Your search found 7 records
1 Roe, T.; Diao, X.. 1997. The strategic interdependence of a shared water aquifer: A general equilibrium analysis. In Parker, D. D.; Tsur, Y. (Eds.), Decentralization and coordination of water resource management. Norwell, MA, USA: Kluwer Academic Publishers. pp.155-178.
Aquifers ; Water policy ; International cooperation ; Water use ; Models ; Water table ; Water rates ; Water rights ; Water supply ; Water costs / Israel / Jordan / Gaza / West Bank
(Location: IWMI-HQ Call no: 333.91 G000 PAR Record No: H020839)
2 Diao, X.; Roe, T. 2000. The win-win effect of joint water market and trade reform on interest groups in irrigated agriculture in Morocco. In Dinar, A. (Ed.), The political economy of water pricing reforms. New York, NY, USA: OUP, for the World Bank. pp.141-165.
Water market ; Irrigated farming ; Water allocation ; Price policy ; Models ; Water rates ; Irrigation water ; Households ; Water market ; Water rights ; Water users / Morocco
(Location: IWMI-HQ Call no: 631.7.4 G000 DIN Record No: H026583)
3 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)
4 Pratt, A. N.; Diao, X.; Johnson, M.; Minde, I.; Chilonda, Pius; Olubode-Awosola, Femi. 2007. Agricultural growth linkages and market opportunities in southern Africa. Pretoria, South Africa: Regional Strategic Analysis and Knowledge Support System for Southern Africa (ReSAKSS-SA) 3. 8p. (ReSAKSS-SA Issues Brief 003)
Agricultural development ; Agricultural production ; Trade ; Food consumption / South Africa / Zambia / Zimbabwe / Malawi / Mozambique
(Location: IWMI HQ Call no: e-copy only Record No: H041606)
http://www.resakss.org/publications/ReSAKSS-SA%20Issue%20Brief%203-Final.pdf
https://vlibrary.iwmi.org/pdf/H041606.pdf
https://vlibrary.iwmi.org/pdf/H041606.pdf
5 Nin-Pratt, A.; Diao, X.; Bahta, Yonas. 2008. Assessing potential welfare impacts on agriculture of a regional free trade agreement in Southern Africa. Pretoria, South Africa: Regional Strategic Analysis and Knowledge Support System for Southern Africa (ReSAKSS-SA); Washington, DC, USA: International Food Policy Research Institute (IFPRI) 69p. (ReSAKSS-SA Working Paper 015)
(Location: IWMI HQ Call no: 338.1 G154 NIN Record No: H042065)
(0.65 MB)
6 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.
7 Boughton, D.; Goeb, J.; Lambrecht, I.; Headey, D.; Takeshima, H.; Mahrt, K.; Masias, I.; Goudet, S.; Ragasa, C.; Maredia, M. K.; Minten, B.; Diao, X.. 2021. Impacts of COVID-19 on agricultural production and food systems in late transforming Southeast Asia: the case of Myanmar. Agricultural Systems, 188:103026. (Online first) [doi: https://doi.org/10.1016/j.agsy.2020.103026]
Agricultural production ; Agrifood systems ; COVID-19 ; Rural areas ; Livelihoods ; Food security ; Agroindustrial sector ; Agricultural trade ; Food prices ; Household income ; Economic aspects ; Policies / South East Asia / Myanmar
(Location: IWMI HQ Call no: e-copy only Record No: H050204)
https://www.sciencedirect.com/science/article/pii/S0308521X20308878/pdfft?md5=8ec3733006656f7e2cb2f2cab3585103&pid=1-s2.0-S0308521X20308878-main.pdf
https://vlibrary.iwmi.org/pdf/H050204.pdf
https://vlibrary.iwmi.org/pdf/H050204.pdf
(2.12 MB) (2.12 MB)
The objective of this contribution is to report the initial impacts of measures taken to contain the COVID-19 pandemic on Myanmar's agri-food system. Myanmar is one of several late-transforming low-income countries in Southeast Asia where agriculture still plays a large role in rural livelihoods, and where food prices are a key factor affecting nutrition security for poor urban and rural households. Whereas the economic impacts of COVID-19 disruptions on tourism and manufacturing were obvious to policymakers, the impacts on the agri-food system were less evident and often more indirect. This resulted in the rural sector being allocated only a very small share of the government's initial fiscal response to mitigate the economic impacts of COVID-19.
To correct this information gap, a suite of phone surveys covering a wide spectrum of actors in the agri-food system were deployed, including farm input suppliers, mechanization service providers, farmers, commodity traders, millers, food retailers and consumers. The surveys were repeated at regular intervals prior to and during the main crop production season which began shortly after nationwide COVID-19 prevention measures were implemented in April. While the results indicate considerable resilience in the agri-food system in response to the initial disruptions, persistent financial stress for a high proportion of households and agri-food system businesses indicate that the road to a full recovery will take time. The experience provides important lessons for strengthening the resilience of the agri-food system, and the livelihoods of households that depend on it.
To correct this information gap, a suite of phone surveys covering a wide spectrum of actors in the agri-food system were deployed, including farm input suppliers, mechanization service providers, farmers, commodity traders, millers, food retailers and consumers. The surveys were repeated at regular intervals prior to and during the main crop production season which began shortly after nationwide COVID-19 prevention measures were implemented in April. While the results indicate considerable resilience in the agri-food system in response to the initial disruptions, persistent financial stress for a high proportion of households and agri-food system businesses indicate that the road to a full recovery will take time. The experience provides important lessons for strengthening the resilience of the agri-food system, and the livelihoods of households that depend on it.
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