Authors
    Bryce McCall
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    LEAP models for SAMSET project.Urbanisation rates in Africa are the highest in the world, and in most Sub-Saharan countries service delivery is inadequate to keep up with the needs. African populations remain amongst the poorest in the world, and efforts to achieve the energy-related dimensions of the Millennium Development Goals s have in most cases not had significant impact on urban populations.The situation can be summarised as one where much urban energy transformation research does not understand the detailed organisational dynamics and constraints in cities and therefore is often of limited use; where there is a gap between policy and implementation; where capacity within local/national government departments involved in energy and urban development is inadequate in the face of increasing challenges; and where modes of knowledge transfer are not effective in facilitating sustainable energy transitions in cities.SAMSET seeks to develop a knowledge exchange framework for supporting local and national bodies involved in municipal energy planning in the effective transition to sustainable energy use in urban areas. Through close partnering with six cities in three African countries (Ghana, Uganda and South Africa), the project aims to develop an information base from which to support cities, undertake direct support for cities around strategy development and priority initiatives, and facilitate knowledge exchange and capacity building.

  10. f

    Data_Sheet_1_Farming Systems, Food Security and Farmers' Awareness of...

    • frontiersin.figshare.com
    docx
    Updated Jun 17, 2023
    + more versions
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    Tesfahun Alemayehu; Guy Marius Assogba; Silke Gabbert; Ken E. Giller; James Hammond; Aminou Arouna; Elliott Ronald Dossou-Yovo; Gerrie W. J. van de Ven (2023). Data_Sheet_1_Farming Systems, Food Security and Farmers' Awareness of Ecosystem Services in Inland Valleys: A Study From Côte d'Ivoire and Ghana.docx [Dataset]. http://doi.org/10.3389/fsufs.2022.892818.s001
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    docxAvailable download formats
    Dataset updated
    Jun 17, 2023
    Dataset provided by
    Frontiers
    Authors
    Tesfahun Alemayehu; Guy Marius Assogba; Silke Gabbert; Ken E. Giller; James Hammond; Aminou Arouna; Elliott Ronald Dossou-Yovo; Gerrie W. J. van de Ven
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Côte d'Ivoire, Ghana
    Description

    Inland valleys (IVs) in West African countries have increasingly been used for crop production, including rice cultivation. Though it is widely assumed that IVs have a high potential to contribute to food security of West African countries, a comprehensive assessment of farming systems addressing agricultural, institutional, food security, poverty, and ecosystem indicators is still lacking. This study characterizes IVs' smallholder farm households at the regional and farm type level using Rural Household Multiple Indicator Survey (RHoMIS) data collected from 733 randomly selected farm households in four agro-ecological regions, i.e., Bouaké and Gagnoa in Cote d'Ivoire, and Ahafo Ano North and Ahafo Ano South in Ghana. A farm typology is developed, and farm households are characterized with regard to demographic, agricultural, economic, and institutional indicators. Furthermore, farm households' food security and poverty status, and the importance of rice in the portfolio of crops, is assessed. Finally, farmers' awareness of different ecosystem services (ES) for their food security is examined. Four farm types are identified, i.e., farmers who rent all the land cultivated, farmers who own some land and rent extra land, farmers who own and cultivate all their land, and farmers cultivating only a part of the land they own. We find that the variation in farm households' demographic, economic, and institutional characteristics is greater between regions than within regions. Crop production, either for direct consumption or marketing, especially rice production, is the main contributor to daily energy intake, followed by wild food consumed. Still, a substantial percentage of the farm households (16–38%) in all regions cannot meet minimum daily energy requirements. Farmers of all farm types, and in all regions, attach high relevance to IVs' provisioning ES, particularly the ability to provide food. A majority of farmers in all regions highlighted the relevance of regulating ES, including climate regulation, water storage, and groundwater values for their wellbeing. In contrast, farmers attached relatively lower relevance to cultural ES. Interventions to improve national rice production need to acknowledge and preserve the diversity ES that IVs provide to smallholder farm households.

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Statista (2024). Number of people living in extreme poverty in Ghana 2016-2026 [Dataset]. https://www.statista.com/statistics/1439971/number-of-individuals-living-in-extreme-poverty-in-ghana/
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Number of people living in extreme poverty in Ghana 2016-2026

Explore at:
Dataset updated
Jun 30, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Ghana
Description

As of 2024, some 6.9 million people in Ghana lived in extreme poverty, with the poverty threshold at 2.15 U.S. dollars per day. This stood as an increase from the previous year when roughly 6.8 million people lived in the said state of poverty. In 2026, around 6.7 million Ghanaians are expected to live on a maximum of 2.15 U.S. dollars daily.

Poverty in the country is segregated

Indeed, poverty figures do not considerably vary when considering men and women apart. In 2024, around 3.5 million men lived in extreme poverty in Ghana, while the count reached roughly 3.3 million for women. On the other hand, in distinguishing the state of extreme poverty among rural and urban dwellers, the difference is striking, even when based on the previously set poverty line of 1.90 U.S. dollars per day. Overall, 1.1 percent of the world's population in extreme poverty lived in Ghana as of 2024.

Ghana's Private Wealth Position in Africa

Ghana is one of the African countries with the highest private wealth concentration, ranking 6th after Kenya as of 2021. That year, the country's total private wealth amounted to 59 billion U.S. dollars, corresponding to around 1,900 U.S. dollars per capita. Between 2011 and 2021, the total wealth held by individuals in Ghana increased, representing a higher growth in comparison to other African countries save five. Overall, the nation ranks 9th in Africa in terms of countries with high net-worth individuals.

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