Leveraging Landscape Change: Instrument design for supporting the evolution of new natural resource industry niches

This paper outlines how resource degradation in Australia could be reversed with innovative investment approaches that compensate for the main impediments to beneficial landscape change. We argue that the existing suite of policy responses is incomplete and there are benefits to be had by introducing some new approaches for encouraging innovative and creative, appropriate landscape change. We discuss two examples that address the need for instruments that encourage the evolution of new natural resource industry niches: 1. the proposal advanced by the Allen Consulting Group in its recommendations to the Business Leaders Roundtable in 2001 on options for leveraging private investment entitled Repairing the Country 2. a pilot project that is being undertaken by Greening Australia and the CSIRO with funding provided under the Market Based Instruments Program of the National Action Plan on Salinty and Water Quality. The paper concludes with a comparison of existing instruments and their usefulness.Environmental Economics and Policy, Research Methods/ Statistical Methods, Q28, D7,

Cluster evolution in steady-state two-phase flow in porous media

We report numerical studies of the cluster development of two-phase flow in a steady-state environment of porous media. This is done by including biperiodic boundary conditions in a two-dimensional flow simulator. Initial transients of wetting and non-wetting phases that evolve before steady-state has occurred, undergo a cross-over where every initial patterns are broken up. For flow dominated by capillary effects with capillary numbers in order of $10^{-5}$, we find that around a critical saturation of non-wetting fluid the non-wetting clusters of size $s$ have a power-law distribution $n_s \sim s^{-\tau}$ with the exponent $\tau = 1.92 \pm 0.04$ for large clusters. This is a lower value than the result for ordinary percolation. We also present scaling relation and time evolution of the structure and global pressure.Comment: 12 pages, 11 figures. Minor corrections. Accepted for publication in Phys. Rev.

Sigma Point Filters For Dynamic Nonlinear Regime Switching Models

In this paper we take three well known Sigma Point Filters, namely the Unscented Kalman Filter, the Divided Difference Filter, and the Cubature Kalman Filter, and extend them to allow for a very general class of dynamic nonlinear regime switching models. Using both a Monte Carlo study and real data, we investigate the properties of our proposed filters by using a regime switching DSGE model solved using nonlinear methods. We find that the proposed filters perform well. They are both fast and reasonably accurate, and as a result they will provide practitioners with a convenient alternative to Sequential Monte Carlo methods. We also investigate the concept of observability and its implications in the context of the nonlinear filters developed and propose some heuristics. Finally, we provide in the RISE toolbox, the codes implementing these three novel filters