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Dual Discounting in Renewable Resource Planning under Risk

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Abstract

Renewable resource planning and management projects entail evaluating economic and ecological criteria in the long term. During the past decade or so, dual discounting––ecological criteria discounted at a smaller rate than that for economic criteria––has been proposed for such projects as an alternative to the prevailing single-discounting scheme, out of theoretical and empirical considerations. We focus on how to apply this principle in planning problems that involve a multitude of risk in the attendant biological-economic system. A stochastic dynamic programming framework is introduced which allows dual discounting rates and finds the optimal decisions (passively) adapting to changes in the system. Furthermore, we show how to evaluate the variances of the criteria in this framework. With a case study of managing public forestlands in the US Pacific Northwestern region for both timber return and habitat preservation for the northern spotted owl (Strix occidentalis caurina), we illustrate the impacts that the dual-discounting scheme has on the trade-off between conflicting management objectives, the optimal planning strategy, the temporal development of the portion of the forestlands suitable for owl habitats, as well as its steady-state expected value and standard deviation.

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Notes

  1. The three pillars of sustainability are social, economic, and environmental sustainability. Whether manufactured goods can substitute environmental goods lies in the heart of the debate of weak and strong sustainability.

  2. What PAM is incapable of accounting for is uncertainty which arises when the probability distributions of future events are indefinite or unmeasurable, also originally defined in Knight (2012). More recently, uncertainty has been disaggregated into reducible uncertainty and random uncertainty (Zio and Pedroni 2013). With the former, as more knowledge or information is gained over time, the probability distributions become more measurable and actionable. However, random uncertainty cannot be reduced due to the inherent unpredictable changes or randomness of a physical or market phenomenon. Like risk, uncertainty takes a variety of forms in resource planning, e.g., changes in climate, social acceptance, and policy. Active adaptive management (AAM, Williams 2011) aimed at reducing uncertainty through learning is salient for renewable resource planning, but is beyond the scope of this paper.

  3. Different measures of social criteria have been proposed, e.g., United Nations Commission on Sustainable Development Framework and Global Reporting Initiative, but no consensus has been reached. Pragmatic measures that can be incorporated into multi-criteria resource planning are extremely rare (Hutchins and Sutherland, 2008).

  4. In the operations research literature, a MDP’s solution is usually referred to as a policy. Because our discussion is closely related to natural resource policy, we use the term strategy instead, to avoid confusion.

  5. The average-criterion MDP can be viewed as taking a single discount rate of zero.

  6. As matter of fact, (4) and (5) are, respectively, the duals of the LP formulations derived from the Bellman optimal Eqs. (1) and (2).

  7. Stumpage prices, i.e., prices of standing trees, were used here to calculate the NPV thus logging and hauling costs were implicitly taken into consideration.

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  1. Department of Forestry and Natural Resources, Purdue University, 715W. State St, West Lafayette, IN, 47906, USA

    Mo Zhou

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Zhou, M. Dual Discounting in Renewable Resource Planning under Risk. Environmental Management 69, 353–366 (2022). https://doi.org/10.1007/s00267-021-01549-9

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