Willingness to Pay among Swedish Households to Avoid Power Outages: A Random Parameter Tobit Model Approach

Fredrik Carlsson and Peter Martinsson

The Energy Journal, 2007, vol. Volume 28, issue Number 1, 75-90

Abstract: Using a contingent valuation survey, we elicit Swedish householdsÕ willingness to pay (WTP) to avoid power outages. In the study respondents are asked to state their WTP for avoiding nine different types of outages. We therefore apply a random parameter Tobit model since there is cross-sectional heterogeneity and a proportion of zero responses. Based on the estimations, we find that the WTP depends positively on the duration of the outages, and that WTP is significantly higher for unplanned outages. The overall variation in the WTP due to observed heterogeneity in housing and socio-economic variables is small compared to the pure effects of power outages. Policy implications of those findings are discussed.

JEL-codes: F0 (search for similar items in EconPapers)
Date: 2007
References: Add references at CitEc
Citations: View citations in EconPapers (72)

Downloads: (external link)
http://www.iaee.org/en/publications/ejarticle.aspx?id=2178 (text/html)
Access to full text is restricted to IAEE members and subscribers.

Related works:
Journal Article: Willingness to Pay among Swedish Households to Avoid Power Outages: A Random Parameter Tobit Model Approach (2007)
Working Paper: Willingness to Pay among Swedish Households to Avoid Power Outages - A Random Parameter Tobit Model Approach (2004)
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:aen:journl:2007v28-01-a04

Ordering information: This journal article can be ordered from
http://www.iaee.org/en/publications/ejsearch.aspx

Access Statistics for this article

More articles in The Energy Journal from International Association for Energy Economics Contact information at EDIRC.
Bibliographic data for series maintained by David Williams ().