This paper focuses on residential water consumption in the Principality of Andorra. Residential water consumption is defined as the quantity of water used to cover household and related utility needs of the population through the water supply industry and self-supply, calculated as a total and per capita. Household water consumption provides a measure of the pressure on the environment in terms of water abstraction from different water sources through household use. This type of indicator is important for defining the level of development of water economy services and the degree of water accessibility to cover all household needs of the population. The indicator may also help to identify trends in household water use in a particular country. To the best of our knowledge, our paper will be the first to provide an econometric analysis of residential water demand in Andorra.
There are several reasons that call for a clear understanding of household water use. First, most national allocation regimes define domestic and human needs as the highest priority use [1
] although there are a few exceptions (the Netherlands, a small number of Canadian provinces, water use in Israel, and Peru). Second, most large-scale water assessment models predict some very significant changes in household water use (or more generally in urban water use) over the next 50 years [2
]. Third, water is an essential good for households in the sense that water has no good substitute for most indoor water use (personal hygiene, cleaning, etc.).
Economists have been working on household water use for some time. However, water demand modelling has taken on new importance with the need to better understand the role economic instruments (i.e., water pricing) may have to induce change in water user behavior (i.e., the reduction of water abstraction or polluted discharge). To this end, economists have developed a large number of models to predict the water demand for industrial, agricultural and domestic users. For domestic users, the level of knowledge is already quite advanced. Estimations of domestic water demand functions have been undertaken for a substantial number of countries around the world, and the existing literature has already been summarized and reviewed by several authors [3
]. In Europe, household water demand functions are available for a large number of countries. However, a report by the European Environmental Agency [5
] points out that most available reference studies in Europe date back 10 or 20 years and that “new case studies with primary data are required to provide fresh and relevant evidence that accounts for the socio-economic, management and technological changes that have taken place in the last 20 years”. This is the main objective of our paper that provides the first econometric analysis of residential water demand in the Principality of Andorra.
Some characteristics of Andorra make the analysis of residential water use particularly interesting. The Principality of Andorra is located in the Pyrénées mountains between France and Spain. The altitude of its capital is 1013 m (the highest capital city of Europe). The tourism sector is highly developed and has a significant specialization in winter activities on offer. Thus, the ratio population of non-permanent to permanent is very high. According to the Andorra Statistical Office, 7.8 million people visited Andorra in 2014 (with a population of 70,540 inhabitants). Lastly, individual metering on household water consumption remains limited in Andorra, where a domestic water subscriber can indeed be either a single-family unit or a multi-family unit. In the latter case, there is typically only one collective meter for all units. We propose here to estimate a domestic water demand function using a panel dataset covering the years 2006 to 2015 for the municipality of Andorra La Vella. Our estimate reveals a price elasticity of the residential water demand equal to –0.7. Facing a price increase of 10 percent, households will react in the short-run by reducing their water consumption by 7 percent. Interestingly, the price elasticity is found to be significantly different in single-family units compared to multi-family units. The domestic water demand is found to be more inelastic in multi-family units compared to single-family units. This suggests a significant impact of individual metering on household water use.
The remainder of this article is organized as follows. Section 2
gives a brief overview of domestic water use is Andorra. Section 3
reviews the existing literature on domestic water use in France and Spain. The following two sections, Section 4
and Section 5
, present the water demand approach and the empirical analysis, respectively. Finally, we summarize the main results in Section 6
3. Residential Water Demand in France and Spain: A Brief Review of the Literature
This section provides a brief review of the empirical literature on residential water demand. Since no published study on domestic water demand is available for Andorra, we focus mainly on studies undertaken in France and Spain, the two neighbors of Andorra.
In Table 1
, we summarize the main findings in terms of significant drivers of the household water demand function in France and Spain. As a word of caution, it should be noted that this cross-country comparison is made difficult by the fact that variables introduced as determinants of the household water demands are not consistently defined across studies. In addition, the dependent variable may also differ between studies, some of which use water consumption per capita while others may refer to water consumption per household. However, certain general and persistent trends do emerge. In order to organize the discussion, we analyze the different groups of determinants, including water price and tariffs, household income, population characteristics, housing characteristics, and climate conditions.
Most economists working on domestic water use generally recognize that domestic water consumption reacts to changes in water prices. It is, however, usually found that the household water demand function is price inelastic, which means that water consumption decreases by less than 1 percent for every 1 percent increase in price, with the price-elasticity typically varying between –0.1 and –1.0. In his recent meta-analysis, Sebri [11
] reports for example mean and median price elasticities equal to –0.365 and –0.291, respectively. A price inelastic water demand function is usually reported in studies focusing on France and Spain. Among all the reviewed studies, only Arbués et al. [12
] have found a price-elastic household water demand. In Table 1
, it appears that the range of price-elasticity is quite similar for France and Spain.
It is also widely accepted that domestic water consumption is positively correlated with income. The explanation is straightforward. A high level of income is associated with higher living standards, which could imply a higher quantity of water-consuming appliances and a higher probability for the presence of high-water demanding outdoor uses, such as lawn gardens and swimming pools. This result holds for France and Spain since all income elasticities presented in Table 1
are positive. It should also be pointed out that the income elasticity is not significantly different from zero in several studies conducted in France or in Spain (i.e., [13
Some household or housing characteristics are important for explaining domestic water use in France or in Spain. Ageing is usually known to be a factor contributing to lower water consumption per capita, the other variables being held constant. This result tends to be true, especially in Spain (i.e., [12
]). Most empirical studies have also found that residential demand for water is influenced by heterogeneity associated with differences in the size of the household [12
]. For France and Spain, it is reported that household size affects the demand for water, in general positively (i.e., [18
]), although a few studies have found the inverse result (i.e., [13
]). Climate is one of the most studied drivers of domestic water demand. Indeed, it is considered that household water consumption varies depending on variables such as temperature and rainfall, which may influence the amount and/or frequency of activities that involve water-consumption (garden watering, swimming pool use and personal hygiene [28
]). The climate indicators usually considered in Table 1
include rainfall (annual or in the summer, number of rainy or dry days) and temperature (maximal or average). For France and Spain, it is found that water use increases with temperature (i.e., [12
]) or with the number of dry days (i.e., [17
]). On the contrary, water consumption decreases with rainfall levels (i.e., [18
As discussed previously, one important characteristic of the inhabitants of Andorra is the large share of the non-resident population in relation to seasonal touristic activities, such as skiing in winter. The impact of the seasonal population on household water consumption has already been investigated in the existing literature. In France and Spain, it is usually found that the seasonal population tends to contribute to an increase per capita water consumption (i.e., [13
]). This positive effect may capture the larger share of recreational water use (swimming pool, garden watering) in holiday homes.
5. Empirical Results
5.1. Model Specification
To estimate Equation (1
), a wide variety of functional forms have been applied in the water demand literature, including linear forms, semi- or double-logarithm forms and more complex forms such as the Stone–Geary specification. The existing literature is, however, not very informative concerning the specification that should be preferred. Since the double-log model is the most common specification in the residential water demand literature, we have adopted this model in order to facilitate comparisons with other studies. Furthermore, the specification implies that coefficient estimates are also elasticity estimates. Two panel data estimators may be used, namely the fixed effects model and the random effects (or error components) model. We use these two estimators to conduct some specification tests (Hausman test) in order to decide which is the most appropriate to our data.
5.2. Endogeneity of the Water Price
As discussed previously, the municipality of Andorra La Vella has implemented an increasing block rate (IBR) pricing structure (three blocks from 2006 to 2009 and from 2013 to 2015, two blocks from 2010 to 2012). This raises a problem of price endogeneity due to the simultaneous determination of marginal price and water demand. This problem has been addressed by estimating instrumental variables (IV) models, such as two-stage least squares [29
]. The use of the average water price as an explanatory variable also raises a problem of endogeneity. Stated simply, the average price a consumer faces depends on his level of consumption, but this level of consumption is also affected by the average price. This simultaneity violates standard assumptions regarding independence of the error term from explanatory variables. Ordinary least squares (OLS) are in such a case inconsistent, and a specific estimation procedure is required. This simultaneity problem can be also addressed by using instrumental variables (IV) techniques. Here, in order to get unbiased price elasticities, the average water price has been first instrumentalized. As instruments, we have used the marginal price for the first and the last block, the upper bound of the first block, the lower bound of the last block, and the number of blocks. All instruments are significant, with the expected sign and the Wald test rejecting the null assumption of joint insignificant parameters (results for the instrumental price equation are available from the authors upon request). In the remainder of the paper, we use the instrumental average water price.
The water demand function is estimated in double logarithm form using panel data methods for Andorra La Vella. All estimated coefficients can be interpreted as elasticities. Estimation results are presented in Table 3
. In models (1)–(3), errors are clustered by street name, whereas, in models (4)–(6), street names are included as fixed effects.
When considering all types of family units together (single-family and multi-family units), the water price elasticity varies between −0.741 and −0.729. This range of values is consistent with estimates reported for France and Spain in Table 1
. The domestic water demand in Andorra La Vella is then inelastic. Facing a price increase by 10 percent, one can expect a reduction of the domestic water consumption by 7.3 to 7.4 percent. The water price elasticity is consistently found to be higher (in absolute value) for single-family units, in comparison with multi-family units. Considering for instance models (3) and (4) where street names are introduced as fixed effects, we report water price elasticity equal to −0.823 and −0.701 for single-family and multi-family units, respectively. This indicates that households are more reactive to a change in water price when they live in a single-family unit. As a robustness check of this result, we have again estimated model (4) by adding an interaction term between the logarithm of the instrumentalized average water price and a dummy variable for households in a single-family unit. The estimated coefficient for this interaction term is equal to −0.112 (significant at 1 percent) and the coefficient of ln Average price is equal in that case to −0.701 (significant at 1 percent): households in single-family units are more reactive to changes in water price than households in multi-family units, all being equal.
Seasonality is a strong characteristic of domestic water consumption in Andorra La Vella. The quarterly dummy variables are indeed highly significant in all models. Compared to the first trimester (January–March), a lower water consumption is found during trimester 2 (April–June), 3 (July–September) and 4 (October–December). This is not surprising given the fact that winter corresponds to the high skiing season when Andorra registers a peak in terms of visiting tourists. The lowest domestic water consumption is found from July to September, both for single-family units and for multi-family units.
Climatic conditions, in particular temperatures, appear to have a significant impact on domestic water consumption. The coefficient of ln Average temperature is always significant at 1 percent, with a range between 0.586 and 0.776. Facing an increase of the average temperature by 10 percent, Andorran households will increase their water consumption by around 5.9 to 7.8 percent. Households in single-family units appear to be more impacted by temperatures than households in multi-family units. To check this result, we have again estimated models (1) and (4) by adding an interaction term between the logarithm of the average temperature and a dummy variable for households in a single-family unit. The estimated coefficient for this interaction term is equal to 0.297 for model (1) and to 0.301 for model (4) (both significant at 1 percent), and the coefficient of ln Average temperature is equal to −0.570 both for models (1) and (4) (significant at 1 percent): households in single-family units are more reactive to changes in temperature than households in multi-family units, all else being equal. This may be due to a larger share of recreative outdoor activities requiring water in single-family units (garden, swimming pool, etc.).
Lastly, a scale effect is documented. The water consumption per family unit tends to decrease with the number of family units per domestic water subscriber. On average, the larger a multi-family dwelling, the lower the water consumption per family unit. This result is consistent with the existing literature on multi-family housing. For example, analyzing water consumption in over 2300 multi-family buildings located in New York City, Kontokosta and Jain [30
] show that there is a negative relationship between water use intensity (i.e., water consumption per square meter) and building size (in square meter), a proxy for the number of family units. More precisely, Kontokosta and Jain [30
] report that, for every 10% of additional floor area, water use intensity decreases by approximately 0.8%. A significant relationship between water use and building size is also found in [31
5.4. Policy Implications
Based on the estimates presented in Table 1
, it appears that households in single-family units differ significantly from households in multi-family units in terms of water price elasticity and in terms of how they react to changes in temperature. From a policy perspective, this raises the issue of whether or not to install individual meters in multi-family units, in order to implement individual pricing mechanisms.
Some empirical studies have been performed to measure the impact of these billing systems, and the effect of switching from collective to individual metering. For instance, in the southeast of England, a program performed in 2015 by the government, prompted the installation of nearly 500,000 m. Before the program, only 40 percent of households were metered. Ornaghi and Tonin [34
] have analyzed the impact of the program before the installation of the meters. Their analysis suggests that households are responding to the installation of meters by decreasing their consumption between 16 and 20 percent. Barraqué [35
] reviews whether or not water utilities in France should individually meter multi-family houses, in Paris specifically. The author bases his analysis in France, but also examines some other countries and cities, such as England and Wales, New York City, Barcelona, Belgian Flanders and Wallonia, which have moved from collective to individual metering of domestic water use. In general, Barraqué [35
] concludes that there is no need for water utilities to separately meter each household in a condominium building. If the concern is redistribution, there are possibilities to support low-income customers under collective metering.
In the Andorran context, a cost–benefit analysis of individual metering in multi-family units would still require additional work, for example regarding the cost of universal metering or understanding the factors influencing water demand for multi-family units (i.e., indoor or outdoor water use).
Demand-side water management has become a crucial activity of water sector regulation in most countries. Even though Andorra is a water-rich country, a good understanding of the main drivers of residential water consumption (including water price) may be useful. Indeed, since an increase of water price is expected in the future, the way in which households adjust their water consumption may inform water utility managers and, more generally, public authorities in charge of water sector regulation.
Surprisingly, and to our best knowledge, no estimate of the residential water demand function in Andorra has yet been published. Our current work aims to fill this gap by providing the first estimate of the residential water demand function in Andorra. We have estimated an econometric model using a panel dataset covering the years 2006 to 2015 for the municipality of Andorra La Vella. Our estimates reveal a price elasticity of the residential water demand around –0.7. Facing a price increase of 10 percent, households will react in the short run by reducing their water consumption by 7 percent. This result has important policy implications. Indeed, pricing reforms are often cited as the first measure to be implemented in order to signal water scarcity and to encourage a reasonable use of water. The effectiveness of any pricing policy in engaging water consumption depends, however, on the price elasticity of consumption. The larger the price elasticity, the more effective these policies are at reducing water consumption. Our estimate of the domestic water demand in Andorra allows decision-makers to simulate the impact of change in the water price on domestic water use. To achieve more significant reductions of household water consumption, public authorities in Andorra should complement their price policies with non-price policies, such as education or awareness campaigns.
We have also shown that Andorran households in single-family units differ significantly from households in multi-family units, for example in terms of water price elasticity and in terms of how they react to increases in temperature. From a policy perspective, this result calls for a differentiated treatment of households depending upon whether they live in single-family or in multi-family units. Finally, seasonality appears to be a strong characteristic of domestic water use in Andorra. This opens the door to consider more sophisticated pricing schemes such as time-of-use (TOU) water prices or peak pricing.