Tradeoff Analysis and Beyond:

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Tradeoff Analysis and Beyond Integrating Science
and Economics to Support Informed Policy Decision
Making John M. Antle Department of Ag Econ
Econ Montana State University
CIP Lima May 2007
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• How can we provide information needed to support
  informed decision making?
• Understanding agriculture as a complex system
• ? full data and coupled, site-specific models
• Matching analysis to levels of spatial and
  system complexity to provide timely information
  that is sufficiently accurate to inform decision
  making
• ? minimum data analysis

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• Example Wetlands conservation in Uganda
• How to prevent encroachment in wetlands to
  protect water quality quantity, biodiversity?

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• The Ecosystem Service Challenge
• When ES not priced, farmers choose practices to
  max private returns, over-exploit wetlands
  resources from social point of view
• What mechanisms can be used to induce farmers to
  use wetlands resources efficiently?
• The stick Command-and-control regulation or
  punitive incentives
• The carrot positive incentives (PES)
• What role can agricultural science and technology
  play in the solution?
• Can institutions be created to link farmers
  (suppliers of ES) to beneficiaries (demanders)?

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Integrated assessment approach using coupled
site-specific bio-phys and econ processes to
characterize spatial and temporal distributions
of environmental and economic outcomes What level
of data and model complexity are needed to
support decision making?
External Drivers and Market Equil.
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In the beginningTradeoff Analysis
A participatory process, not a model

• Public stakeholders
• Policy makers
• Scientists

• Identify key sustainability indicators and
  tradeoffs
• Identify technology and policy scenarios

• Identify key disciplines in research team
• Define spatial and temporal scales of analysis
  for
• disciplinary integration and policy analysis

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• What are the sustainability indicators for the
  wetland agro-ecosystem?
• Economic and social indicators
• Agricultural prod. productivity
• Income
• Food security
• Poverty
• Conflicts over use
• Soil productivity/degradation
• Environmental indicators
• Water quality (eutrophication, contamination,
  sedimentation)
• Water quantity (less water in boreholes (wells))
• Biodiversity (fish, birds, plants)
• Micro-climate
• Health indicators
• Malaria
• Malnutrition
• Bilharzia

There was a consensus that most of the indicators
are worsening.
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• What can be done to improve the system
  (scenarios)?
• Create awareness and provide training and
  incentives for improved soil and water
  conservation (for both uplands and lowlands).
• Restoration of wetlands and water catchments
  (e.g. agro-forestry).
• Nutrient management improved access and
  affordability of fertilizers, use of cover crops
  and green manure.
• Improved rice varieties for uplands.
• Improved markets for produce.

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• Research Question Can PES provide a viable
  alternative approach to protecting wetlands
  areas?
• Need to identify and quantify wetlands ES (note
  advantage over C).
• Are farmers willing to participate in PES? At
  what price? Impact on poverty and sustainability
  of their production systems?
• Who would pay for the ES? How to design and
  implement payment mechanisms?
• Who are beneficiaries? What are they willing to
  pay? (local people and communities, national
  policy organizations, people downstream in the
  Nile watershed, global organizations and
  individuals?)
• Can local institutions manage PES?

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Economics of ES supply Spatial distribution of
opportunity cost for changing practices
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• System 1 current practice including lowlands
  rice uplands subsistence crops
• System 2 uplands crop only
• Three possibilities
• System 2 is profitable for some farms without
  additional incentives
• System 1 is more profitable without a payment for
  environmental services, but System 2 is more
  profitable with environmental payments
• System 1 is more profitable even with a payment

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Derivation of the Supply of Environmental
Services from the Spatial Distribution of
Opportunity Cost Source Antle and Valdivia,
Aust. J. Ag Res Econ. 2006
Technical Potential
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• Minimum Data Methods to Simulate the Supply of
  Environmental Services
• How to estimate the spatial distribution of opp
  cost of changing practices?
• Full data -- to construct site-specific
  simulation models, simulate opportunity cost
• MD approach use available data to estimate
  parameters of opportunity cost distribution
• Validation studies show MD can approximate full
  data analysis of ES

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Could put dual-purpose sweet potato in the system?
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Simulated Participation Rates in Contracts for
Wetlands Protection in Pallisa District, Uganda
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Simulated Change in Crop Income from ES Contract
Participation for Wetlands Protection in Pallisa
District, Uganda
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Conclusions

• TOA an integrative, participatory approach to
  support informed policy decision making
• TOA software provides a transparent, modular
  approach to model agriculture as a complex system
• Spatial and system complexity ? model design
• MD approach provides a low-cost (data, learning)
  way to implement analysis to support policy
  decision making
• Current research themes
• System dynamics, multiple steady states, market
  equilibria (RV!)
• Refining MD and applying to new problems