A latent class nested logit model for rank-ordered data with application to cork oak reforestation

Oviedo, J.L.; Yoo, H.I.

doi:10.1007/s10640-016-0058-7

A latent class nested logit model for rank-ordered data with application to cork oak reforestation

Oviedo, J.L.; Yoo, H.I.

Authors

J.L. Oviedo

H.I. Yoo

Abstract

We analyze stated ranking data collected from recreational visitors to the Alcornocales Natural Park (ANP) in Spain. The ANP is a large protected area which comprises mainly cork oak woodlands. The visitors ranked cork oak reforestation programs delivering different sets of environmental (reforestation technique, biodiversity, forest surface) and social (jobs and recreation sites created) outcomes. We specify a novel latent class nested logit model for rank-ordered data to estimate the distribution of willingness-to-pay for each outcome. Our modeling approach jointly exploits recent advances in discrete choice methods. The results suggest that prioritizing biodiversity would increase certainty over public support for a reforestation program. In addition, a substantial fraction of the visitor population are willing to pay more for the social outcomes than the environmental outcomes, whereas the existing reforestation subsidies are often justified by the environmental outcomes alone.

Citation

Oviedo, J., & Yoo, H. (2017). A latent class nested logit model for rank-ordered data with application to cork oak reforestation. Environmental and Resource Economics, 68(4), 1021-1051. https://doi.org/10.1007/s10640-016-0058-7

Journal Article Type	Article
Acceptance Date	Jul 26, 2016
Online Publication Date	Aug 3, 2016
Publication Date	Dec 1, 2017
Deposit Date	Aug 8, 2016
Publicly Available Date	Aug 3, 2017
Journal	Environmental and Resource Economics
Print ISSN	0924-6460
Electronic ISSN	1573-1502
Publisher	Springer
Peer Reviewed	Peer Reviewed
Volume	68
Issue	4
Pages	1021-1051
DOI	https://doi.org/10.1007/s10640-016-0058-7
Public URL	https://durham-repository.worktribe.com/output/1376730