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Will I tell you that you are smart (dumb)? Deceiving Others about their IQ or about a Random Draw
Abstract
We investigate whether individuals’ deception rates differ by whether the messages they send to others are about the latter’s relative ability or not. We also study whether they are more likely to deceive when it is in their interest to make others believe that they are either of high ability or low ability. In the experiment, participants play a sender-receiver game. The experiment features a 2 × 2 factorial design. First, we vary whether the state is determined by the receiver’s relative performance in an IQ test or it is about a randomly drawn number. Second, monetary incentives, which are common knowledge, are such that the sender is better off (worse off) when the receiver’s action is about him being of high (low) relative ability, while the receiver benefits from selecting the action that matches his true ability. We do not find systematic differences in the deception rates due to the ego-relevance of the condition. However, we find that senders believe they are more likely to move the beliefs of the receivers when they send a deceiving message saying that the receiver is of high ability.
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Lies can have profoundly negative consequences for individuals, groups and even for societies. Understanding how lying evolves and when it proliferates is therefore of significant importance for our personal and societal well-being. To that effect, we here study the sender-receiver game in well-mixed populations with methods of statistical physics. We use the Monte Carlo method to determine the stationary frequencies of liars and believers for four different lie types. We consider altruistic white lies that favour the receiver at a cost to the sender, black lies that favour the sender at a cost to the receiver, spiteful lies that harm both the sender and the receiver, and Pareto white lies that favour both the sender and the receiver. We find that spiteful lies give rise to trivial behaviour, where senders quickly learn that their best strategy is to send a truthful message, while receivers likewise quickly learn that their best strategy is to believe the sender's message. For altruistic white lies and black lies, we find that most senders lie while most receivers do not believe the sender's message, but the exact frequencies of liars and non-believers depend significantly on the payoffs, and they also evolve non-monotonically before reaching the stationary state. Lastly, for Pareto white lies we observe the most complex dynamics, with the possibility of both lying and believing evolving with all frequencies between 0 and 1 in dependence on the payoffs. We discuss the implications of these results for moral behaviour in human experiments.
We use a repeated sender-receiver game in which sender behavior is revealed to future counterparts either by (i) standardized computer reports or (ii) individual reports composed by the receivers. Compared to our baseline, both reporting systems significantly decrease the rate of deceptive messages chosen by senders. However, we find that computer reports reduce deception to a higher extent than individually written reports. This comparably higher impact can be explained by the senders’ anticipation of a high number of missing or deficient receiver reports that we find. We conclude that the precision of a reporting system has a higher importance for reducing deception than its personal character via individual feedback. Surprisingly, the reliability of computer reports is not correctly anticipated by receivers, who trust individually written reports more in the beginning and hence seem to back the wrong horse initially.
oTree is an open-source and online software for implementing interactive experiments in the laboratory, online, the field or combinations thereof. oTree does not require installation of software on subjects’ devices; it can run on any device that has a web browser, be that a desktop computer, a tablet or a smartphone. Deployment can be internet-based without a shared local network, or local-network-based even without internet access. For coding, Python is used, a popular, open-source programming language. http://www.oTree.org[www.oTree.org] provides the source code, a library of standard game templates and demo games which can be played by anyone.
We examine a prevalent form of client–agent interaction through a feedback-giving game. In this game, a client undertakes a nontrivial task and is compensated based on her task performance, which is only made known to her when the client–agent interaction ends. Meanwhile, her performance is disclosed to an agent, who must then give the client feedback on her performance. Upon receiving the feedback, the client reports her happiness level, which in turn determines the agent's payoff. In eight studies involving 928 subjects, we vary the way the agent's cash earnings depend on the client's reported happiness. When we make the agent's earnings proportional to the client's reported happiness, the agent inflates his feedback, and the client reports a higher level of happiness (than that reported in a control condition where the agent always provides honest feedback). We show that neither the agent nor the client behaves altruistically in their reporting. The client reports being happier because she overestimates her performance and mistakenly believes that the agent's feedback is genuine. The agent stops inflating his feedback when doing so no longer benefits him. Finally, our main findings are shown to be robust with respect to several factors, including making the agent's feedback consequential in affecting the client's payoff. In summary, we show that the agent behaves opportunistically, and the client's overconfidence of her own performance is what makes this strategy successful.
Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2013.1846 .
This paper was accepted by Uri Gneezy, behavioral economics.
Background
The p value obtained from a significance test provides no information about the magnitude or importance of the underlying phenomenon. Therefore, additional reporting of effect size is often recommended. Effect sizes are theoretically independent from sample size. Yet this may not hold true empirically: non-independence could indicate publication bias.
Methods
We investigate whether effect size is independent from sample size in psychological research. We randomly sampled 1,000 psychological articles from all areas of psychological research. We extracted p values, effect sizes, and sample sizes of all empirical papers, and calculated the correlation between effect size and sample size, and investigated the distribution of p values.
Results
We found a negative correlation of r = −.45 [95% CI: −.53; −.35] between effect size and sample size. In addition, we found an inordinately high number of p values just passing the boundary of significance. Additional data showed that neither implicit nor explicit power analysis could account for this pattern of findings.
Conclusion
The negative correlation between effect size and samples size, and the biased distribution of p values indicate pervasive publication bias in the entire field of psychology.
This article reviews findings on the predictive validity of psychometric tests of intelligence. The article is divided into five major parts. In the first part, the issues with which the article deals are introduced. In the second part, we discuss what psychologists can learn about the predictive validity of intelligence tests from results obtained in the established market economies. Intelligence quotient (IQ) is considered in relation to educational achievement, employment prospects and wealth generation, career outcomes, and well-being. In the third part, the intelligence tests (primarily for infants and children) that yield the IQ scores are discussed. In the fourth part, constraints are presented on the interpretations of findings, including cross-cultural issues. We conclude that conventional tests of intelligence can be useful but only if they are interpreted very carefully, taking into account the factors that can affect them, and in conjunction with other measures.
We report experiments on sender-receiver games with an incentive for senders to exaggerate. Subjects "overcommunicate" -- messages are more informative of the true state than they should be, in equilibrium. Eyetracking shows that senders look at payoffs in a way that is consistent with a level-k model. A combination of sender messages and lookup patterns predicts the true state about twice as often as predicted by equilibrium. Using these measures to infer the state would enable receiver subjects to hypothetically earn 16-21 percent more than they actually do, an economic value of 60 percent of the maximum increment. (JEL C72, C91, D82, Z13)
The authors present a reconciliation of 3 distinct ways in which the research literature has defined overconfidence: (a) overestimation of one's actual performance, (b) overplacement of one's performance relative to others, and (c) excessive precision in one's beliefs. Experimental evidence shows that reversals of the first 2 (apparent underconfidence), when they occur, tend to be on different types of tasks. On difficult tasks, people overestimate their actual performances but also mistakenly believe that they are worse than others; on easy tasks, people underestimate their actual performances but mistakenly believe they are better than others. The authors offer a straightforward theory that can explain these inconsistencies. Overprecision appears to be more persistent than either of the other 2 types of overconfidence, but its presence reduces the magnitude of both overestimation and overplacement.
This paper develops a model of strategic communication, in which a better-informed Sender (S) sends a possibly noisy signal to a Receiver (R), who then takes an action that determines the welfare of both. We characterize the set of Bayesian Nash equilibria under standard assumptions, and show that equilibrium signaling always takes a strikingly simple form, in which S partitions the support of the (scalar) variable that represents his private information and introduces noise into his signal by reporting, in effect, only which element of the partition his observation actually lies in. We show under further assumptions that before S observes his private information, the equilibrium whose partition has the greatest number of elements is Pareto-superior to all other equilibria, and that if agents coordinate on this equilibrium, R's equilibrium expected utility rises when agents' preferences become more similar. Since R bases his choice of action on rational expectations, this establishes a sense in which equilibrium signaling is more informative when agents' preferences are more similar.
This paper uses laboratory experiments to directly test a central prediction of disclosure theory: that strategic forces can lead those who possess private information to voluntarily provide it. In a simple sender-receiver game, we find that senders disclose favorable information, but withhold unfavorable information. The degree to which senders withhold information is strongly related to their stated beliefs about receiver actions, and their stated beliefs are accurate on average. Receiver actions are also strongly related to their stated beliefs, but their actions and beliefs suggest that many are insufficiently skeptical about nondisclosed information in the absence of repeated feedback. (JEL C70, D82, D83)
The credibility revolution in economics has promoted causal identification using randomized control trials (RCT), difference-in-differences (DID), instrumental variables (IV) and regression discontinuity design (RDD). Applying multiple approaches to over 21,000 hypothesis tests published in 25 leading economics journals, we find that the extent of p-hacking and publication bias varies greatly by method. IV (and to a lesser extent DID) are particularly problematic. We find no evidence that (i) papers published in the Top 5 journals are different to others; (ii) the journal “revise and resubmit” process mitigates the problem; (iii) things are improving through time. (JEL A14, C12, C52)
We examine whether changes in perceived norm of dishonesty can offset the effects of changes in benefit from the dishonest action. We find partial support for the hypothesis in laboratory experiments on lying behavior in a cheap-talk sender-receiver game, conducted in two countries. In the experiments, we vary benefit from lying and shift senders’ norm perception by providing them information on lying from prior sessions. The findings suggest that senders adjust their perceived norm as expected, but they respond to norm in a somewhat self-serving manner. Specifically, when benefit from lying is lowered but senders are induced to believe in a higher norm of lying, they lie significantly more than when norm is not intervened. However, when benefit from lying is raised, our intervention to shift perceived norm of lying downward succeeds in altering senders’ belief as intended, but does not lower lying significantly. The results can be conceived as an indirect evidence of the challenge in curbing dishonesty by reducing private pecuniary gains in a society with a culture of dishonesty, while suggesting that even societies with history of low dishonesty may succumb to dishonesty when pecuniary incentives for dishonesty rise.
Private information is at the heart of many economic activities. For decades, economists have assumed that individuals are willing to misreport private information if this maximizes their material payoff. We combine data from 90 experimental studies in economics, psychology, and sociology, and show that, in fact, people lie surprisingly little. We then formalize a wide range of potential explanations for the observed behavior, identify testable predictions that can distinguish between the models, and conduct new experiments to do so. Our empirical evidence suggests that a preference for being seen as honest and a preference for being honest are the main motivations for truth‐telling.
We study cheating behavior in a large sample of elementary school children in the context of a creative performance task, in the presence and absence of performance incentives. Our data come from a sample of 720 elementary school children with an average age of 8, and contain rich information on a large set of correlates, such as risk and time preferences, IQ, gender and family characteristics. We document that children with higher IQ and higher socioeconomic status have a higher likelihood of cheating. We find that the presence of incentives for better performance does not increase cheating behavior. We also document an interesting interaction between altruism and incentives: altruistic students cheat significantly less in the presence of incentives.
The present paper reports the results of two experimental studies designed to examine the effects of optimism, pessimism, and mood swings on dishonest behavior. In Study 1, optimistic and pessimistic moods were exogenously induced to two classes of economics students who subsequently performed the die-under-the-cup task. Subjects experiencing an optimistic mood were found to exhibit greater dishonesty than those experiencing a pessimistic mood. In Study 2, economics students were asked, before and after taking a much-feared exam, to indicate on an optimism/pessimism mood scale how they felt about their success in it, subsequently performing the die-under-the-cup task. Dishonesty was found to be positively (negatively) correlated with post-exam optimism (pessimism) as well as with mood upswings (downswings) occurring between the post and pre-exam points of time. A side study ruled out the possibility that post-exam optimism induced a sense of entitlement which could have driven greater dishonesty.
Over the past decade, a large and growing body of experimental research has analyzed dishonest behavior. Yet the findings as to when people engage in (dis)honest behavior are to some extent unclear and even contradictory. A systematic analysis of the factors associated with dishonest behavior thus seems desirable. This meta-analysis reviews four of the most widely used experimental paradigms: sender–receiver games, die-roll tasks, coin-flip tasks, and matrix tasks. We integrate data from 565 experiments (totaling N = 44,050 choices) to address many of the ongoing debates on who behaves dishonestly and under what circumstances. Our findings show that dishonest behavior depends on both situational factors, such as reward magnitude and externalities, and personal factors, such as the participant’s gender and age. Further, laboratory studies are associated with more dishonesty than field studies, and the use of deception in experiments is associated with less dishonesty. To some extent, the different experimental paradigms come to different conclusions. For example, a comparable percentage of people lie in die-roll and matrix tasks, but in die-roll tasks liars lie to a considerably greater degree. We also find substantial evidence for publication bias in almost all measures of dishonest behavior. Future research on dishonesty would benefit from more representative participant pools and from clarifying why the different experimental paradigms yield different conclusions.
How do agency relationships affect an individual's willingness to lie for monetary advantage? Does lie aversion decline if a lie (or truth) is sent through an agent, rather than sent directly by the individual? In a recent paper, Erat (2013) shows that a significant proportion of his subjects prefer to delegate a deception decision. We present experiments designed to focus on one of several possible explanations for this intriguing behavior – that delegation reduces lie aversion. The experiments reveal that subjects are more willing to lie through a delegate than to lie directly despite controlling for potential effects of delegated decision-making on preferences over payoffs, probabilities of actions, and/or the desire to avoid taking a decision.
This paper uses laboratory experiments to directly test a central prediction of disclosure theory: that market forces can lead businesses to voluntarily provide information about the quality of their products. This theoretical prediction is based on unraveling arguments, which require that consumers hold correct beliefs about non-disclosed information. Instead, we find that receivers are insufficiently skeptical about nondisclosed information, and as a consequence, senders do not always disclose their private information. However, when subjects are informed about non-disclosed information after each round, behavior slowly converges to full unraveling. This convergence appears to be driven by an asymmetric response in receiver actions after learning that they were profitably deceived. Despite the change in receiver behavior, stated beliefs about sender strategies remain insufficiently skeptical, which suggests that while direct and immediate feedback induces equilibrium behavior, it does not reduce strategic naivete.
We examine under what conditions people provide accurate feedback to others. We use feedback regarding attractiveness, a trait people care about, and for which objective information is hard to obtain. Our results show that people avoid giving accurate face-to-face feedback to less attractive individuals, even if lying in this context comes at a monetary cost to both the person who gives the feedback and the receiver. A substantial increase of these costs does not increase the accuracy of feedback. However, when feedback is provided anonymously, the aversion to giving negative feedback is reduced.
One constraint we face as economists is not being able to observe all the relevant variables required to test our theories or make policy prescriptions. Laboratory techniques allow us to convert many variables (such as beliefs) that are unobservable in the field into observables. This article presents a survey of the literature on belief elicitation in laboratory experimental economics. We discuss several techniques available to elicit beliefs in an incentive-compatible manner and the problems involved in their use. We then look at how successful these techniques have been when employed in laboratory studies. We find that despite some problems, beliefs elicited in the laboratory are meaningful (i.e., they are generally used as the basis for behavior), and the process of eliciting beliefs seems not to be too intrusive. One hope for the future is that by eliciting beliefs, we may be able to develop better theories of belief formation.
Scientific methods of investigation offer systematic ways to gather information about the world; and in the field of psychology application of such methods should lead to a better understanding of human behavior. Instead, recent reports in psychological science have used apparently scientific methods to report strong evidence for unbelievable claims such as precognition. To try to resolve the apparent conflict between unbelievable claims and the scientific method many researchers turn to empirical replication to reveal the truth. Such an approach relies on the belief that true phenomena can be successfully demonstrated in well-designed experiments, and the ability to reliably reproduce an experimental outcome is widely considered the gold standard of scientific investigations. Unfortunately, this view is incorrect; and misunderstandings about replication contribute to the conflicts in psychological science. Because experimental effects in psychology are measured by statistics, there should almost always be some variability in the reported outcomes. An absence of such variability actually indicates that experimental replications are invalid, perhaps because of a bias to suppress contrary findings or because the experiments were run improperly. Recent investigations have demonstrated how to identify evidence of such invalid experiment sets and noted its appearance for prominent findings in experimental psychology. The present manuscript explores those investigative methods by using computer simulations to demonstrate their properties and limitations. The methods are shown to be a check on the statistical consistency of a set of experiments by comparing the reported power of the experiments with the reported frequency of statistical significance. Overall, the methods are extremely conservative about reporting inconsistency when experiments are run properly and reported fully. The manuscript also considers how to improve scientific practice to avoid inconsistency, and discusses criticisms of the investigative method.
We introduce a simple method to construct an incentive compat- ible scoring rule to elicit an agent's subjective belief about a random variable. The method does not depend on the exact form of the agent's utility function. Independent of her risk-preference, it is optimal for her to report the value that minimizes the expected value of a loss func- tion specified in the incentive scheme. Under this incentive scheme, the agent receives a fixed prize when her prediction error, defined by the relevant loss function, is smaller than a randomly generated value and earns nothing otherwise. Adjusting the loss function according to our goal for eliciting the agent's beliefs, the scoring rule can be used in a rich assortment of situations. We run experiments using our scoring rule and the quadratic scoring rule and find that our scor- ing rule performs as well as the quadratic scoring rule. In fact, our scoring rule's performance seems to improve as subjects become more familiar with it.
This paper studies risk attitudes using a large representative survey and a complementary experiment conducted with a representative subject pool in subjects' homes. Using a question asking people about their willingness to take risks “in general”, we find that gender, age, height, and parental background have an economically significant impact on willingness to take risks. The experiment confirms the behavioral validity of this measure, using paid lottery choices. Turning to other questions about risk attitudes in specific contexts, we find similar results on the determinants of risk attitudes, and also shed light on the deeper question of stability of risk attitudes across contexts. We conduct a horse race of the ability of different measures to explain risky behaviors such as holdings stocks, occupational choice, and smoking. The question about risk taking in general generates the best all-round predictor of risky behavior.
In this paper we conduct laboratory experiments to test the Crawford and Sobel [Crawford, V., Sobel, J., 1982. Strategic information transmission. Econometrica 50, 1431–1451] theory of strategic information transmission. Our experimental results strongly support the basic insight of the theory, namely, that less information is transmitted when preferences of the sender and the receiver diverge. Moreover, the average payoffs for the senders, the receivers, and the overall subject population are very close to those predicted by the most informative equilibrium. However, the evidence shows that subjects consistently overcommunicate in that the senders' messages are more informative about the true states of the world and that the receivers rely more on the senders' messages in choosing actions, compared with what the theory allows in the most informative equilibrium. To understand the overcommunication phenomenon, we use two popular approaches of bounded rationality: behavior type analysis and quantal response equilibrium, to analyze subjects' behavior in our experiment data.
This review considers several meta-regression and graphical methods that can differentiate genuine empirical effect from publication bias. Publication selection exists when editors, reviewers, or researchers have a preference for statistically significant results. Because all areas of empirical research are susceptible to publication selection, any average or tally of significant/insignificant studies is likely to be biased and potentially misleading. Meta-regression analysis can see through the murk of random sampling error and selected misspecification bias to identify the underlying statistical structures that characterize genuine empirical effect. Meta-significance testing and precision-effect testing "PET" are offered as a means to identify empirical effect beyond publication bias and are applied to four areas of empirical economics research - minimum wage effects, union-productivity effects, price  elasticities, and tests of the natural rate hypothesis. Copyright Blackwell Publishers Ltd, 2005.
Gneezy [Gneezy, U., 2005. Deception: the role of consequences. American Economic Review 95, 384-394.] recently showed that lying is costly. Using the same experimental design we test whether there is a gender difference in deception. We find that men are significantly more likely than women to lie to secure a monetary benefit.
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