A multiple indicator solution approach to endogeneity in discrete-choice models for environmental valuation
Author
dc.contributor.author
Mariel, Petr
Author
dc.contributor.author
Hoyos, David
Author
dc.contributor.author
Artabe, Alaitz
Author
dc.contributor.author
Angelo Guevara, C.
Admission date
dc.date.accessioned
2018-10-08T16:12:06Z
Available date
dc.date.available
2018-10-08T16:12:06Z
Publication date
dc.date.issued
2018-08-15
Cita de ítem
dc.identifier.citation
Science of the Total Environment 633 (2018) 967–980
es_ES
Identifier
dc.identifier.other
10.1016/j.scitotenv.2018.03.254
Identifier
dc.identifier.uri
https://repositorio.uchile.cl/handle/2250/152025
Abstract
dc.description.abstract
Endogeneity is an often neglected issue in empirical applications of discrete choice modelling despite its severe consequences in terms of inconsistent parameter estimation and biased welfare measures. This article analyses the performance of the multiple indicator solution method to deal with endogeneity arising from omitted explanatory variables in discrete choice models for environmental valuation. We also propose and illustrate a factor analysis procedure for the selection of the indicators in practice. Additionally, the performance of this method is compared with the recently proposed hybrid choice modelling framework. In an empirical application we find that the multiple indicator solution method and the hybrid model approach provide similar results in terms of welfare estimates, although the multiple indicator solution method is more parsimonious and notably easier to implement. The empirical results open a path to explore the performance of this method when endogeneity is thought to have a different cause or under a different set of indicators. (C) 2018 Elsevier B.V. All rights reserved.
es_ES
Patrocinador
dc.description.sponsorship
Department of Education of the Basque Government
IT-642-13
IT-783-13
Spanish Ministry of Economy and Competitiveness
ECO2017-82111-R
University of the Basque Country (UPV/EHU)
US15/11
CONICYT
FONDECYT
1150590
Complex Engineering Systems Institute, Chile
CONICYT FB0816