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Financial and economic history is strewn with bubbles and crashes, booms andbusts, crises and upheavals of all sorts. Understanding the origin of theseevents is arguably one of the most important problems in economic theory. Inthis paper, we review recent efforts to include heterogeneities andinteractions in models of decision. We argue that the Random Field Ising model(RFIM) indeed provides a unifying framework to account for many collectivesocio-economic phenomena that lead to sudden ruptures and crises. We discussdifferent models that can capture potentially destabilising self-referentialfeedback loops, induced either by herding, i.e. reference to peers, ortrending, i.e. reference to the past, and account for some of the phenomenologymissing in the standard models. We discuss some empirically testablepredictions of these models, for example robust signatures of RFIM-like herdingeffects, or the logarithmic decay of spatial correlations of voting patterns.One of the most striking result, inspired by statistical physics methods, isthat Adam Smith's invisible hand can badly fail at solving simple coordinationproblems. We also insist on the issue of time-scales, that can be extremelylong in some cases, and prevent socially optimal equilibria to be reached. As atheoretical challenge, the study of so-called "detailed-balance" violatingdecision rules is needed to decide whether conclusions based on current models(that all assume detailed-balance) are indeed robust and generic.

Crises and collective socio-economic phenomena: simple models and challenges