1 Online Gambling and more| Brussels Conference | 30 September 2013 Online gambling and more: potential and limits of policy oriented behavioural experiments

1Online Gambling and more| Brussels Conference | 30 September 2013

Online gambling and more: potential and limits of policy oriented behavioural experiments

G. Gaskell, C. Codagnone, F. Bogliacino, G. Veltri, A. Ivchenko, F. Lupiañez, F. Mureddu

APPLYING BEHAVIOURAL INSIGHTS TO POLICY-MAKING: RESULTS, PROMISES AND LIMITATIONSBrussels, 30 September 2013


Look at the two and think which stands a higher chance to influence:

A car buyerThis one? Or this one?

General


Changing mind, changing behaviourGeneral


Multi-dimensional response variablesGeneral introducing online gambling


Five reasons why gambling is ‘bad’… and companies/governments profit from it

Biases Brief illustrationGambler’s fallacy The gambler’s fallacy is particular form of representativeness

where people rely on the law of small numbers and perceive small samples to represent their population to the same extent as large samples.

Near miss fallacy a near miss is a special kind of failure to reach a goal, one that comes close to being successful.

Overconfidence effect This is a well known bias in which someone's subjective confidence in their judgments is reliably greater than their objective accuracy, especially when confidence is relatively high

Hot and Cold Streaks Some consumers believe in hot and cold streaks, so that they may be more willing to bet after wins and less willing to bet after losses, ignoring the ‘regression to the mean’.

Loss Aversion and Reflection

On the other hand the reflection effect states that typically gamblers are risk averse for gains, but risk seeking for losses.

Zoom on online gambling


… and five key ‘nudges’ we are testingTreatment Theoretical rationale Example of test

Pop-up pictorial warning message

Elicitation of emotions Is the response on conative variable stronger?

Overconfidence Activation of slow but accurate reasoning “reflective thinking”:

Is the average bet less risky?

Push pop up “You lose”

Elicitation of emotions Is the average bet less risky?

Fixed monetary limit

Default option Are participants less likely to recharge the wallet?

Self-defined Monetary limits

House money effect Is the average bet lower?



Snapshot of lab experiment designZoom on online gambling


…how we tested them (1/2)

• Short video of experiment in practice to be projected and commented

• We then re-test some of the nudges in a online experiment conducted in 7 countries with a total N= 5600



Preliminary results

• IF available by the 30 of September: we will add and comment a few findings in this slide



Nudges: looking beyondBack to general

• Most nudges and behavioural experiments have been tested only on WEIRD (Western, Educated, Industrialized, Rich and Democratic) people

• Manipulating restraining and driving ‘forces’ (K. Lewin), the idea behind nudges, also included the social dimension:– Network effects. People are influenced by what other

people do: adoption of behaviour is filtered by people’s social networks

– Nudges + Network effects. Effective behaviourally-inspired policies have to consider both effective nudges and the social networks through which they can be adopted


Nudge versus deliberation: a normative dispute

Back to general

Nudge Deliberation

Subjects Cognitive misers, bounded rationality and prone to heuristics

Reasonable, knowledge hungry and capable of collective reflection

Cost to the individual Low but repeated High but only occasional

Unit of analysis The citizen The group

How change happens Cost-benefit led shift in choice environment

Value led outline of new shared policy platform

Civic conception Increase the appeal of positive-sum action

Addressing the general interest

Role of Policy Customize and design choice

Create new institutional spaces to support citizen-led investigation, respond to citizens


Less is more …

• Best experiments make a strong case for design parsimony: reduce the complexity of the real world to the manageable

• We had to test a lot of treatments in very complex designs:– Lab + online experiment in up to 10 countries (external validity)– Graphic and interactive simulation for realism (ecological validity)– Tight timeline suffering from overconfidence bias:

• Programming time consuming, changing protocols not like cut and past in simple survey questionnaire

• Consultation design would be needed in both pre- and post- procurement phase, rephrasing famous quip by Fisher:– “if experimenter is called after the treatments are decided, she can only

tell what the experiment will die of”

Lessons learnt


… but it’s a complex multi-stakeholder domain• The Commission and the Member States …

• We are not in the much simpler business of running experiment just for one single client– Our presentation to MS representatives in the online gambling expert

group: Commission had to ‘rescue’ as after we dared affirm that mere provision of information and Authority’s logo may have no effect whatsoever

• There is still a long way to go in some countries and/or policy verticals before legacy approaches will be opened to behavioural foundations of policy

• Regulatory capture by industry still a challenge

Lessons learnt


A great opportunity: now it is time to openly share

• The Commission’s great contribution: – Play a pioneer and catalyser role – Fund studies breaking new grounds and cumulating new evidence

• In “Open Data Europe” the community of researchers and the general public should not be denied access to such evidence for too long

• We call on our colleagues/competitors to join forces and set up an online portals where reports, protocols, and dataset are made accessible to researchers and the public at large

A final call

Documents

1 Online Gambling and more| Brussels Conference | 30 September 2013 Online gambling and more: potential and limits of policy oriented behavioural experiments