Decision making under Risk and Uncertainty

 

Nowadays people make many decisions that involve uncertainty and risk, including important choices like taking insurance, getting mortgage, or medical treatments.Risky decisions, from barely conscious ones when driving ( “ Should I overtake this car? ” ) to carefully deliberated ones about capital investments( “ Do I need to adjust my portfolio weights? ” ). Benjamin Franklin famously stated that the only things certain in life are death and taxes. If anything, the amount of uncertainty in our world has increased between the eighteenth and twenty-first centuries. The economist Frank Knight was the first to make a conceptual distinction between decisions under risk and under uncertainty.  Risk refers to situations where the decision-maker knows with certainty the mathematical probabilities of possible outcomes of choice alternatives.  Uncertainty refers to situations where the likelihood of different outcomes cannot be expressed with any mathematical precision (Weber and Johnson, 2008). 

Daniel Bernouli (1954) found that most of the people don’t tend to maximize expected value. He introduced a game known as St. Petersburg paradox. Asking a question how much would you pay in order to play the game? One toss a coin until it lands on heads. If the coin lands on heads on the first throw, the game ends and you will win £1, if it lands on the heads on the second toss the game ends and you win £2. Every coin toss with tail outcome will double the previous outcome. So from the probabilistic point of view the pay out of the game could be infinitive. However he found that people are nor willing to pay big amount of money to play this game. The expected utility theory indicates that when utility is not favourable or seen as potential losses people will not participate. Simply saying people are more sensitive to looses that gains by showing risk averse behaviour. Nerveless, Kahneman's and Tversky's(1979) prospect theory shows how people handle risk and uncertainty. They argued that people's risky decision will depend on how the problem is formulated. For example the subjective value between gains of £10 and 20£ is greater then the subjective differences between gains of  £110 and  £120.  I think  that the formulation plays a very important role in people decision making.  Our decision will depend on whether the problem was presented to us negatively or positively.

You have 5%  chance  of winning £1000 when betting £100.

      OR

You have 95% chance of loosing £100 when betting to win £1000.

Which one is more appealing to you ?  

PS: I was doing a little research about coin tossing outcomes. If anyone is interested please read this. http://www.codingthewheel.com/archives/the-coin-flip-a-fundamentally-unfair-proposition 

Experiment about coin flip. After I read it, I started to think that if someone would offered me to pay money for  playing the game of coin flipping  like "St. Petersburg Paradox", I would not sign for it :)) 

References
David Hardmam (2009) Judgement and decision making: Psychological perspective. Chichester, UK: BPS-Blackwell
Elke U. Weber & eric J. Johson (2008) Neuroeconomics Decision making and the Brain.   Available on: http://www.mendeley.com/research/decisions-under-uncertainty-psychological-economic-neuroeconomic-explanations-risk-preference/
Last entered 09/11/2011

Bailing and Jailing the Fast and Frugal way. Or are the decisions made in Fast and Frugal way always right ?

This time we had to read articles about decision making in fast and frugal way. The article our group had to read and discuss was ‘Bailing and jailing the Fast and Frugal way’ Dhami and Ayton (2001). The main focus of the article was to review how magistrates make decisions about whether to release defendants on bail based on their previous crimes.  

We would think that magistrates are the people who would carefully consider their decisions, because defendants life and society's well-being depends on how well those decisions are made. Unfortunately, magistrates have to work under constraints such as time pressure. So usually their decisions are being criticized by organizations supporting victims, groups representing defendants and professional agencies such as prosecution agencies. The authors of the article tried to analyze more into depth  how and with what confidence those important decisions are made. They identified the different process models such as the due-process which should work towards reducing crime by minimizing the number of innocent people incorrectly convicted. My attention was drawn to the Fast and Frugal models. For example, the matching heuristic is a simple process model that do not search through all available information, but just through small subset of cues and base decision one cue only. One would think that decisions made based on these heuristics should be inaccurate and poorly made. However, those models are accurate and the evidence for Fast and Frugal models are as good as compensatory integration models.

The results of the study found that majority of magistrates showed inconsistency in their bail decision and they are usually influenced by defended and crime related cues. So simply saying most of the magistrates ‘did not bother’ to look at all the information they were provided with. And in the end their decision depended on their own experience and presumptions about particular individual appearance. However, all magistrates were highly confident that they had made the appropriate decisions. The findings of the article made me wonder whether the justice system is 'Justice' after all and made me to understand how highly social norms and presumptions can influence people's judgments.

The heuristics and biases of judgement under uncertainty. Gigerenze's normative critique of Kahneman and Tversky.

This week our group has been given to read and discus article ‘A reply to Kahneman and Tversky (1996) by Gigerenzer, On Narrow norms and Vague Heuristics’. Thru the discussion of the article we had to form our understanding about the cognitive processes that produce both valid and invalid judgements.

Kahneman and Tversky (1974) described three heuristics that are employed in making judgments under uncertainty; (1) representativeness,  which  is  usually  employed  when  people  are  asked  to  judge  the  probability that  an  object  o r   event  A  belongs  to class or  process  B; (2)availability of  in- stances o r  scenarios, which is  often employed  when  people  are  asked  to  assess the  frequency of  a class or the plausibility  of  a  particular  development;  and (3)  adjustment  from  a n  anchor,  which is usually employed in numerical prediction  when  a  relevant  value  is  available ( Kahneman and Tversky, 1974).  They argued that these  heuristics  are  highly  economical and  usually  effective,  but  they  lead  to systematic  and  predictable  errors.  A better  understanding  of  these  heuristics and  of  the  biases  could  improve judgments  and  decisions in  situations  of  uncertainty. However, Gigerenzer, in his reply to Kahneman and Tversky, argued that some of the biases identified are unstable, for example in some cases their degree can be reduced by asking questions in terms of frequencies rather than in terms of probabilities. Secondly, Gigerenzer argued that, because Kahneman and Tversky’s heuristics are formulated by means of vague, l terms like “representativeness”, the appeal to these heuristics as generators of biases has limited explanatory power. Thirdly, he argued that it may be inappropriate to characterize some of the biases identified by Kahneman and Tversky as “errors” or “fallacies” for three reasons. (a) According to frequentists, no norms are appropriate for single-case judgements, because single-case probabilities are meaningless. (b) Even if single-case probabilities make sense, they need not to be governed by statistical norms because norms are “content-blind” and can conflict with conversational norms. (c) In some cases conflicting statistical norms exist (“statistics does not speak with one voice”) (Vranas, 1999).

Gigerenzer did not neglect the fact that Kahnemans and Tversky’s work gave a big impact to the field of decision making. However, he states:“In place of plausible heuristics that explain everything and nothing- not even conditions that trigger one heuristic rather than another- we will need models that make surprising ( and falsifiable) predictions and that reveal the mental processes that explain both valid and invalid judgment” ( Gigerenzer, 1996). 

References

A. Tversky and D.Kahneman (1974). Judgemnt under Uncertainty: Heuristics and Biases. Science, New Series, Vol. 185, No. 4157. (Sep. 27, 1974), pp. 1124-1131.

Peter B.M. Vranas (1999). Gigerenzer's normative critique of Kahneman and Tversky. Department of Philosophy, The University of Michigam, 2215 Angel Hall, Ann Arbor.