We observe that a Pigovian climate policy need not exact full payment of the social cost of carbon upon emission to yield optimal incentives. Following this insight, we propose the creation of a carbon liabilities market to address climate change. Each period, countries would be made liable for...

We propose a nouvel methodology for forecasting chaotic systems which uses information on local Lyapunov exponents (LLEs) to improve upon existing predictors by correcting for their inevitable bias. Using simulations of the Rössler, Lorenz and Chua attractors, we find that accuracy gains can be...

The siting of public facilities such as prisons or waste disposal facilities typically faces rejection by local populations (the "NIMBY" syndrome, for Not In My BackYard). These public goods exhibit a private bad aspect creating an asymmetry: all involved communities benefit from their...

Due to meteorological factors, the distribution of the environmental damage due to climate change bears no relationship to that of global emissions. We argue in favor of offsetting this discrepancy, and propose a "global insurance scheme" to be fincanced according to countries responsibility for...

Implementing a project, like a nationwide nuclear waste disposal, which benefits all involved agents but brings major costs only to the host is often problematic. In practice, revelation issues and redistributional concerns are significant obstacles to achieving stable agreements. We address...

We propose a novel methodology for forecasting chaotic systems which is based on exploiting the information conveyed by the local Lyapunov exponents of a system. This information is used to correct for the inevitable bias of most non-parametric predictors. Using simulated data, we show that...

A general framework is suggested to describe human decision making in a certain class of experiments performed in a trading laboratory. We are in particular interested in discerning between two different moods, or states of the investors, corresponding to investors using fundamental investment...

We propose a novel methodology for forecasting chaotic systems which is based on the nearest-neighbor predictor and improves upon it by incorporating local Lyapunov exponents to correct for its inevitable bias. Using simulated data, we show that gains in prediction accuracy can be substantial....

Previous research on male subjects has conjectured that subjective self-reports of health status may lead to an upward bias in the estimated effect of health on labor force participation because subjects who are out of the labor force may be more likely to understate their health status so as to...

We argue for the creation of a carbon liabilities market to address climate change. Each period, countries would be made liable for their share of responsibility in current climate damage. Because liabilities could be traded like financial debt, robustness to strategic manipulations and...