Targeting capacity building for quantitative foresight modeling - G.Nelson - GCARD Uruguay
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The document discusses capacity building for quantitative foresight modeling, targeting users such as policymakers, researchers, and civil society. It highlights the Global Futures Project, which aims to determine optimal investment strategies for the CGIAR, assessing financial returns and impacts on poverty and sustainability through various climate scenarios. Additionally, it presents insights into drought-resistant technologies and their welfare effects across several developing countries.
![Who is the user?
 Policy users
• High level policy makers
• Policy staff [advisor to policy maker]
• Technical staff
 Research users
• Foresight modelers
• Researchers and research funders
 Range of end users
• Civil society organizations
• Private sector [includes farmers, input suppliers, downstream and
upstream businesses, etc.)](https://image.slidesharecdn.com/targetingcapacitybuildingforquantitativeforesightmodeling-121030031758-phpapp01/85/Targeting-capacity-building-for-quantitative-foresight-modeling-G-Nelson-GCARD-Uruguay-2-320.jpg)
Targeting capacity building for quantitative foresight modeling - G.Nelson - GCARD Uruguay
- 1. Targeting capacity building for quantitative foresight modeling Gerald Nelson Senior Research Fellow IFPRI INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE
- 2. Who is the user?  Policy users • High level policy makers • Policy staff [advisor to policy maker] • Technical staff  Research users • Foresight modelers • Researchers and research funders  Range of end users • Civil society organizations • Private sector [includes farmers, input suppliers, downstream and upstream businesses, etc.)
- 3. What is the question? For the Global Futures project…. If an investor provides an additional $x million to the CGIAR, how should it be spent to provide the greatest return on investment? • Financial ROI • Reduction in poverty • Improvements in sustainability  Global Futures project develops methods, tools, and a consistent system to help the CGIAR answer this question.  Plausible scenarios are key
- 4. Overall scenarios: Plausible futures for population and GDP growth  Optimistic • High GDP and low population growth  Baseline • Medium GDP and medium population growth  Pessimistic • Low GDP and high population growth
- 5. Five climate scenarios  Climate scientists “All scenarios have equal probability.”  Our modeling approach, for each overall scenario, use climate scenarios from… • Two GCMs – MIROC (Japanese) and CSIRO (Australian) with • Two SRES scenarios – A1B and B1 • Perfect mitigation
- 6. Climate change scenario effects differ (price increase (%), 2010 – 2050, Baseline economy and demography) Minimum and maximum effect from four climate scenarios
- 7. Assessing food security and climate change outcomes 3,600 Optimistic scenario Pessimistic scenario Developed 3,400 countries 3,200 3,000 2,800 All developing Kcals/day countries Perfect 2,600 mitigation 2,400 Low-income developing 2,200 countries 2,000 1,800
- 8. ROI, Drought Tolerant Groundnut (Proof of Concept Only) Welfare and returns on Climate change scenarios investment No climate MIROC MIROC CSIRO CSIRO change 369 A1B 369 B1 369 A1B 369 B1 Changes in producer surplus -3,876 -4,275 -3,790 -4,540 -4,698 (NPV, m US$) Changes in consumer surplus 10,443 11,338 10,082 11,997 12,507 (NPV, m US$) 6,567 7,063 6,292 7,457 7,809 Net welfare change (NPV, m US$) Cost (NPV, m US$) 15 15 15 15 15 Benefit-cost ratio 448 482 430 509 533 Net benefits (NPV, m US$) 6,553 7,048 6,277 7,443 7,795 IRR (%) 54 55 53 55 56
- 9. Welfare Effects: Drought-tolerant groundnut (Proof of concept only) D Malnourished D At Risk of Target D Kcals per $ Regions children per $ Hunger per $ countries invested invested invested (million) Malawi 1.9 -1,285 -6.1 ESA Tanzania 0.6 -672 -3.6 Uganda 1.7 -1,824 0.0 Burkina Faso 3.6 -1,666 -1.8 Ghana 3.1 -904 0.0 WCA Mali 2.5 -935 0.0 Nigeria 4.4 -13,604 -4.9 Senegal 5.6 -973 0.0 India 0.9 -8,840 -32.0 Indonesia 1.2 -1,429 0.0 SSEA Myanmar 3.0 -971 -6.9 Vietnam 1.0 -511 -1.4
- 10. Global Futures outputs  Strategic foresight quantitative modeling tools for ex ante evaluation of promising technologies  Outreach – Food Security Futures Conference • first scheduled tentatively April 11-12, 2013  Capacity building • To increase range of foresight tools available to users
Editor's Notes
- #6: Two GCMs and two SRES scenarios, chosen for wide range of global average precipitation outcomes. MIROC has higher temperatures and more precipitation on average but greater variation across the globe. Data from 4th IPCC assessment. Perfect mitigation is extremely unlikely. It would mean an immediate stop to all GHG emissions AND the momentum given the existing GHGs in the atmosphere.
- #7: Maize price mean increase is 101 % higher; max is 131, min is 83Rice price mean increase is 55; max is 57, min is 53Wheat price mean increase is 54; max is 66, min is 45All these are for the baseline overall scenario
- #8: Key messagesWith income per capita growth rates in the optimistic scenario, average kcals per day growth very rapidly in the developing countries. Climate change reduces calorie availability, partially offsetting the benefits from income growthThe kink around 2025 is due to our assumptions of a switch to celluosic ethanol, reducing biofuels use of food.