We investigate how key features associated with the Proof-of-Work consensus mechanism of Bitcoin (commonly referred to as mining) affect pricing. In a controlled laboratory experiment, we observe that price bubble formation can be attributed to mining. Moreover, overpricing is more pronounced if the mining capacity is centralized to a small group of individuals. The order book data reveal that miners seem to play a crucial role in bubble formation. Further probing the mechanism in a second study, we find that both mining costs and decisions jointly with the sluggish rate of supply of the asset contribute to the bubble formation. Our results demonstrate that erratic pricing is an inherent feature of cryptocurrencies based on a mining protocol, thus, seriously limiting any prospects for such assets becoming a medium of exchange.

The economics literature has increasingly been studying how intelligence relates to economic decision-making. This has developed a large literature that aims to understand how cognitive abilities and processes relate to both individual decision-making and strategic interactions. Such studies in the economics literature have predominantly used pattern recognition style tests like the Raven test and measures of cognitive reflection, namely the Cognitive Reflection Test. The literature has uncovered some consistent results, for example, intelligence allows for more patient attitudes and is related to behavior closer to equilibrium play in strategic interactions. There has so far been some mixed evidence in studies that link intelligence with biased decision-making. Meanwhile, there is an ongoing lively debate on how intelligence influences risk attitudes. A theme that appears to resonate in several studies is the link between cognitive ability and error-prone behavior. The key studies across these topics are reviewed and some interesting future avenues for research are outlined.

How does the information on players’ intelligence affect strategic behavior? Game theory, based on the assumption of common knowledge of rationality, does not provide useful predictions. We experimentally show that in the Prisoners’ Dilemma disclosure hampers cooperation; higher intelligence players trust their partners less when playing against someone of lower ability. Similarly, in the Battle of Sexes with low payoff inequality, disclosure disrupts coordination, as higher intelligence players try to force their most preferred outcome. Instead, with higher payoff inequality, behaviour changes and higher intelligence players concede. We analyse the reasons for these patterns of behaviour.

In recent years, there has been growing interest in capturing, manipulating, and analyzing the effects of decision-making processes that underlie economic choice. This editorial discusses these recent developments by contextualizing the six contributions to the special issue “Cognition and Economic Behavior” within the broader scope of the existing literature.

The frustration-aggression hypothesis posits that anger affects economic behaviour essentially by temporally changing individual social preferences and specifically attitudes towards punishment. Here, we test a different channel in an experiment where we externally induce anger to a subgroup of participants (following a standard procedure that we verify by using a novel method of textual analysis). We show that anger can impair the capacity to think strategically in a beauty-contest game, in a pre-registered experiment. Angry participants choose numbers further away from the best response level and earn significantly lower profits. Using a finite mixture model, we show that anger increases the number of level-zero players by 9 percentage points, a percentage increase of more than 30%. Furthermore, with a second pre-registered experiment, we show that this effect is not common to all negative emotions. Sad participants do not play significantly further away from the best response level than the control group and sadness does not lead to more level-zero play.

We study how strategic interaction and cooperation are affected by the heterogeneity of cognitive skills of groups of players, over consecutive plays of repeated games with randomly matched opponents using Prisoner's Dilemma as stage game. We observe overall higher cooperation rates and average final payoffs in integrated treatment groups -- where subjects of different IQ levels interact together-- than in separated treatment groups. Lower IQ subjects are better off and higher IQ subjects are worse off in integrated groups than in separated groups.

Higher IQ subjects adopt harsher strategies when they are pooled with lower IQ subjects than when they play separately. We demonstrate that this outcome should be expected in learning and evolutionary models where higher intelligence subjects exhibit lower frequency of  errors in the implementation of strategies. Estimations of errors and strategies in our experimental data are consistent with the model's assumptions and predictions.

We present a new and simple mechanism for repeated public good environments. In the Conditional Contribution Mechanism (CCM), agents send two messages of the form, "I am willing to contribute x units to the public good if in total y units are contributed." This mechanism offers agents risk-free strategies, which we call unexploitable. Our main theorem states that all outcomes of the CCM will eventually be Pareto efficient if agents choose unexploitable better responses. We conduct a laboratory experiment to investigate whether observed behavior is consistent with this prediction. In the complete information case we find that indeed almost 80% of outcomes are Pareto optimal. Furthermore, in comparison to the Voluntary Contribution Mechanism, the CCM leads to significantly higher contribution rates. Even under incomplete information, contributions are fairly high and do not deteriorate over time, although surprisingly the VCM does equally well in this case. Theoretically, allowing agents to send two messages helps them ensure the status-quo and at the same time offer higher contribution levels. In a further treatment, where we allow agents to send only one message, we find that total contributions are consistently lower than the CCM in early periods but are similar in later periods.

I study the relationship between self-declared trust attitudes - using a well-recognised and established personality questionnaire - and trust choices in an induced infinitely repeated trust game. I find that self-reported trust measures are significantly related with trust choices as long as trust is part of equilibrium strategies. I find that questions regarding others' intentions is a missing component in previous work that studies self-reports of trust. An important aspect of the design is that first movers are not privy to the choices made by their partners. This design feature, coupled with an uncertainty element introduced in determining the first mover's final payoff, allows me to analyse how first movers react to bad outcomes. Trusting individuals are more likely to give the benefit of doubt to others. Analysis of the incentivised subjective beliefs reveals that the effect of personality traits on trust choices is not through the formation of beliefs.

We test whether the binary lottery procedure makes participants behave as if they are risk neutral in the Holt and Laury (2002) and Eckel and Grossman (2002) tasks. Depending on the task, we find that less than half of the participants behave as if risk neutral. In fact, when we compare the distribution of choices, we find no significant difference to standard experiments that did not use the binary lottery procedure. Using a structural model we find modest evidence that the binary lottery procedure might move participants at least slightly towards risk neutrality.

Intelligence and personality significantly affect outcomes of individuals. We study how these traits affect the outcome of groups, looking specifically at repeated interactions providing opportunity for profitable cooperation. Our experimental method creates two groups of subjects with different levels of certain traits, such as higher or lower levels of Intelligence, Conscientiousness and Agreeableness, and are very similar otherwise. We find that Intelligence has a large and positive long-run effect on cooperative behaviour. The effect is strong when at the equilibrium of the repeated game there is a trade-off between short-run gains and long-run losses. Initially similar, cooperation rates for groups with different intelligence levels diverge, declining in groups of lower intelligence, and increasing to reach almost full cooperation levels in groups of higher intelligence. Cooperation levels of more intelligent subjects are not unconditional; they are low when continuation probability are low. Personality traits have a natural, significant but transitory effect on cooperation rates.

Bayesian updating is the dominant theory of learning. However, the theory is silent about how individuals react to events that were previously unforeseen. We study how decision makers update their beliefs if unforeseen events materialize, and under which conditions they revise their views about previously observed relationships.  We base our analysis on the framework of "reverse Bayesianism", under which the relative likelihoods of prior beliefs remain unchanged after an unforeseen event materializes. We find that participants do not systematically deviate from reverse Bayesianism when the unforeseen changes result in a new world that contains elements of the old world. In contrast, if a regime change is possible, decision makers eventually overhaul their model of the old world in favor of a completely different view of uncertainty.

Although in the lab we often assume a deterministic relationship between contributions to public goods and their returns, in real life this relationship is often uncertain: consider corruption or inefficiencies in governments, or areas where our knowledge is limited such as climate change mitigation. Rational individuals may change their contributions to respond to this uncertainty, but we may also observe a reduction in contributions if people take advantage of the plausible deniability about one's actions that this uncertainty creates. The reduction of prosocial behaviour in the presence of  plausible deniability was documented in Dana et al. (2007) and has since been widely replicated in two-person non-strategic settings. We test whether people exploit uncertainty in public good games (PGG) by using it as an excuse to free-ride. In two online studies that entail 5 between-subjects treatments, we varied whether the marginal per capita returns (MPCR) were certain or uncertain, and whether this uncertainty could give participants plausible deniability for their low or zero contributions. We found no change in free-riding or average contributions across treatments, suggesting that cooperation under uncertainty is accurately captured by the standard PGGs with certain MPCR, and that uncertainty need not hamper cooperation in social dilemmas.

We model personality as a type of skill that implies different personalities will be better suited for different jobs, i.e. an extravert being better at being a salesperson or an introvert being better suited to be a librarian. The literature has traditionally considered personality to be a single point measure. When thinking of personality as a skill, single point measures would make it difficult for individuals to perform jobs that are not their ideal ones. For this reason, we propose that personality can be better understood as a distribution rather than a single point. This implies that individuals are able to perform jobs that are not their ideal ones with some non-zero level efficiency. We implement this model and run an agent-based simulation to study personality trait variation - in terms of different ideal jobs according to personality types - and its implications on society's welfare. Our agent-based simulation results show that population personality compositions are adaptive on the job distribution. Additionally, simulations indicate that precise job match screening is beneficial not only for society's welfare but also for subjective well-being. In utilising the model of personality as a distribution of skills across different jobs, we are also able to study the effect of individuals being more or less specialised at their ideal job. We can do this by agents enjoying tighter or wider personality distributions. These simulations indicate that there will always be the need for some individuals of lower specialisation, which to some extent confirms the conventional wisdom of the need for a 'jack of all trades'.