Using regulation as a last resort? An assessment
of the performance of voluntary approaches
Donal McCarthy, Royal Society for the Protection of Birds (RSPB)
envecon 2015
Introduction to Voluntary Approaches
•
What? Arrangements involving actions by the private sector that go
beyond existing legal requirements or regulatory standards
•
Example: Public Health Responsibility Deal
•
Why do firms participate and comply? Moral responsibility vs.
economic self-interest?
•
For vs. Against? Cost vs. effectiveness?
For
Against
“Regulation is not cost free...some
policy aims might be delivered more
flexibly through voluntary
measures.”
“...like putting Dracula in charge of
the blood bank“
UK Policy Context
“I want us to be the first government in modern history to leave office having
reduced the overall burden of regulation, rather than increasing it”
– David Cameron (2010)
The Government’s Principles of Regulation
We see conventional regulation as a last resort. The Government will regulate to
achieve its policy objectives only:

having demonstrated that satisfactory outcomes cannot be achieved by
alternative, self-regulatory, or non-regulatory approaches

where analysis of the costs and benefits demonstrates that the regulatory
approach is superior by a clear margin to alternative, self-regulatory or nonregulatory approaches
Source: Better Regulation Framework Manual (BIS, 2013)
Existing Evidence
• Data availability limited: schemes lack clearly
specified targets and transparent monitoring/
reporting requirements
• Effectiveness: limited improvements in
participants’ performance beyond ‘business as
usual’
• Cost-effectiveness: largely unproven
Data and Methods
•
Extensive web-based search to identify relevant schemes: further
targeted search to obtain detailed performance-related information
(e.g. academic literature, progress reports, newspaper articles etc.)
•
161 schemes assessed: UK (29%); Other EU Countries (30%); USA
and Canada (19%). Range of sectors and issues covered: 68% of
schemes “environment-related”
•
Assessing performance: do schemes deliver desired policy
objectives?
•
Scoring: 3 ‘performance dimensions’ on a 3-point scale
– Target Achievement
– Target Ambition
– Level of Uptake
Scoring
• Target Achievement: proportion of scheme
targets achieved or rate of compliance [≤50% = 0;
51-75% = 0.5; >75% = 1]
• Target Ambition: extent to which scheme targets
went beyond ‘business-as-usual’ or were in line
with what would be required to achieve the
overarching policy objective.
• Level of Uptake: proportion of ‘relevant’ firms
participating, ideally based on ‘problem coverage’
[≤50% = 0; 51-75% = 0.5; >75% = 1]
Case Study: Campaign for the
Farmed Environment (2009)
Target Achievement
0
Target Ambition
Level of Uptake
0.5
• 50% of targets achieved; no
progress against key target to
retain and increase area of uncropped land.
• Just over half of arable farmers
recorded land in at least one
Campaign measure.
• Verification monitoring found
consistent over-recording
(farmers doing 30% less than
reported).
Case Study: Country of Origin
Food Labelling (2010)
Target Achievement
Target Ambition
Level of Uptake
“The EU is considering new rules
…while Defra would prefer industry
to respond voluntarily…[we] will
also be pressing for the option of
compulsion to be kept open”
0.5
– Defra Press Release (August 2010)
•
“...we will continue to improve the level
and clarity of country of origin
information” – BRC (November 2010)
•
Initial evaluation in 2011 based on
product label information:
– Meat: 70% compliance with principles
– Dairy: 65% compliance with principles
•
Follow-up in 2012:
– No statistically significant difference
in overall rates of compliance
% of Schemes
Results: Individual Performance Scores
100%
75%
50%
25%
0%
78%
64%
57%
13%
23%
6%
% of Schemes
Target Achievement
[n=147]
100%
75%
50%
25%
0%
20% 23%
16%
Target Ambition
[n=49]
55%
24%
18%
3%
0
1
2
3
Number of Low Performance Scores
Level of Uptake
[n=84]
Low
Medium
High
Results: ‘Average’ and ‘Impact’ Scores
Performance Metric
Average Performance Score
Formula
APS
 j 3

i 
 j 1
PS n
ij
j 3
Scheme Impact Score
SIS PS
i

j 1
ij
 min

1
1
0.8
0.8
0.6
UK
Non-UK
0.4
0.2
0
0.29
0.19
APS
0.07 0.16
SIS
Note: * denotes a significant difference at the p<0.05 level,
** at the p<0.01 level, and *** at the p<0.001 level.


i

PS 
ij
0.6
Env.
Non-env.
0.4
0.2
0
0.32
0.13
APS***
0.18 0.04
SIS*
Results: ‘Policy Drivers’
•
Are complementary ‘policy drivers’ important? Presence (but not
absence) information available for 40% of schemes
•
Schemes implemented as part of a policy mix or under the threat
of regulation performed significantly better (p<0.001)
1
0.8
0.6
Regulations/Fiscal Incentives
0.4
Regulatory Threat
0.2
0.41 0.4
Not Present/No Information
0.17
0
APS
0.25 0.24 0.06
SIS
Conclusions and Policy Implications
• Regulation ‘as a last resort’? overall impact of most voluntary
schemes limited; rarely an effective substitute for regulatory
measures or fiscal incentives in seeking to achieve public policy
objectives.
• Implement as part of a policy mix: voluntary schemes work best
when used as a complement to other regulatory/fiscal measures
that provide incentives to firms to participate and comply.
• Design and evaluation: clear unambiguous targets (set against
well-defined baseline), transparent reporting and monitoring/
verification requirements.
– Helps to improve evidence-base, strengthen incentives, and prevent freeriding
Thanks for Listening!
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organisations working to give nature a
home around the world.