a r t i c l e i n f o a b s t r a c t Social scientists often estimate models from correlational data, where the independent variable has not been exogenously manipulated; they also make implicit or explicit causal claims based on these models. When can these claims be made? We answer this question by first discussing design and estimation conditions under which model estimates can be interpreted, using the randomized experiment as the gold standard. We show how endogeneity -which includes omitted variables, omitted selection, simultaneity, common-method variance, and measurement error -renders estimates causally uninterpretable. Second, we present methods that allow researchers to test causal claims in situations where randomization is not possible or when causal interpretation could be confounded; these methods include fixed-effects panel, sample selection, instrumental variable, regression discontinuity, and difference-in-differences models. Third, we take stock of the methodological rigor with which causal claims are being made in a social sciences discipline by reviewing a representative sample of 110 articles on leadership published in the previous 10 years in top-tier journals. Our key finding is that researchers fail to address at least 66% and up to 90% of design and estimation conditions that make causal claims invalid. We conclude by offering 10 suggestions on how to improve non-experimental research.

We used incentivized experimental games to manipulate leader power-the number of followers and the discretion leaders had to enforce their will. Leaders had complete autonomy in deciding payouts to themselves and their followers. Although leaders could make prosocial decisions to benefit the public good they could also abuse their power by invoking antisocial decisions, which reduced the total payouts to the group but increased leader's earnings. In Study 1 (N = 478), we found that both amount of followers and discretionary choices independently predicted leader corruption. In Study 2 (N = 240), we examined how power and individual differences (e.g., personality, hormones) affected leader corruption over time; power interacted with testosterone in predicting corruption, which was highest when leader power and baseline testosterone were both high. Honesty predicted initial level of leader antisocial decisions; however, honesty did not shield leaders from the corruptive effect of power.

Social competition is a fundamental mechanism of evolution and plays a central role in structuring individual interactions and communities. Little is known about the factors that affect individuals' competitive success, particularly in humans. Key factors might include stress, a major evolutionary pressure that can affect the establishment of social hierarchies in animals, and individuals' trait anxiety, which largely determines susceptibility to stress and constitutes an important determinant of differences in competitive outcomes. Using an economic-choice experiment to assess competitive self-confidence in 229 human subjects we found that, whereas competitive self-confidence is unaffected by an individual's anxiety level in control conditions, exposure to the Trier social stress test for groups drives the behavior of individuals apart: low-anxiety individuals become overconfident, and high-anxiety individuals become underconfident. Cortisol responses to stress were found to relate to self-confidence, with the direction of the effects depending on trait anxiety. Our findings identify stress as a major regulator of individuals' competitiveness, affecting self-confidence in opposite directions in high and low anxious individuals. Therefore, our findings imply that stress may provide a new channel for generating social and economic inequality and, thus, not only be a consequence, but also a cause of inequality through its impact on competitive self-confidence and decision making in financially-relevant situations.

Most leadership and management researchers ignore one key design and estimation problem rendering parameter estimates uninterpretable: Endogeneity. We discuss the problem of endogeneity in depth and explain conditions that engender it using examples grounded in the leadership literature. We show how consistent causal estimates can be derived from the randomized experiment, where endogeneity is eliminated by experimental design. We then review the reasons why estimates may become biased (i.e., inconsistent) in non-experimental designs and present a number of useful remedies for examining causal relations with nonexperimental data. We write in intuitive terms using nontechnical language to make this chapter accessible to a large audience.

Decision-making processes can be modulated by stress, and the time elapsed from stress induction seems to be a crucial factor in determining the direction of the effects. Although current approaches consider the first post-stress hour a uniform period, the dynamic pattern of activation of the physiological stress systems (i.e., the sympathetic nervous system and hypothalamic-pituitary-adrenal axis) suggests that its neurobehavioural impact might be heterogeneous. Here, we evaluate economic risk preferences on the gain domain (i.e., risk aversion) at three time points following exposure to psychosocial stress (immediately after, and 20 and 45 min from onset). Using lottery games, we examine decisions at both the individual and social levels. We find that risk aversion shows a time-dependent change across the first post-stress hour, evolving from less risk aversion shortly after stress to more risk averse behaviour at the last testing time. When risk implied an antisocial outcome to a third party, stressed individuals showed less regard for this person in their decisions. Participants' cortisol levels explained their behaviour in the risk, but not the antisocial, game. Our findings reveal differential stress effects in self-and other-regarding decision-making and highlight the multidimensional nature of the immediate aftermath of stress for cognition.

In strategic prospective, scenario thinking and negotiation processes, analysis of the actor game plays an important role. Such an analysis endeavours to rank the positions of stakeholders on many strategic issues, to assess potential convergences and divergences, and to anticipate coalitions and conflicts. Many models and tools that have been proposed and used for these purposes rest on matrix analysis, game theory and simulation. The present paper examines two of them: Mactor, a model of scenario planning, and a negotiation model derived from a political decision model based on game theory. This paper detects the flaws, similarities and differences of these approaches. Based on this comparison, a new model is proposed, with the advantages of both, but without their detected flaws. The model has been applied to an assessment of the public WLAN landscape. The paper sketches the first results which now should be integrated into a more sophisticated scenario analysis. RÉSUMÉ. Dans les approches prospectivistes et autres processus de négociation, l'analyse du jeu des acteurs joue un rôle important. Ce type d'analyse étudie la position des acteurs, évalue leurs divergences et convergences ; on essaie notamment d'anticiper les conflits et les coalitions. Plusieurs modèles et outils ont été proposés et utilisés avec plus ou moins desuccès. Cet article examine deux d'entre eux : l'un (Mactor) basé sur une analyse matricielle et destiné à s'intégrer dans une approche par scénario, l'autre, une déclinaison de modèles de négociation basés sur la théorie des jeux. Cet article détecte les similarités, les points forts et les déficiences de ces deux approches. Il propose ensuite un modèle fédérateur, avec les avantages des deux approches mais sans leurs déficiences constatées. Ce modèle a été appliqué à une évaluation du paysage technologique des réseaux publics sans fil (WiFi). Les premiers résultats de cette évaluation sont communiqués ; ils constituent la première partie d'une démarche plus ambitieuse de construction de scénarios dans ce contexte.

Although the inhibitory control of aggression by the prefrontal cortex (PFC) is the cornerstone of current theories of aggression control, a number of human and laboratory studies showed that the execution of aggression increases PFC activity; moreover, enhanced activation was observed in aggression-related psychopathologies and laboratory models of abnormal aggression. Here, we investigated these apparently contradictory findings in the post-weaning social isolation paradigm (PWSI), an established laboratory model of abnormal aggression. When studied in the resident-intruder test as adults, rats submitted to PWSI showed increased attack counts, increased share of bites directed towards vulnerable body parts of opponents (head, throat, and belly) and reduced social signaling of attacks. These deviations from species-typical behavioral characteristics were associated with a specific reduction in the thickness of the right medial PFC (mPFC), a bilateral decrease in dendritic and glial density, and reduced vascularization on the right-hand side of the mPFC. Thus, the early stressor interfered with mPFC development. Despite these structural deficits, aggressive encounters enhanced the activation of the mPFC in PWSI rats as compared to controls. A voxel-like functional analysis revealed that overactivation was restricted to a circumscribed sub-region, which contributed to the activation of hypothalamic centers involved in the initiation of biting attacks as shown by structural equation modeling. These findings demonstrate that structural alterations and functional hyperactivity can coexist in the mPFC of rats exposed to early stressors, and suggest that the role of the mPFC in aggression control is more complex than suggested by the inhibitory control theory.

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