A real options-net present value approach to assessing land use change: A case study of afforestation in Canada
Denys Yemshanov,
Geoffrey R. McCarney,
Grant Hauer,
Martin Luckert,
Jim Unterschultz and
Daniel W. McKenney
Forest Policy and Economics, 2015, vol. 50, issue C, 327-336
Abstract:
Geographically explicit land use change models based on net present value have been criticized for not reflecting the breadth of economic considerations relevant to private land use decisions. An alternative approach is to econometrically estimate land allocations from historical transactions, but this approach requires extensive historical econometric data sets, which may not be available, and may be difficult to model spatially. We show that a geographically explicit net present value approach inclusive of an option value to defer land conversion can be a viable and insightful alternative to econometric approaches. The model is applied to Alberta, Canada where historical land use change data are not available. The elasticity estimates of converting agricultural land to afforestation, 0.21 to 0.37, are similar to other North American estimates from econometric studies.
Keywords: Afforestation; Real options; Land use; Bioeconomic model; Afforestation elasticities (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1389934114001749
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:forpol:v:50:y:2015:i:c:p:327-336
DOI: 10.1016/j.forpol.2014.09.016
Access Statistics for this article
Forest Policy and Economics is currently edited by M. Krott
More articles in Forest Policy and Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().