How do we value bare, naked forestland? Timberland investment models and appraisals often use a special application of net present value (NPV) called bare land value (BLV). Also known as land expectation value (LEV) or soil expectation value (SEV), BLV uses timber prices, forest management costs and interest rates to determine the optimal economic rotation (age) for a forest. BLV remains a standard approach for maximizing forest value in short and long-term analysis.

What makes BLV useful for evaluating forestry investments? BLV helps (1) identify the optimal rotation length for a forest; (2) order the management activities associated with a forest; and (3) determine whether or not to invest in specific silvicultural activities. BLV also helps us conduct marginal analysis on short-term harvesting decisions related to price “spikes” or declines in local markets. For a forest analyst, BLV is better than a Leatherman.

BLV relies on “strong” assumptions. For example, it assumes that costs and revenues for all future rotations remain identical. BLV also assumes that the land will be reforested in perpetuity. So BLV provides a “theoretically” appropriate measure for valuing bare land managed exclusively for timber production; it represents the maximum you “would” pay to buy bare land at the beginning of a forest rotation and earn the target rate of return (represented by the discount rate) on the total investment.

In practice, the estimated BLV may not correspond to current market values for the land. Investors may have alternative uses for the land, in which case the forestry-centric BLV may not be competitive. Investors may also have different costs of capital (discount rates), which would produce different BLVs even with identical assumptions for initial costs and revenues.

 

Click here to learn about and register for “Applied Forest Finance” on March 30^th in Atlanta, Georgia. The course details necessary skills and common errors associated with the financial analysis of timberland investments and forest management decisions.