Claudio M. Radaelli Professor of Political Science University of Exeter (UK) IAL CONFERENCE

1. LEARNING FROM THE INTERNATIONAL EXPERIENCECONTEXT, MECHANISMS AND THE REFORM OF REGULATORY IMPACT ASSESSMENT Claudio M. Radaelli Professor of Political Science University of Exeter (UK) IAL CONFERENCE Lisbon, Portugal, 2010

2. Abstract (1) • A number of international and transnational networks have been created over the last ten years or so to generate learning about regulatory reform. These networks deal with specific innovations in regulation, such as regulatory impact analysis (RIA), indicators of regulatory quality, advanced techniques for legislative drafting, simplification, and the reduction of administrative burdens. • One of these innovations, RIA, has been adopted by most OECD countries. Yet implementation of this regulatory innovation and ultimately cross-national learning has been uneven. • In this paper we argue that the problem has less to do with the presence of networks and more with the normative and cognitive assumptionsthat explicitly or implicitly inform the approach to learning.

3. Abstract (2) • In the first part of the paper, we reviewbenchmarking, diffusion/transfer, legal transplants and lesson-drawing and find them wanting, albeit for different reasons. • Therefore, we turn to an analytical approach to this problem of learning drawing on extrapolation models, originally inspired by Eugene Bardach and developed by Michael Barzelay. We introduce the main concepts and logic of extrapolation, and apply it to RIA, explaining how different types of mechanisms (individual, relational, and environmental) can be identified in the international experience. • The extrapolation approach is then tried on the ground, by using a recent study on the reform of RIA we carried out for the Dutch government, based on evidence of Canada, Germany, the European Commission, the UK and the USA. • We find that the extrapolation approach has three advantages: it brings attention to the context and to complementary innovations in reform processes; it sheds light on mechanisms rather than formal structure, thus dealing with the problem of equifinality better than other approaches; and it provides tools for self-diagnosis to the adopters of reform, instead of cookbooks and checklists. We also discuss on the limitations of extrapolation, and, in a reflexive mode, on the role of social scientistsin extrapolation exercises.

4. TOPIC • Learning from the international experience of regulatory reform, specifically regulatory impact assessment (RIA) • .... When we say ‘international experience’ we mean ‘the outcome of reforms in countries A,B,C,... as observed by policy makers in country X’

5. Field • Cross-national and international policy learning... • As design • As social science

6. Claim The selection of conceptual frameworks determines our understanding and design capabilities The frameworks we current use are not the most appropriate, especially if we wish to target both ‘understanding’ and ‘design’ The framework proposed in this presentation has advantages

7. Theory • Advantage of learning from the experience of others rather than your own • How do policymakers learn across-nations? • There are at least four different theoretical frameworks available in the literature

8. Learning: theoretical frameworks

9. Evaluating the frameworks

10. Back to our claim: type and amount of learning depend on the theory of learning embedded in transnational network activities • s - Benchmarking has several conceptual limits - Lesson-drawing has potential but it is limited by its checklist approach. Reform is not a cookbook - The other two approaches have little to say on how to go about learning in the real world

11. A different approach • Extrapolation in public management research (Bardach and Barzelay) • Extrapolation as explanatory social science (cognitive assumptions; assumptions about structures and functions) • Extrapolation as design science (normative assumptions; role of trade-offs and deliberation)

12. A real-world case • Report for the Dutch government • Task: Reform of the RIA system in the Netherlands, “how can we learn from the experience of others?” • Current stage of the policy mix in the Netherlands Caveat: final report is not public but it was cleared by the client

13. Defining the steps

14. S T E P S • Identification of source and target jurisdictions • Analysis of context (6 variables) • Examination of mechanisms in source cases • Vulnerability analysis • Functional equivalents • Situating mechanisms in the context of the target case • Provide a tool for self-evaluation and deliberation to the client in the target case

15. Step 1 – Source jurisdictions Countries that ‘do well’ with RIA as well as countries that do not perform particularly well • Canada, Germany, US, UK and EU • Partial analysis of Denmark • Both Germany and Denmark have made limited progress with RIA • Canada was criticised in the past for lack of oversight but has recently invested in this direction • UK and USA are seen as strong performers • Opinions on the EU differ, but our research suggests it is a strong performer

16. Step 2 - Modelling context If context matters, one should model it! • Indicators of potential for reform • Implications for regulatory reform • Relaxing the deterministic approach to ‘context’ – the analysis of context does not show that RIA is possible in one country but not in another. It shows how one type of RIA fits in with a type of context, another type may instead have a good fit with a different context

17. table

18. Step 3 - Mechanisms • How lessons are elaborated in our report (strengths but also vulnerability analysis) • Mechanisms as theorised causal relationships • Emphasis on social mechanisms as defined in analytical sociology (Hedström: Dissecting the Social) and in new public management (Unleashing Change) • The report also considers the vulnerability of mechanisms

19. Entering the mechanisms

20. Accountability and its trade-offs • Mechanisms for accountability as control: the principal is the government, and the bureaucracy is the agent. RIA provides the type of information that is necessary to the principal to rein in agencies and departments when they try to exercise autonomy by deviating from the preferences of the elected officers [Weak potential for this type of control in the NL] • Mechanisms for democratic accountability: RIA used by citizens/firms to monitor and evaluate the behavior of the executive. Democratic accountability provides public administrations with feedback-based inducements to increase their effectiveness and their efficiency [High potential] • Dialogic accountability: mechanisms that open up administrations to regulatory encounters with citizens and firms, essentially by using RIA, and more generally better regulation, to structure the interaction between regulator and regulatee [High potential] Trade-off among the three dimensions: The main vulnerability in terms of accountability is about getting the control-dialogue tension right

21. The fourth step • Mechanisms and functional equivalents • Situating mechanisms in their political institutional context • Assembling the mechanisms • Extrapolation as tool for self-evaluation (the hard questions that governments have to ask in their deliberation) and project planning – not a cookbook!

22. Step 5 - Self-diagnosis and deliberation

23. Hard questions

24. (Instead of) a conclusion • This extrapolation exercise leads to recommendations that are contingent on trade-offs and how the government answers the hard questions via a process of deliberation • Difference with the benchmarking approach where the government is asked to reach some threshold values on a list of 1,2,3,...n goals. The approach presented here, instead, helps with setting priorities. • Another difference is that extrapolative analysis acknowledges functional equivalents. The mechanisms show how to reach objectives that have been prioritised by the government in its deliberative process, but there are functional equivalents to how to reach the outcome produced by a mechanism

25. Thank you! • These thoughts on learning arises out of my research funded by the European Research Council, project ALREG – Analysis of Learning in Regulatory Governance • The specific project on RIA is funded by the Dutch government, Regulatory Reform Group. RRG has kindly given me permission to present this paper • I wish to thank Lorna Schrefler, Exeter University, for her input on all aspects of the project. The report for the Dutch government is authored by Claudio Radaelli, Lorenzo Allio, Andrea Renda and Lorna Schrefler. Errors and mistakes in this presentation are mine.