Alexander Vostroknutov

Norms Make Preferences Social

We explore the idea that prosocial behavior in experimental games is driven by social norms imported into the laboratory. Under this view, differences in behavior across subjects is driven by heterogeneity in sensitivity to social norms. We introduce an incentivized method of eliciting individual norm-sensitivity, and we show how it relates to play in public goods, trust, dictator and ultimatum games. We show how our observations can be rationalized in a stylized model of norm-dependent preferences under reasonable assumptions about the nature of social norms. Then we directly elicit norms in these games to test the robustness of our interpretation.

Causes of social reward differences encoded in human brain.

Rewards may be due to skill, effort, and luck, and the social perception of inequality in rewards among individuals may depend on what produced the inequality. Rewards due to skill produce a conflict: higher outcomes of others in this case are considered deserved, and this counters incentives to reduce inequality. However, they also signal superior skill and for this reason induce strong negative affect in those who perform less, which increases the incentive to reduce the inequality. The neurobiological mechanisms underlying evaluation of rewards due to skill, effort, and luck are still unknown. We scanned brain activity of subjects as they perceived monetary rewards caused by skill, effort, or luck. Subjects could subtract from others. Subtraction was larger, everything else being equal, in luck but increased more as the difference in outcomes grew in skill. Similarly, reward-related activation in medial orbitofrontal cortex was more sensitive to the difference in relative outcomes in skill trials. Orbitofrontal activation reflecting comparative reward advantage predicted by how much subjects reduced unfavorable reward inequality later on in the trial. Thus medial orbitofrontal cortex activity reflects the causes of reward and predicts actions that reduce inequality.

The Social and Ecological Determinants of Common Pool Resource Sustainability

We study a dynamic common pool resource game in which current resource stock depends on resource extraction in the previous period. Our model shows that for a sufficiently high regrowth rate, there is no commons dilemma: the resource will be preserved indefinitely in equilibrium. Lower growth rates lead to depletion. Laboratory tests of the model indicate that favorable ecological characteristics are necessary but insufficient to encourage effective CPR governance. Before the game, we elicit individual willingness to follow a costly rule. Only the presence of enough rule-followers preserves the resource given favorable ecological conditions.

Experience and Abstract Reasoning in Learning Backward Induction

Backward induction is a benchmark of game theoretic rationality, yet surprisingly little is known as to how humans discover and initially learn to apply this abstract solution concept in experimental settings. We use behavioral and functional magnetic resonance imaging (fMRI) data to study the way in which subjects playing in a sequential game of perfect information learn the optimal backward induction strategy for the game. Experimental data from our two studies support two main findings: First, subjects converge to a common process of recursive inference similar to the backward induction procedure for solving the game. The process is recursive because earlier insights and conclusions are used as inputs in later steps of the inference. This process is matched by a similar pattern in brain activation, which also proceeds backward, following the prediction error: brain activity initially codes the responses to losses in final positions; in later trials this activity shifts to the starting position. Second, the learning process is not exclusively cognitive, but instead combines experience-based learning and abstract reasoning. Critical experiences leading to the adoption of an improved solution strategy appear to be stimulated by brain activity in the reward system. This indicates that the negative affect induced by initial failures facilitates the switch to a different method of solving the problem. Abstract reasoning is combined with this response, and is expressed by activation in the ventrolateral prefrontal cortex. Differences in brain activation match differences in performance between subjects who show different learning speeds.

Growth and Inequality in Public Good Games

In a novel experimental design we study dynamic public good games in which wealth is allowed to accumulate. More precisely each agents income at the end of a period serves as her endowment in the following period. In this setting growth and inequality arise endogenously allowing us to address new questions regarding their interplay and effect on cooperation levels. We find that average cooperation levels in this setting are high (between 20-60% of endowments) and that amounts contributed do not decline over time. Introducing the possibility of punishment leads to lower group income, but less inequality within groups. In both treatments (with and w/o punishment) inequality and group income are positively correlated for poor groups (with below median income), but negatively correlated for rich groups (with above median income). There is very strong path dependence: inequality in early periods is strongly negatively correlated with group income in later periods. These results give new insights into why people cooperate and should make us rethink previous results from the literature on repeated public good games regarding the decay of cooperation in the absence of punishment.

Manipulation of Pro-Sociality and Rule-Following with Non-invasive Brain Stimulation

Decisions are often governed by rules on adequate social behaviour. Recent research suggests that the right lateral prefrontal cortex (rLPFC) is involved in the implementation of internal fairness rules (norms), by controlling the impulse to act selfishly. A drawback of these studies is that the assumed norms and impulses have to be deduced from behaviour and that norm-following and pro-sociality are indistinguishable. Here, we directly confronted participants with a rule that demanded to make advantageous or disadvantageous monetary allocations for themselves or another person. To disentangle its functional role in rule-following and pro-sociality, we divergently manipulated the rLPFC by applying cathodal or anodal transcranial direct current stimulation (tDCS). Cathodal tDCS increased participants’ rule-following, even of rules that demanded to lose money or hurt another person financially. In contrast, anodal tDCS led participants to specifically violate more often those rules that were at odds with what participants chose freely. Brain stimulation over the rLPFC thus did not simply increase or decrease selfishness. Instead, by disentangling rule-following and pro-sociality, our results point to a broader role of the rLPFC in integrating the costs and benefits of rules in order to align decisions with internal goals, ultimately enabling to flexibly adapt social behaviour.

The Role of Intelligence in Social Learning

Studies in cultural evolution have uncovered many types of social learning strategies that are adaptive in certain environments. The efficiency of these strategies also depends on the individual characteristics of both the observer and the demonstrator. We investigate the relationship between intelligence and the ways social and individual information is utilised to make decisions in an uncertain environment. We measure fluid intelligence and study experimentally how individuals learn from observing the choices of a demonstrator in a 2-armed bandit problem with changing probabilities of a reward. Participants observe a demonstrator with high or low fluid intelligence. In some treatments they are aware of the intelligence score of the demonstrator and in others they are not. Low fluid intelligence individuals imitate the demonstrator more when her fluid intelligence is known than when it is not. Conversely, individuals with high fluid intelligence adjust their use of social information, as the observed behaviour changes, independently of the knowledge of the intelligence of the demonstrator. We provide evidence that intelligence determines how social and individual information is integrated in order to make choices in a changing uncertain environment.

Observational Learning and Intelligence

We study experimentally how individuals learn from observing the choices of others in a non-stationary stochastic environment. The imitation choices of participants with low score in an intelligence test are driven solely by the value of imitation. High intelligence score participants, in addition, use choices of others to better understand the environment. They imitate more when others choices are stable, which makes them more optimal than low score participants. The knowledge that the observed other has high intelligence score affects behavior of only low score participants. Overall, intelligence predicts the usage of simple or sophisticated observational learning strategy.

Dynamic Regret Avoidance

We experimentally explore and structurally estimate the decision to sell a stock in a setting similar to a financial market in order to provide an insight on how regret avoidance shapes decision making. We exploit the dynamic nature of the environment to study the avoidance of not only past regret, as is common in the literature, but also future regret, which is defined as the possible experience of regret in the future if an irreversible action has been taken today. In the experiment participants observe a stock price changing over time and decide when to sell it. Before the market begins, participants know whether they will observe the future prices after they sell the stock or not. We find that this information clearly affects the decision to sell: participants with no future information are affected only by past regret, while, if future prices are available, they also demonstrate future regret avoidance. Estimation of a structural dynamic discrete choice model shows that the two types of regret are not complementary: either past or expected future regret dominates the decision to sell depending on which one is larger. JEL classifications: C91, C57, C61, D03, G02In a stock market experiment we examine how regret avoidance influences the decision to sell an asset while its price changes over time. Participants know beforehand whether they will observe the future prices after they sell the asset or not. Without future prices participants are affected only by regret about previously observed high prices (past regret), but, when future prices are available, they also avoid regret about expected after-sale high prices (future regret). Moreover, as the relative sizes of past and future regret change, participants dynamically switch between them. This demonstrates how multiple reference points dynamically influence sales.