Evolutionary psychologists have suggested that confidence and conservatism promoted aggression in our ancestral past, and that this may have been an adaptive strategy given the prevailing costs and benefits of conflict. However, in modern environments, where the costs and benefits of conflict can be very different owing to the involvement of mass armies, sophisticated technology, and remote leadership, evolved tendencies toward high levels of confidence and conservatism may continue to be a contributory cause of aggression despite leading to greater costs and fewer benefits. The purpose of this paper is to test whether confidence and conservatism are indeed associated with greater levels of aggression—in an explicitly political domain. We present the results of an experiment examining people’s levels of aggression in response to hypothetical international crises (a hostage crisis, a counter-insurgency campaign, and a coup). Levels of aggression (which range from concession to negotiation to military attack) were significantly predicted by subjects’ (1) confidence that their chosen policy would succeed, (2) score on a liberal-conservative scale, (3) political party affiliation, and (4) preference for the use of military force in real-world US policy toward Iraq and Iran. We discuss the possible adaptive and maladaptive implications of confidence.
Empirical testing of competing theories lies at the heart of social science research. We demonstrate that a well-known class of statistical models, called finite mixture models, provides an effective way of rival theory testing. In the proposed framework, each observation is assumed to be generated either from a statistical model implied by one of the competing theories or more generally from a weighted combination of multiple statistical models under consideration. Researchers can then estimate the probability that a specific observation is consistent with each rival theory. By modeling this probability with covariates, one can also explore the conditions under which a particular theory applies.We discuss a principled way to identify a list of observations that are statistically significantly consistent with each theory and propose measures of the overall performance of each competing theory. We illustrate the relative advantages of our method over existing methods through empirical and simulation studies.
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