Impact Assesment

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ENVIRONMENTAL POLICY INTEGRATIONAND MULTI-LEVELGOVERNANCE

Co-ordinating and synthesising research on environmentalpolicy integration and multi-level governance, 2006-2008

A Co-ordinated Action under the European Union's6th Research Framework Programme

CITIZENS-2004-4.2.2 - Governance for SustainableDevelopmentDG Research

EPIGOV Paper No. 7

Evaluating Integrated Impact Assessments a conceptual framework

Klaus Jacob and Julia Hertin(Environmental Policy Research Centre, FU Berlin)

Ecologic Institute for International and European Environmental PolicyBerlin, 2007

January 2007


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EPIGOV is a research project on the modes of governance employed at global, EU,

national and regional/local levels to support the integration of environmental concerns

into other policy areas. Relevant policy areas are, for example, transport, agricultural, and

energy policy. Running over three years (2006-2008), EPIGOV brings together nineteen

research institutions from ten European countries.

EPIGOV aims to co-ordinate and synthesise existing research on environmental policy

integration and multi-level governance and to generate new research questions and

initiatives. To obtain feedback and disseminate results, EPIGOV will also involve policy-

makers and non-state stakeholders.

http://www.ecologic.de/projekte/epigov/

Citing this EPIGOV Paper:

Jacob, Klaus and Julia Hertin (2007): Evaluating Integrated Impact Assessments a

conceptual framework, EPIGOV Paper No. 7, Ecologic Institute for International and

European Environmental Policy: Berlin.


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Jacob/Hertin: Evaluating Integrated Impact Assessments a conceptual framework

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Abstract

Impact Assessment (IA) has become a standard procedure of policy making in

the European Commission as well as on the national level. It aims to rationalise

the decision making process by systematically collecting information about thelikely impacts of a planned policy, by evaluating these impacts and thereby

providing the basis for choosing the best policy option. IA is seen by many as a

core instrument in the context of the better regulation agenda which aims to

reduce regulatory burden on business. Recently, additional functions have been

assigned to this tool, e.g. increasing the transparency of decision making,

improving interdepartmental cooperation, and - crucially - addressing cross-

cutting issues such as environmental policy integration. With these different

functions, the institutional design of IA systems has diversified. IA systems canbe distinguished regarding a number of features of their institutional framework

and practice, for example their timing in decision making process, the degree of

transparency and openness for participation, the presence of quality control

mechanisms, and the degree to which impacts are quantified. This paper - which

draws on the ongoing research in the EVIA project - aims to set out a framework

for exploring the contribution of IA to policy integration. This is done by firstly

developing a typology of IA systems based on their institutionalisation, orientation

and practice and secondly by developing a framework for the analysis of

integrated IA, including explicit hypotheses about how different factors are

expected to impact on the ability of IA to improve the evidence-base of policy and

to promote (environmental) policy integration.


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Table of Contents

ABSTRACT................................................................................................3

DEFINITION OF INTEGRATED IMPACT ASSESSMENTS ...................... 5

CHARACTERISTICS OF IMPACT ASSESSMENTS ................................8

INTEGRATED IMPACT ASSESSMENT..................................................12

APPLICATION OF INTEGRATED IMPACT ASSESSMENTS ................12

QUALITY OF IA .......................................................................................14

IMPACTS OF IA.......................................................................................16

DETERMINANTS OF QUALITY OF INTEGRATED IMPACTASSESSMENTS ......................................................................................16

VARIABLES AND HYPOTHESES ..........................................................17

CONCLUSIONS.......................................................................................24

BIBLIOGRAPHY......................................................................................24


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1. THE GOVERNANCE OF POLICY MAKING: BETTER REGULATION

AND ENVIRONMENTAL POLICY INTEGRATION

New forms and processes of rulemaking as well as instruments to regulate and to

provide public goods are not limited to the intersection of governments and

enterprises or citizens, but entail the internal procedures of policy making as well.

Governments themselves and their procedure to provide services, goods and to

develop regulations are subject of (self)regulation. These procedures and

regulations are subject of reform, and some elements of new forms of

governance can be observed in this domain as well as in the regulation of private

actors. In many countries as well as in European institutions, rule making is

subject of Better Regulation Programs. The aim is to decrease the burden

imposed by regulation, to increase the knowledge basis and hence the overall

quality of regulation and to increase coherence and transparency of policies.

Better Regulation Programs having several elements that vary across the

countries. They entail programs to review existing laws regarding their

appropriateness, effectiveness and efficiency. A recent trend in many countries

are programs to review laws (both existing as well as proposals) regarding the

administrative burden in terms of information requirements based on the

Standard Cost Model (SCM). Some countries adopted quantitative goals toreduce the costs imposed by information requirements. The Netherlands and

Germany set up high level advisory councils that review legislative proposals

before their enactment regarding administrative burden. More comprehensive

Impact Assessments are another central part of Better Regulation Programs.

These systems will be discussed in greater detail in this paper.

From an EPI perspective, it is a question open to investigation, in how far Better

Regulation Programs promote or rather inhibit the consideration of environmental

aspects in policy making. On the one hand, Better Regulation Programs areperceived as instruments of deregulation: Regulatory standards that impose

costs on business run the risk of being lowered if no immediate and obvious

benefits can be proved that outweigh the costs of regulation. For environmental

standards, however, is often difficult to calculate the benefits of preserving

environmental goods and accordingly, environmental policies run the risk of being

watered down.

On the other hand, the requirements of linking the policy proposals with broad

political strategies, e.g. for sustainable development or for competitiveness and

the requirements to take into consideration different kinds of possible impacts,


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including side effects, trade offs and synergies on the environment, has the

potential of improving EPI in the early phases of policy making.

We therefore analyse procedures of Impact Assessment to explore their potential

for improving EPI. We are interested, what features of IA systems and what other

factors are likely to determine their contribution for an improved EPI.

The paper is organised as follows: in the next section we develop a definition of

Impact Assessment to distinguish such procedures from other means to develop

expectations about the likely impacts of planned policies. In the next step we

elaborate about common features of IA systems as well as properties that vary

among the different jurisdictions. A brief review of studies about the

implementation however reveals that the expectations regarding the

consideration of concerns of Sustainable Development (SD) in the Impact

Assessments are not fulfilled. However, this may be justified by the nature of the

policy proposal and it is not necessarily a result of political bargaining or a lack of

knowledge or resources. We therefore develop a more elaborated concept of

quality in regards of SD-consideration that also takes into account process

variables. Finally, we explore a set of variables beyond the IA system that we

expect to influence the quality of Impact Assessments.

2. DEFINITION OF INTEGRATED IMPACT ASSESSMENTS

Impact Assessment (IA) has become a standard procedure of policy making in

the European Commission as well as on the national level. It aims to rationalise

the decision making process by systematically collecting information about the

likely impacts of a planned policy, by valuating these impacts and thereby

providing the basis for a decision in which the policy is chosen with the best net

benefit. Impact Assessment has been defined as an information-based analytical

approach to assess probable costs, consequences, and side effects of planned

policy instruments (laws, regulations, etc.) (OECD 2001, p. 10). It is distinct from

assessment procedures of projects, plans and programmes such as

Environmental Impact Assessment and Strategic Environmental Assessment.

Typically, IA is conceived as an assessment of distinct alternatives to achieve a

specified policy objective. The specification of the objectives of a policy is usually

not part of the assessment, and IA is meant to inform, but not determine the final

decision.

In the following, we concentrate on integrated Impact Assessments, i.e. those IA

that assess several different issue areas. In order to identify such Assessmentsand to operationalise them for analytical research, it is necessary to develop a


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clear definition of IA. This paper will contribute to such a definition and it aims to

define different types of IA.

Whenever decisions on policies are taken, this is done on the basis of certain

explicit or implicit expectations about their likely effects. Such expectations are

not necessarily gathered in Impact Assessment procedures. Instead, they might

be derived from other forms of reasoning among the decision makers.

Bureaucrats might discuss their proposals with colleagues, stakeholders,

academics or politicians. Researchers attempt to forecast impacts of proposed

policies either because they are commissioned to carry out a study or on own

accord. A legislative proposal will be debated in parliament or it might be subject

to judicial review where the court may collect evidence on impacts. Every

decision taken within these arenas is justified by expectations on the future and

certain effects of the concerned proposal.

To develop a concept of IA that is fruitful for empirical research, we have to adopt

a definition which is more specific than the OECD definition cited above which

would cover all activities that aim to create expectations on possible impacts of a

planned policy.

We are particularly interested in recent efforts to encourage integrated Impact

Assessment. Since the 1970s, a wide range of different sectoral IA have been

developed: Proposals should be assessed regarding potential impacts on the

economy, on health and other social aspects, on the environment, on gender, on

small and medium enterprises, etc. In several countries as well as the European

Union these different sectoral procedures were merged into a single procedure,

in order to reduce the burden of having the obligations for many different

assessment procedures and to allow a systematic assessment of interlinkages

between the different issue areas.

Thereby, integrated systems of IA have different historical roots. One precursor is

in Regulatory Impact Assessment (RIA) that focuses on the economic orbusiness impacts of policies and to which other aspects such as environmental or

social aspects were added later. A different root is Strategic Environmental

Assessment (SEA). In some countries, SEA is developed towards a sustainability

appraisal by an integration of social and economic aspects (A. Chaker, K. El-Fadl

et al. 2006).

Within the different functions and objectives tensions may arise. In addition to the

merging of different procedures, requirements are needed to deal with trade-offs,

interlinkages, synergies but also conflicts between different impacts of a proposalin order to maintain the overall legitimacy of IA. A lack of legitimacy might either


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degrade an IA into a meaningless exercise or lead to highly contested

assessments that delay the process of rule-making.

3. CHARACTERISTICS OF IMPACT ASSESSMENTS

To distinguish IA from other means to develop expectations on the impacts of

policies, some characteristics can be observed in practice. We suggest to use the

following criteria to provide a narrower definition of IA.

1. IA is formalised: There are written regulations that define the objectives

of IA, the individual steps, responsibilities, provide advice on the selection

procedure of proposals and issues to be assessed. Their bindingness

may, however, vary: The rules may only be formulated as a suggestion or

as binding prescriptions for the rule making departments. Requirements

for IA can be issued by law, presidential or prime ministerial decree,

cabinet directive, cabinet decision, resolution, etc. (OECD 2004)

2. IA has defined purposes: IA is an instrument to achieve governmental

objectives beyond the purposes of the individual proposal. It is related to

generic objectives to which a government is committed: Improving

economic performance, achieving gender equality, avoiding risks to health

or to the environment, etc. IA aims to reveal the contributions of an

individual proposal on these generic objectives and the side effects and

interlinkages between the main purposes of the proposal and these other

objectives.

However, some IA systems do not provide substantive criteria, instead

they only require the assessment of the effectiveness and efficiency of the

planned regulation. These systems of IA do not challenge the objectives

of the departments.

3. IA is fact-based: IA is a systematic, scientifically grounded process to

identify the likely impacts on a defined list of issue areas: It should be

robust, transparent and politically neutral. If value-based judgements

cannot be avoided, they should be made explicit. Again, this might be

different in practice.

While these three characteristics are common to IA, we can identify a number of

other significant qualities on which there is considerable variation between

countries:

1. Timing in decision making: IA is often described as a separate step of

decision making which takes place after the definition of objectives andbefore the final decision on a policy proposal is taken. IA does not


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question the objectives of a proposal nor is it supposed to pre-judge the

political decisions. Often, the guidelines stipulate a specific timing for the

IA, i.e. before the interdepartmental consultation, before the parliamentary

decision, etc. However, the distinction of problem definition and setting of

objectives on the one side and assessment of impacts on the other side is

often not very clear cut in reality: Firstly, objectives are most often vaguely

defined, they are changed during the decision making process (and

accordingly during the IA), sometimes even through the IA.

Acknowledging this, in some IA systems, the definition of problems and

objectives is seen as an integral step of the IA. Secondly, it is not

uncommon that IA takes place after the key decisions are taken, it then

largely fulfils formal obligations and contributes to the justification of a

proposal.

2. Degree of transparency and disclosure: Countries vary regarding the

degree of transparency and the disclosure of IA to the public. In some

countries, IA is inevitably open to the general public because it is

perceived as a tool to increase transparency of rulemaking. Examples are

UK, USA, Canada, and the European Union. In other countries, a

dominant purpose of IA is the fostering of interdepartmental negotiations

and transparency of rulemaking is not perceived as a goal in itself. In

these jurisdictions, IA are not published to the general public. In some

countries, IA are attached to the legislative proposal and published by the

parliament.

3. Degree of involvement of external expertise: IA is typically a duty of

the rulemaking department. Frequently, other departments will be

involved in delivering data, contributing to the assessment or reviewing

the results. IA can be commissioned from other agencies, consultants or

academics. Sometimes, IA is commissioned or performed by non stateactors that expect to be particularly affected by the planned policy.

Likewise, other levels of governance, i.e. the national or even the regional

level for European policies or the regional level for national policies may

review the IA or perform own IA with their specific needs. The

commissioning of IA studies took place extensively during the decision

making process on REACH. Up to now, there are no specialised IA

departments established, although this could be thought of, in particular

for sectoral IA such as Strategic Environmental Assessments.


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4. Participation: In few countries as well as in the European Union, IA is a

frame for the participation of non governmental actors in the development

of a proposal. The inclusion of interest groups may have different

functions: Either to discuss or to negotiate the proposal with the groups

affected or to obtain data . However, in other countries as well as in

practice of those countries where participation is foreseen, the inclusion of

societal interests is often separated from IA.

5. Main purpose of the IA: In some systems of IA, the function of reducing

costs of regulation is the prevailing function of IA. The main focus is on

reducing costs of regulation and maximising benefits. Other IA aim to

inform the decision maker on specific issue areas (environment, social,

health, gender aspects, SMEs, etc). A third category that has gained

recently some importance are systems of IA that should contribute to the

implementation of Sustainable Development. Typically, these IA covering

social, economic and environmental issues.

6. Role of quantification: There are different degrees of formalisation and

rigidity regarding the use of quantitative approaches and economic

modelling. In some systems of IA, few generic questions are provided and

there is no indication that specific methods are proposed or favoured. The

questions may be answered qualitatively. Other systems putting great

emphasis on quantification and monetisation wherever this is possible.

7. Scope of IA: Most often, IA is limited to new legislation. Countries vary in

the inclusion of subordinate regulations. Sometimes governmental

strategies (white papers) and international treaties are also subject of

assessment. In few countries, existing regulation is subject of IA.

8. Degree of detail: Reports on IA vary considerably regarding their volume

(from few pages to hundreds of pages) and accordingly the level of detail.

IA procedures may be limited to checkboxing a few generic questions orby an extensive and detailed evaluation for every issue. In some systems

for IA, IA is separated in a preliminary scoping phase and an extended IA.

9. Quality Control: Countries vary regarding the existence and strength of

institutions to control the quality of IA. Three groups may be distinguished:

In some countries, there are no institutions at all, the compliance is left to

the departments responsible for the IA. In other countries, there are

institutions that should provide assistance to the departments, but they

have no rights to sanction an IA. Finally, there are countries withinstitutions that have the power to impose obligations to the departments


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boundaries of IA can be misused to neglect environmental aspects (or

other unwanted issues) at an early point of time in the design of the IA.

IAs do not always cover appropriately likely modifications at later stages

of the decision making process and implementation in member states.

Typically, the evaluations are based on an analysis of the IA reports according to

a set of criteria or as case studies. A recent study by Ecologic and others studies

also the practice in selected Member States and draws a more optimistic picture:

Environmental aspects are considered in the majority of cases and the results

have been considered in the decision making as well (Ecologic, Vrije Universiteit

Amsterdam et al. 2007). It is open to investigation whether these results are

generalisable as the number of cases is rather small and the selection may have

favoured policies in which environmental aspects are a direct and obvious issue,

while other studies reveal a sidelining of environmental effects if these are rather

side effects.

Until now, much attention has been paid to the improvement of the IA systems:

Observers recommend the improvement of the IA system, placing more

emphasis on requirements, to include environmental actors at every stage, to

scrutinize the quality of IAs, and to spend more efforts in the development of tools

and methods for assessing costs and benefits for the environment (Volkery and

Jacob 2005, Wilkinson, Monkhouse et al. 2005, Jacob, Hertin et al. 2007). Other

aspects that may explain the consideration of environmental aspects, such are

the type of the policy proposal, the capacities available, etc. have received less

attention. To analyse if the consideration of environmental aspects was taken

seriously, and to understand if a lack of analysis can be attributed to the IA

system, we develop a notion of quality of IAs with a focus of integration of cross

cutting aspects and we develop a set of hypotheses about influencing factors of

the quality.

6. QUALITY OF IA

How can we assess the quality of IA? Many IA evaluations focus on the quality of

assessment reports - for example their scope, level of detail and methodological

rigour - not least because it can be easily analysed on the basis of a document

review. Empirical research has shown, however, that high-quality analysis is not

a guarantee for impact on decision-making as it is not uncommon that IA reports

are prepared at a late stage in the decision process. It is therefore important to

evaluate the process as a whole. We have identified the following criteria toassess the quality and impact of IA (see Meuwese, Radaelli et al. 2006):


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In how far are possible negative effects considered and in how far are the

benefits of a proposal considered? To what degree are costs and benefits

quantified?

In how far are potential side effects on other policy areas and objectives

considered?

Openness: Is the IA transparent and open for stakeholder involvement?

Participation. In how far were stakeholders involved in the design and the

conduct of IA. Is an involvement of non-governmental actors foreseen? In

many countries only the results of the IA are made public.

7. IMPACTS OF IA

We assume that a good IA is likely to have impacts on the final policy decision.

However, it is difficult to attribute changes to the policy to an IA, as there are

many different factors, institutions, and actors that influence the final decision.

Therefore, one appropriate way is to use interviews with desk officers to develop

a counterfactual 'no-IA' scenario. Questions may refer to:

Did the IA have a direct impact on the design of the IA? In what way?

Has the IA process increased the knowledge available for the policy

process?

If the IA contributes to a more cooperative decision making is theevidence convincing for other institutions/actors? Did the IA contribute to

a consensus/improved understanding among the actors involved?

Was the IA used or referred to during the political process (in Parliament,

by stakeholder?)

Is the policy formulation more transparent with IA (question addressed to

the stakeholders as well)

Were the requirements of sustainable development (different stocks, long

term focus and external effects) considered in the policy proposal and can

this attributed to the IA?

8. DETERMINANTS OF QUALITY OF INTEGRATED IMPACT

ASSESSMENTS

We expect the quality of IAs and the resulting impact on policy decisions to be a

result of different groups of variables within the institutional framework of decision

making, the design of the IA system, the decision making context, the type of

policy, resources available and the use of analytical methodologies.


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The variables can be divided in three different groups according to their relative

stability and the opportunities to change and influence. Three different levels may

be distinguished: a systemic level which are rarely and slowly changing, a policy

level, i.e. the specific proposal and the context of an individual policy and thirdly

the specific setup of an IA.

Amongst the independent variables, we expect particularly strong links between

the two groups of systems variables: the institutional framework and the design of

the IA system. This relationship will therefore be analysed in more detail (see

section 3 below).

Independent variables Dependent variables

Institutional Framework

Design of IA System

Decision Making Context

Type of Policy

Resources for IA

Quality of IA

Impacts of IA

System

variables

Policy

variables

Methodological ApproachIAv

ariables

Figure 1: Explaining quality of Impact Assessments

9. VARIABLES AND HYPOTHESES

In the following, the variables will be explained in further detail to develop a

common understanding and terminology and to describe the underlying

hypotheses. For some variables we have no explicit hypotheses but instead we

have the opportunity to explore the relations between the respective variable and

the quality of IA.

The aim of this paper is to provide a rich overview of potentially relevant variablesand relationships. We should keep in mind, however, that it will not be possible to


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accurately measure all those variables, especially in a way that is consistent

across jurisdictions and would allow robust comparative analysis. Once data

collection has been completed we should therefore review the analytical

framework with a view to narrowing it down to focusing on the more operational

variables.

Independent variables

System Variables

Institutional Framework

The institutional framework includes the constitutional and basic legal

framework of a jurisdiction, its political system, political and administrative

culture, including the strength and the role of interest groups.

We can expect the following factors to be particular relevant for IA:

Degree of independence of individual departments from a central

coordinating department. If a central department exists that may refuse

individual proposals brought forward by the ministries, this may serve as a

powerful institution for the control of quality. Furthermore, such a central

unit may develop an own stake in IA, as this is a mean to oversee and to

control the activities of the various departments. On the other hand, a

large degree of independence of the ministries e.g. by guaranteeing them

own rights to initiate proposals, by providing them with the power to veto

proposals in the cabinet, etc. may weaken the interest to conduct

integrated IA.

Number of political institutions in the decision making context. The larger

the number of institutions involved in the decision on policies, the less

likely it is that IA plays a role, while other, more formalised mechanisms

for coordination between these actors prevail. Federalism, Bicameralism,

independent institutions such are national reserve bank or a constitutional

court are examples for potential veto players in the political process. Judicial review and the existence of an administrative procedure act is on

the one side an incentive to prepare well founded IAs to minimise the risk

of refusal. On the other hand, the judicial review may be a functional

equivalent to IA, as the officers in charge for the development of the

proposal anticipate the review and consider possible side effects or other

issues in early stages as if informed by an IA.

The role of interests groups. The role of interest groups in the policy

process varies not only for the political system as a whole, but also for the

specific policy proposal. This will be captured in the Decision Making


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Context (see below). However, the level of corporatism and the access of

interest groups to the decision making is relevant also on the system

level. In this case, IA may become subject of political bargaining. On the

other hand, if there is a stronger inclusion of non-state actors, it is more

likely that participatory approaches are applied.

Design of the IA system

IA is defined as a formalised procedure with a defined purpose beyond the

individual proposal to systematically collect facts on the likely effects of a planned

policy. While these elements are common, there are a number of differences

concerning provisions in relation to timing, transparency, use of external

expertise, transparency, quantification, scope, detail and quality control. It

is important to note that these variables concern the system-level requirements

(as for example expressed in guidance documents) rather than the actual

characteristics of IAs which will be considered under 'Resources for IA',

'Methodological approach' and 'Quality of IA').

Basic orientation of the procedure: There is a considerable variation in the

main function(s) attributed to IA in different jurisdictions. The main

different orientations that can be observed are: improving the quality of

regulation, reducing regulatory burden, enhancing transparency,

promoting sustainable development. We would expect the basic

orientation has an influence on the dominant choice of methodologies and

on a range of quality variables (level of integration, sophistication,

openness etc.)

Foreseen timing in the decision making process. Guidance documents

make different provisions regarding the timing of the assessment. We

expect an IA to be of higher quality if it is required at early stages of

decision making. However, while some countries require the IA only when

a proposal is forwarded to the parliament, others require it for the

interdepartmental consultation (EC) or even before the consultation

(Poland).

Degree of transparency and disclosure. We expect a higher quality if the

IA is subject of public review and the results have to be published.

However, the disclosure of the IA may inhibit an open debate, encourage

the lead ministry to use IA purely defensively, and opens up opportunities

for interest-based lobbying by stakeholders. On the other hand, a highlevel of transparency may make it more difficult to pursue private interests


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distinguished: no control at all, supporting units without the power to

sanctioning poor quality IA, and finally institutions that have an however

varying degree of independence and possibilities for interventions. We

expect the quality of IAs to be better if there is a stronger quality control

and if there are more resources available for assistance.

It is, however, important to keep in mind that guidelines and actual

implementation often fall apart. This is partially due to the opportunities and

restrictions to actually apply the generic framework on specific policies as well as

to the resources available for a specific IA. Therefore, both factors will be

elaborated in further detail in the following.

Policy variables

While the institutional framework and the design of the IA systems are rather

static, IA has to be applied on a great variety of policy initiatives that are related

to different problems and interests of actors. Two categories of variables may be

distinguished: firstly we expect the decision making context, i.e. the definition of

the problem, the actors involved, the specifics of the responsible unit and the

expectations in a certain IA are likely to make a difference for the quality of IA, as

well as the type of policy that is subject of the IA.

Decision making contextThe decision-making context covers variables related to the origin of the policy

problem (agenda setting), the relevant network of actors and the function of

IA (i.e. the aims key actors try to achieve).

Definition of the policy problem: The decision making context is firstly

determined by the definition of the problem. Problems may firstly come on

the agenda by scientific studies, by monitoring, scientific agencies, etc.

The initiative comes most often from within the administration. Policies are

hardly discussed in the media. Another mode of defining problems is

driven by interests groups, the heads of departments, or the parliament.

Policies are developed on response of political decisions. Thirdly, policy

problems may be derived from external initiatives, i.e. the national

implementation of international or European law. We expect IA to play a

greater role when the definition of problem is controlled by the

administration compared to political problems or external initiatives. In the

latter cases, there is much less room for manoeuvre to assess different

options.


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Rationale for intervention: Another dimension of the policy type refers to

the objectives of the intervention. Policies that aim for a re-distribution of

resources, or that are based on values that are not consensus in a society

are more difficult to accomplish than policies that are distributive or that

aim for a coordination of action and that are pareto efficient. The first type

of difficult policies are likely to meet on resistance by affected groups,

thereby, the IA will be subject of a political debate. The second category

of easy policies is less likely to become subject of bargaining, and the

mode of arguing will prevail.

Maturity of policies. Policies might be developed from the green table, in

particular if this refers to a new policy field in which institutions have not

been evolved. In these cases it is easier to develop possible alternatives

and to compare impacts. The maturity of policies may be indicated by the

age and the importance of the political institutions involved and their path

dependency in developing new proposals. The type of proposals is

another indicator, ranging from green paper, white paper, action plan, new

policy to amendment of existing policy. We expect the quality of IA to be

higher the less mature a policy field is as the assessment is likely to be

open to alternative options. On the other hand, well developed institutions,

their experience and their resources may improve the quality of IA as well.

IA variables

Finally we expect the operational design of IA to be of relevant for the quality of

IA. The actual design is not only determined by the guidelines and the type of

policy at stake. Instead, 1) the resources available and 2) the methodologies

used are of importance in his regard.

Resources for IA

A number of constraints can be thought of when setting up an IA project

within a department. IA might be limited by the availability of staff and

their training and expertise, money to commissioning studies, availability

of data and pervious studies. Furthermore, IAs are performed often in

great time pressure. We expect that quality improves with budget, time,

staff and their training.


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Methodological approach

In our case studies we will explore in how far the actual application of formalised

methodologies will influence the quality of IA. A number of different

methodologies can be categorised:

Modelling tools: three different families of models can be distinguished,

i.e. economic models, biophysical models, social models.

Tools to support stakeholder participation of stakeholders

Comparison tools such as Monetary Assessment Tools and Multicriteria

Analysis methods

We expect particularly more stringent and rigid quantitative tools to favour greater

depth of analysis, but broader and more flexible qualitative (or semi-qualitative)

tools to be more akin to policy integration.

10. CONCLUSIONS

In this paper we have set out a conceptual framework of and put forward

hypotheses about integrated Impact Assessment. The aim was to develop an

empirical research agenda for studying the contribution integrated IA may make

to improving integration of cross-cutting policy objectives (such as the protection

of the environment). In the next phase of the EVIA project, we will undertake to

apply this framework to the study of IA practice in several EU countries throughthree methodologies: 1) a (largely desk-based) analysis of national-level IA

procedures in all EU Member States, 2) a set of case studies of individual IAs in

five selected jurisdictions and 3) a survey of desk officers and stakeholders in two

countries.

11. BIBLIOGRAPHY

A. Chaker, K. El-Fadl, et al. (2006). "A review of strategic environmentalassessment in 12 selected countries." Environmental Impact AssessmentReview 26: 15-56.

Bartolomeo, Matteo, Piero Giugni, et al. (2005). Approaches to ImpactAssessment in six OECD countries and at the European Commission.Findings and recommendations for the European Commission. UnpublishedReport. Milano, Avanzi

Ecologic, Vrije Universiteit Amsterdam, et al. (2007). Improving Assessment ofthe Environment in Impact Assessment http://www.ecologic-events.de/eu-impact-assessment/en/documents/Env_in_IA_final.pdf.

EEAC Working Group on Governance (2006). Impact Assessment of EuropeanCommission Policies: Acheivements And Prospects. Brusselshttp://www.eeac-


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Volkery, Axel and Klaus Jacob(2005). The Environmental Dimension of ImpactAssessment. Documentation of a Workshop organised together with theFederal Ministry for the Environment, Nature Conservation and NuclearSafety, 17-18 June 2004, Berlin. Berlin, Environmental Policy ResearchCentre http://www.fu-berlin.de/ffu/download/Rep-01-2005.pdf.

Wilkinson, David, Malcolm Fergusson, et al. (2004). Sustainable Development inthe European Commission's Integrated Impact Assessments for 2003.London, IEEPhttp://www.ieep.org.uk/publications/pdfs//2004/sustainabledevelopmentineucommission.pdf.

Wilkinson, David, Claire Monkhouse, et al. (2005). For Better or for Worse? TheEUs Better Regulation Agenda and the Environment. London, Institute forEuropean Environmental Policyhttp://www.ieep.eu/publications/pdfs/2005/forbetterorforworse.pdf.

Documents

Impact Assesment