The best forestry money can buy: Efficient contracting for silvicultural expertise (and the limits thereof)
Main Article Content
Keywords
northern hardwoods, optimal contracting, tree-level optimization
Abstract
From the typical forest owner’s kitchen window, thoughtful silviculture looks no different from lazy silviculture. Thus, a landowner cannot directly compensate a forester based on their evaluation of the quality of the work performed. Is there an incentive contract, reliant only on observable outcomes, that could induce optimal effort from a skillful forester? We frame this contracting question as a bi-level optimization problem in which the forester (Agent) solves an integer programming problem to choose the individual-tree cutting schedule that will maximize her payoff, net of the cost of her effort, given the contract parameters specified by the forest owner (Principal). The forest owner optimizes his choice of those parameters so as to maximize the value of returns generated from the resulting cutting schedule, net of the forester’s compensation. We apply this approach to empirical data collected from a hardwood forest in northern Vermont, USA. Harvest schedules differ noticeably between a naïve, costless baseline scenario, a scenario in which only management costs (but not contracting distortions) are accounted for, and the bi-level optimal contracting model. We observe not just a transfer of wealth between the landowner and forester, but a deadweight loss as the maximum feasibly contractable gross value production is less than the first-best level of output.
References
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Fenichel EP, Adamowicz W, Ashton MS, Hall JS. 2019. Incentive systems for forest-based ecosystem services with missing financial service markets. J Assoc Environ Resour Econ. 6(2):319-347. https://doi.org/10.1086/701698
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https://doi.org/10.1111/1467-6419.00150
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Koster R, Fuchs JM. 2022. Opportunity costs of growing space-an essential driver of economical single-tree harvest decisions. For Policy Econ. 135:102668. https://doi.org/10.1016/j.forpol.2021.102668
Leak WB, Yamasaki M, Holleran R. 2014. Silvicultural guide for northern hardwoods in the northeast. Gen Tech Rep NRS-132. Newtown Square (PA): USDA Forest Service, Northern Research Station. 46 p. https://doi.org/10.2737/NRS-GTR-132
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Leffler KB, Rucker RR, Munn IA. 2000. Transaction costs and the collection of information: presale measurement on private timber sales. J Law Econ Organ. 16(1):166-188. https://doi.org/10.1093/jleo/16.1.166
Li WD, Ashlagi I, Lo I. 2022. Simple and approximately optimal contracts for payment for ecosystem services. Manag Sci. https://doi.org/10.1287/mnsc.2021.4273
Lohmander P. 2019. Market adaptive control function optimization in continuous cover forest management. Iran J Manag Stud. 12(3):335-361.
Maker NF, Foppert JD. 2023. Nonparametric individual-tree growth models for the northern forest. In: Kern CC, Dickinson YL, editors. Proceedings of the first biennial Northern Hardwood Conference 2021. Gen Tech Rep NRS-P-211. Madison (WI): USDA
Forest Service, Northern Research Station. p. 83-95. https://doi.org/10.2737/NRS-GTR-P-211-paper19
Mason CF, Plantinga AJ. 2013. The additionality problem with offsets: optimal contracts for carbon sequestration in forests. J Environ Econ Manag. 66(1):1-14. https://doi.org/10.1016/j.jeem.2013.02.003
Matthews JD. 1989. Silvicultural systems. Oxford (UK): Oxford University Press.
McIntosh MG, Zhang D. 2024. Faustmann formula and its use in forest asset valuation: a review and a suggestion. For Policy Econ. 160:103158. https://doi.org/10.1016/j.forpol.2024.103158
Mebane WR Jr, Sekhon JS. 2011. Genetic optimization using derivatives: the rgenoud package for R. J Stat Softw. 42:1-26. https://doi.org/10.18637/jss.v042.i11
Mei B. 2019. Timberland investments in the United States: a review and prospects. For Policy Econ. 109:101998.
https://doi.org/10.1016/j.forpol.2019.101998
Mei B, Clutter ML. 2023. Forestland investment: valuation and analysis. New York (NY): Routledge. https://doi.org/10.4324/9781003366737
Meilby H, Nord-Larsen T. 2012. Spatially explicit determination of individual tree target diameters in beech. For Ecol Manag. 270:291-301. https://doi.org/10.1016/j.foreco.2011.08.037
Nautiyal JC, Williams JS. 1990. Response of optimal stand rotation and management intensity to one-time changes in stumpage price, management cost, and discount rate. For Sci. 36(2):212-223. https://doi.org/10.1093/forestscience/36.2.212
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Newman DH. 2002. Forestry's golden rule and the development of the optimal forest rotation literature. J For Econ. 8(1):5-27. https://doi.org/10.1078/1104-6899-00002
Niemi MT, Vauhkonen J, Uusitalo J. 2025. Trade-off analysis for multi-objective boreal forest thinning. Forestry. cpaf027. https://doi.org/10.1093/forestry/cpaf027
Oliver CD, Larson BC. 1996. Forest stand dynamics: updated edition. New York (NY): Wiley. https://doi.org/10.1093/forestscience/42.3.397
Ostrom E. 1990. Governing the commons: the evolution of institutions for collective action. Cambridge (UK): Cambridge University Press. https://doi.org/10.1017/CBO9780511807763
Palik BJ, D'Amato AW, Franklin JF, Johnson KN. 2021. Ecological silviculture: foundations and applications. Long Grove (IL): Waveland Press.
Paradis G, Bouchard M, LeBel L, D'Amours S. 2018. A bi-level model formulation for the distributed wood supply planning problem. Can J For Res. 48(2):160-171. https://doi.org/10.1139/cjfr-2017-0240
Parkatti VP, Tahvonen O. 2020. Optimizing continuous cover and rotation forestry in mixed-species boreal forests. Can J For Res. 50(11):1138-1151. https://doi.org/10.1139/cjfr-2020-0056
Pascual A. 2021. Multi-objective forest planning at tree-level combining mixed integer programming and airborne laser scanning. For Ecol Manag. 483:118714. https://doi.org/10.1016/j.foreco.2020.118714
Pascual A, Guerra-Hernández J. 2022. Spatial connectivity in tree-level decision-support models using mathematical optimization and individual tree mapping. For Policy Econ. 139:102732. https://doi.org/10.1016/j.forpol.2022.102732
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Dec 10, 2025
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Foppert, J., & Maker, N. (2025). The best forestry money can buy: Efficient contracting for silvicultural expertise (and the limits thereof). Journal of Forest Business Research, 4(2), 95–125. https://doi.org/10.62320/jfbr.v4i2.83
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