We develop a model of political cycles driven by time-varying risk aversion. Heterogeneous agents make two choices: whether to work in the public or private sector and which of two political parties to vote for. The model implies that when risk aversion is high, agents are more likely to elect the party promising more fiscal redistribution.
Imagine you are lying in bed at 6:30 in the morning and you hear the newspaper land at your front door. You get up and look at the front page and see the headline: “Bank Run Today, see page 2.”
Do patients follow prescribed medical treatment more closely when a pharmacy opens in their neighborhood? How do hospitals respond to performance-based incentives to improve the quality of care?
Richard Evans is a Senior Fellow in Computational Social Science at the University of Chicago, and Fellow here at the institute.
A recent wave of research has demonstrated the existence of generic Early Warning Signals (EWS’s) that help predict a large class of abrupt changes in the state of ecological systems -- e.g. “tipping points.” Examples range from experimental laboratory systems of living organisms at tiny scales such as microbes up to ecosystems at the scale of lakes, rangelands, marine systems, or coral reefs.