Your search found 9 records
1 Pender, J.; Gebremedhin, B.; Benin, S.; Ehui, S. 2001. Strategies for sustainable agricultural development in the Ethiopian highlands. IFPRI discussion paper - Environment and production Technology Division. ii, 21p. (EPTD discussion paper no.77)
Sustainable agriculture ; Agricultural development ; Soil degradation ; Population growth ; Farmers ; Villages ; Land management / Ethiopia
(Location: IWMI-HQ Call no: P 5935 Record No: H029409)
2 Omamo, S. W.; Diao, X.; Wood, S.; Chamberlin, J.; You, L.; Benin, S.; Wood-Sichra, U.; Tatwangire, A. 2006. Strategic priorities for agricultural development in eastern and central Africa. Washington, DC, USA: IFPRI. 140p. (IFPRI Research Report 150)
Agricultural development ; Economic aspects ; Models ; Land use ; Poverty / Africa / Burundi / Congo / Eritrea / Ethiopia / Kenya / Madagascar / Rwanda / Sudan / Tanzania / Uganda
(Location: IWMI HQ Call no: 338.1 G100 OMA Record No: H040109)
3 Benin, S.; Johnson, M.; Beintema, N.; Bekele, H.; Chilonda, Pius; Kirsten, I.; Edeme, J.; Elmekass, A.; Govereh, J.; Kakuba, T.; Karugia, J.; Makunike, R.; Massawe, S.; Mpyisi, E.; Nwafor, M.; Omilola, B.; Olubode-Awosola, Femi; Sanyang, S.; Taye, B.; Wanzala, M.; Yade, M.; Zewdie, Y. 2008. Monitoring and Evaluation (M&E) System for the Comprehensive Africa Agriculture Development Programme (CAADP). Washington, DC: International Food Policy Research Institute (IFPRI). 45p. (ReSAKSS Working Paper 6)
Agriculture ; Economic aspects ; Monitoring ; Evaluation ; Investment ; Expenditure ; Indicators ; Data collection / Africa
(Location: IWMI HQ Call no: e-copy only Record No: H042797)
(0.52 MB)
The purpose of this document is to develop a framework to be used in monitoring progress towards the successful implementation of CAADP and for providing a conceptual basis for assessing the impacts and returns to CAADP investments. With the perspective of managing for impact, the main objectives are: (1) to identify a set of key indicators that are consistent with the underlying logic of CAADP to track progress in resource allocation and achieving stated targets and help answer questions related to the relevance, effectiveness, efficiency, impact and sustainability of the programme; (2) to identify the data required, sources, and methods for estimating values of the indicators; and (3) to lay out a plan for implementing the framework in terms of collecting, managing and analyzing the data, reporting results of the analysis, and obtaining and incorporating feedback for further improvement of the system. This document, and the ultimate outputs of the M&E system, is thus primarily targeted to stakeholders at the national, regional and continent-wide level involved with directing or managing resources for implementing CAADP. This includes: Ministries of Finance, Agriculture, and Local Governments; Departments of Agriculture within Regional Economic Communities, AU/NEPAD, and the donor community concerned with agriculture in Africa. The document and outputs of the system will also be useful to researchers and others interested in CAADP or knowledge on monitoring and evaluating public agricultural investments in general.
4 Chilonda, Pius; Johnson, M.; Benin, S.. 2010. Strategic Analysis and Knowledge Support System (SAKSS): informing the implementation of the Comprehensive Africa Agriculture Development Program (CAADP) in Africa. [Abstract only] In ACP-EU Technical Centre for Agricultural and Rural Cooperation (CTA). CTA Annual Seminar, Closing the Knowledge Gap: Integrated Water Management for Sustainable Agriculture, Johannesburg, South Africa, 22–26 November 2010. Abstracts. Wageningen, Netherlands: ACP-EU Technical Centre for Agricultural and Rural Cooperation (CTA). pp.36.
(Location: IWMI HQ Call no: 630 G100 TEC Record No: H043478)
(0.06 MB) (652.11 KB)
5 Johnson, M.; Benin, S.; You, L.; Diao, X.; Chilonda, Pius. 2014. Exploring strategic priorities for regional agricultural research and development investments in Southern Africa. Washington, DC, USA: International Food Policy Research Institute (IFPRI). 140p. (IFPRI Discussion Paper 01318)
Agricultural research ; Agricultural development ; Investment ; Economic growth ; Indicators ; Markets ; Models ; Yield gap ; Cereal crops ; Farming systems ; Livestock products / Southern Africa
(Location: IWMI HQ Call no: e-copy only Record No: H046297)
http://www.ifpri.org/sites/default/files/publications/ifpridp01318.pdf
https://vlibrary.iwmi.org/pdf/H046297.pdf
https://vlibrary.iwmi.org/pdf/H046297.pdf
(4.27 MB) (4.27 MB)
An in-depth quantitative analysis is undertaken in this paper to assist the Southern African Development Community (SADC) Secretariat, member countries, and development partners in setting future regional investment priorities for agricultural research and development in the SADC region. A primary goal of this work was to identify a range of agricultural research priorities for achieving sector productivity and overall economic growth in southern Africa, at both the country and regional levels. This is accomplished by adopting an integrated modeling framework that combines a disaggregated spatial analytical model with an economywide multimarket model developed specifically for the region. The spatial disaggregation uses information on current yield gaps to project growth and technology spillovers across countries among different agricultural activities that share similar conditions and thus potential for adoption and diffusion in the region. The economywide multimarket model is used to simulate ex ante the economic effects of closing these yield gaps through a country’s own investments in research and development (R&D) and from potential R&D spill-ins from neighboring countries. Results indicate a high potential of spillovers and technology adaptability across countries due to similar agroecological and climatic conditions and the countries’ own capacities for adaptive R&D. The greatest agriculture-led growth opportunities reside in staple crops and in roots and tubers, especially among the low-income countries. Together, these sectors have the potential to contribute up to 40 percent of future possible growth. There are differences (areas of comparative advantage) at the country level that offer opportunities for specialization. For example, grains are the dominant subsector for Zimbabwe; in Botswana, opportunities will depend on more growth in its livestock sector; and for Namibia promoting fish growth may be more important. The root crops sector is as important as that of grains in Angola, Democratic Republic of the Congo, and Malawi, but even more important in Mozambique. The study finds evidence of high spillover potential, especially for maize, rice, cattle, cassava, sorghum, and beans. Low-income countries gain the most from spill-in of R&D in the grains and roots subsectors; yield growth in these subsectors explains about 20 percent of these countries’ gains in the total value of production, compared with only 2.2 percent among middle-income countries. Our results emphasize not only the importance of expanding regional cooperation in R&D and technology diffusion in southern Africa, but the importance of strengthening regional agricultural markets and linkages with nonagricultural sectors.
6 Benin, S.. (Ed.) 2016. Agricultural productivity in Africa: trends, patterns, and determinants. Washington, DC, USA: International Food Policy Research Institute (IFPRI). 359p. [doi: https://doi.org/10.2499/9780896298811]
Agricultural production ; Land productivity ; Agricultural development ; Growth rate ; Trends ; Development policies ; Farming systems ; Crop production ; Intensification ; Labour productivity ; Fertilizer application ; Technological changes ; Farmland ; Typology ; Spatial variation ; Development projects ; Performance evaluation ; Sustainability ; Farmers ; Population density ; Market access ; Forests ; Case studies / Africa
(Location: IWMI HQ Call no: 338.16 G100 BEN Record No: H047988)
http://www.ifpri.org/cdmref/p15738coll2/id/130468/filename/130679.pdf
https://vlibrary.iwmi.org/pdf/H047988.pdf
https://vlibrary.iwmi.org/pdf/H047988.pdf
(5.03 MB) (5.03 MB)
7 Makombe, T.; Tefera, W.; Matchaya, Greenwell; Benin, S.. 2017. Tracking key CAADP [Comprehensive Africa Agriculture Development Programme] indicators and implementation processes. In De Pinto, A.; Ulimwengu, J. M. (Eds.). A thriving agricultural sector in a changing climate: meeting Malabo declaration goals through climate-smart agriculture. Washington, DC: International Food Policy Research Institute (IFPRI) pp.147-157. ( ReSAKSS Annual Trends and Outlook Report 2016)
Agricultural development ; Agricultural production ; Agricultural sector ; Economic growth ; Poverty ; Food security ; Nutrition ; Stakeholders ; Risk management / Africa
(Location: IWMI HQ Call no: e-copy only Record No: H048453)
https://www.ifpri.org/publication/tracking-caadp-indicators-and-processes
https://vlibrary.iwmi.org/pdf/H048453.pdf
https://vlibrary.iwmi.org/pdf/H048453.pdf
8 Benin, S.; Ulimwengu, J.; Matchaya, Greenwell; Makombe, T.; Lorka, M.; Vodounhessi, A.; Tefera, W. 2018. Mutual accountability in CAADP [Comprehensive Africa Agriculture Development Programme] and agricultural transformation. In Alliance for a Green Revolution in Africa (AGRA). Africa agriculture status report: catalyzing government capacity to drive agricultural transformation (Issue 6). Nairobi, Kenya: Alliance for a Green Revolution in Africa (AGRA) pp.150-184.
Agricultural development ; Agricultural policy ; Agricultural sector ; Development programmes ; Stakeholders ; Infrastructure ; Food security ; Nutrition ; Policy making ; Accountability ; Assessment ; Resource allocation ; Water governance / Africa
(Location: IWMI HQ Call no: e-copy only Record No: H048892)
(13.6 MB)
9 Benin, S.; Karugia, J.; Matchaya, Greenwell; Yade, M. 2020. Improving data quality for the CAADP [Comprehensive Africa Agriculture Development Programme] biennial review: a partnership initiative piloted in five countries. Washington, DC, USA: International Food Policy Research Institute (IFPRI). 54p. (IFPRI Discussion Paper 01925) [doi: https://doi.org/10.2499/p15738coll2.133715]
Data management ; Agricultural development ; Pilot projects ; Development programmes ; Partnerships ; Planning ; Assessment ; Indicators ; Standards ; Knowledge management ; Policy making ; Hunger ; Strategy planning ; Stakeholders ; Training ; Organizations / Kenya / Malawi / Mozambique / Senegal / Togo
(Location: IWMI HQ Call no: e-copy only Record No: H049714)
https://www.ifpri.org/cdmref/p15738coll2/id/133715/filename/133927.pdf
https://vlibrary.iwmi.org/pdf/H049714.pdf
https://vlibrary.iwmi.org/pdf/H049714.pdf
(1.11 MB) (1.11 MB)
This paper presents results of a data partnership framework for strengthening evidence-based planning and implementation that was initiated in 2019 in five selected African countries (Kenya, Malawi, Mozambique, Senegal, and Togo) during the second round of the CAADP biennial review (BR) process. It analyzes the effect of the activities conducted on the data reporting rate and the quality of data reported in the five pilot countries, compared with what was achieved in like-pilot countries. The like-pilot countries are non-pilot countries that have characteristics like the pilot countries at the baseline which affect selection into the pilot or the data reporting and quality outcomes. Different methods (standard deviations, propensity score matching, and two-stage weighted regression) are used to identify the like-pilot countries, and a difference-in-difference method is used to estimate the effect of the pilot activities on the outcomes.
The capacity-strengthening activities focused on working with the country Biennial Review (BR) team to: assess the inaugural or 2018 BR process and identify the data gaps; constitute and train members of data clusters to compile and check the data for the 2020 BR; and then validate and submit the data. The findings show that the activities helped the pilot countries to improve their performance in the data reporting rate and the quality of data reported in the 2020 BR. The largest improvement is observed in Togo and Senegal, followed by Kenya and Malawi, and then Mozambique.
The average increase in the data reporting rate between 2018 and 2020 BRs for the pilot countries is greater than the average progress made in the like-pilot countries by about 6 to 9 % pts. This derives mostly from improvements in the data reporting rate for the indicators under theme 3 on ending hunger. Regarding the quality of data reported (measured as the percent of the data reported that have issues) too, the pilot countries on average performed better than the like-pilot countries, especially with respect to the data reported under themes 2 on investment in agriculture and 3 on ending hunger. But most of the estimated differences have low or no statistical significance. Implications for sustaining the progress made in the pilot countries, as well as for extending the activities to other countries, for the next rounds of the BR are discussed.
The capacity-strengthening activities focused on working with the country Biennial Review (BR) team to: assess the inaugural or 2018 BR process and identify the data gaps; constitute and train members of data clusters to compile and check the data for the 2020 BR; and then validate and submit the data. The findings show that the activities helped the pilot countries to improve their performance in the data reporting rate and the quality of data reported in the 2020 BR. The largest improvement is observed in Togo and Senegal, followed by Kenya and Malawi, and then Mozambique.
The average increase in the data reporting rate between 2018 and 2020 BRs for the pilot countries is greater than the average progress made in the like-pilot countries by about 6 to 9 % pts. This derives mostly from improvements in the data reporting rate for the indicators under theme 3 on ending hunger. Regarding the quality of data reported (measured as the percent of the data reported that have issues) too, the pilot countries on average performed better than the like-pilot countries, especially with respect to the data reported under themes 2 on investment in agriculture and 3 on ending hunger. But most of the estimated differences have low or no statistical significance. Implications for sustaining the progress made in the pilot countries, as well as for extending the activities to other countries, for the next rounds of the BR are discussed.
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