Universidad del Desarrollo1
Expected future population growth in developing countries and emerging economies will increase the water demand for residential use. Moreover, projected changes in temperature and precipitation as a result of climate change will affect the water available to alternative uses. An increase in the demand along with a potential reduction in the supply of water constitutes an important and critical issue for policy makers. These issues will have a substantial influence in the efficient management of water resources and the public policies adopted to deal with water scarcity and adaptation to climate change in developing countries. Efficient management and water-related public policies require rigorous economic analysis of the potential effects of the climate change on water demand. A structural discrete/continuous choice (DCC) model consistent with utility theory was used to estimate residential water demand for households in the Biobio region in Chile. Households faced nonlinear prices as a result of an increasing block price (IBP) structure set administratively by the water supplier and based on regulations of a public utility commission. This research explored how sensitive households are to changes in water prices, measured by the price elasticity. We estimated a demand function using monthly water consumption (m3), for the period 2007-2012; weather variables corresponding to monthly average temperature and precipitation, for the period 2007-2013; household characteristics such as household size and number of rooms; marginal prices; and virtual income, or income adjusted by the subsidies derived of purchasing not all water units at the same marginal price. The socioeconomic characteristics were collected from the national CENSUS (2002), using the census districts average for each household. The total database included information for water consumption, monthly charge ($), socioeconomic and climate characteristics, covering 345.243 households. The estimated demand function included two error terms to account for heterogeneous household preferences for water consumption and both optimization and measurement error. In our model, the demand was specified using a log-log function estimated by the DCC model through maximum likelihood. In order to compare different model specifications, we also computed the model using both Ordinary Least Square (OLS) and Two Stage Least Square. According to our results, household characteristics affect positively the residential water demand. These results are consistent with previous. On the other hand, the coefficients estimated for the temperature and precipitation variables were both positive and statistically significant. The price coefficient of -1.47 was also statistically significant and reflected the price elasticity conditional on the observed block of water consumption. According to the results, the residential water demand is elastic (with respect to the price), this could be explained due to the block rate pricing, specifically the second one that corresponds to overconsumption during summer (December -- March). We think that this behavior could be explained by outdoor consumption (most of them for recreational proposes). The estimated DCC model adequately explained the discrete and continuous choices when a household is faced to a decision related to water consumption. Although the DCC model seems to be more complicated to estimate compared to alternative econometric approaches (e.g., ordinary least squares or instrumental variables), it allows to understand the consumer behavior under nonlinear prices and to estimate consistent price and income coefficients in a model of water demand. 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