Assistant Economist

FR’s Centre for Forest Management applies a wide range of expertise to important issues concerning the resilience and value of Britain’s trees, woods and forests. As part of this centre, the Forestry Economics Research Unit within FR’s Climate Change Research Group aims to provide outstanding forestry economics research – developing the evidence base, recognised for scientific excellence, objective and authoritative advice, and valued for its effective contribution to addressing key issues of forest policy and management. We work with end users and the wider science community to ensure that research is directed to priority issues and helps inform government policy and sector practice.

The Unit currently has six team members and is involved in a wide range of interdisciplinary projects. These include forest sector modelling, agroforestry, policy nudges in forestry and agriculture, and development of a Woodland Water Code to encourage greater private sector investment in UK woodland creation for water-related benefits. We also support the core funded programmes under the Science and Innovation Strategy for GB forestry with projects such as optimal rotation length modelling and the economics of climate change adaptation and mitigation. We are looking to expand our team to be able to enhance our capacity and capability to deliver such a broad set of interesting projects. The unit is split in terms of location between Northern Research Station in Roslin and Alice Holt in Farnham.

The purpose of the role is to support the economics team on a variety of projects under the banner of economics of mitigation and adaptation to climate change. Current topics are varied and therefore the preferences of the post holder can be taken into account when allocating work.

Key projects which require additional support currently ongoing in the team are:

• Development of a Forest Sector Model (FSM) – this project looks to combine the biophysical elements of forest dynamics to economic markets to run climate scenarios, for example, to understand how the forestry sector might respond under alternative scenarios
• Developing the timber evidence base – this project proposes the development of a novel Bayesian hierarchical structural time-series (BSTS) model to forecast softwood and hardwood utilisation in the UK economy. Outputs of which will directly support sustainable forest management by improving demand projections for domestic timber, informing afforestation strategies, and enhancing resilience to supply disruptions.
• Compound risks – this project uses Bayesian Decision Theory to translate a list of risks into decision-relevant insights through a scenario-based economic optimisation framework. This enables comparison of adaptation strategies in terms of costs and benefits analysis (CBA) under climate uncertainty.
• Economics of tree pests and disease – looking at the economic impact on GB forestry of pest and disease and cost effectiveness analysis of management options.