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Targeting capacity
                 building for quantitative
                   foresight modeling

                               Gerald Nelson
                           Senior Research Fellow
                                   IFPRI




INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE
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.)
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
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
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
Climate change scenario effects differ
  (price increase (%), 2010 – 2050, Baseline economy and
                        demography)


                 Minimum and maximum
                 effect from four climate
                         scenarios
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
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
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
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

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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

  1. 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.
  2. 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
  3. 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.