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Quantifying
Regulatory Efficacy
OECD Workshop on Socioeconomic
Impact Assessment of Chemicals
Management
Susan E. Dudley, Director Helsinki, Finland 6-8 July 2016
Susan E. Dudley
@RegStudies
RegulatoryStudies.gwu.edu
Agenda
• Why evaluate efficacy of regulation?
• How does evaluation fit in the regulatory
process?
• Why is evaluation so challenging?
• Methods for better regulatory evaluation
• Improving incentives for robust evaluation
• Discussion
2
Susan E. Dudley
@RegStudies
RegulatoryStudies.gwu.edu
Why evaluate?
• Feedback is important
• Systems mindset
• Inform existing regulations
– Delivering expected results?
– Revise or rescind?
• Inform future regulations/policies
– Improve ex ante analysis
– Understand causal relationships
3
Susan E. Dudley
@RegStudies
RegulatoryStudies.gwu.edu
Scientific method
4
Observation Hypothesis Experiment
Results
Revise or
Support
Susan E. Dudley
@RegStudies
RegulatoryStudies.gwu.edu
Regulatory process
• Regulatory impact assessment (ex ante)
– Hypothesize causal links between action & outcome
– Assess risks (models, assumptions)
– Identify alternative actions to manage risks
– Estimate benefits, costs & distributional effects
• Public engagement (ex ante)
• Implementation
• Ex post evaluation?
5
Susan E. Dudley
@RegStudies
RegulatoryStudies.gwu.edu
Challenges
Ex-ante analysis
• Well-established
principles & procedures
• Challenging
methodologically
– Assumptions and models
– Hypothesize outcomes
Ex-post analysis
• Procedures less well-
established
• Challenging
methodologically
– Counterfactual?
– Opportunity costs?
– Measuring actual reduction
in risks
• Incentives lacking
6
Susan E. Dudley
@RegStudies
RegulatoryStudies.gwu.edu
Responding to
Methodological Challenges
• Plan for retrospective review at outset
• Design rules to allow natural experiments
• Lay out theory of change
• Determine proper scope
• Measure causal relationship
7
Susan E. Dudley
@RegStudies
RegulatoryStudies.gwu.edu
Plan for review at the outset
• Problem to be solved
• Criteria for measuring success
• Causal logic model
• Time frame
8
Susan E. Dudley
@RegStudies
RegulatoryStudies.gwu.edu
Design to enhance learning
• Randomized controlled experiment
• Variation facilitates natural experiments
– Pilots or trials
– Different compliance thresholds or timing
– Differences across jurisdictions
9
Susan E. Dudley
@RegStudies
RegulatoryStudies.gwu.edu
Illustrative Causal Model
Policy Design
• Problem
identification,
• Risk assessment
• Impact analysis
Policy
Implementation
• Enforcement
Behavioral
Change
• Compliance costs
• Emission reductions
• Substitution
Outputs
• Concentration
changes
• Exposure changes
• Opportunity costs
• Co-benefits & costs
Environmental
& Health
Outcomes
• Risk reduction
• Benefits
• Unintended effects
10
Susan E. Dudley
@RegStudies
RegulatoryStudies.gwu.edu
Scope
• Specific regulation vs. program-wide
• Outputs vs. outcomes
• Quantified benefits & costs
• Other factors
– Innovation
– Flexibility
– Distribution
11
Susan E. Dudley
@RegStudies
RegulatoryStudies.gwu.edu
Measure causal relationship
• Quasi-experimental approaches
– Over time
– Across jurisdictions
• Statistical tests
– Is X informative about Y?
– Does X precede Y?
– Does ∆X explain ∆Y?
– What do non-parametric methods show?
– Effect of X w/ other variables held constant
12
Susan E. Dudley
@RegStudies
RegulatoryStudies.gwu.edu
Responding to Incentive Challenges
• Condition new regulation on ex post
learning
• Institutionalize independent review
• Change default rules
• Reallocate resources
13
Susan E. Dudley
@RegStudies
RegulatoryStudies.gwu.edu
Conclusions
• Evaluation & feedback important
– Identify underperforming (or overly costly) rules
– Improve future policy
• Modify ex ante assumptions
• Calibrate risk assessments
• Improve causal predictions of health benefits & other
regulatory effects
• Solutions must address methods & incentives
14
Susan E. Dudley
@RegStudies
RegulatoryStudies.gwu.edu
Contact: Susan E. Dudley
@RegStudies
RegulatoryStudies@gwu.edu
Regulatorystudies.gwu.edu

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Quantifying Regulatory Efficacy