Integrating Agri-Environmental

Indicators and the OECD Policy Inventory

By Ralph E. HeimlichOECD Workshop

March 19-21, 2007Washington, DC

A Vision of Agri-Environmental Policy

Development Two contexts for analysis: Inter- and Intra-

NationalInter-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

Industry-steel, agriculture, etc.

Sector-crops, livestock

Enterprise-corn for grain, hogs, etc.

Technology-irrigated, no-till,

BT corn

Field-Tama silt loam, 2-5%

slope,irrigate, no-till, Bt corn

Sectoral disaggregation

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: SOILRESOURCE CONCERN: SOIL EROSION

SHEET AND RILL WINDEPHEMERAL GULLY CLASSIC GULLYSTREAMBANK IRRIGATION INDUCEDSOIL MASS MOVEMENTROADBANK/CONSTRUCTION     

RESOURCE CONCERN: SOIL CONDITIONSOIL TILTH SOIL COMPACTIONSOIL CONTAMINATION  SALTS ORGANICS

FERTILIZERS PESTICIDESDEPOSITION/DAMAGE DEPOSITION/

SAFETY    RESOURCE: WATERRESOURCE CONCERN: WATER QUANTITY

SEEPS RUNOFF/FLOODINGEXCESS WATER INADEQUATE OUTLETSWATER MGT. IRRIGATION      

SURFACE SPRINKLERWATER MGT. NON-IRRIGATED

RESTRICTED FLOW CAPACITY (H20 Convey.)     

RESTRICTED STORAGERESOURCE: WATER RESOURCE CONCERN: WATER QUALITY

GROUNDWATER CONTAMINANTSPESTICIDES NUTRIENTS

ORGANICS SALINITYHEAVY METALS PATHOGENSSURFACE WATER CONTAMINANTS

PESTICIDES NUTRIENTS ORGANICS SEDIMENTSDISSOLVED OXYGEN SALINITYHEAVY METALS TEMPERATURE

PATHOGENS

RESOURCE: AIRRESOURCE CONCERN: AIR QUALITY

AIRBORNE SEDIMENT AND SMOKE PARTICLES     AIRBORNE SEDIMENT CAUSING CONVEYANCE PROBLEMSAIRBORNE CHEMICAL DRIFTAIRBORNE ODORSFUNGI, MOLDS, AND POLLEN      

RESOURCE CONCERN: AIR CONDITIONAIR TEMPERATUREAIR MOVEMENT (Windbreak Effect)HUMIDITY

RESOURCE: PLANTRESOURCE CONCERN: SUITABILITY

SITE ADAPTATION PLANT USE     

RESOURCE CONCERN: CONDITION PRODUCTIVITY HEALTH, VIGOR, SURVIVAL

RESOURCE CONCERN: MANAGEMENTESTABLISHMENT/ GROWTH HARVESTNUTRIENT MANAGEMENT PESTSTHREAT/ENDANGERED PLANTS

RESOURCE: WILDLIFERESOURCE CONCERN: HABITAT

FOOD COVER/SHELTERWATER (QUANTITY & QUALITY)     

RESOURCE CONCERN: MANAGEMENTPOPULATION BALANCE THREAT/ENDANGEREDHEALTH

The Policy Inventory II Types of Measures

– Make explicit the spectrum of measures from least coercive through voluntary methods, quasi-regulatory 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

Education

ResearchTechnical assistance/

extension

Payments based on farm fixed assets

Community-based measures

Payments based on farming practices

Inspection/controlPayments based on land

retirement

Tradable rights/quotas

Labelling standards/certification

Cross-compliance mechanisms

Environmental taxes/charges

Regulatory requirements

Range of Environmental Policy Measures

Level of Coerciveness

High

Low

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 modelsPrincipal advantage as a communications

toolBecause 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