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Running head: THE DUNNING-KRUGER EFFECT AND COMPETITION
The Relationship Between The Dunning-Kruger Effect and Competition Entry
Debra Shteinberg
Wagner College
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Abstract
Studies show that most people are overconfident about their own relative abilities, even
when these abilities are unsubstantiated. Overconfidence plays an important role in a person’s
decision to enter into a competition and this decision can have a significant effect on economic
behavior. In the present study, 30 Wagner College students were asked to answer a 10 question
quantitative reasoning questionnaire with five subsequent questions that asked them how
difficult they thought the questionnaire was, to compare how they think they scored on this
questionnaire to other college students based on percentile rank, and to note how many questions
out of 10 they think they answered correctly. Participants were also asked if they would like to
enter their scores into competition with other Wagner College students and if they would like to
enter their scores into competition with Harvard University students. The relationship between
overconfidence and entry into competition were then analyzed. Evidence of overconfidence was
present, but the results did not support the hypothesis that the proportion of overconfident
Wagner students who enter into a competition with other Wagner students is greater than the
proportion of overconfident Wagner students who enter into a competition with Harvard
students. Implications of this study and future applications of the model are discussed.
Keywords: Dunning-Kruger effect, overconfidence, quantitative reasoning, competition
economic behavior
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The Relationship Between The Dunning-Kruger Effect and Competition Entry
Beliefs about one’s abilities are an important ingredient to making decisions. Beliefs that
are misinformed by a person's own overconfidence, however, can lead people to make decisions
with disastrous consequences. The Dunning-Kruger effect explains why people are
overconfident, particularly when they lack the very abilities they believe they possess. The
Dunning-Kruger effect is an observation recognizing that incompetent individuals, or those who
have low levels of ability in a particular area, tend to have high levels of confidence in this
ability (Kruger & Dunning, 1999). On the other hand, individuals who are more competent tend
to have lower levels of confidence in their ability than those who are incompetent.
Overconfidence occurs when an individual's certainty that their predictions are correct exceeds
the accuracy of these predictions (Simon & Houghton, 2003). When people are incompetent in
the strategies they choose to reach success, they suffer a dual burden: They not only reach wrong
conclusions, but they are not competent enough to recognize their own mistakes.
Studies show that most people are overconfident about their own relative abilities, and
unreasonably optimistic about their futures (Camerer & Lovallo, 1999). Individuals are
overconfident in their everyday lives, for example, people report themselves to be above average
in driving ability, their ability to get along with others, and their chances of obtaining jobs that
they like (Moore & Cain, 2007). Overconfidence plays a significant role in people’s decisions to
enter competitions. People compete all the time, whether they notice it or not. They contend with
others for top grades, jobs, trophies, and friends. It is optimal to enter into competitive
environments in which they are certain to do well and to avoid those in which they are doomed
to fail. (Rose et al., 2012).
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The relationship between overconfidence and competition entry has been observed in
multiple studies. Researchers have found that gender plays a role in the decision to enter a
competition (Niederle and Vesterlund, 2007). When people decide to enter into a competition,
researchers have noted that they tend to overweight beliefs about their own performance and
underweight beliefs about the performance of their competition, causing them to enter without
full consideration of the entire scenario (Moore et al. 2007). Research done on the relationship
between overconfidence and entry into competitive markets shows that people tend to enter into
competitions they deem “easy” and avoid those they perceive as “difficult” Cain et al. (2015).
The extent to which overconfident individuals enter into competitions can have a
significant effect on economic markets. Overconfidence can have severe implications on industry
profits and wages. If people are generally overconfident about their relative abilities, then in
industries or professions where overconfidence is likely to be largest, industry profits or total
wages may be negative (Camerer & Lovallo, 1999). If a person enters an industry as an
employee with high optimism in his or her ability, but is unable to supply the high quality of
work that they predicted, the firm the person works for loses money. Overconfidence occurs
when decision makers, such as traders, investors, managers and financial analysts, are too
confident about their ability to make the right decision and give appropriate advice. These overly
optimistic estimates of ability can have negative consequences in several domains: People
overestimate their own ability to pick stocks, and then trade stocks too often; they take
inappropriate risks in product development; they overestimate their chances of winning in court
and are therefore too willing to take their lawsuits to trial; and they take excessive risks in
founding firms (Moore et al., 2007). Simon and Houghton (2003) find that overconfident
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managers overestimate the success of pioneer products, Malmendier and Tate (2008) find that
confident CEOs are more prone to take value-destroying merger decisions, and Odean (1999)
finds that overconfident investors trade too much.
The goal of the present study is to understand the relationships between overconfidence
and entry into competition. It will first aim to show that individuals with low levels of ability,
determined by low scores on quantitative reasoning questions, will be more confident in how
well they did compared to those who received high scores. Next, it will aim to show the
relationship between overconfidence and competition entry by asking participants if they would
enter their scores into a competition with Wagner College students and if they want to enter their
scores into a competition with Harvard University students, based on how well they perceived
they did. To maintain overconfidence, people might self select into “groups” to help sustain this
confidence. Because of self selection bias, those who are overconfident are likely to want to
remain confident, and therefore likely to choose the “easier” option that will help them do so. It
is expected that the proportion of overconfident Wagner students who enter into a competition
with other Wagner students is greater than the proportion of overconfident Wagner students who
enter into a competition with Harvard students.
Literature Review
The Dunning-Kruger Effect and Overconfidence
Kruger and Dunning (1999) established The Dunning-Kruger Effect across four initial
studies. In their second study in particular, the researchers provided 45 Cornell undergraduate
students from a single introduction to psychology class with a 20-item logical reasoning test
taken from a previous LSAT. After taking this test, participants made three estimates about their
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ability and test performance: They compared their "general logical reasoning ability" with that of
other students from their psychology class on a percentile scale, they estimated how their score
on the test would compare with that of their classmates on a percentile scale and they estimated
how many test questions they thought they had answered correctly. The researchers found that
participants in the bottom quartile overestimated their logical reasoning ability and test
performance to the greatest extent. Individuals scored at the 12th percentile on average, but
believed that their general logical reasoning ability fell at the 68th percentile and their score on
the test fell at the 62nd percentile. They thought they had answered 14.2 problems correctly on
average, but actually had a mean score of 9.6. However, participants in the top quartile
underestimated their ability. Individuals scored at the 86th percentile on average, but believed
that their general logical reasoning ability fell at the 74th percentile and their score on the test
fell at the 68th percentile, a significantly lower percentile.
Pennycook et al. (2017) conducted two studies examining this phenomenon using a
cognitive reflection test (CRT), and produced similar results to Kruger and Dunning (1999). This
test aims to measure analytic thinking disposition and can include questions such as the
following: “A bat and ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much
does the ball cost?” A previous study done by these researchers in 2016 determined that around
sixty-five percent of people respond with ten cents, despite this being the wrong answer. A
possible reason for this occurrence is that people tend to be cognitive misers, or they aim to
avoid overusing mental resources in order to conserve energy and rely on solving problems in
the most simple and straightforward manner possible, saying the first thing that comes to mind.
Pennycook et al. (2017) applied the Dunning-Kruger Effect to this problem, believing that
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participants who gave incorrect intuitive responses would fail to recognize their biases. In their
first study, participants were given eight CRT items and then asked to estimate the number of
questions they had answered correctly. On average, participants estimated that they had correctly
solved 5.59 CRT problems but the mean was only 3.88. Additionally, those who scored high on
the CRT, receiving a 7 out of 8, estimated that they had scored a 6.36 on average, a statistically
significant underestimation of their actual score.
Kruger and Dunning (1999) claim that incompetence stems from a lack of metacognitive
skills, or ability to know how well one is performing. One reason incompetent individuals fail to
learn that they are unskilled may be because they do not receive enough negative feedback about
their abilities from others in everyday life (Kruger & Dunning, 1999). The researchers give an
example of the common saying, “If you do not have something nice to say, don’t say anything at
all,” to demonstrate how negative feedback is not commonly welcomed. However, it is not
mentioned how competent individuals, who will also experience a lack of negative feedback in
their lives, are able to respond to the issue so differently from those who end up being
incompetent. The researchers also state that even if individuals do receive negative feedback it is
important that they understand why the failure has occurred in order to learn from it, but
oftentimes this understanding is limited. In order to be successful, a person must experience
several factors: skill, effort, and luck. However, in order to fail, lacking just one of these is
enough. It is the inability of individuals to pinpoint why exactly they failed that leads them to
attribute their shortcomings not to factors such as skill or effort, but rather to a lack of luck. By
doing so, individuals are put under the impression that their failures and any subsequent efforts
to correct them, are out of their control.
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Kruger and Dunning (1999) studied one particular feedback to which they believe
incompetent individuals are unable to respond: social comparison. The incompetent cannot gain
insight into their own competence by watching the behavior of others. The researchers gave 84
Cornell undergraduate students a 20-question grammar test then asked them to complete a
self-assessment similar to the one given in study one. In the next phase, participants were asked
to grade the exams of five other students and evaluate how competent they had been. After
grading, participants were asked to reassess themselves. As predicted, participants who scored in
the bottom quartile were less able to accurately assess the performance of others than those who
scored in the top quartile. These individuals were also unable to gain insight into their own
incompetence by observing the behavior of other people. Despite observing high performances
by other students, bottom quartile participants did not change assessments of themselves, and
some even raised their estimates. On the other hand, top quartile participants raised their self
assessment rating after recognizing that other participants had not done as well as them. Kruger
and Dunning (1999) attribute their original underestimates to the false-consensus effect. The
participants assumed that because they performed so well, their peers must have performed well
too. This would lead them to underestimate their comparative abilities. The researchers infer that
poor performers provide inaccurate estimates because they are wrong about their own
performance, while top performers provide inaccurate estimates because they are wrong about
other people. Similarly, Simon and Houghton (2003) suggest that receiving little or ambiguous
feedback about prior decisions also increases overconfidence.
Overconfidence and Competition
Overconfidence in one's ability is observed in real life scenarios and can become
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problematic when it comes to competition between individuals. For example, Niederle and
Vesterlund (2007), conducted a laboratory experiment in which they examined whether men and
women of the same ability differ in their selection into a competitive environment. Participants
were asked to solve a mathematical task, first under a noncompetitive piece rate and then a
competitive tournament incentive scheme. Although they found no gender differences in
performance, men selected the tournament twice as much as women when choosing their
compensation scheme. The researchers found that men are substantially more overconfident
about their relative performance than women and that these beliefs about relative performance
help predict entry decisions. Such differences in overconfidence and therefore preferences for
competition have economic effects. Holding performance levels between men and women and
job characteristics constant, women are less likely to enter into competitions and therefore less
likely to win them. Consequently, the chance for women to succeed in competition for
promotions or more lucrative jobs decreases.
Cain et al. (2015) further explain the relationship between overconfidence and entry into
competitive markets with varying degrees of difficulty within these markets. In this study,
participants had to complete two quizzes, one easy and one difficult, which represented making a
choice about entering the market with easy or difficult tasks. As they predicted, participants
preferred competing on an easy quiz, in which they believed they outperformed others, over a
difficult one. The better a person believes they are on a certain task, the higher the chance that
they will compete in that task. Therefore, a relationship is developed between task difficulty and
competitive market entry. The economic effect of such a concept is that industries thought to be
“easy” attract more competitors than difficult ones. If competitors believe that running a business
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in a certain industry will be easier than another, then the landscape of that industry will become
more competitive. The researchers point out that if there are too few businesses entering into a
particular market, prices will rise and the consumers will be the ones who suffer (Cain et al.,
2015). However, if there is overentry, businesses will waste resources on fixed costs.
When people compare themselves to others, their judgments tend to be short-sighted.
(Moore et al., 2007). Their judgements more closely represent their own abilities with respect to
a task, rather than these abilities in relation to others. When a task is relatively easy or all the
competitors are strong, each individual competitor tends to believe that he or she will be above
average. In other words, people tend to discount the abilities of others and overweight their own.
When a task is simple and people predict they will perform well, they expect that their
performance will be above average, despite the fact that simple tasks are simple for everybody
and not everybody can be above average. When a task is difficult and people expect to perform
poorly, they believe that their performance will be below average, despite the fact that difficult
tasks are difficult for everybody and not everybody can be below average. Therefore,
comparative judgments are often based on short-sighted self-evaluations.
Moore et al. (2007) observed this relationship between overconfidence and entry into
competition. In this study, the researchers aimed to examine the market-entry decisions of three
groups: actual entrepreneurs, working professionals who considered starting their own firms but
did not, and participants in a market-entry experiment. They found that overconfidence played a
role in excess market entry, but such confidence was limited to markets in which entrants felt
confident about their own personal performance, often ignoring the performance of their
competitors. Essentially, they entered markets that they perceived to be “easy,” but avoided those
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that seemed “difficult.” Some entry decisions may be seen as easy because success in these
industries (such as coffee shops, restaurants, or retail) is based in part on knowledge or abilities
that most people believe they possess. The researchers noted that entrepreneurs tended to
overweight beliefs about their own performance and underweight beliefs about the performance
of their competition, causing them to enter a market without full consideration of their
surroundings. However, over entry was not observed for all markets. Focusing on oneself
increased entry in simple-rank markets, but decreased entry in difficult-rank markets. This means
that the tendency to be overconfident in oneself without valuing the success of potential
competitors can lead to excess entry in some markets and insufficient entry into others.
A similar result was found by Moore and Cain (2007) who state that people tend to
predict that they will be better than others on easy tasks where their own performance is high, but
worse than others on difficult tasks where their own performance is low. This is because on
skill-based tasks, people have better information about themselves than they do about others,
including those who might be competing against them, so their beliefs about others’
performances tend to be less extreme than their beliefs about their own performances. Doing
well on a task should leave one thinking that they did better than others and doing poorly on a
task should leave them thinking that they did worse than others. Moore and Cain (2007) point
out that when people use their beliefs about their own performance, they are predicting another
person’s performance and that is what allows them to decide to enter into competition. However,
predictions can only go so far since they are based on one’s own beliefs about themselves and
therefore the ignorance of another’s belief. According to Camerer and Lovallo (1999), this is due
to reference group neglect. Reference group neglect predicts that when people compete with each
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other based on skill, they will not be insufficiently aware of the quality of competition. One
implication of this is that people will gather too little data about the nature of their competitors
when deciding whether to enter a competition.
Impact on Economic Behavior
Overconfidence is a persistent and prominent behavioral bias found among top
executives and has great influence over their firms’ financial decisions (Yu, 2014). Firms may
often hire overconfident employees for strategic reasons. Overconfident CEOs tend to act more
aggressively in research and development to maintain a competitive edge over their rivals. When
managers, competing to be appointed CEO, are overconfident, they tend to underestimate project
risks and therefore take on more projects than their more realistic counterparts. These managers
therefore have a higher probability of being promoted to CEO. While overconfidence may
facilitate a firm’s economic progress by spurring experimentation, it can lead many individual
firms down pathways to disaster and to ultimate failure.
For example, Simon and Houghton (2003) analyze the impact of CEO overconfidence on
ill-structured decisions made by managers, such as product introductions. They explain that one
important prediction tool that managers use when attempting to forecast the success of their
strategies is called a diagnostic cue. Diagnostic cues allow people to retrieve information from
previous experiences stored in their memory that will help them predict the extent of success in
regards to the scenario at hand (Soll, 1996). They use previous examples of success to make their
current predictions. For example, when predicting the success of a new product, a manager may
use "positive customer feedback prior to an introduction" as a diagnostic cue that has been
frequently associated with the outcome of “achieving positive demand.” Overconfidence steps in
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when these managers overestimate the extent to which a diagnostic cue can make an accurate
prediction. Diagnostic cues are especially poor in predictive validity when the context in which
decisions must be made is unfamiliar, such as with a pioneer product, or a product that
incorporates a major innovation (Dean, 1969). Its market is therefore ill-defined, since potential
and decisions usually have to be made recognizing wide margins of error in terms of cost,
demand, and competitor capabilities. In such an instance, the predictive ability of a diagnostic
cue breaks down, but a risk averse manager may not recognize this (Simon & Houghton, 2003).
Instead, the managers become overconfident because they disproportionately observe instances
of the cue's association with positive outcomes, even though they may not pertain to the pioneer
product. Therefore, managers responsible for making decisions regarding the product, may
overestimate the predictive validity of a cue because they have information about the instances
when the cue was associated with a positive outcome and limited information about instances
when the cue was associated with a negative outcome, even if the negative outcome was more
likely. Therefore, the presence of overconfidence encourages managers to pursue actions that are
riskier than those they might have pursued without a biased perception of risk. Simon and
Houghton (2003), find that managers taking riskier actions are too certain they will achieve
success and thereby underestimate risk.
Malmendier and Tate (2003) analyze the impact of CEO overconfidence on mergers and
acquisitions. They looked at Fortune 500 CEOs who held options in their own company’s stock
until the year of their expiration. They state that, “Previous literature in corporate finance shows
that risk-averse CEOs should exercise stock options well before expiration” (Malmendier and
Tate, 2003). By exercising options early, the CEO can diversify his portfolio. But, thet define an
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overconfident CEO as someone who will hold an option until its final year, showing that he is
consistently optimistic about the company’s prospects. The researchers argue that
overconfidence can drive the acquirer's, or the company purchasing another company, decision
to merge. Mergers and acquisitions are among the most significant and disruptive activities
undertaken by large corporations. Overconfident CEOs overestimate their ability to generate
returns, both in their current firm and in potential targets. Thus, they undertake mergers their
rational counterparts would not. According to Malmendier and Tate’s (2003) theory,
overconfidence can manifest itself in two ways. On one hand, the manager may overestimate the
value of the potential merger. This stems from the manager’s belief that his leadership skills are
“better than average,” and thereby better than the target’s current management, or from an
underestimation of the downside to the merger due to the “illusion of control” over its outcome.
Because the CEO conducting the merger is essentially replacing the current management of the
target firm with himself, he is likely to feel an illusion of control over the outcome and to
underestimate the likelihood of failure. On the other hand, the manager may overestimate the
value of his current company or that his company’s worth is undervalued by the market.
Malmendier and Tate (2003) find that not only are overconfident CEOs more likely to conduct
mergers on average, but they
are also more likely to conduct bad mergers, or mergers that either have no value or destroy
value for the acquiring firm’s shareholders.
Overconfidence is also an issue in investment and trading. Odean (1999) proposed that
due to their overconfidence, investors will trade too much. People who are more overconfident in
their investment abilities may be more likely to seek jobs as traders. This would result in an
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increase of overconfident individuals in the population of investors. Consequently, traders who
find further success in their investments successful in the past may overestimate the degree to
which they are responsible for their own successes and grow increasingly overconfident. Odean
(1999) found that when trading is costly, rational investors will not make trades if the expected
returns from trading are insufficient to offset costs. Overconfident investors, however, have
unrealistic beliefs about their expected trading profits. They may engage in costly trading, even
when their expected trading profits are insufficient to offset the costs of trading, mainly because
they overestimate the magnitude of expected profits. Overconfident investors often believe that
they have useful information, when in fact they have no information.
Cooper et al. (1988) collected data from 2994 entrepreneurs who had recently become
business owners and analyzed it to determine their perceived chances of success. They perceived
their prospects as very favorable. Out of almost 3,000 entrepreneurs, 81% believed that their
chance of success was 70% or higher; and a massive 33% estimated their chance of success to be
100%.
In the world of business and finance, such overconfidence can lead to erroneous decisions
with serious financial consequences. Moosa and Ramiah (2017), state that it is not implausible to
suggest that overconfidence has been a reason for corporate collapses and recurring financial
crises where decision makers put too much faith in their predictions. They give an example of
the collapse of the hedge fund LTCM (Long-Term Capital Management) in 1998 and the
insurance giant AIG (American International Group) in 2008. These events were the results of
blind beliefs in models predicting that something would never happen, which then ended up
happening. The LTCM model was devised by Nobel Prize winners who were known to be good
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at solving partial differential equations. It predicted that bond yields could not deviate
significantly, but this was not the case. LTCM’s capital fell from $4.8 billion at the beginning of
1998 to only $600 million in September. Its investors lost 88 percent of their investment
(Stonham, 1999). The AIG copula-based model (a multivariate distribution whose marginal
distributions are uniformly distributed on the interval (0,1) (Kolev & Paiva, 2009)), constructed
by statisticians, predicted that house prices in the United States could not fall nationwide, leading
to overselling of credit default swaps, without adequate financial cover. Terzi and Uluçay (2011)
define credit default swaps as privately negotiated bilateral contracts in which one party, the
buyer, pays a fee or premium to the other party, the seller, to protect himself against the loss that
may be acquired due to exposure to an individual loan or bond as a result of an unforeseen event.
AIG, with $1 trillion in assets, lost $99.3 billion during 2008 (McDonald & Paulson, 2015).
Policy makers, who put too much trust into their models and believed too much in the ability of
the market to correct itself, were false in their predictions, which led to the collapse of their firms
(Moosa & Ramiah, 2017).
The current study will show that individuals with low levels of ability, determined by low
scores on a mathematical series questionnaire (Appendix B), will be more confident in how well
they did compared to those who received high scores. These individuals are expected to rank
themselves higher when comparing how they think they scored on the questionnaire to other
college students, estimate that they received a higher score on the questionnaire than they
actually did, and to find the questionnaire less difficult than participants who are not
overconfident. The relationship between overconfidence and competition entry will be observed
by asking Wagner College participants if they want to enter their scores into a competition with
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other Wagner students and if they want to enter their scores into a competition with Harvard
students. It is hypothesized that the proportion of overconfident Wagner students who enter into
a competition with other Wagner students is greater than the proportion of overconfident Wagner
students who enter into a competition with Harvard students. In other words, overconfident
participants will be more likely to enter a competition with other Wagner students.
Considerations of previous literature by Moore et al. (2007) and Cain et al. (2015) led to
the assumption that overconfident participants will be more likely to enter a competition with
other Wagner students rather than Harvard students. At first, it may seem as though
overconfident individuals should be expected to enter into competitions with both Wagner and
Harvard students. The very definition of overconfidence should suggest that these individuals are
confident in their abilities and should be willing to enter into any competition. However, these
researchers have shown that although they have high levels of confidence in their abilities,
individuals do not prefer to enter into competitions pertaining to difficult tasks. It is possible that
they want to maintain their high levels of confidence by self selecting into easier options, which
will help them remain overconfident. In the current study, participants are tasked with entering
into a tournament, or a “winner takes all'' situation. Here, only the winner will be rewarded and
the loser will get nothing, therefore participants should be self-assured that their scores will be
strong enough to win. In this study, the degree of difficulty of the questions does not change.
Rather, the perceived difficulty of the competition itself changes. The options to enter into
competition with students from Wagner, a small liberal arts school with an acceptance rate of
70% (The Princeton Review, Wagner College) and students from Harvard, an ivy-league school
with an acceptance rate of 5%, (The Princeton Review, Harvard College) represent these changes
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in difficulty. Harvard was chosen as an option because of the stereotype that students there are
exceptionally smart. Though these questions are rather subjective, it is interesting to observe
whether this stereotype and the name “Harvard” will have an effect on competition entry.
One aspect of the study will examine the Dunning-Kruger effect by measuring
overconfidence among participants. The second aspect will examine if a higher frequency of
overconfident individuals choose to compete with Wagner students compared to Harvard
students.
Method
Participants
Participants were 30 Wagner College students who received access to a Qualtrics
questionnaire link via social media and messaging. Ages of the participants ranged from 18 to 22
years old, ethnicity was mainly white, but included one of each of the following: African
American, Hispanic, and mixed. Out of the participants 3 were male and 27 were female.
Participants did not receive any benefits, such as money or class credits, all participation was
strictly voluntary.
Materials and Procedures
After filling out an informed consent form (Appendix A), participants were asked to fill
out a questionnaire containing 5 mathematical reasoning questions (Appendix B) taken from a
math practice website (Number Series Questions and Answers, 2005). These questions required
participants to have strong quantitative reasoning abilities. After answering these questions,
participants were given 5 self-assessment questions asking them how difficult from 1 to 10 they
thought the questionnaire was, to compare how they think they scored on this questionnaire to
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other college students based on percentile rank, and to note how many questions out of 10 they
think they answered correctly. The last two questions asked participants: if you were told that in
a tournament, the student with the greater score would win $10, would you enter your answers
into this tournament with another Wagner College student? Would you enter your answers into
this tournament with a Harvard University student? Participants were not given a timeframe to
complete the questionnaire. A debriefing statement (Appendix C) and scores to the questionnaire
were provided at the end of the survey.
A within-subject design was used in this study, exposing all participants to both
tournament conditions. Each participant was asked whether they would like to enter the scores
into either tournament, one with Wagner students and one with Harvard students. However,
between-subjects would likely have been a cleaner experimental design, as explained in the
discussion.
By using math series questions, the study aims to challenge the participants’ quantitative
reasoning ability. Quantitative reasoning is the application of basic mathematics and statistics
skills, interpret data, draw conclusions, and solve problems (Elrod, 2014). It requires critical
thinking and problem solving. While the questions used in this study (Appendix B) may appear
inconsequential and tedious, the ability to interpret quantitative information is not only relevant,
but critical in the analysis and interpretation of data in real world scenarios.
Examples of quantitative reasoning can be found in areas such as health, economics,
politics, science, engineering, social science, and even the arts. For example, parents face the
vaccination question early in the life of their children. Parents might ask questions like, "What
are the risks associated with vaccinating my child and what are the benefits?" In order to answer
�THE DUNNING-KRUGER EFFECT AND COMPETITION
20
these questions, they must take into account quantitative information, such as disease occurrence
rates in populations over time, or numbers of cases of complications with certain vaccine
preparations (Elrod, 2014). In economics, quantitative reasoning can be applied in understanding
the power of compound interest or the uses of percentages and in research, it can be applied to
analyze accuracy of a statistical study.
.
Results
Overconfidence
To first demonstrate that participants were overconfident in their abilities on the
questionnaire, a series of regressions were performed. The tests analyzed the relationship
between overconfidence and three different variables: estimated percentile rank compared to
other students, estimated score out of 10 questions, and actual score. Overconfidence was
operationally defined as the estimated score divided by the actual score participants received on
the questionnaire. If this number was greater than zero, the participants were said to have
overestimated their scores. If this number was zero or less than zero, the participants were said
not to have overestimated their scores. Five participants overestimated their performance by at
least one question and 25 participants did not overestimate.
As anticipated, participants identified as overconfident (M = 67.00, SD =8.36) rated
themselves as doing better on the questionnaire than other students in contrast to participants
who were not overconfident (M = 57.44, SD = 24.22) (Figure 1). The regression, rank = β0 + β1
overconfidence + ε, was run and the following equation was established: rank = 34.53 + 28.15
overconfidence. Using the T- Distribution table and 29 degrees of freedom, the critical t value
�THE DUNNING-KRUGER EFFECT AND COMPETITION
21
(tc) is found to be 2.045 at a 5% level of significance. The t-statistic for overconfidence, t = 3.09,
is greater than tc indicating that a statistically significant relationship exists between
overconfidence and the percentile rank that participants predicted. The p value from the F-test
also suggests that the regression is valid, Prob > F = 0.0044.
Similarly, participants identified as overconfident (M = 5.40, SD = 0.89) predicted
receiving higher scores in contrast to participants who were not overconfident (M = 4.84, SD =
2.03) (Figure 2). The regression, guess = β0 + β1 overconfidence + ε, was run and the following
equation was established: guess = 2.47 + 2.83 overconfidence. The t-statistic for
overconfidence, t = 4.02, is greater than tc = 2.045 at a 5% level of significance, indicating that a
statistically significant relationship exists between overconfidence and participants’ estimated
score. The p value from the F-test also suggests that the regression is valid, Prob > F = 0.0004.
Also as expected, participants identified as overconfident (M = 3.60, SD = 0.89) received
lower scores in contrast to participants who were not overconfident (M = 6.28, SD = 1.62)
(Figure 3). The regression, score = β0 + β1 overconfidence + ε, was run and the following
equation was established: score = 6.63 - 0.91 overconfidence. However, the absolute value of
the t-statistic for overconfidence, t = 1.09, is not greater than tc = 2.045 at a 5% level of
significance, indicating that a statistically significant relationship does not exist between
overconfidence and participants’ scores. This is also suggested by the p value from the F-test,
Prob > F = 0.2843.
Additionally, a regression was run to identify the relationship between overconfidence
and the perceived difficulty of the math series questions. Participants identified as overconfident
(M = 4.40, SD = 1.34) found the questions to be less difficult in contrast to participants who were
�THE DUNNING-KRUGER EFFECT AND COMPETITION
22
not overconfident (M = 7.36, SD = 1.86) (Figure 4). The regression, difficult = β0 + β1
overconfidence + ε, was run and the following equation was established: difficult = 10.04 - 3.65
overconfidence. The absolute value of the t-statistic for overconfidence, t = -5.23, is greater than
tc = 2.045 at a 5% level of significance, indicating that a statistically significant relationship
exists between overconfidence and perceived difficulty of the questions. The p value from the
F-test also suggests that the regression is valid, Prob > F = 0.0000.
Competition Entry
After establishing the presence of overconfident participants, three subequations were
established to determine the relationship between overconfidence and the participants' decision
to enter into a competition with Wagner or Harvard students. A third equation was included to
observe the relationship between overconfidence and the participants' decision to enter into a
competition with students from both schools. The equations used to model these relationships
are:
Wagner = β0 + β1 overconfidence + ε
Harvard = β0 + β1 overconfidence + ε
Both = β0 + β1 overconfidence + ε
After running the regressions, the following equations and t-statistics were established:
Wagner = 0.70 - 0.002 overconfidence, where tWagner = -0.01; Harvard = 0.48 - 0.02
overconfidence where tHarvard = -0.07; Both = 0.43 + 0.01 overconfidence, where tBoth = 0.04.
However, no absolute values of the t-statistic for overconfidence were greater than tc = 2.045 at a
5% level of significance, indicating that the coefficient, or marginal effect, is not statistically
significantly different from zero for the decision to enter into a competition with Wagner
�THE DUNNING-KRUGER EFFECT AND COMPETITION
23
students, Harvard students, or both. Therefore, the null hypothesis that the proportion of
overconfident Wagner students who enter into a competition with other Wagner students is not
greater than the proportion of overconfident Wagner students who enter into a competition with
Harvard students, cannot be rejected.
Lastly, a proportion test was run to determine what proportion of strictly overconfident
participants chose to compete against Wagner College students and what proportion chose to
compete against Harvard University students. A greater proportion of overconfident participants
chose to enter into a competition with other Wagner students (M = 0.60, SD = 0.22) than they did
with Harvard students (M = 0.40, SD = 0.22) (Figure 5). However, by evaluating the p value of
the z-test, P > |z| = 0.527, it is evident again that there is no statistically significant difference
between the proportion of participants who chose to compete with Wagner students and the
proportion of participants who chose to compete with Harvard students.
Discussion
These results show that several participants could be identified as overconfident in their
ability to perform well on this quantitative reasoning questionnaire. The results also demonstrate
a statistically significant relationship between overconfidence and three other variables:
percentile rank, estimated score, and perceived difficulty. As the number indicating how well
participants think they did on the questionnaire based on percentile rank increased, so did levels
of overconfidence. Similarly, as the number of questions participants believed they got correct
increased, overconfidence increased. As perceived difficulty of the questionnaire increased, the
level of overconfidence actually decreased. As explained by the Dunning Kruger effect,
overconfident individuals have high levels of certainty that their abilities are strong, even though
�THE DUNNING-KRUGER EFFECT AND COMPETITION
24
this confidence is unfounded. Because these individuals are confident in their abilities, they don’t
find this questionnaire as difficult as their non-overconfident counterparts. The observed
relationship between overconfidence and scores was also supported by the Dunning Kruger
effect, as it showed that overconfident participants received lower scores on the questionnaire
than those who were not overconfident. However, these results were not statistically significant
and it cannot be ruled out that this relationship occurred by chance.
These results cannot support the hypothesis that a greater proportion of overconfident
participants will enter into a competition with other Wagner College students than the proportion
of overconfident participants who enter into a competition with Harvard students. Though the
observed proportion of participants entering into a competition with Wagner students was greater
than those entering into a competition with Harvard students, these results were not statistically
significant and again, it cannot be ruled out that this relationship occurred by chance.
There were several limitations associated with this study. One such limitation is the small
number of participants in the study. Had there been a larger sample size, the data would have
likely been more accurate and representative of the population of Wagner College students. A
larger sample size would allow for more accurate mean values and a smaller margin of error.
Only 5 participants were identified as overconfident, making the chance of accurately identifying
the proportion of overconfident participants entering into a competition very low. Had the
sample size been larger, more overconfident participants would have been recognized, which
would have allowed for a far more accurate regression and proportion test, possibly with
statistical significance.
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25
Another limitation of this study was the use of a within-subjects design, rather than a
between-subjects design. In between-subjects, participants would have been assigned to two
different conditions, with each participant experiencing only one of the tournament conditions.
Half of the participants could have been asked whether they would like to enter into a
tournament with Wagner students and the other half could have been asked if they would like to
enter into a tournament with Harvard students. Using this design could provide more confidence
that the differences between the groups, those exposed to Wagner and those exposed to Harvard,
are due to the differing treatments rather than to other treatment factors, such as order effects,
that can occur when the same individual is exposed to more than one treatment. Order effects
occur when participants are exposed to the same treatment conditions, in the same order. This is
especially prominent in within-subject designs. In this study, displaying the same questions
regarding Wagner students and Harvard students, particularly in the same order, could have
made order effects more pronounced. Respondents could have reacted differently to the
questions based on the order in which the questions appeared. Seeing the ‘Wagner question’ first,
could have affected the way they answered the ‘Harvard question.’
Another limitation of the study was the subjective nature of the Wagner and Harvard
options. It was thought that participants would assume entering into a competition with Harvard
students would be more challenging simply based on stereotypes. However, it cannot be
expected that all participants feel the same way about Harvard students’ levels of intelligence
compared to students at Wagner. Because of within-subjects design, it is possible that
participants may have actually been looking at these options as substitutes. Rather than observing
�THE DUNNING-KRUGER EFFECT AND COMPETITION
26
two distinct options, participants may have felt as though they had to have chosen to compete
against Wagner students or Harvard students.
Despite its limitations, this study adds to the understanding of the relationship between
overconfidence, as explained by the Dunning Kruger effect, and entry into competition.
Although the hypothesis that the proportion of overconfident Wagner students who enter into a
competition with other Wagner students is greater than the proportion of overconfident Wagner
students who enter into a competition with Harvard students could not be accepted, the research
provides a basis for future studies. If the study were to be conducted again it is recommended
that a between-subjects design and a larger sample size be used so more tests can be run on
strictly overconfident individuals.
Conclusion
The impact of overconfidence on economic behavior is explained by Simon and
Houghton (2003), Malmendier and Tate (2003), and Odean (1999). Managerial overconfidence
regarding decisions about product introductions, mergers and acquisitions, and trading can lead
severe financial consequences for firms. Moosa and Ramiah (2017) demonstrate how
overconfidence likely led to the collapse of two firms which resulted in severe financial financial
crises. Overconfidence and misguided predictions clearly play a significant role in business,
finance, and simply in everyday life.
However, Kruger and Dunning (1999) explain that overconfidence can be unlearned with
an improvement in metacognitive skills. When Kruger and Dunning (1999) gave participants a
training session to improve logical reasoning skills before being asked to make self assessments,
they made much more accurate judgements. After being given a training packet, participants who
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were originally in the bottom quartile were just as accurate in monitoring their test performance
as those in the top quartile. Ehrlinger et al. (2016) state that one effective strategy for improving
accuracy in self assessments is to shift people's attention toward more difficult aspects of a task,
which can inspire more accurate self evaluations among people who demonstrate the most
overconfidence. This agrees with research conducted by Moore et al. (2007) and Cain et al.
(2015). After conducting a study to determine initial levels of confidence, the researchers
manipulated their participants’ attention towards easier or more difficult problems on a general
knowledge quiz. When attention was placed on easier problems, participants with entity views of
intelligence (a belief that intelligence is fixed) showed greater overconfidence in their abilities
than participants with incremental views of intelligence (a belief that intelligence can be
improved). However, when attention was placed on more difficult problems, confidence fell to
the same level for both types of participants, showing that this intervention might help
discourage overconfidence and inspire greater self-insight.
Beliefs about one’s abilities are incredibly important when it comes to decision making.
But in order for beliefs to be helpful in making unbiased and careful decisions, a person must not
be overconfident. A person must not overestimate their abilities, especially when these abilities
are not realistic. Such overconfidence plays a huge role in decisions to enter into competitions,
decisions people have to make in their everyday life. If people are not careful, their misinformed
beliefs can lead to negative consequences.
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Works Cited
Cain, D. M., Moore, D. A., & Haran, U. (2015). Making sense of overconfidence in market
entry. Strategic Management Journal, 36, 1–18.
Camerer, C. & Lovallo, D. (1999). Overconfidence and excess entry: An experimental
approach. The American Economic Review, 89, 306.
Cooper, A. C., Woo, C. Y., & Dunkelberg, W. C. (1988). Entrepreneurs’ perceived chances for
success. Journal of Business Venturing, 3, 97–108
Dean, J. (1969). Pricing pioneering products. Journal of Industrial Economics, 17, 165.
Ehrlinger, J., Mitchum, A. L., & Dweck, C. S. (2016). Understanding overconfidence: Theories
of intelligence, preferential attention, and distorted self-assessment. Grantee Submission,
63.
Elrod, S. (2014). Quantitative reasoning: The next “Across the Curriculum” movement. Peer
Review, 16, 4–8
Kolev, N., & Paiva, D. (2009). Copula-based regression models: A survey. Journal of Statistical
Planning and Inference, 139, 3847–3856.
Kruger, J., & Dunning, D. (1999). Unskilled and unaware of it: How difficulties in recognizing
one’s own incompetence leads to inflated self-assessments. Journal of Personality and
Social Psychology, 77, 1121–1134.
Malmendier, U., & Tate, G. A. (2003). Who makes acquisitions? CEO overconfidence and the
market’s reaction. SSRN Electronic Journal.
McDonald, R., & Paulson, A. (2015). AIG in hindsight. The Journal of Economic Perspectives,
29, 81.
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29
Moore, D. A., & Cain, D. M. (2007). Overconfidence and underconfidence: When and why
people underestimate (and overestimate) the competition. Organizational Behavior and
Human Decision Processes, 103, 197–213.
Moore, D. A., Oesch, J. M., & Zietsma, C. (2007). What competition? Myopic self-focus in
market-entry decisions. Organization Science, 18, 440.
Niederle, M., & Vesterlund, L. (2007). Do women shy away from competition? Do men
compete too much? The Quarterly Journal of Economics, 122, 1067.
Number Series Questions and Answers. (2005). The Online Test Center. Retrieved from
http://www.theonlinetestcentre.com/number-series7.html
Odean, T. (1999). Do investors trade too much? The American Economic Review, 89, 1279.
Pennycook, G., Ross, R. M., Koehler, D. J., & Fugelsang, J. A. (2017). Dunning–Kruger effects
in reasoning: Theoretical implications of the failure to recognize incompetence.
Psychonomic Bulletin & Review, 24, 1774–1784.
Rose, J. P., Windschitl, P. D., & Smith, A. R. (2012). Debiasing egocentrism and optimism
biases
in repeated competitions. Judgment & Decision Making, 7, 761–767.
Simon, M., & Houghton, S. M. (2003). The relationship between overconfidence and the
introduction of risky products: Evidence from a field study. Academy of Management
Journal, 46, 139–149.
Soll, J. B. (1996). Determinants of overconfidence and miscalibration: The roles of random
error and ecological structure. Organizational Behavior & Human Decision Processes,
65, 117–137.
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30
Stonham, P. (1999). Too close to the hedge: the case of long term capital management LP.
European Management Journal, 17, 282–289.
Terzi, N., & Uluçay, K. (2011). The role of credit default swaps on financial market stability.
Procedia - Social and Behavioral Sciences, 24, 983–990.
The Princeton Review (n.d.). Harvard College. https://www.princetonreview.com/college/
harvard-college-1022984
The Princeton Review (n.d.). Wagner College. https://www.princetonreview.com/college
/wagner-college-1023835
Yu, C.-F. J. (2014). CEO overconfidence and overinvestment under product market competition.
Managerial and Decision Economics, 35, 574–579.
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Figure 1. Participants identified as overconfident significantly overestimated how well they did,
in terms of percentile rank, on the questionnaire than other students in contrast to participants
ability in contrast to participants who were not overconfident.
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32
Figure 2. Participants identified as overconfident significantly overestimated their scores on the
questionnaire in contrast to participants who were not overconfident.
�THE DUNNING-KRUGER EFFECT AND COMPETITION
Figure 3. Participants identified as overconfident saw lower scores in contrast to participants
who were not overconfident. However, this difference was not statistically significant.
33
�THE DUNNING-KRUGER EFFECT AND COMPETITION
Figure 4. Participants identified as overconfident found the questions to be significantly less
difficult than participants who were not overconfident.
34
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35
Figure 5. A greater proportion of overconfident participants chose to enter into a competition
with other Wagner students than they did with Harvard students. However, this difference was
not statistically significant.
�THE DUNNING-KRUGER EFFECT AND COMPETITION
36
Appendix A
Informed Consent Form
The Department of Psychology at Wagner College supports the practice of protection of
human participants in research. The following information is provided for you to decide whether
you wish to participate in the present study. You should be aware that even if you agree to
participate, you are free to withdraw at any time.
In this study you will be asked to complete a questionnaire. You will be asked to report your
answers 3 demographic questions, 10 math series questions, and 5 self assessment questions.
Immediately following your participation today, you will be provided with more detailed
information regarding the purpose of this study. Although participation will not directly benefit
you, it is believed that information you provide will be useful in furthering our understanding of
perceptions and attitudes.
Your participation is solicited although strictly voluntary. Although this questionnaire will
request some demographic information about you, your responses will be kept completely
confidential. If you would like additional information concerning this study before or after it is
completed, please feel free to contact me by email.
Sincerely,
Debra Shteinberg
Debra.Shteinberg@wagner.edu
Do you consent to these terms?
(1) Yes
(2) No
�THE DUNNING-KRUGER EFFECT AND COMPETITION
Appendix B
Knowledge of Quantitative Reasoning Questionnaire
Demographics
1. What is your age?
_______________
2. What is your gender identity?
_______________
3. What is your ethnicity?
________________
Mathematical Series Questions
1. Look at this series: 42, 40, 38, 35, 33, 31, 28 ... What numbers should come next?
(1) 25, 22
(2) 26, 23
(3) 26, 24
(4) 25, 23
(5) 26, 22
2. Look at this series: 3, 5, 35, 10, 12, 35, 17 ... What numbers should come next?
(1) 22, 35
(2) 35, 19
(3) 19, 35
(4) 19, 24
(5) 22, 24
3. Look at this series: 544, 509, 474, 439 ... What number should come next?
37
�THE DUNNING-KRUGER EFFECT AND COMPETITION
(1) 404
(2) 414
(3) 420
(4) 445
4. Look at this series: 2, 3, 4, 5, 6, 4, 8 ... What numbers should come next?
(1) 9, 10
(2) 4, 8
(3) 10, 4
(4) 9, 4
(5) 8, 9
5. Look at this series: 28, 25, 5, 21, 18, 5, 14 ... What numbers should come next?
(1) 11, 5
(2) 10, 7
(3) 11, 8
(4) 5, 10
(5) 10, 5
6. Look at this series: 5, 16, 49, 104 ... What number should come next?
(1) 171
(2) 191
(3) 181
(4) 161
38
�THE DUNNING-KRUGER EFFECT AND COMPETITION
7. Look at this series: 664, 332, 340, 170, ____, 89, ... What number should fill the blank?
(1) 85
(2) 97
(3) 109
(4) 178
8. Look at this series: 5, 8, 28, 162, ____, 12870 ... What number should fill the blank?
(1) 1738
(2) 2318
(3) 1288
(4) 2224
(5) 2950
9. Look at this series: 16, 41, 61, 85, ____, 145... What number should fill the blank?
(1) 124
(2) 167
(3) 119
(4) 113
(5) 185
10. Look at this series: 16, 43, 98, 209, ____, 879... What number should fill the blank?
(1) 428
(2) 432
(3) 386
(4) 422
(5) 396
39
�THE DUNNING-KRUGER EFFECT AND COMPETITION
40
Self Assessment
1. How difficult did you find this questionnaire? (On a scale from 1 to 10)
0
1
2
3
4
5
6
7
Not at all difficult
8
9
10
Extremely difficult
2. Compare how you think you scored on this questionnaire to other students based on percentile
rank. (Rank from 1-99)
Note: For example, if you say you are in the 75th percentile this means you scored as
well or better than 75% of students.
Percentile Rank:
______
3. How many questions out of 10 do you think you got correct?
_____/10
4. If you were told that in a competition, the student with the greater score would win $10, would
you enter your answers into a competition with another Wagner College student?
Note: This is a hypothetical scenario.
(1) Yes
(2) No
5. If you were told that in a competition, the student with the greater score would win $10, would
you enter your answers into a competition with a Harvard University student?
Note: This is a hypothetical scenario.
(1) Yes
(2) No
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Appendix C
Debriefing Statement
Thank you for participating in this study!
As a reminder, all of your results will be kept confidential.
This study examines the relationship between knowledge of quantitative analysis,
overconfidence in this knowledge, and the decision to enter into a competition regarding this
subject area.
Each participant was given a questionnaire that contained 10 mathematical series questions
found online.
Based on my review of previous research, I am interested in determining if individuals with
lower levels of proficiency (lower scores on the questionnaire) will overestimate their ability
and performance in this subject area and subsequently enter into competition more often.
Previous studies have confirmed this hypothesis and the phenomenon has been called the
Dunning-Kruger Effect.
If you have any questions or would like a copy of the final research report, please feel free to
contact me.
Contact Information:
Debra Shteinberg - Researcher
Debra.Shteinberg@wagner.edu
41
�
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Shteinberg, Debra
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The Relationship Between the Dunning-Kruger Effect and Competition Entry
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Behavioral Economics
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Description
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Studies show that most people are overconfident about their own relative abilities, even when these abilities are unsubstantiated. Overconfidence plays an important role in a person’s decision to enter into a competition and this decision can have a significant effect on economic behavior. In the present study, 30 Wagner College students were asked to answer a 10 question quantitative reasoning questionnaire with five subsequent questions that asked them how difficult they thought the questionnaire was, to compare how they think they scored on this questionnaire to other college students based on percentile rank, and to note how many questions out of 10 they think they answered correctly. Participants were also asked if they would like to enter their scores into competition with other Wagner College students and if they would like to enter their scores into competition with Harvard University students. The relationship between overconfidence and entry into competition were then analyzed. Evidence of overconfidence was present, but the results did not support the hypothesis that the proportion of overconfident Wagner students who enter into a competition with other Wagner students is greater than the proportion of overconfident Wagner students who enter into a competition with Harvard students. Implications of this study and future applications of the model are discussed.
Economics