applying behavioural insights · an high-level interdepartmental strategy event took place on...
TRANSCRIPT
Behavioural Insights Team EZ | Nov 2016
Applying Behavioural Insights
Dr. Eva van den Broek
Wageningen Economic Research
(Behavioural Insights Team EZ)
Behavioural Insights in policy
Reflects shift in perspective on human nature:
Theory vs Reality
6
Classic policy maker vs behavioral insights
7
- People are rational
- Information influences behaviour
- More choices -> more happiness
- Preference now = preference later
- People compute ‘expected value’ of risks
- Loss = - gain
- People know their abilities
stress!
intention
overestimate
Well, partially
2 x
overestimate
Theory vs Evidence
Behavioural insights
Policy instruments
8
Nudging
- maintains
choices but
makes ‘good’
choice easier
Information
- maintains
choices
Regulation
-limits choices
Incentives
- rearranges
choices by cost /
reward
Overview
• How behavioral insights are becoming fashionable among policy makers
• Some recent policy examples
• Commercial applications
9
10
The Ministry of Economics Affairs
Policy areas:
- Innovation & Entrepreneurship
- Agriculture & Nature
- Energy, Telecom, Competition & Consumers
- Economic policy in general
Directorate for General Economic Policy (AEP) = Chief economist
- Advising the minister on all policy areas
- Helping the minister answering questions from parliament and citizens
- Strategy (the long term view)
- International organisations (OECD, EU)
- Policy research
- Behavioural Insights Team EZ
Behavioural Insights Team EZ
- started in 2014
- supports the policy directorates in the application of behavioral insights in the
EZ policies
- chairs the interdepartmental BIT network and an internal EZ network
- responsible for the behavioural sciences research agenda
11
Behavioural insights are relevant for policy makers
Applying behavioural insights means
- richer and more realistic policy analysis ->
more effective policies;
- less restrictive way of influencing behaviour
by nudging;
- empirical testing beforehand -> more
effective policies
12
International developments:
the rise of the BITs
- From the year 2000 and onwards the number of policy-
oriented publications on behavioral insights increases
- 2008 the book Nudge by Thaler and Sunstein is
published
- Not much later President Obama appoints Cass Sunstein
as Chief Executive of the Office of Information and
Regulatory Affairs (OIRA) where he puts into practice
many of his ideas about nudging
- In the UK, MINDSPACE appears in 2010 and in the same
year the Behavioural Insights Team is founded by Prime
Minister Cameron
13
15
Source: Behavioural Insights Applied to Policy: Overview across 32 European Countries
Our mandate
“The cabinet opts for an evidence based approach in which departments,
through pilots, test the added value of behavioural insights on concrete policy
issues.”
17
I would like a seat
I would like meat
Policy experiment:
• Randomize population into control and intervention group
• Compare two groups on a relevant measurable outcome
18
Why experiment?
- Assumptions are sticky
- Inferences are easily made
....but causality is hard to prove
21 november 2016
Ministerie van Economische Zaken 19
Policy examples
Disclaimer: not all of them from BIT EZ !
20
Dutch Tax Authority: personal
12 days
7 days
Defaults in applying for student loans
Defaults in applying for student loans
Maximum loan
0%
20%
40%
60%
80%
Voor 2009/2010 2010/2011
Percentage “maximaal
leenbedrag”
BIT UK: donor registration
Norm + pic
control Loss
frame
reciprocity
BIT UK: EAST
Organ donations after message (n=1085322)
Energy efficiency
26
Behavioral approach
27
energy
management
CEO
Energy
coordinator
PJ contact BIT NL
Increase
commitment
increase
downloads
Increase
contact increase
enforcement
Experimental design
Problem: energy coordinators do not download energy reports
Intervention: email with announcement and simpler download; survey
Metric: # downloads; “contact manager” via follow-up survey
Treatments:
1. Control: last year’s email
2. Shortened email, simple download
3. Shortened email, simple download, social comparison
28
Results
29
p<0.01
ns
p<0.05
# reports
downloaded
# letters
sent
(n=519)
Ongoing policy research:
- Municipalities experimenting with unconditional unemployment benefits
- Various letters sent to 170.000 prospective students to nudge them towards
a more conscious choice
- Municipalities experimenting with norms, reciprocity, goal setting, distance to
containers... to encourage waste sorting
- How to decrease household energy consumption with smart meters
- Encouraging households in debt to take on subsidies / help programs
30
Commercial examples
31
Context matters
33
- 12.5% meat
+100%
veggies
- 33% meat leftovers
+30% veggies
consumed
If you switch providers
now, you save 38,20!
If you don’t switch providers
now, you forgo 38,20!
+ 23%
Loss aversion
Sign up front
35
One bottle taken:
+ 15 % sales
37
Other commercial examples
• Amazon / bol.com run >2000 tests a day
• Booking.com even nudges and ‘optimizes’ their own employees
• Facebook experiments with your timeline
• Supermarkets are optimized and auction of shelf space, like google
• Packaging lies optically:
38
Both policy makers and marketeers discovered nudging...
And are taking first steps
• sometimes without checking effects
• sometimes with unintended side-effects
• sometimes without being transparent
• usually without explicit consent of participants
but there are many sludges to be uncovered
39
Assignment (groups of 2)
- Come up with a testable behavioral intervention
- Constraints:
should yield results < 1 year
must be politically feasible (Should be in line with all stakeholder
interests)
should be measurable
- Area: food waste in out – of – home setting
Deliverables (1/2 hour):
- Proposed intervention + targeted actor + behavioral insight
- Outcome parameter + randomisation level + estimation of impact
- Estimation of costs of implementation (scaling up) 42
Randomisation
- What is the appropriate level or unit of randomization?
- What is the appropriate method of randomization? Beyond the political,
administrative and ethical constrains, what technical issues could
compromise the integrity of our study, and how can we mitigate these threats
in the design?
- How would we implement the randomization?
- What is the necessary sample size to answer our questions?
21 november 2016
Ministerie van Economische Zaken 43
Behavioural Insights | 24 March 2014 RUN
Ministry of Economic Affairs 44
Working at EZ: how to apply
• We are always looking for good economists
• Internship / master thesis
• BOFEB / Rijkstrainee
• Applying to job vacancies.
http://www.werkenbijdeoverheid.nl/
Behavioural Insights | 24 March 2014 RUN
Ministry of Economic Affairs 45
Working at EZ: BOFEB
• Post academic study
• Combination of:
• Training (1/2 year): interactive lectures, policy cases, visits, skills training
• Internship (1/2 year): ministries, National Bureau for Economic Policy Analysis
(CPB), Dutch Central Bank (Nederlandsche Bank)
• Start: September or March
• www.bofeb.nl
Mindspace
Messenger
Incentives
Norms
Defaults
Salience
Priming
Affect
Commitment
Ego
21 november 2016
Ministerie van Economische Zaken 46
Behavioural Insights Team EZ | February 2016
Ministry of Economic Affairs 47
The Ministry of Economics Affairs
Our history
On 15 May 2014, initiated by the Ministry of Economic Affairs,
an high-level interdepartmental strategy event took place on applying
behavioural insights to policy making.
Main conclusions:
- Government policy can benefit form applying behavioral insights and an
evidence based approach.
- Departments are responsible for the implementation
- Interdepartmental network with secretariat
- Cabinet reaction to the three advisory reports will be send to parliament
Behavioural Insights Team EZ | February 2016
Ministry of Economic Affairs 48
Food waste
Goal: reduce food waste among consumers / companies
Behavioural Insights Team EZ | February 2016
Ministry of Economic Affairs 49
Purchase
Cook
Preserve Serve
Waste
Steps:
1. Analysis and goal
2. Context
3. Design intervention
4. Test and adapt
Project Energy efficiency
Goal: to measurably improve energy efficiency among 1100 heavy industrial
users
Instrument: convenants
Behavioural Insights Team EZ | February 2016
Ministry of Economic Affairs 50
Sign convenant
Draw up EEP
Implement EEP
Yearly monitoring
Reports
Steps:
1. Analysis and goal
2. Context
3. Design intervention
4. Test and adapt
Pilot study
Tel no: 133/183
No contact: 83
reached: 48
letter: 26
clear: 14/26 = 54%
Contact: 9/26 = 35%
Letter + norm: 22
Helder: 17/22 = 77%
Contact: 11/22 =50%
Energy coordinator “Was it a clear message? “ “Did you contact your manager, or did they contact you?”
p=0.13 (2sided) p=0.38
klik
Information security
Goal: measurably reduce security breaches at Ministry
Examples of target behaviour:
- Logging off computer during lunch
- Smartphone use / protection
- Transferring documents to personal email
- Leaving printed documents in tray
Behavioural Insights Team EZ | February 2016
Ministry of Economic Affairs 52
Steps:
1. Analysis and goal
2. Context
3. Design intervention
4. Test and adapt
Essent: loss aversion
Behavioural Insights Team EZ | February 2016
If you switch providers
now, you save 38,20!
If you don’t switch providers
now, you would forgo savings
of 38,20!
+ 23%
signed up
Erasmus University: social norm
Behavioural Insights Team EZ | February 2016
Fewer pickup moments
Leads to more initiative
(phone calls)
But also to more garbage
next to containers
(Robert Dur, 2015)
Experimental design: CEO commitment
Behavioural Insights Team EZ | September 2015
55
Experimental design
Problem statement: energy efficiency no priority for CEO
Intervention: asking for explicit commitment of CEO; public statement and
ranking site
Timing: letters are sent between May – Oct 2016
- After report, during writing phase of energy 4 year plan
Metrics:
- % KJ saved
- # new measures implemented (april 2017)
- # measures in EEP 2017-2020
- # measures implemented in 2017
Behavioural Insights Team EZ | September 2015
56
Behavioural Insights Team EZ | February 2016
Ministry of Economic Affairs 57
A
d
m
i
n
i
s
t
r
a
t
i
o
n
P
o
l
i
c
y
L
o
c
a
t
i
o
n
P
e
o
p
l
e
S
c
h
o
l
a
r
s
h
i
p
E
x
p
e
r
i
m
e
n
t
a
t
i
o
n
Food waste: field research
Behavioural Insights Team EZ | February 2016
Food waste
Target behavior: Less garbage weight
at 3 restaurants
Intervention:
- Fewer side dishes
- Half portions on menu
Behavioural Insights Team EZ | February 2016
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
Groente Aardappels Friet Bord Totaal
p<0.01 ns p<0.01 p<0.05
p<0.05
NL history
In 2014 three independent advisory body for the Dutch government
came forward with reports on applying behavioural insights to policy
making
Behavioural Insights Team EZ | February 2016
Ministry of Economic Affairs 60
Target behavior: more contact
Intervention: add social norm
More than 80% of the
companies have
executed their EEP
according to plan
X 92
X 91
Outcome measure: “Did you contact your manager
about the letter?’’
Behavioural Insights Team EZ | September 2015
62
Approach
- Start with field research / user journey
- Define an exact target behavior and outcome measure
- Make an estimate of the effect (moment, target group, power, magnitude)
- Find the best way to randomize
- Run the experiment
- Repeat the above
Behavioural Insights Team EZ | February 2016
Ministry of Economic Affairs 63
Lessons learned
- Field research is important; coming up with feasible intervention is an iterative
process; adapt and learn
- Plenty of dead ends: data is not measured, many interventions aren’t feasible,
some designs not possible because of heterogeneity or small groups...
- Large part of the job is micromanagement: cooperation and timing v important
- Measurability is an enourmous issue- make no assumptions!
- Impact conflicts with scientific approach: Kitchen sink approach may be best
- Lack of knowledge on behavioral experiments with companies
64