An analysis of the price escalation of non-linear water tariffs for domestic uses in Spain
Roberto Martinez-Espineira () and
Utilities Policy, 2015, vol. 34, issue C, 82-93
Efficient and sustainable water resource use and management is becoming increasingly important, especially in regions under water stress. The use of increasing block pricing involving an escalation or progressivity of unit prices in tariff systems is an economic instrument that contributes to achieving this objective. More progressive tariffs are expected to contribute to a better allocation of resources and avoid their wastage. This article analyses the determinants of the price escalation of water supply tariffs in Spain, a country subject to a high water stress throughout most of its territory. The main objective is to discern whether differences in the degree of progressivity in the tariffs are explained fully by climatic and scarcity factors or are, instead, disproportionately affected by political and business criteria. Data from 967 municipalities are analysed using conditional mixed process (CMP) modelling. Among the obtained results, we find that tariff escalation is influenced by factors related to the environment in which the service is supplied, as well as by factors related to the decision makers’ own strategic choices.
Keywords: Water tariffs; Price escalation; Progressivity; Spain; Increasing block rates (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:juipol:v:34:y:2015:i:c:p:82-93
Access Statistics for this article
Utilities Policy is currently edited by D. Smith
More articles in Utilities Policy from Elsevier
Bibliographic data for series maintained by Haili He ().