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GUIDELINES for . . .
Spacer graphic Developing Stand Density Management Regimes

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Conclusions and recommendations

      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.

Long-run real log price increases

      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.

Long-run real lumber and chip prices

      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)


    Spacer graphic Lumber ($/MBF) Wood chips
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    Species 2x4 2x6 2x8 2x10 ($/BDU)

    Coastal Douglas-fir 455 460 455 560 110
    Lodgepole pine 380 369 376 452 110
    Western hemlock 406 406 414 491 110
    Sitka spruce 380 369 376 452 110
    Western redcedar 482 482 583 583 15
    White spruce 380 369 376 452 110
    Interior Douglas-fir 426 430 439 554 110

    Source: Stone et al. 1996.

Real per annum price increases - a word of caution

      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.

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    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%.


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Copyright 1999 Province of British Columbia
Forest Practices Branch
BC Ministry of Forests
This page was last updated January 1999

Comments to: Tim Ebata <Tim.Ebata@gems8.gov.bc.ca>