Transcript Integrating Agri-Environmental Indicators and the OECD

Integrating AgriEnvironmental Indicators
and the OECD Policy
Inventory
By Ralph E. Heimlich
OECD Workshop
March 19-21, 2007
Washington, DC
A Vision of Agri-Environmental Policy Development
Two contexts for analysis: Inter- and Intra-National
Inter-National-analyze relationships between more
aggregate agri-environmental indicators (AEIs) and
policies across countries
– Observations from many countries
– Abstracts from or controls for differences in policy
implementation and physical, climatic, cultural, economic,
and political context across countries
– Objective: Which policies work best to improve the AEIs?
– Implicit: what works well in one or a set of countries will
work well in others.
A Vision II
Intra-National-analyze relationships between
hierarchically disaggregated AEIs and policies within
each member country
– Disaggregates indicators and policies within a member country
– Abstracts policies and programs or controls for context
– Objective: Which policies work well in one area that could be
applied to others? or What changes could improve efficiency
and effectiveness?
– Geographic disaggregation for understanding fine distinctions
between
– policies,
– their parameters,
– limitations of the resources and agricultural production practices to
which they apply.
Hierarchical Disaggregation
Sectoral
disaggregation
Industry-steel,
agriculture, etc.
Sector-crops,
livestock
Enterprise-corn for
grain, hogs, etc.
Technologyirrigated, no-till,
BT corn
Field-Tama silt
loam, 2-5%
slope,irrigate, notill, Bt corn
Geographic
disaggregation
Previous OECD Activities Modeling AEI/Policies
– Causal graph analysis on data for nutrient balances provided
“proof of concept”, but there remain severe data limitations,
and problems with the model specification
– Applied the OECD Policy Evaluation Model (PEM),
specifically for Canada, to a set of alternative policy
instruments on nitrogen balance
– Three analyses (Swiss dairy production, Finnish arable crop
and forestry production, and U.S. land retirement and tillage
practices) using the Stylized Agri-Environmental Policy
Impact Model (SAPIM)
– A great many other analyses using country-specific modeling
frameworks presented within the JWP framework.
– These uses of ag sector programming models could be
modified in a uniform way and used to produce coordinated
analyses of uniform policies or examine the responsiveness of
AEIs (constructed to be analogous with the OECD set) to
policy change
The Indicators
Won’t quarrel with details of current set, but focus on adapting
them for use in policy analysis.
Criticisms of AEIs Usefulness for Inter-national Analysis
– Designed for international-specified at a high level of
generality and aggregation, and a low level of detail and
specificity.
– Universality-does everyone have these problems?
– Inherent and managerial effects-focus on what policy can
affect
– Scale-neutrality-all indicators should be normalized
– Data issues
 Do the data that support qualitative classes used in constructing the
indicators measure the same things?
 Monitoring design and coverage is likely inherently unequal. This
probably leads to estimates with differing reliability across countries.
The Indicators II
Criticisms of AEIs Usefulness for Intra-national
Analysis
– Hierarchical disaggregation-Can indicators (or
analogs) be disaggregated to every geographical/
sectoral level?
– Size and scale- Does the meaning of the indicator
remain the same when disaggregated?
– Methods of quantification- Indicators may need to
be calculated differently as the size of the unit of
observation decreases
The Policy Inventory
Environmental Objectives
– Agri-environmental policies affect more than one (all)
environmental outcomes.
– Environmental objectives are not mutually exclusive
categories.
– Make objectives consistent with/parallel to the AEIs.
– Objectives should not mix up outcomes and methods,
resources of concern and techniques.
– “Generic/Broad Spectrum” is not useful- admission that
there is no clear objective of the policy.
– A Side Benefit: Direction and magnitude of entire vector of
impacts on environmental outcomes is a step toward a
cost/benefit framework.
NRCS CONSERVATION PRACTICE PHYSICAL
EFFECT WORKSHEET
RESOURCE: SOIL
RESOURCE CONCERN: SOIL EROSION
SHEET AND RILL
WIND
EPHEMERAL GULLY
CLASSIC GULLY
STREAMBANK
IRRIGATION INDUCED
SOIL MASS MOVEMENT ROADBANK/CONSTRUCTION
RESOURCE CONCERN: SOIL CONDITION
SOIL TILTH
SOIL COMPACTION
SOIL CONTAMINATION
SALTS
ORGANICS
FERTILIZERS PESTICIDES
DEPOSITION/DAMAGE
DEPOSITION/SAFETY
RESOURCE: WATER
RESOURCE CONCERN: WATER QUANTITY
SEEPS
RUNOFF/FLOODING
EXCESS WATER
INADEQUATE OUTLETS
WATER MGT. IRRIGATION
SURFACE
SPRINKLER
WATER MGT. NON-IRRIGATED
RESTRICTED FLOW CAPACITY (H20 Convey.)
RESTRICTED STORAGE
RESOURCE: WATER
RESOURCE CONCERN: WATER QUALITY
GROUNDWATER CONTAMINANTS
PESTICIDES
NUTRIENTS
ORGANICS
SALINITY
HEAVY METALS
PATHOGENS
SURFACE WATER CONTAMINANTS
PESTICIDES
NUTRIENTS
ORGANICS
SEDIMENTS
DISSOLVED OXYGEN
SALINITY
HEAVY METALS
TEMPERATURE
PATHOGENS
RESOURCE: AIR
RESOURCE CONCERN: AIR QUALITY
AIRBORNE SEDIMENT AND SMOKE PARTICLES
AIRBORNE SEDIMENT CAUSING CONVEYANCE PROBLEMS
AIRBORNE CHEMICAL DRIFT
AIRBORNE ODORS
FUNGI, MOLDS, AND POLLEN
RESOURCE CONCERN: AIR CONDITION
AIR TEMPERATURE
AIR MOVEMENT (Windbreak Effect)
HUMIDITY
RESOURCE: PLANT
RESOURCE CONCERN: SUITABILITY
SITE ADAPTATION
PLANT USE
RESOURCE CONCERN: CONDITION
PRODUCTIVITY
HEALTH, VIGOR,
SURVIVAL
RESOURCE CONCERN: MANAGEMENT
ESTABLISHMENT/ GROWTH
HARVEST
NUTRIENT MANAGEMENT
PESTS
THREAT/ENDANGERED PLANTS
RESOURCE: WILDLIFE
RESOURCE CONCERN: HABITAT
FOOD
COVER/SHELTER
WATER (QUANTITY & QUALITY)
RESOURCE CONCERN: MANAGEMENT
POPULATION BALANCE THREAT/ENDANGERED
HEALTH
The Policy Inventory II
Types of Measures
– Make explicit the spectrum of measures from least
coercive through voluntary methods, quasiregulatory measures, and on to the most coercive.
(see graph)
– Further disaggregate the taxonomy of payment
types
– Differentiate payments based on farming practices
between cost-share and incentive.
– Accommodate policies using a variety of measures
by separating their component parts and assigning
the level of resources committed to each.
Continuum of Policy Measures
High
Regulatory requirements
Environmental
taxes/charges
Cross-compliance
mechanisms
Level of
Coerciveness
Low
Labelling standards/
certification
Tradable rights/quotas
Payments based on land
retirement
Inspection/control
Payments based on
farming practices
Community-based
Payments based on farm
measures
fixed assets
Technical assistance/
Research
extension
Education
Range of Environmental Policy Measures
Incorporating AEIs and Policies Into Quantitative
Models
– Positive and Normative approaches
– Econometric models;
– Single equation
– Multi-equation simultaneous systems
– Inter-industry (Leontiev) models;
– I/O models
– CGE models
– Ag sector programming models.
Representative Farm Models (SAPIM)
A special case of programming models
Principal advantage as a communications tool
Because of diversity in agriculture, it would take a large
number of representative farms to accurately portray
even one sector in one region or country
Useful for understanding, but not for estimating overall
impacts
Coordinated Ag Sector Modelling
– Activity level is the unit of production (acre, hectare,
animal unit)
– Activities embody dissaggregation of
– Resources (soils, climate, etc.)
– Sectors (crops, livestock enterprises, etc.)
– Technology (tillage, fertilization, pesticides, irrigation,
conservation practices, etc.)
– Vector of AEIs is differentiated by activity, implied
by dissaggregation
– Develop and require:
– A coordinated set of policy questions
– Guidance on how to adapt the set of AEI’s
Conclusions
The AEIs
–
–
–
–
Scale-or Size-neutral
Universally relevant
Sectorally and geographically dissaggregable
Measures of data quality for comparability
The Policy Inventory
–
–
–
–
–
Focus on entire vector of environmental impacts
Don’t mix outcomes and methods
Eliminate the “catch all”
Make more parallel with the AEIs
Make continuum of coercivness more explicit as an
organizing principle
– Subdivide policies/programs based on their objectives and
allocation of resources
Conclusions II
Policy Analytic Approaches
– Fit the analytic approach to the policy being analyzed:What
policies does the JWP most want to analyze?
– Let those who know best do the work
– Develop a coordinated set of policy questions
– Develop guidance on how to adapt the set of AEI’s to the questions
– Let modelers in each member country (or group of countries) adapt
existing disaggregated models for the analyses,
– Conduct hybrid analyses that “cascade” results from one level
of modeling to more and more dissaggregated levels.
– A more “black box” approach that deemphasizes causality
may be useful to develop reliable econometric estimates of
coefficients between existing policies and the levels of the
AEI’s
Reflections
Policy development is highly articulated (many roles
and many players)
– Policy formulation (developing good questions)- NGOs,
agricultural interests, political figures
– Policy research (what are the relationships?) Universities,
research agencies, consultants
– Policy analysis (refining proposals, estimating effects on
key outcomes) The Secretariat, upper agency officials,
consultants
– Policy making (cutting deals) politicians compromising
on the results for competing objectives
– Policy implementation (putting programs in place)
agencies in member countries, international institutions
Reflections II
The limits of policy analysis
– Illuminating tradeoffs between agricultural
production and environmental consequences.
– Timely and to the point
– Process allows for iteration and successive
approximations
– Inform at all points of policy development
– Don’t defer input for the “perfect” analysis