|GUIDELINES for||. . .|
|Developing Stand Density Management Regimes|
Time in and of itself has no effect on prices, and past prices do not dictate what future prices will be. Market supply and demand forces, which change over time, cause prices to change. Use of simple trend models to predict future prices assumes that forces of supply and demand which caused the past price changes are closely correlated with time and that this correlation will continue into the future. This assumption is simplistic, and warrants caution in the use of models based on similar logic.
Given the factors that mitigate against real price increases, it is appropriate to select a conservative estimate of future real price increases. The estimates presented in Table A1-1 are examples of those typical within the range of most estimates. They are not unreasonable, especially if limited to the 50 year period shown.
The real lumber and wood chip prices presented in Table A1-2 may provide reasonable long-run estimates (Stone et al. 1996). The long-run real price of 2x4 lumber for each species is the average for the periods studied, while the price for other dimensions is a function of the 2x4 price and the average price ratio of dimension lumber to 2x4 lumber.
Table A1-2. Default lumber and wood chip prices used in the TIPSY ECONOMIST (constant 1995 dollars)
Given the lack of any clear trend in past real lumber prices (as indicated in Figure A1-2), and the likelihood of only modest real price increases for logs in the future, caution is warranted in making future value assumptions when evaluating the economic efficiency of silviculture investments. For example, Figure A1-9 illustrates the cumulative effect of annual real price increases of 1%, 2%, 3% and 4%. If these annual price increases were compounded over a period of 75 years, as they might be in an analysis of juvenile spacing for instance, the resulting cumulative increase in timber value would be 111%, 342%, 818% and 1795%, respectively.
Figure A1-9. Cumulative real price increase resulting from 1%, 2%, 3% and 4% annual real price increases.
The significance of these extremely high future values is considerable in the calculation of NPV or site value of a stand density management investment analysis.
The compounding effect of an assumed annual price increase can be reduced by limiting the period during which the compounding takes place. For example, an assumption of a 1% per annum real price increase over the first 25 years with no real price increase thereafter results in a cumulative real price increase of only 28%.
Copyright 1999 Province of British Columbia