Resource production under uncertainty: a stochastic control approach to timber harvest scheduling

Most empirical natural resource management problems are intertemporal optimization problems under uncertainty. The Linear-Quadratic-Gaussian (LQG) method derives an approximate stochastic solution to such problems. The error in modeling resource dynamics and error in observing resource stocks are in...

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Bibliographic Details
Published in:American journal of agricultural economics 1980-08, Vol.62 (3), p.499-507
Main Authors: Dixon, B.L, Howitt, R.E
Format: Article
Language:English
Subjects:
Cost estimates
Cost functions
Determinism
Forest resources
National forests
Natural resource management
Objective functions
resource management
Resource stocks
Scheduling
stochastic optimal control
Timber
timber harvest scheduling
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Summary:Most empirical natural resource management problems are intertemporal optimization problems under uncertainty. The Linear-Quadratic-Gaussian (LQG) method derives an approximate stochastic solution to such problems. The error in modeling resource dynamics and error in observing resource stocks are incorporated explicitly into the LQG problem solution. The LQG is outlined briefly and applied to the harvest-scheduling problem on the Stanislaus National Forest. The importance of knowing management preferences precisely is shown by stochastic simulations. In particular, harvest levels and the cost of a given source of uncertainty are shown to be quite sensitive to the objective function specification.
ISSN:0002-9092
1467-8276
DOI:10.2307/1240204