Exploring The Spatial Heterogeneity of Individual Preferences for Ambient Heating Systems

Franceschinis, C.; Scarpa, R.; Thiene, M.; Rose, J.; Moretto, M.; Cavalli, R.

doi:10.3390/en9060407

Exploring The Spatial Heterogeneity of Individual Preferences for Ambient Heating Systems

Franceschinis, C.; Scarpa, R.; Thiene, M.; Rose, J.; Moretto, M.; Cavalli, R.

Authors

C. Franceschinis

Professor Riccardo Scarpa riccardo.scarpa@durham.ac.uk
Professor

M. Thiene

J. Rose

M. Moretto

R. Cavalli

Abstract

The estimation and policy use of spatially explicit discrete choice models has yet to receive serious attention from practitioners. In this study we aim to analyze how geographical variables influence individuals’ sensitivity to key features of heating systems, namely investment cost and CO2 emissions. This is of particular policy interest as heating systems are strongly connected to two major current environmental issues: emissions of pollutants and increased use of renewable resources. We estimate a mixed logit model (MXL) to spatially characterize preference heterogeneity in the mountainous North East of Italy. Our results show that geographical variables are significant sources of variation of individual’s sensitivity to the investigated attributes of the system. We generate maps to show how the willingness to pay to avoid CO2 emissions varies across the region and to validate our estimates ex-post. We discuss why this could be a promising approach to inform applied policy decisions.

Citation

Franceschinis, C., Scarpa, R., Thiene, M., Rose, J., Moretto, M., & Cavalli, R. (2016). Exploring The Spatial Heterogeneity of Individual Preferences for Ambient Heating Systems. Energies, 9(6), Article 407. https://doi.org/10.3390/en9060407

Journal Article Type	Article
Acceptance Date	May 19, 2016
Online Publication Date	May 25, 2016
Publication Date	Jun 1, 2016
Deposit Date	Jun 1, 2016
Publicly Available Date	Jun 13, 2016
Journal	Energies
Publisher	MDPI
Peer Reviewed	Peer Reviewed
Volume	9
Issue	6
Article Number	407
DOI	https://doi.org/10.3390/en9060407
Public URL	https://durham-repository.worktribe.com/output/1381625

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© 2016 by the authors; licensee MDPI, Basel, Switzerland. This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.