Experimental and Behavioural Economics
Experimental and Behavioural Economics
The Experimental and Behavioural Economics Research Group (EBERG) draws its membership from economists based at the Economics Department at Warwick who work in the fields of Experimental Economics, Behavioural Economics and/or Subjective Wellbeing (“Happiness Economics”). Experimental methods are used in many fields of economics, including behavioural economics, public economics, labour economics, political economy, game theory, and financial economics. Behavioural economics is an attempt to understand decision-making in the context of the many psychological, cognitive and emotional factors that influence behaviour. Behavioural economists typically build on traditional economic models with insights from psychology or neuroscience. Since behavioural economics concerns the underlying motivations for behaviour it can be hard (though not impossible) to find data to support or develop behavioural theories without the use of experimental methods which explains the close relationship between the two fields.
Experimental and behavioural research are fundamentally interdisciplinary and this is reflected in the fact that the group is linked to other similar groups across the University of Warwick and beyond. DR@W is the overarching interdisciplinary group of all behavioural scientists in Warwick which, together with EBERG, also takes members from the Behavioural Science Group at Warwick Business School and behavioural and experimental psychologists based in the Psychology Department, and hosts a weekly seminar, the DR@W Forum. Many members of EBERG are also affiliated with Bridges, an interdisciplinary centre that includes behavioural and experimental work in its remit that also hosts regular seminars and workshops. Behaviour, Brain and Society is one of the University of Warwick’s global research priorities (GRPs) and the co-ordinator of EBERG sits on the board of the GRP. Several group members are actively involved in the ESRC CAGE centre. Theme 3 of CAGE is led by the co-ordinator of EBERG and has a special focus on subjective wellbeing.
People
Academics
Academics associated with the Reseach Group Name research group are:
Research Students
Events
DR@W Forum (Two short talks): Ty Hayes (WBS, Behavioural Science) & James Price (Warwick, Mathematics for Real-World Systems)
The effects of cash-out availability on horse-race betting: A common feature in many online betting platforms is the ability to “cash out” of a bet after it has been placed. This feature somewhat mitigates the risk of placing bets and may encourage people to gamble with more and riskier bets. To test the effects of this cash-out feature on betting, we ran an online experiment where people could place bets on horse-racing videos. In a first session, participants (N = 378) filled out some questionnaires and completed a real-effort task to earn a bonus of up to £3. They were then invited to a second session where they could place bets on a series of 3 horse races via a naturalistic interface. Participants were randomly assigned to either have cash-out available or not available during their betting session. People in the cash-out group were more likely to choose the betting task over a distractor (non-gambling) game and bet ~10% more of their available stake than people who did not have cash-out available. There was no effect on the average odds of bets placed. The effect of cash-out availability on bet size was more pronounced amongst those with low PGSI scores (<3), with those participants betting nearly 20% more of their stake. This differential impact makes low-risk bettors’ behaviour less distinct from that of high-risk bettors when cash-out is available. This similarity raises concerns about the ability of operators to identify those at risk of harm, as well as potential longer term effects of cash-out on low-risk bettors.
The dynamics of decision making with uncertain outcomes: In situations where an agent repeatedly makes decisions with uncertain outcomes there is no metric to definitively compare different strategies. A common approach is to use an expected value, this represents a scenario being repeated infinitely many times and outcomes averaged. However, this approach overlooks that a single agent observes an outcome only once, and there is no guarantee the expected value with be representative. Instead, the approach investigated in this talk is to consider the long-term rate of growth in wealth of a single agent - that is, rather than average over an ensemble we instead average over time. This talk will introduce the relevant theory and conclusions that a growth-based viewpoint of sequential decision making provides. We will also focus on novel extensions of growth-rate theory to a wider class of decision making problems that include phenomena, such as ruin, that are found in the real-world.