Discount rates for corporate forest valuations. Issue 3 (3rd July 2018)

• Record Type: Journal Article
• Authors: Ferguson, I.
• Is Part Of: Australian forestry. Volume 81:Issue 3(2018)
• Page Start: 142
• Page End: 147
• Publication Date: 2018-07-03
• Subjects: valuation -- discount rate -- stochastic analysis -- deterministic analysis; Forests and forestry -- Australia -- Periodicals; Forests and forestry -- Australasia -- Periodicals; 634.90994
• DOI: 10.1080/00049158.2018.1471788
• Languages: English
• ISSNs: 0004-9158

Abstract

ABSTRACT: This paper reviews and identifies the discount rates and associated provisions appropriate to corporate forest valuations using deterministic or stochastic analyses. In stochastic analyses, these provisions include the recognition of time-varying discount rates that stem from annual variation in bond rates. Four different components (the risk-free discount rate, the discount rate for debt, the discount rate for equity, and a final weighted average cost of capital (WACC)) are involved in developing final discount rates. We reject using the traditional Capital Asset Pricing Model (CAPM) analysis for want of sufficient forestry data, and use instead industry evidence, based on separate but mutually consistent paths for deterministic and stochastic analyses. Based on a hypothetical major company, with substantial investment in more than 40 000 ha of radiata pine plantations, and an equity to debt ratio around 60:40, the empirical evidence available for the four components indicated a WACC of 7.4% y −1 was appropriate for deterministic analyses. For stochastic analyses, an initial WACC of 5.0% y −1 was deemed appropriate, subject to random annual variation with a standard deviation of ±2.63% y −1 . These estimates are illustrative and are not intended to be specific to a particular company. Safety margins may still have to be applied to account for unpredictable events. Companies and independent valuers need to place more emphasis on estimating the components appropriate to their own setting, rather than relying on the CAPM approach.