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Monteiro, H., Cardoso, M. & Figueiredo, M. C. T. (2014). Going Beyond Average Response: Modeling Portuguese Residential Water Demand with Quantile Regression. International Water Association World Water Congress.

H. P. Monteiro et al.,  "Going Beyond Average Response: Modeling Portuguese Residential Water Demand with Quantile Regression", in Int. Water Association World Water Congr., Lisboa, 2014

@misc{monteiro2014_1714870236838,
	author = "Monteiro, H. and Cardoso, M. and Figueiredo, M. C. T.",
	title = "Going Beyond Average Response: Modeling Portuguese Residential Water Demand with Quantile Regression",
	year = "2014",
	howpublished = "Outro",
	url = "http://www.iwa2014lisbon.org/wp-content/uploads/2013/03/posters.pdf"
}

TY  - CPAPER
TI  - Going Beyond Average Response: Modeling Portuguese Residential Water Demand with Quantile Regression
T2  - International Water Association World Water Congress
AU  - Monteiro, H.
AU  - Cardoso, M.
AU  - Figueiredo, M. C. T.
PY  - 2014
CY  - Lisboa
UR  - http://www.iwa2014lisbon.org/wp-content/uploads/2013/03/posters.pdf
AB  - Reconciling the conflicting goals of water pricing policies like water conservation, efficient use or generating revenue to cover the costs of providing water services requires the knowledge of the consumers’ response to prices. Increasing the price of water supplied to consumers may have a more significant impact on the utility’s revenues than on water conservation if water demand is inelastic. Recent research has pointed out that price-elasticity of residential water demand may not be constant throughout the consumption distribution with some consumers adapting more to price hikes, while others may prefer to pay the price of maintaining their level of consumption.

Pricing policies for water supply often resort to nonlinear prices, namely using two-part tariffs, where the variable component may include several blocks usually increasing in price. Pricing decisions  should be well-informed about the impacts of the tariff structure and price levels on the water utility’s revenues and on the amount of water consumed. The knowledge of the price-elasticity of water demand for the average of the sample or population of consumers is insufficient to predict the possible impacts of a proposed price change if consumers’ response to price differs across the distribution of consumption levels.

We use quantile regression to get estimates of the impacts that different relevant explanatory variables (including price) may have on water consumption for different consumption quantiles in order to get a more accurate picture of the full impact of price changes.

The use of quantile regression is a novel contribution to the field of water demand estimation.

ER  -