Pollution control with uncertain stock dynamics: When, and how, to be precautious

How uncertain do we need to be ? ?

Expert probability forecasts can be useful for decision making (§1). But levels of uncertainty escalate: however the forecaster expresses the uncertainty that attaches to a forecast, there are good reasons for her to express a further level of uncertainty, in the shape of either imprecision or higher order uncertainty (§2). Bayesian epistemology provides the means to halt this escalator, by tyi...

Foundations for Learning How to Invest when Returns are Uncertain

Most asset returns are uncertain, not merely risky: investors do not know the probabilities of different possible future returns. A large body of evidence suggests that investors are averse to uncertainty, as well as to risk. This paper builds up an axiomatic foundation for the dynamic portfolio and consumption choices of an uncertainty-averse (as well as risk-averse) investor who tries to lear...

Pollution Control in an Uncertain Environment

When and How to Control Consumption

Pollution control: targets and dynamics

In this paper I study the e¤ects of environmental regulation which establishes upper and lower binding targets to pollution emissions. Essentially, I deal with the properties of a stochastic model of pollution control in continuous-time under emission targets and uncertainty, emphasizing dynamic nonlinearities. Inside the targets pollution behaves as if it were freely ‡oating until it hits one ...