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Thought Questions

 

211

 

 

 

 

 

 

 

 

 

 

 

 

 

Biographical Note

Colin F. Camerer (1959–)

B.A., Johns Hopkins University, 1977; M.B.A., University of Chicago, 1979; Ph.

D., University of Chicago, 1981; held faculty positions at Northwestern University,

University of Pennsylvania, University of Chicago, and California Institute of

Technology

By the age of 22, Colin Camerer had already obtained an M.B.A. specializing in nance and his Ph.D. in behavioral decision theory from the University of Chicago Graduate School of Business and began his faculty appointment at Northwestern University. He is an accomplished and renowned scholar both in behavioral theory and in experimental economic methods. He is best known for his work on decision under risk and uncertainty and behavioral game theory. Camerer is the author of the premier book on behavioral game theory, as well as scores of articles and book chapters developing the theory of behavior in games. He has also contributed to the growing eld of neuroeconomics, serving as the president for the Society of Neuroeconomics from 2005 to 2006. Camerer is a Fellow of the Econometric Society and a member of the American Academy of Arts and Sciences. In addition to his academic work, Camerer has taken an interest in punk music, founding and running his own punk recording label since 1983. His label, Fever Records, produced recordings for such underground Chicago bands as Bonemen of Baruma and Big Black.

T H O U G H T Q U E S T I O N S

1.Conrmation bias leads people to interpret the same information in very different ways. Given such a bias is pervasive, one must be careful in forming initial opinions. If conrmation bias is pervasive, what might this say about the quality of information sources that are available for controversial topics in which people often hold sharply diverging views? When people claim strong evidence for their opinion, should we believe them? Is there a way to obtain unbiased assessments?

2.Suppose you hold a stock and are considering whether to sell it or keep it. You initially believe that the probability the stock will rise in value in the long run is 0.7. You decide you will sell the stock when the probability of a long run drop in value reaches 0.5. Then, over the course of time you watch the changes in the value of the stock day to day, each days outcome

serving as a forecast of future value. Further, suppose that PRISErise = 0.6 where RISE indicates a longrun future rise in value and rise indicates an observed daily rise in value. Correspondingly, PFALLfall = 0.6, where FALL indicates a long-run decline in future values of the stock and fall indicates a daily observed decline in value. Suppose the probability that you misperceive a signal given it contradicts your current belief is q = 0.4. How many daily declines would you need to observe before you would sell the stock according to Rabin and Schrags model of conrmation bias? What would a Bayesians beliefs be regarding the probability of a decline at that point? How many daily declines would you need to observe in order to sell if you had perfect perception q = 0?

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

212

 

 

 

CONFIRMATION AND OVERCONFIDENCE

 

 

 

 

 

 

 

 

 

 

 

3. In this chapter, we motivated the rational model of

 

impossible comes to pass. What would happen in these

 

 

information search by showing that rational people

 

cases if people were not required to insure? What

 

 

should prefer information that is accurate no matter

 

problems might arise if governments also prepared for

 

 

how it relates to their current hypothesis. People should

 

emergencies in a way that displayed overcondence?

 

 

continue to seek new information until they are certain

 

What mechanisms could prevent overcondence in

 

 

enough of the answer that the cost of new information

 

government action?

 

 

 

 

 

 

 

 

 

is not justied by the degree of uncertainty. Conr-

5.

Suppose

we consider

producers

in a

competitive

 

 

mation bias can lead to overcondence, where people

 

 

 

market. Hence all producers are price takers and earn

 

 

fail to

recognize the

level of uncertainty they face.

 

 

 

 

prot

π = pq − c q ,

where

p is

a

random variable.

 

 

What implications are there for information search by

 

 

 

 

Thus,

the

mean

of

prot

is E π

= μpq − c q ,

and

 

 

those

displaying conrmation bias? When will they

 

 

 

 

variance of prot is VAR π

= σ2q2

. Further, suppose

 

 

cease to search for information? What might this imply

 

 

 

 

 

 

 

 

 

 

p

 

 

 

 

 

 

regarding

people who have chosen to

cease their

 

that each producer has an expected utility of wealth

 

 

 

function

that

can

 

be

approximated

as

 

 

education

efforts at various phases? What education

 

 

 

 

 

E u π

= E π − RA

2

VAR π

 

and

that

each

 

 

policy might be implied by this result?

 

 

 

 

 

 

 

behaves so as to maximize expected utility of wealth.

 

 

 

 

 

 

 

 

 

4. Governments often require people to obtain insurance;

 

Consider that some producers are overcondent and

 

 

for example, all drivers are required to carry auto

 

others are not. Which will produce more (larger q)?

 

 

insurance to cover damages to others in the event of a

 

Which will obtain a higher prot on average? Suppose

 

 

crash. Homeowners are often required by banks to

 

that the mean price declines over time. What is the

 

 

carry insurance on their home. Why do these require-

 

condition for shut down? Will rational or overcon-

 

 

ments exist? Would they be necessary if people truly

 

dent producers shut down rst? What does this say

 

 

recognized the risk they faced? One characteristic of an

 

about the rationality of rms in a competitive

 

 

overcondent person is that she is continually sur-

 

environment?

 

 

 

 

 

 

 

 

 

 

prised

when what

she thought was

unlikely or

 

 

 

 

 

 

 

 

 

 

 

 

R E F E R E N C E S

Alpert, M., and H. Raiffa, A Progress Report on the Training of Probability Assessors.In D. Kahneman, P. Slovic, and A. Tversky (eds.). Judgment under Uncertainty: Heuristics and Biases. New York: Cambridge University Press, 1982, pp. 294305.

Babcock, L., and G. Loewenstein. Explaining Bargaining Impasse: The Role of Self-Serving Biases.” Journal of Economic Perspectives 11(1997): 109126.

Barber, B.M., and T. Odean. Boys will be Boys: Gender, Overcondence and Common Stock Investment.” Quarterly Journal of Economics 116(2001): 261292.

Bogan, V., and D.R. Just. What Drives Merger Decision Making Behavior? Dont Seek, Dont Find, and Dont Change Your Mind.” Journal of Economic Behavior and Organization 72 (2009): 930943.

Brockhaus, R.H. Risk Taking Propensity of Entrepreneurs.” Academy of Management Journal 23(1980): 509520.

Busenitz, L.W., and J.B. Barney, Differences Between Entrepreneurs and Managers in Large Organizations: Biases and Heuristics in Strategic Decision-Making. Journal of Business Venturing 12(1997): 930.

Compte, O., and A. Postlewaite, Condence-Enhanced Performance.” American Economic Review 94(2004): 15361557.

Dahl, G.B., and M.R. Ransom. Does Where You Stand Depend on Where You Sit? Tithing Donations and Self-Serving Beliefs.

American Economic Review 89(1999): 703727.

Darley, J.M., and P.H. Gross. A Hypothesis-Conrming Bias in Labeling Effects.” Journal of Personality and Social Psychology

44(1983): 2033.

Malmendier, U., and G. Tate. Who Makes Acquisitions? CEO Overcondence and the Markets Reaction.” Journal of Financial Economics 89(2007): 2043.

 

 

 

 

 

 

References

 

213

 

Mynatt, C.R., M.E. Doherty, R.D. Tweney. Conrmation Bias in a

Ross, M., and F. Sicoly. Egocentric Biases in Availability and

Simulated Research Environment: An Experimental Study of

Attribution.” Journal of Personality and Social Psychology 37

Scientic Inference.” Quarterly Journal of Experimental Psy-

(1979): 322336.

 

 

chology 29(1977): 8595.

Svenson, O. Are We all Less Risky and More Skillful than our

 

Oskamp, S. Overcondence in Case-Study Judgments.” Journal of

Fellow Drivers?” Acta Psychologica 47(1981): 143148.

 

 

Consulting Psychology 29(1965): 261265.

Wason, P.C. Reasoning About a Rule.” Quarterly Journal of

 

Rabin, M., and J.L. Schrag. First Impressions Matter: A Model of

Experimental Psychology 20(1968): 273281.

 

 

Conrmatory Bias.” Quarterly Journal of Economics 114(1999):

 

 

 

 

3782.

 

 

 

 

 

 

 

 

 

Decision under Risk

 

9

 

and Uncertainty

 

 

 

 

 

 

In many elds of occupation, there are regular and agreed-upon cycles to the job market. For example, because college students generally graduate in June, many employers focus their efforts for hiring entry-level positions to begin work soon thereafter. Some employers are very highly sought after for their level of pay and the future career opportunities of their employees. Consider a less-sought-after employer who has difculty offering salaries that are similar to those commonly offered in the market. Very often, in such markets, less-sought- after employers start their process of seeking recruits earlier than their peers and make offers that expire before their competitors will make their initial offers. Such exploding offers are designed to put the recruit in a quandary. Consider a very qualied recruit with an exploding offer. He can take the offer and obtain the lower pay and a secure job with certainty. Alternatively, if he rejects the offer, he takes his chances and potentially fails to nd a moredesirable job. If the salary offer is low enough, he might have a very high probability of obtaining a more-lucrative offer when the real cycle of offers begins. Nonetheless, it can be very difcult to turn down a job without another offer in hand.

People often face problems of decision under risk. In general, models of decision under risk consist of two-component models: a model of preferences over outcomes and a model of risk perception. Rational models of decision under risk depend heavily on the assumption that people understand the potential outcomes of any risky choice and the probability of each of those outcomes. In the previous chapters, we discussed several anomalies related to how people deal with probabilistic information. Behavioral models of risky choice generally base the component model of beliefs on behavior observed in experimental settings. For example, people seem to treat certainty in a very different way than probabilistic outcomes, an effect that might make exploding job offers more protable for inferior rms. Or people may be reluctant to invest in the stock market despite higher average returns, opting for low-returning savings accounts. Interestingly, experimental observations of choice under risk sometimes contradict the common behaviors discussed in the previous chapters.

Examining the economics of decision under risk is a bit of a challenge. In a standard consumption context, we may observe whether someone chooses to purchase an apple or not. We know with relative certainty that the person understood the characteristics of either choice and we can also know with relative certainty what those characteristics are. In the context of risk, we may observe whether someone chooses to purchase a share of a particular stock, and we can observe subsequent changes in the value of that stock. However, we will never easily be

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