Presentation from the CCAFS Farm-household Modeling workshop - Amsterdam, 23-35 April 2012

1. TOA-MD: Tradeoffs Analysis for
Multidimensional Impact Assessment
Roberto O.Valdivia
and
John M. Antle
CCAFS Modeling Workshop
Amsterdam, The Netherlands
April, 2012

2. What is the TOA-MD Model?
The TOA-MD Model is a unique simulation tool for multi-dimensional impact
assessment that uses a statistical description of a heterogeneous farm population
to simulate the adoption and impacts of a new technology or a change in
environmental conditions.
TOA-MD is designed to simulate what would be observed if it were possible to
conduct a controlled experiment. In this experiment, a population of farms is
offered the choice of continuing to use the current or “base” production system
(System 1), or choosing to adopt a new system (System 2).
In fact it is never possible to carry out such ideal experiments, so TOA-MD is
designed to utilize the available data to attain the best possible approximation,
given the available time and other resources available to conduct the analysis.
Additionally, TOA-MD is designed to facilitate analysis of the inevitable
uncertainties associated with impact assessment.

3. TOA-MD approach: modeling systems
used by heterogeneous populations
A system is defined in terms of
household, crop, livestock and
aquaculture sub-systems
Systems are
being used in
heterogeneous
populations

4. (ω)
Opportunity cost, system
choice and adoption
Opportunity cost = v1 – v2 follows
distribution ( )
v1 = returns to system 1
V2 = returns to system 2
System 2: < 0 System 1: > 0
(adopters) (non-adopters)
0 opportunity cost
Map of a
heterogeneous
region

5. A useful adaptation shifts the
distribution of opportunity cost
and the adoption curve,
increasing gains and reducing The difference between the
losses, to give a net gain from curves is the gain from
adaptation when all farms
adaptation
use the adapted technology
( ) r(2)
100
Adoption
rate

6. Adoption, Outcome Distributions and Impact
Indicators
 Outcome distributions are associated with system choice
◦ Farms select themselves into “non-adopter” and “adopter” sub-
populations, generating corresponding outcome distributions for
these sub-populations
 Impact indicators are based on system choice and
outcome distributions
◦ TOA-MD produces mean indicators and threshold-based indicators
 Analysis shows that impacts depend on the correlations
between adoption (opportunity cost) and outcomes
◦ Many impact assessments ignore correlations
◦ Yet these correlations are often important for accurate impact
assessment!

7. Adoption and outcome distributions
(z|1)
System 1 before adoption:
25% > threshold
r(1,a)% non-
Outcome z
adopters
r(2,a)% adopters
(z|1,a) (z|2,a)
System 1: 20% > (z|a)
System 2: 90% >
Entire Population with
adoption: 55% >

8. Components of the Model
Design
Population (Strata)
System characterization Impact indicator design
Data
Opportunity cost distribution Outcome distributions
Simulation
Indicators and
Adoption rate
Tradeoffs

9. Types of application
TECHNOLOGY ADOPTION AND IMPACT ASSESSMENT
The TOA-MD allows users to simulate technology adoption (i.e. adoption rate)
under a variety of conditions defined by the user. The TOA-MD has the
capability of simulate impacts of technology adoption using statistical
relationships between technology adoption and environmental, economic and
social outcomes. Impacts are defined as population means or as the proportion
of the population above or below a threshold (e.g. poverty line). Examples of
technology adoption applications are:
• Introduction of new crop varieties
• Crop and livestock management
• Soil conservation & agroforestry
• Integrated agriculture – aquaculture

10. Types of application, cont.
ECOSYSTEM SERVICES SUPPLY AND PAYMENTS
The TOA-MD can simulate supply curves for ecosystem services associated
with agricultural systems and payments schemes. Examples of these
applications are:
Soil carbon sequestration and GWP
Water quality and quantity
Biodiversity
ENVIRONMENTAL CHANGE
The TOA-MD allows users to assess impacts of any exogenous
environmental change such as climate change on population of farms.
Examples of these applications are:
Simulate impacts of and adaption to climate change
Changes in water quantity and quality

11. Application Impacts
Economic (e.g. income based
Technology Adoption poverty rate, farm income, other
poverty indicators)
cv
Ecosystemcv
services Social (e.g. food security
indicators, , health)
Environmental change Environmental (e.g. soil depletion,
water quality)
Recent applications
- Preliminary Economic, Environmental and Social Impact Assessment of the EADD Project in Kenya using
Minimum-Data Tradeoff Analysis. Gates Foundation, ILRI
- Integrated Agriculture-Aquaculture in Malawi. –USAID/AQCRSP
- IFAD Projects: Ghana, Bangladesh, Malawi - World Fish Center
- Climate change and adaptation : AgMIP
- Livelihood Strategies and Adoption of Endemic Ruminant Livestock Breeds, ILRI
- Climate change: Kenya (Claessens et al, 2012), CIP-ICRISAT

12. Final remarks
The TOA-MD can:
 Simulate technology adoption (estimate an adoption rate) under a
variety of conditions defined by the user
 Assess economic, environmental and social impacts of technology
adoption, using population mean and threshold indicators
 Simulate supply curves for ecosystem services associated with
agricultural systems
 Assess impacts of environmental change, such as climate change,
with or without adaptation
Training in use of the model, and the model software are available
from the TOA Team.

13. Key Publications
Claessens, L., J.M. Antle, J.J. Stoorvogel, R.O. Valdivia, P.K. Thornton, and M. Herrero. 2012. “A minimum-data approach for agricultural
system level assessment of climate change adaptation strategies in resource-poor countries.” Agricultural Systems, Forthcoming.
Antle, J.M. 2011. “Parsimonious Multi-Dimensional Impact Assessment.” American Journal of Agricultural Economics.
Antle J.M. and R.O. Valdivia. "Methods for Assessing Economic, Environmental and Social Impacts of Aquaculture Technology: Integrated
Agriculture-Aquaculture in Malawi.” 9th Annual Fisheries and Aquaculture Forum, Shanghai Ocean University, April 22 2011
Antle, J.M., B. Diagana, J.J. Stoorvogel and R.O. Valdivia. 2010. “Minimum-Data Analysis of Ecosystem Service Supply in Semi-Subsistence
Agricultural Systems: Evidence from Kenya and Senegal.” Australian Journal of Agricultural and Resource Economics 54:601-617.
Claessens, L., J.J. Stoorvogel, and J.M. Antle. 2009. “Economic viability of adopting dual-purpose sweetpotato in Vihiga district, Western
Kenya: a minimum data approach. ” Agricultural Systems 99:13-22.
Nalukenge, I., J.M. Antle, and J.J. Stoorvogel. (2009). “Assessing the Feasibility of Wetlands Conservation Using Payments for Ecosystem
Services in Pallisa, Uganda.” In Payments for Environmental Services in Agricultural Landscapes . Ed. L. Lipper, T. Sakuyama, R. Stringer and D.
Zilberman. Springer Publishing.
Smart, F. 2009. Minimum-Data Analysis of Ecosystem Service Supply with Risk Averse Decision Makers. Ms. Thesis, Montana State University –
Bozeman.
Immerzeel, W., J. Stoorvogel and J. Antle. 2007. "Can Payments for Ecosystem Services Secure the Water Tower of Tibet?" Agricultural
Systems 96:52-63.
Antle, J.M. and J.J. Stoorvogel. 2006. "Predicting the Supply of Ecosystem Services from Agriculture." American Journal of Agricultural
Economics 88(5):1174-1180.
Antle, J.M., Valdivia, R. 2006. “Modelling the supply of ecosystem services agriculture: a minimum-data approach.” Australian Journal of
Agricultural and Resource Economics 50: 1–15.

14. Thanks..
http://tradeoffs.oregonstate.edu

15. Developments needed
to better deal with
this attribute
Attribute Covered If ‘yes’, which Which indicators For your For
in indicators were would you like to use model household
previous used? in future to deal with level models
analyses? attribute? in general
Economic Yes Poverty rate Link to
performanc Per capita income Market
e Total farm income equilibrium
Models
Food self- Yes - Protein
sufficiency Consumption
Food Yes Total calorie
security consumption, fish
consumption
(WF), dairy
consumption
(EADD)

16. Developments needed
to better deal with
this attribute
Attribute Covered If ‘yes’, which Which indicators For your For
in indicators were would you like to use model household
previous used? in future to deal with level models
analyses? attribute? in general
Climate Yes Change in
variability poverty,
environment,
other socio-econ
Risk Yes
Mitigation Yes
Adaptation Yes