An agent-based model of centralized institutions, social network technology, and revolution.

This paper sheds light on the general mechanisms underlying large-scale social and institutional change. We employ an agent-based model to test the impact of authority centralization and social network technology on preference falsification and institutional change. We find that preference falsification is increasing with centralization and decreasing with social network range. This leads to greater cascades of preference revelation and thus more institutional change in highly centralized societies and this effect is exacerbated at greater social network ranges. An empirical analysis confirms the connections that we find between institutional centralization, social radius, preference falsification, and institutional change.

Endogenous Group Formation via Unproductive Costs.

Sacrifice is widely believed to enhance cooperation in churches, communes, gangs, clans, military units, and many other groups. We find that sacrifice can also work in the lab, apart from special ideologies, identities, or interactions. Our subjects play a modified VCM game-one in which they can voluntarily join groups that provide reduced rates of return on private investment. This leads to both endogenous sorting (because free-riders tend to reject the reduced-rate option) and substitution (because reduced private productivity favours increased club involvement). Seemingly unproductive costs thus serve to screen out free-riders, attract conditional cooperators, boost club production, and increase member welfare. The sacrifice mechanism is simple and particularly useful where monitoring difficulties impede punishment, exclusion, fees, and other more standard solutions.

Environmental management with knowledge of uncertainty: a methylmercury case study.

In Oregon's Willamette River Basin, health advisories currently limit consumption of fish that have accumulated methylmercury to levels posing a potential health risk for humans. Under the Clean Water Act, these advisories represent an impairment of the beneficial use of fish consumption and create the requirement for a mercury total maximum daily load. A percent load reduction for total mercury was determined by comparing mercury levels in surface water to a water column guidance value linked to the protection of specified beneficial uses. In this case study, we discuss how probabilistic (Monte Carlo) methods were used to quantify uncertainty in the water column guidance value, how they provided decision makers with knowledge as to the probability of any given water column guidance value affording human health protection for methylmercury, and how this knowledge affected decisions as to a mercury load reduction for the Willamette River Basin. Through consultations with stakeholders, a water column guidance value of 0.92 ng/L (a median for higher trophic level fish) was chosen from among a suite of values of differing probabilities. The selected water column guidance value, when compared with ambient total mercury levels, indicated that a 50% probability of achieving the tissue criterion would require a load reduction of about 26%. Having and working with an explicit knowledge of uncertainty was not easy for many decision makers or stakeholders. However, such knowledge gave them more informed choices, a better understanding of what a specific choice of water column guidance value could mean in terms of achieving protectiveness, and led to a lower load reduction than suggested by a purely deterministic analysis. Nonetheless, more attention must be given to developing management, communication, and regulatory frameworks that can effectively use the greater knowledge of uncertainty afforded by probabilistic methods.