Implementing Faustmann–Marshall–Pressler at Scale: Stochastic Dynamic Programing in Space
ISBN: 978-1-83867-576-9, eISBN: 978-1-83867-575-2
Publication date: 19 October 2020
Abstract
The authors construct an intertemporal model of rent-maximizing behavior on the part of a timber harvester under potentially multidimensional risk as well as geographical heterogeneity. Subsequently, the authors use recursive methods (specifically, the method of stochastic dynamic programing) to characterize the optimal policy function – the rent-maximizing timber-harvesting profile. One noteworthy feature of their application to forestry in the province of British Columbia, Canada is the unique and detailed information the authors have organized in the form of a dynamic geographic information system to account for site-specific cost heterogeneity in harvesting and transportation, as well as uneven-aged stand dynamics in timber growth and yield across space and time in the presence of stochastic lumber prices. Their framework is a powerful tool with which to conduct policy analysis at scale.
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Acknowledgements
Acknowledgments
We are grateful to several individuals at the British Columbia Ministry of Forests and Range (prior to June 16, 2005, this ministry was known as the Ministry of Forests) for their coöperation and help. Peter Fuglem, then Manager of the Development and Policy Section of the Timber Supply Branch (which is now known as the Forest Analysis Branch), took an early interest in the project after Bill Howard, then Director of the Revenue Branch, organized an interministry meeting at which the basic idea was pitched. Thereafter, Dave Waddell, Tim Bogle, and Albert Nussbaum (all of the Forest Analysis Branch) were instrumental in helping our research assistant, Mark Weldon, construct the geographical information system that was central to organizing the data for the project.
Cam Bartram and Rob Drummond, of the Ministry of Sustained Resource Management, provided much early helpful advice necessary when implementing the program VDYP for our problem; Shelley Grout, of the Research Branch at the Ministry of Forests and Range, provided us with a copy of the program VDYP. Ken Polsson, of the Research Branch, gave extensively of his time using the program TASS to create the data necessary for us to estimate the growth–yield equations. Jim Goudie and Ken Mitchell, also of the Research Branch, provided advice that was useful in evaluating our timber-growth model.
We cannot overstate the contribution of our research assistant, Mark Weldon. A mechanical engineer by training, a forester in a previous profession, and a Ph.D. student in environmental engineering (at that time), Mark toiled quietly and efficiently for two years to build us an extraordinary data set; we are in his debt. At a later stage in the research, Clinton J. Levitt also provided invaluable research assistance, particularly by using animation to depict the solutions to our dynamic programs.
The financial support of the National Science Foundation (NSF) under grant SES-0241509 made the entire project possible; we are also grateful to the NSF for ongoing support and, in particular, to Dan Newlon for his encouragement.
This chapter has benefitted from the helpful suggestions of Caralyn Clark, Cristina Gualdani, Logan Hoffman, John Kennedy, and David Prentice as well as the editors and four anonymous referees.
Citation
Paarsch, H.J. and Rust, J. (2020), "Implementing Faustmann–Marshall–Pressler at Scale: Stochastic Dynamic Programing in Space", de Paula, Á., Tamer, E. and Voia, M.-C. (Ed.) The Econometrics of Networks (Advances in Econometrics, Vol. 42), Emerald Publishing Limited, Leeds, pp. 145-174. https://doi.org/10.1108/S0731-905320200000042011
Publisher
:Emerald Publishing Limited
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