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.

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.

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.