1. Liangzhi You February 20, 2017 Dar es Salaam, Tanzania
Strengthening Capacity For Evaluating Impact Of Agricultural R&D: The Case Of DREAM
Liangzhi You
February 20, 2017
Dar es Salaam, Tanzania

2. Presentation Outline Rationale – Why Evaluate R&D? What does DREAM do?
How did DREAM evolve?
How was DREAM used?
Lessons and conclusions
Further Development of DREAM

3. Why Evaluate R&D? External needs Justify past investments
Demonstrate institutional effectiveness
Reassure stakeholders that their concerns are being addressed
Substantiate new funding requests
Emphasis: Accountability and Securing Funding

4. Why Evaluate R&D? Internal needs
Learn lessons on what does and what doesn’t work
Set strategic priorities
Evaluate investment targeting options
Improve research efficiency
Emphasis: More bang for the buck (“learning”)

5. What does DREAM do? Dynamic Research EvAluation for Management - DREAM
A menu-driven software package that would improve the effectiveness of R&D analysts, often working alone with limited resources
Provide IFPRI and others with its own means of supporting strategic research evaluation activities
As a platform for delivering incremental method and data advances to analysts as we do more research, gain more experience in applications, and get better in interpreting and packaging results
Welfare measures, counterfactuals
trade, technology spillover, regional R&D
Common conceptual approach and R&D method

6. DREAM Market Screen

7. DREAM Adoption Screen

8. How did DREAM evolve?
Intellectual heritage from Australian agricultural economists in 1980s
First DOS version was developed at ISNAR in early 1990s. First used by ISNAR staff and then by consultants and collaborators
DREAM model first included in Science Under Scarcity by Alston, Norton and Pardey in 1995
First windows-based version in 1999, and freely available at a dedicated DREAM homepage. An official release during 2000 CGIAR Annual General Meeting

9. DREAM Downloads From 1999 to 2014

10. Regional shares of DREAM web downloads (1999-2014)

11. DREAM Downloads by Organizational Type (1999-2014)

12. How was DREAM used?
IFPRI SAKSS: DREAM was used along with multi-market model and CGE model for priority setting and investment options
ACIAR funded DREAM development and adopted DREAM as impact assessment tool
Two IFPRI research reports, over 10 known peer-reviewed publications using DREAM (e.g. on Food Policy, Agricultural Economics, Australian J of Ag Econ).
Many researchers outside IFPRI used DREAM in project reports and internal publications
A few Master theses using DREAM

13. DREAM training
DREAM training workshops in Africa such as Nigeria, Uganda, Kenya, Egypt.
ACIAR conducted DREAM trainings in Asia such as Thailand, Vietnam, Indonesia
Chinese Academy of Agricultural Science sent two researchers to IFPRI to learn and translate/customize DREAM for Chinese policy analysts

14. What did users say about DREAM?
“The model’s attractions were that it provided a rigorous benefit-cost mechanism based on the principles of economic surplus analysis… We used the model in several applications; in evaluating the costs of annual grass weeds in temperate pastures (Vere et al. 2002), in estimating the benefits from the biological control of rabbits in the temperate areas (Vere et al. 2004), and in estimating the costs of weeds in winter cropping systems (Jones et al. 2005)”.
By an Australian researcher

15. Lessons and Conclusion
DREAM has been proved to be not only a useful tool for research evaluation but also an effective tool for training and capacity building.
Explore the synergy between research and capacity building
To enable greater access and the increased capacity to use DREAM model, it needs updating to incorporate the recommended revisions of past users, dissemination of the new modules and software, and capacity strengthening through training of trainers.
New version of DREAM is coming soon

16. Further development of DREAM
DREAM dreaming?
Further development of DREAM

17. 1. Calculate K From Farm-level Data
supply shift for annual crop – pre-harvest
supply shift for annual crop – post-harvest
Supply shift for perennial crop
Supply shift for aquaculture
Livestock model (?)

18. DREAM Interface
simply increasing production, which engages the “race-to-bottom’ competition between coffee producer countries, is not a good policy because oversupply is the root cause of the coffee price collapse.
Uganda has room and even advantage to improve its coffee quality and farm productivity. Improve economic incentives at farm-level to produce better quality coffee and raise productivity
The world market is all-decisive to Uganda coffee. Uganda therefore needs to get more involved in efforts to stablize world coffee price: increase coffee consumption, reduce production of lower-quality coffee worldwide.

19. On-farm Data Input

20. 2. Stochastic DREAM
Include probability distributions for key parameters
K shift
Adoption rate
Spillover coefficient
Elasticities of supply, demand, income
Generate benefit distributions

21. 3. Interface to Other Applications
Import function for market data
Import function for spillover matrix
Interface to input/output data to CGE (Computable General Equilibrium) Model

22. International Food Policy Research Institute
My Contact
Liangzhi You
International Food Policy Research Institute
2033 K Street, NW
Washington, DC 20006
USA
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