How Hunger Affects our Financial Risk Taking ‘Metabolic State Alters Economic Decision Making under Risk in Humans’ Symmonds et al. (2010) Written by: Joanne McGuire, Mair Roberts, Nancy Singh, Simon Stevens & Joe Bell
Introduction • Financial decisions are made everyday… • … But have you ever thought about how hunger might affect your financial decision making???
Overview • Aim: To asses whether human financial decision making is affected by hunger and metabolic state. • Hypothesis: Changes in metabolic state would modulate decision-making and financial risk-taking in humans. • Prediction: Likely to be more risk-averse after eating a high-calorie meal and more risk-neutral when satiated.
Method • 19 out of a potential 24 male volunteers • Mean age: 25±7 • Healthy BMI: 22.6±1.7 kg/m² • Tests carried out over 3 sessions, each one week apart
Method Continued… • Each week the lottery task was carried at different times, pre/post meal Figure 1
Method Continued… • Each participant was tested on a sequence of 200 paired lotteries; see Figure 2 below. • . Figure 2.
Dependant Variables • Visual Analogue Scores (VAS) • Prandial suppression of Acyl-ghrelin • Circulating Leptin levels
Results p = 0.022, r²= 0.22 (n=18)
Background research • Extending research on animal foraging behaviours and instinctive reactions of humans. • Is this study question relevant? • Utility theory
Prospect theory • People are more risk averse over gains
Symmondsel at., 2010 • Decisions are more risk averse above a metabolic reference point Figure S1
Did the study methods address the most important potential sources of bias? • Systematic bias • Confirmatory bias/ overconfidence? • Bias leads us to seek out information that supports existing instincts or points of view while avoiding contradictory information. • Sample Size Neglect • When results have been generalised to a population from a less than representative number of data points.
Was the study performed according to the original protocol? • Yes – the study protocol was followed apart from the number of participants • Not all original 25 participants were included in the experiment • This reduces the potential to generalise findings to real-world situations
Strengths • Controlled changes in cognition • Kept all the conditions constant • Mixed the tests up over 3 weeks so there was no conditioning to tests • VAS • Randomized trials to stop habituation • 14 hour fast is realistic
Critiques of method • BMI vs. WHR • Gender • Providing a 2066 calorie meal isn’t very realistic straight after a fast • No feedback is given on the results of the lotteries which is not realistic in real life financial risks
Confounding variables • Whether hunger affects other variables (eg. mood, emotion, other hormones) • Boredom • Stress • Income • Occupation • Age • Education
Other Literature • Genetics: Cesarini et al. (2010) have found that genetic variation accounts for 25% of an individuals risk portfolio • Gender:It has been found that women are more risk-averse than men (Johnson & Powell, 1994) • Culture: Hens & Weng (2007) found that there are cultural differences in risk taking
Other Literature (cont)… • Emotion: Emotional effects can have a large impact on risky decision-making as Zhao (2006) found. • Age: Older people tend to take less financial risks than younger people (Jianakoplos & Bernasek, 2006) • All of these effects show that Symmond’s study cannot be generalised to a population and may lack internal validity as none of these other variables were controlled for.
How we would investigate this within a student environment • Bigger sample • Mixed sample • Mixed BMIs • Use an incentive • Different cultures • Account for obesity and anorexia • Take into account losses
How can it be applied to real life • Dieting and obesity • Are dieters more vulnerable to risky decision making?
How can it be applied to real life • Casinos • Snacks vs. meals
How can it be applied to real life • The importance of breakfast
Conclusions • Symmonds et al’s experiment showed that metabolic states affect financial risk-taking • Addressing a new line of research and extending previous studies on animal behaviours. • However, the experimental method is flawed and results appear slightly ambiguous
References • Byrnes, J. P., Miller, D. C., Schafer, w. D. (1999). Gender differences in risk taking: A meta-analysis. Psychological Bulletin, 125(3), 367-383. • Cesarini, D., Johannesson, M., Lichtenstein, P., Sandewall, O., & Wallace, B. (2010). Genetic variation in financial decision making. Journal of Finance, 65(5), 1725-1754. • Comings, D,E., Rosenthal, R,J., Lesieur ,H,R., Rugle, L,J., Muhleman, D., Chiu, C., Dietz,G., & Gade, R. (1996). A study of the dopamine D2 receptor gene in pathological gambling. Pharmacogenetics ,6(3), 223-34 • Dwyer ,p., Gilkeson, J., & List, J. (2001). Gender differences in revealed risk taking: evidence from mutual fund investors. Economics Letters 76, 151-158 • Eckel, C. C., & Grossman, P. J. (2002). Sex differences and statistical stereotyping in attitudes towards financial risk. Evolution and Human Behavior, 23(4), 281-295. • Hens, T., & Weng, M. (2007). Does Finance have a cultural Dimension? FINRISK Working Paper, 377.
References Cont… • Hill, A,J., Weaver, C,F., & Blundell, J,E. (1991). Food craving, dietary restraint and mood. Appetite ,17(3), 187-97. • Hunton, J., Hall, T., & Price, K (1998). The value of voice in participative decision making. Journal of Applied Psychology, 83 (5), 788-797 • Johnson, J., & Powell, P. (1994). Decision Making, Risk and Gender: Are managers different? British Journal of Management, 5(2), 123-138. • Kahneman, D., & Tversky, A. (1979) "Prospect Theory: An Analysis of Decision under Risk", Econometrica, XLVII, 263-291. • Powell, M., & Ansic, D. (1997). Gender differences in risk behaviour in financial decision-making: An experimental analysis. Journal of Economic Psychology, 18, 605-628. • Schubert, R., Brown, M., Gysler, M., & Brachinger, H. (1999). Financial Decision-Making: Are Women Really More Risk-Averse? An American Economic Review, 89(2), 381-385.
References Cont… • Symmonds, M., Emmanuel, J. J., Drew, M. E., Batterham, R. L., & Dolan, R. J. (2010). Metabolic State Alters Economic Decision Making under Risk in Humans. PLoS One, 5(6), e11090. • Vroom, V, H., & Pahl, B. (1971). Relationship between age and risk taking among managers. Journal of Applied Psychology, 55 (5), 399-405. • http://www.alexwhittaker.org/?p=26