Your search found 3 records
1 Chilonda, Pius; Govereh, J.; Kumwenda, I.; Chalomba, N. 2009. Recent food price trends in southern Africa: causes, impacts and responses. Pretoria, South Africa: Regional Strategic Analysis and Knowledge Support System for Southern Africa (ReSAKSS-SA). 77p. (ReSAKSS-SA Annual Trends Report 2009)
Food ; Prices ; Inflation ; Cereals ; Maize ; Seasonal variation ; Biofuels ; Food consumption ; Government policy ; Consumers / Africa / Southern Africa
(Location: IWMI HQ Call no: IWMI 338.1 G154 CHI Record No: H044075)
(0.31 MB)
2 Vermeulen, S.; Moussa, A. S.; Bhatta, Gopal Datt; Radeny, M. 2013. Knowledge: its role in hunger, nutrition and climate justice. In Irish Aid Programme. A new dialogue: putting people at the heart of global development. Papers of the Hunger, Nutrition and Climate Justice Conference, Dublin, Ireland, 15-16 April 2013. Dublin, Ireland: Irish Aid Programme. pp.15-18.
(Location: IWMI HQ Call no: e-copy only Record No: H045832)
http://www.irishaid.ie/media/irishaid/allwebsitemedia/30whatwedo/HNCJ-conference-papers_final_small.pdf
https://vlibrary.iwmi.org/pdf/H045832.pdf
https://vlibrary.iwmi.org/pdf/H045832.pdf
(0.39 MB) (10.58MB)
Climate change will change conditions for food and farming beyond all previous human experience. We need a new era of innovation, in which farmers and communities participate in learning networks, drawing on science and on others’ experiences to complement their local knowledge.
3 Li, J.; Huang, D. 2023. Multi-dimensional dynamic spatio-temporal evolution of the green development efficiency of water-energy-food in China. Water Policy, 25(2):122-145. [doi: https://doi.org/10.2166/wp.2023.145]
Water ; Energy consumption ; Food ; Environmental economics ; Economic development ; Policies ; Models ; Research / China
(Location: IWMI HQ Call no: e-copy only Record No: H051714)
https://iwaponline.com/wp/article-pdf/25/2/122/1178013/025020122.pdf
https://vlibrary.iwmi.org/pdf/H051714.pdf
https://vlibrary.iwmi.org/pdf/H051714.pdf
(0.87 MB) (888 KB)
This paper constructs a green development efficiency index framework of water-energy-food in China, and uses the Super-EBM model to measure it more accurately and scientifically. The existing studies on water-energy-food efficiency lack the analysis of regional differential decomposition and spatial state transition. In this paper, two kinds of models are used for complementary analysis. One is kernel density map, Dagum spatial Gini coefficient decomposition and traditional Markov chain, which does not contain spatial factors. The other is the global Moran index, spatial Markov chain and spatial spillover effect, including spatial factors. The spatio-temporal dynamic evolution of the green development efficiency of water-energy-food (GWEF) in China is compared from the perspective of national, regional and provincial dimensions. The conclusion is more scientific and comprehensive, which is conducive to the green collaborative development among water-energy-food, economy and environment in China. The study found that GWEF had a lot of room for improvement. The overall spatial difference was mainly derived from the regional difference. GWEF had a significant positive spatial autocorrelation. The development of GWEF maintained the convergence characteristics of clubs. The spatial spillover effect of the main influencing factors was studied.
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