Uncertainty appears to vary strongly over time, temporarily rising by up to 200% around major shocks like the Cuban Missile crisis, the assassination of JFK and 9/11. This paper offers the first structural framework to analyze uncertainty shocks. I build a model with a time varying second...

We derive the asymptotic distribution of a new backfitting procedure for estimating the closest additive approximation to a nonparametric regression function. The procedure employs a recent projection interpretation of popular kernel estimators provided by Mammen, Marron, Turlach and Wand...

We propose a new estimator for nonparametric regression based on local likelihood estimation using an estimated error score function obtained from the residuals of a preliminary nonparametric regression. We show that our estimator is asymptotically equivalent to the infeasible local maximum...

Natural capital should be preserved because it exhibits features that distinguish it from all other kinds of capital. The notorious prevalence of risk, uncertainty and ignorance makes it difficult, however, to state which parts of it should be preserved. Some forms of natural capital are more...

Volatility risk premia compensate agents for holding assets whose payoffs correlate with times of high return variation. This paper takes a structural approach to explain the cross-section of volatility risk premia of stocks using a Lucas orchard with heterogeneous beliefs, stochastic...

A central limit theorem is given for certain weighted partial sums of a covariance stationary process, assuming it is linear in martingale differences, but without any restriction on its spectrum. We apply the result to kernel nonparametric fixed-design regression, giving a single central limit...

To what extent does economic analysis of climate change depend on low-probability, high-impact events? This question has received a great deal of attention lately, with the contention increasingly made that climate damage could be so large that societal willingness to pay to avoid extreme...

This paper derives the asymptotic distribution of nonparametric neural network estimator of the Lyapunov exponent in a noisy system proposed by Nychka et al (1992) and others. Positivity of the Lyapunov exponent is an operational definition of chaos. We introduce a statistical framework for...

This paper derives the asymptotic distribution of the nonparametric neural network estimator of the Lyapunov exponent in a noisy system. Positivity of the Lyapunov exponent is an operational definition of chaos. We introduce a statistical framework for testing the chaotic hypothesis based on the...

The paper analyses the implications of landowners’ option values in land allocation and derives policy recommendations for payments for Reducing Emissions from Deforestation and Forest Degradation (REDD). Given that REDD will not represent a permanent change in the cumulative flux of carbon...