DO DROUGHTS HAVE LONG-TERM EFFECTS ON WATER
CONSUMPTION? EVIDENCE FROM THE URBAN AREA OF BARCELONA
Valeria Bernardo, Xavier Fageda and Montserrat Termes
(University of Barcelona & GIM-IREA)
Abstract: This paper examines the long-term effects of droughts on water consumption
using data of municipalities of the urban area of Barcelona. Two important
characteristics of the sample of municipalities are the relatively low water consumption
in the pre-drought period and the fact that indoor uses are clearly predominant.
Controlling for prices, income and several socio-demographic factors, we find that a
severe drought episode along with the communications campaigns launched in response
may have stimulated a change in the attitudes and habits of consumers about water
conservation not only during the drought episode but also in later periods.
Keywords: Water consumption, droughts, communication campaigns, high density
cities, panel data.
Address for correspondence (all authors): Department of Economic Policy,
University of Barcelona. Av. Diagonal 690, 08034 Barcelona (Spain). Tel.
[email protected],
+34934039721.
Fax.+34934024573.
E-mail:
[email protected], [email protected]
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DO DROUGHTS HAVE LONG-TERM EFFECTS ON WATER
CONSUMPTION? EVIDENCE FROM THE URBAN AREA OF BARCELONA
1. INTRODUCTION
Many regions around the world are vulnerable to drought, with climates that are
characterized by irregular rainfall patterns and long periods of high temperature. This is
the case of the Mediterranean area afflicted in recent years by episodes of severe
drought that have jeopardized the availability of water for all uses. According to the
UN’s Food and Agriculture Organization (FAO) since 1990 droughts have had a greater
detrimental impact on people than any other physical hazard: 11 million have died as a
consequence of drought and 2 billion have been affected. Moreover, drought episodes
are expected to increase in the future as a result of global climate change.
In 2007-2008, the Metropolitan Area of Barcelona suffered one of the severest
drought episodes of the last century both in terms of its duration and intensity (Ortega
and Markandya, 2009). Public concern at the lack of precipitation was evident by the
end of 2006 when warnings first began to be raised. In April 2008, reservoirs supplying
Barcelona had fallen to 20% of their capacity and supply for essential uses was under
serious threat. The episode lasted until June 2008, when an extremely wet May and
subsequent rainy months brought it to an end.1
The emergency situation provoked by this lack of precipitation saw notable legal and
political actions being adopted at both regional and national levels to increase water
supply and reduce water consumption. For example, the authorities placed a ban on
public fountains and the watering of public parks, while restrictions were put on the use
of water for private gardens and swimming pools (March et al., 2013). In addition,
structural actions were designed aimed at increasing supply (including the shipping of
water from other areas of Spain and France), while intensive communication campaigns
seeking voluntary reductions in consumption (especially for indoor uses) were launched
between February 2007 and May 2008, the latter having repercussions throughout the
media. Finally, water saving devices were distributed among the population to reduce
household consumption.
1
See Table A1 in the Appendix for a detailed chronology of the events and the measures
applied during the drought episode suffered by the Metropolitan Area of Barcelona in 20072008.
2
According to the International Water Association (2010), water consumption per
capita in the Metropolitan Area of Barcelona lies in the lowest range for cities around
the world with a similar climate. Interestingly, this rate experienced a steady fall during
and after the 2007/2008 drought episode, which is even more remarkable if we bear in
mind that indoor uses are the predominant source of consumption in this metropolitan
area. A possible explanation for this reduction in consumption following the drought
episode is the greater level of environmental awareness among consumers resulting
from the drought episode and the consequent intensive communication campaigns
conducted at that time.
In this paper, we estimate the determinants of domestic water consumption to
provide econometric evidence of the long-term effects of a severe drought episode on
water consumption. Controlling for prices, income and various socio-demographic
factors, we find that a severe drought episode along with public communication
campaigns in the peak of such episode may have stimulated a change in consumers’
water conservation attitudes and habits not only during the drought episode but also in
subsequent periods. While we might expect a reduction in water consumption at the
peak of the drought episode when several demand and supply measures had been
applied, the patterns of consumer behavior following the drought are less clear.
Among the empirical studies that have analyzed non-pricing measures during
drought episodes, several have examined their effects on welfare (see, for example,
Roibás et al., 2007 and Mansur and Olmstead 2012). Another line in the literature – and
one that is more closely related to ours – has focused on the impact on demand of these
measures – see, for example, Berk et al. (1980) on the case of California during the
1976-1977 drought; Michelsen et al. (1999) on the southern United States during the
period 1984-1995; Schuk et al. (2006) on Colorado in 2002; Kenney et al. (2008) on
Aurora, Colorado in 2002; Halich and Stephenson(2009) on the drought in Virginia in
2002; and, Polebitski and Palmer (2013) on the 2002-2003 drought in Seattle. All cited
find non-price measures effective for reducing water consumption during drought and
contribute to our understanding of the effect of policies in a variety of different aspects.
More specifically, with regard to the timing of the impact of drought measures on
demand, Berk et al. (1980) reported that measures introduced before the drought were
relevant in two out of three communities, while those adopted during the drought
episode were significant in four out of four communities. Schuk et al. (2006) found less
severe policies implemented early in the summer season to be more successful than
3
more severe policies adopted later. Michelsen et al. (1999) reported non-price programs
to be effective in reducing demand for water, but that their application appeared to
present diminishing returns as effectiveness per program fell with the increment in the
number of programs introduced. In this same line of research, Halich and Stephenson
(2009) compared the outcomes of different policies and found that the most successful
involved moderate to high levels of both information and enforcement efforts, with
consumption being cut in such instances by between 15% and 22%. Polebitski and
Palmer (2013) study identifies that curtailments effectiveness during drought periods is
sensitive to household size: increasing household size decrease curtailments
effectiveness, whereas decreasing household size increase the effect over per-capita
consumption of such policy. Finally, in an examination of the impact of a mixed policy
approach, Kenney et al. (2008) found that outdoor restrictions implemented jointly with
price restrictions have a greater effect in reducing consumption than when the two
policies are adopted separately.
This paper reports results of a quantitative analysis of the long-term effects of
drought measures on residential water consumption in the years following the drought
episode. To the best of our knowledge, this is the first paper to measure long-term
effects of public campaigns and water restrictions in response to drought episode.
The remainder of the paper is organized as follows. In the next section, we specify
the empirical model and state our expectations for each explanatory variable. Then, we
discuss the data used in the empirical analysis and the criteria applied in building the
sample and variables. Section 4 deals with various econometric issues and reports the
regression results. The last section contains our concluding remarks.
2. EMPIRICAL MODEL
A multivariate analysis is implemented to identify the determinants of the per capita
domestic consumption of water using aggregate data at the municipal level as
household-level data are not available. In fact, most studies of water demand in Europe
are undertaken on an aggregate basis with just a few exceptions (see Schleich and
Hillenbrand, 2009 for a detailed list of studies of residential water demand in Europe).
The use of data collected over a period of several years at the municipality level has
the advantage of enabling us to examine the impact of climate variables, which is
clearly of importance here. This need to capture the impact of climate variables and to
focus on the specific period in which drought policy measures were implemented also
4
makes it more advisable to use monthly data, although here data for several variables
are only available on an annual basis. Overall, our sample contains 2,459 observations.
For methodological reviews containing exhaustive analyses of the literature on water
consumption, see Espey et al. (1997), Dalhuisen et al. (2003), Worthington and
Hoffman (2008) and House-Peters and Chang (2011). Here, we use similar control
variables to those typically employed in these empirical studies2: including, price,
income, demand management policies, climate variables, household size, population
density and housing characteristics. In addition, we incorporate explanatory variables
that are of relevance in the context of our data: namely, the unemployment rate, the
percentage of elderly (old) and foreign population.
Our specific contribution is the analysis we conduct of the impact of the drought
episode and the consequent public campaigns to afford it on water consumption in the
following years. The aim in this analysis is to quantify the effects of droughts on water
consumption while controlling for as many factors as possible. To this end, we estimate
the following equation using monthly data for municipalities in the urban area of
Barcelona:
Water_Consumption_per_capitaimt= α + β1Income_per_capitait +
β2Unemployment_rateimt + β3Household_sizeit + β4Density_of_populationit +
β5Percentage_old_populationit + β6Percentage_foreign_populationit +
β7Water_price_increasest + β8Mean_Temperatureimt + β9Rainfallimt + β10Ddroughtimt +
β11Dpost-droughtimt + µ’DMonthm + λ’Dyeart + α’Dmunicipalityi + εit
(1)
In this equation, the dependent variable is the total domestic consumption of water
per capita of municipality i in month m of year t. The dependent variable is expressed in
logs to facilitate the interpretation of the results for the dummy policy variables, which
are the variables of main interest in our analysis.
As explanatory variables, we take into account the influence of factors capturing the
economic condition of the municipality: namely, per capita income and the
unemployment rate. A positive relationship is generally found between income and
domestic water consumption (e.g., Agthe and Billings, 1980; Lyman, 1992; Rock, 2000;
Martínez-Espiñeira, 2002; Martinez-Espiñeira and Nauges, 2004; Domene and Saurí,
2
Our sample of municipalities includes the city of Barcelona, which is much larger than the
other municipalities. We ran regressions in which the city of Barcelona was excluded, but the
results were qualitatively identical to those obtained in regressions in which it was included.
Note that previous studies of water demand do not consider population as an explanatory
variable.
5
2006; Schleich and Hillenbrand, 2009). However, this positive relationship is less clear
when water bills represent only a small proportion of the residents’ disposable income.
In fact, there are some works that suggest that income might not be a relevant variable
to explain water consumption (House-Peters et al., 2010; Musolesi and Nosvelli, 2011).
In this regard, water expenditure in the province of Barcelona is less than 1 per cent of
the total income of the households (ACA, 2013).
In line with Gaudin et al. (2006) and Castillo-Manzano et al. (2013) we include a
variable measuring the monthly unemployment rate in each municipality. This variable
seeks to capture the impact of the economic and financial crisis on the municipalities in
the sample since 2008. Indeed, unemployment, being more sensitive to economic
shocks, captures the effect of business cycles more clearly than is the case when using
the income variable. We would, therefore, expect water consumption to be negatively
associated with the unemployment rate since it is related to a household’s disposable
income. However, controlling for income, the unemployed are likely to spend more
time at home and this would have a positive effect on water consumption. All in all,
therefore, the expected sign of the coefficient associated with this variable is unclear.
We also include a household size variable, for which we expect a negative
coefficient given the existence of economies of size. As such, the consumption of water
per capita should be greater in smaller households, as is generally reported elsewhere
(e.g., Lyman, 1992; Campbell et al., 2004; Arbués and Villanúa, 2006; Domene and
Saurí, 2006).
Variables accounting for housing characteristics are also used in water consumption
studies. They typically include the size of the house, the number of bedrooms, the
amount of outdoor space, the presence of gardens and swimming pools and the
proportion of single-family households (see, for example, Wentz and Gober, 2002;
Campbell et al., 2004; Domene and Saurí, 2006; Randolph and Troy, 2008; and Fox et
al., 2009). All these variables (with the exception of the proportion of single-family
households) can be used at the household level and we would expect them to correlate
strongly with income.
Here, given our data limitations, we approximate the impact of urban land uses by
using population density data. Examples of studies that use the density of population as
an explanatory variable include Williams and Suh (1986), Renwick and Archibald
(1998) and Gaudin (2006). Denser municipalities can be expected to be associated with
a more compact urban form and so outdoor uses of water should be more limited in
6
these municipalities. Thus, we expect a negative sign for the coefficient associated with
this variable.
March et al. (2012) hypothesize that the decreasing levels of per capita water
consumption in the Metropolitan Area of Barcelona can be attributed to its changing
demographic structure, with an increasing number of immigrants from developing
countries and a greater presence of the elderly. They find some evidence in favor of this
hypothesis when using aggregate data for the period 2003-2007; yet, they recognize that
these demographic characteristics may be correlated with income and housing
typologies.
Here, we need to capture the impact of these two factors in order to determine the
effects of droughts and the consequent public campaigns to save water in periods
following the drought episode. Thus, we include a variable for the percentage of elderly
population in the municipality.3 The expected sign for this variable is not clear a priori
given the conflicting outcomes reported in the literature (see, for example, MartínezEspiñeira, 2002; Schleich and Hillenbrand, 2009). We also include a variable for the
percentage of foreign population in the municipality. Likewise, the expected sign for
this variable is unclear given that the only previous study to incorporate it was March et
al. (2012).4 While these authors draw a distinction between immigrants from the
developing and developed worlds, our concern is to include a variable that captures
different conservation attitudes among immigrants to water consumption.
In addition, we consider a variable that measures the real increases in prices and
taxes faced by water consumers in the municipalities included in our sample, all of
which are served by the same supplier. As such they are subject to the same price (and
taxes) and, thus, the variable essentially captures the evolution of water prices and taxes
over time. For the period considered here, the real price increase of water was
frequently close to zero, with the exceptions of 2009, when the increase was about 8%,
and 2012, when it was around 23%. Regarding taxes, the real increases in the years of
the considered period are generally in the range 3-5% although they are close to zero in
2005 and 2010 and they are about 7% in 2012. We expect a negative sign for the
coefficient associated with prices, given that demand should fall as prices rise. There is
an extensive literature on water demand elasticities to prices, and there is still some
3
We also ran regressions with a variable for the percentage of young people in the population,
but none was found to be statistically significant.
4
Some studies conducted in the US (including Gaudin et al., 2001 and Ballings et al., 2008)
have considered the percentage of Hispanics; however, this is clearly not relevant in our context.
7
debate as to the magnitude of such elasticities (see the detailed reviews of Espey et al.,
2007; and Dalhuisen et al., 2003).
We also include two variables – mean temperature and total rainfall – to capture a
municipality’s climate conditions. Many studies have considered climate variables as
explanatory factors of water consumption (see, for example, Billings and Agthe, 1998;
Zhou et al., 2000; Arbués and Villanúa, 2006; Balling and Gober, 2007; Schleich and
Hillenbrand, 2009; McNown et al., 2015). Water consumption is generally found to
increase with temperature and to decrease with rainfall, although there is some debate
about the most appropriate measure of rainfall (Martinez-Espiñeira, 2002). Hence, we
expect a positive sign for the coefficient associated with the temperature variable and a
negative sign for the coefficient associated with the rainfall variable.
The main focus of our analysis is, however, on the drought variables. Thus, we
include a dummy variable that takes a value of 1 for the period in which concerns about
the drought were most severe and the regional government implemented a public
campaign to save water. In our case, it ran from February 2007 to May 2008. Given that
the public campaign was implemented in the drought period, we should interpret the
coefficient of this variable as a combination of the policy effect and the drought effect.
Additionally, we include a dummy variable for the subsequent, post-drought period,
by which time the public campaign had terminated. This period ran from June 2008 to
December 2011. Although we control for price and tax increases, there was a
particularly marked hike in prices and taxes in 2012 making it more difficult to isolate
the effect of prices for that year. However, virtually no changes in water prices were
introduced in the period from February 2007 to May 2008, while the price increase in
the period from June 2008 to December 2011 was only 2% in annual terms. Tax
increases are of similar magnitude in the three sub-periods considered (before, during
and after the drought episode). Therefore, all in all, price and tax increases should not
play a primary role in reducing water consumption during these different periods.
Consumers’ water conservation attitudes and habits may play a role in explaining
residential water consumption (Gilg and Bar, 2006). In this regard, several studies have
shown that domestic water-saving devices and garden irrigation technologies can help
save water (see, for example, Campbell et al., 2004; Renwick and Archibald, 2004;
Kenney et al., 2008; Randolph and Troy, 2008). Thus, our hypothesis is that a severe
drought episode along with a public communication campaign implemented to save
water during such episode served to increase consumers’ environmental awareness in
8
the post-drought period. Here, therefore, we seek to examine whether the impact of the
drought and the campaign had not only an immediate effect but also a longer term effect
on water consumption.
In interpreting the results for the drought variables, reference should be made to two
previous studies conducted in the municipalities of the Metropolitan Area of Barcelona,
namely, Domene and Saurí (2006) and March et al. (2013). The first of these authors
drew on data obtained from interviews conducted in 2004 with 532 households in 22
municipalities. They used these data to construct a conservation index based on the
following practices that served as explanatory factors of water consumption: the
installation of water-saving devices in taps, toilets and showers; turning off running
water while brushing one’s teeth, the purchase of water-efficient appliances and the
consultation and comparison of water consumption between periods. They found that
domestic water consumption fell significantly as the number of water conservation
practices increased.
March et al. (2013) conducted interviews with 437 households in the Metropolitan
Area of Barcelona in November 2009 to obtain information about perceptions of the
2007-2008 drought episode. A high proportion of those interviewed claimed to have
adopted one or more measures to reduce their water consumption (such as spending less
time in the shower, switching the tap off while brushing their teeth/soaping up, or
reducing the time spent washing their hands) during the drought. Other actions that
ranked high included using washing machines/dishwashers at full capacity, while
installing diffusers in taps or devices in toilets where used to a lesser extent. Most of the
residents adopting actions in response to the drought claimed to have maintained them
even after the episode had passed.
Based on these earlier reports, the aim of our empirical analysis is to assess whether
per capita domestic water consumption continued to fall even after the drought episode
and the consequent campaign launched had terminated. At the same time, we conduct
this analysis while controlling for all the explanatory factors taken into consideration in
previous studies of water consumption.
Finally, we include dummies in the regressions for all months and years, the former
to control for those seasonal effects not already captured by the climate variables and
the latter to control for the common trend for all municipalities in the dataset. We also
include dummies in some of the regressions for the municipalities to control for timeinvariant municipality-specific omitted variables. εkt is a mean-zero random error term.
9
3. DATA
The dataset used contains monthly data from 23 municipalities in the Metropolitan Area
of Barcelona for the period 2004-2012. The Metropolitan Area lies in the Province of
Barcelona, within the Autonomous Community of Catalonia, Spain. In the figure below
the 23 municipalities included in the analysis are presented.
Insert Figure 1 about here
The dataset was built by merging information from different sources. Domestic
consumption of water per municipality and the tariffs charged during the period were
provided by Aigües de Barcelona, the supplier firm (which accounts for the fact that
tariffs were identical for all municipalities in the sample). Information on taxes has
been obtained from the Agència Catalana de l’Aigua (a public agency that acts as
regulator of the sector in Catalonia). Taxes are also identical for all municipalities in the
sample. In fact, these municipalities were chosen as the basis for the sample because of
the greater availability of water consumption data. Our sample has the added advantage
of the fact that prices and taxes play only a modest role.
The dependent variable, the per capita domestic consumption of water, was built
with population data for each municipality obtained from the Barcelona provincial
council. The same source also provided the explanatory variable of population density
(population/km2) as a proxy for the housing characteristics, the unemployment rate, the
percentage of immigrants (foreign) and the percentage of people over the age of 65. The
household size (average number of members) was built with population data and the
number of residential buildings published in the cadastral survey of Spain. The climate
factors of average temperature (ºC) and rainfall (mm) were provided by the
Meteorological Services of Catalonia. However, as not every municipality has a weather
station, six climatic zones were created using a distance criterion. Finally, policy
variables were created in line with the information provided in Martin-Ortega and
Markandya (2009).
Figure 2 shows the evolution of the dependent variable – the per capita consumption
of water – for the whole panel. This shows that the mean per capita consumption ranged
from 4 m3 at the beginning of the period to 3 m3 in 2012, falling by 20 per cent between
2004 and 2012. Moreover, it can be seen that together with a fall in mean consumption,
10
the data were more heavily concentrated around this mean value in the latter years of
the period and more dispersed in the earlier years, indicating a convergence in water
consumption rates across the municipalities during the period. The outliers correspond
to five municipalities (Begues, Castelldefels, Pallejà, Sant Just Desvern and Torrelles de
Llobregat), primarily reflecting consumption in the summer months.
Insert Figure 2 about here
Interestingly, four of these five outliers in our sample (Pallejà, Castelldefels, Begues
and Torrelles de Llobregat) present the greatest reduction in per capita consumption of
residential water between 2004 and 2012, having begun the period with the highest
rates. This is illustrated in Figure 3 below, where the change in per capita consumption
by municipality for this period (vertical axis) is contrasted with the per capita
consumption in 2004 (horizontal axis). Moreover, it is evident that water consumption
has fallen by more than 10% for all the municipalities in the sample, the greatest
occupying a band of reduction of between 15 and 20%.
Insert Figure 3 about here
Table 1 presents the descriptive statistics of the principal variables. Across the entire
period, the mean per capita consumption of the selected municipalities is around 3.5 m3.
Recall, as pointed out in the introduction, that according to the International Water
Association, the city of Barcelona has one of the lowest rates of per capita consumption
among all of Europe’s largest cities. This was the case even in the period prior to the
severe drought episode of 2007-2008. The mean rate of per capita water consumption in
the city of Barcelona is 3.35 m3, which is similar to the mean for all the municipalities.
Thus, we are dealing with municipalities that have low rates of domestic water
consumption at least in comparison to the rest of Europe. Likewise, the variation in per
capita water consumption across municipalities is quite similar to the variation within
the municipalities over time.
Insert Table 1 about here
The explanatory variables can be aggregated into two groups: those that vary
considerably across the municipalities and those whose mean is more closely
representative of all the municipalities but which vary over time. As expected, in the
first group we find those variables that control for differences across municipalities:
population, density of population, , per capita income, percentage of foreign population,
11
percentage of elderly population and household size. In these cases, the standard
deviation between the municipalities accounts for most of the deviations around the
mean value. However, the degree of dispersion of the values around the mean varies
considerably from one variable to another. Those that present the greatest variability are
population, density of population and the number of hotel beds per inhabitant while
household size is the variable with the lowest variation coefficient.
In the second group we find the following variables: the unemployment rate, median
temperature and total rainfall. These are fairly homogeneous across the municipalities
but do vary over time. Within this group, the variable that shows greatest dispersion
around the mean is total rainfall.
4. ESTIMATION AND RESULTS
In this section, we address a number of econometric considerations, given that the
estimates may present problems of heteroscedasticity, non-stationarity and temporal
autocorrelation, and we discuss the results of the regressions. Our application of the
Breusch-Pagan/Cook-Weisberg test under the null hypothesis of constant variance
indicated that there could be a problem of heteroscedasticity that requires correction.
We also applied the Wooldridge test for autocorrelation in panel data that showed that
we may have a problem of serial autocorrelation. Finally, we applied a panel unit root
test which can be regarded as an augmented Dickey-Fuller (ADF) test when lags are
included with the null hypothesis of non-stationarity I(1) behavior. This test with one
lag indicates that there is no non-stationarity problem with our dependent variable.
We estimated a pooled linear regression with panel-corrected standard errors with
two different specifications: one without the dummies for municipalities, the other with
the dummies of municipalities. Recall that these dummies control for time-invariant
municipality-specific omitted variables. Hence, they may be correlated with several
explanatory variables that are characterized by low within variation, including for
example income per capita or household size. As such, the first specification arguably
captures the individual effect of the control variables more appropriately. However, the
advantage of the second specification is that by adding controls (omitted factors that are
municipality-specific) we can be more confident of our results for the policy variables.
The regressions use a panel-specific AR-1 autocorrelation structure and assume panellevel heteroscedastic errors.
12
We did not undertake the estimation using the fixed effects model (within
regression). With this technique, estimates of regressors are very imprecise if most of its
variation is cross sectional rather than over time as it is the case of several explanatory
variables of the equation to estimate. Furthermore, the within variation captured by the
fixed effects regression is monthly, so that such regression may not capture
appropriately the individual effect of several explanatory variables that vary only at the
annual level. Note that the main advantage of the fixed effects model is that it allows us
to control for any omitted variables that correlate with the variables of interest and
which do not change over time but we already control for time-invariant omitted
variables with the inclusion of dummies of municipalities.
Table 2 shows the correlation matrix of the variables used in the empirical analysis.
The correlation between the control variables and the policy variables is generally low.
The only exception is the unemployment rate, which presents a correlation of 0.50 with
the dummy variable in the years following the termination of the public campaign to
save water. However, the computation of the variance inflation factors, which reports
values well below 5 for all variables, shows that there we have no problem of
multicollinearity distorting the individual identification of the explanatory variables.
Insert Table 2 about here
Table 3 shows the results of the estimates of the water consumption equation. Results
are very similar regardless we include or not the dummies of municipalities. The overall
explanatory power of the model is very high. Hence, we can be confident that no
omitted variable is distorting the results of the regressions.
Insert Table 3 about here
In general, the control variables work as expected. The coefficient of the income
variable is positive and statistically significant. Thus, water consumption increases with
income as expected. In contrast, the coefficient of the unemployment variable is positive
and statistically significant. Controlling for income, it seems that domestic water
consumption is higher in municipalities with a higher proportion of unemployed people.
A possible explanation for this result is that the unemployed may spend more time at
home.
The coefficients of the household size and density variables are, as expected,
negative and statistically significant. Hence, it is confirmed that outdoor uses of water
are lower in denser municipalities, while we find evidence of economies of size. Note
13
also that the coefficients of the variables for the percentage of the elderly and foreign
people are also statistically significant.
The coefficient of the price variable is negative and statistically significant.
According to expectations, domestic water consumption falls as the price of the
commodity rises. Additionally, the results for the climate variables confirm our a priori
expectations: the coefficient of the mean temperature variable is positive and
statistically significant, while the coefficient of the total rainfall variable is negative and
also statistically significant.
In the case of the main variables of interest in our analysis, we find that the drought
episode and the public campaigns launched in such episode to save water have had
important effects on consumption. The coefficients of both drought variables are
negative and statistically significant in all regressions. The reduction in domestic water
consumption per capita during the drought period was between 2.2 and 2.4%, while the
reduction in the subsequent period was between 4.6 and 4.9%.
Note that these dummy variables need to be interpreted in relation to the reference
case, i.e., the period prior to the drought episode. Thus, what these figures are saying is
that per capita domestic water consumption was about 2% lower in the period of
drought and intensive communication campaigns than consumption in the previous predrought scenario, while an additional 2% reduction was recorded in the period once the
drought episode and communication campaigns had ended in relation to the pre-drought
scenario. Hence, we find evidence that the drought and the public campaigns to save
water may have been successful in increasing consumers’ environmental awareness.
Although these coefficients may appear low, the reduction in water consumption in
the municipalities of the Metropolitan Area of Barcelona recorded here are fairly
remarkable if we take into account that consumption levels in the period prior to the
drought were already below European mean values.
The reduction in the domestic water consumption per capita found here is also
remarkable given that outdoor uses represent a very small proportion of total per capita
water consumption in most of the municipalities in our sample. To test this further, we
ran additional regressions in which we excluded those municipalities in which we
expected outdoor uses to represent a higher proportion of total water consumption. The
municipalities excluded are those occupying the lowest range in terms of population
density (Begues, El Papiol, Pallejà, Sant Climent de Llobregat, Santa Coloma de
Cervelló, Torrelles de Llobregat) and Castelldefels, a municipality with a population
14
lower than the mean in our sample but also the municipality with the highest density of
swimming pools (Vidal et al., 2011).
Table 4 shows the results of these additional regressions using the restricted sample
with an absolute predominance of indoor uses. For the sake of simplicity, we only
report results for the drought variables. The results for the control variables are
qualitatively identical to those obtained in the regressions with all municipalities.
Interestingly, the reduction in per capita water consumption is lower than that obtained
in the regressions with the whole sample. In relation to the pre-drought period, the
reduction in domestic water consumption per capita is slightly less than 2% during the
period in which the regional government implemented the public communication
campaign and slightly more than 2% subsequently.
Insert Table 4 about here
In the case of this restricted sample, the results of the regressions indicate that there
was no a substantial additional reduction in water consumption in the period subsequent
to the communication campaigns in relation to the drought scenario. Indeed, per capita
water consumption was at similar levels during and after the drought episode. Thus, the
additional reduction in water consumption that we found in this later period in the
regression for the whole sample could be attributed to those municipalities in which
outdoor uses are more predominant. This would seem logical as the change in consumer
attitudes and habits with regard to indoor uses may have meant that water consumption
in the post-drought period was lower than in the pre-drought period; however, it is more
difficult to justify the lower water consumption in the post-drought period than during
the drought episode itself. The scope for reduction in water consumption is logically
more important in the case of outdoor uses.
Recall that several policy measures were implemented during the drought, including
a ban on such outdoor uses of water as the irrigation of gardens and swimming pools.
Thus, it is unsurprising that the reduction in per capita water consumption during and
after the drought period was lower in high-density municipalities than it was in
municipalities where outdoor uses are more prevalent. Yet, the reduction in water
consumption in the restricted sample is still significant both statistically and
economically. Hence, we can confirm that there was a reduction in water consumption
even in municipalities where outdoor uses of water are minimal.
15
5. CONCLUDING REMARKS
In this paper, we have estimated a water consumption function to examine the longterm effects of a severe drought episode on domestic water consumption. Controlling
for several explanatory factors, we have found that water consumption fell during, as
well as after, the drought episode in a sample of municipalities characterized by their
low water consumption in the pre-drought period and in which indoor uses of water are
clearly predominant.
The results of our analysis suggest that the reduction in per capita water consumption
that was recorded even after the campaigns had finished cannot be explained by income,
prices or the changing nature of the socio-demographic variables typically used in the
literature to explain water consumption. The reduction in water consumption was still
significant when we focused on those municipalities with an absolute predominance of
indoor water uses.
A potential limitation of our analysis is that the drought and the related
communication campaigns affect all the municipalities in the sample to the same
degree. In this regard, it would have been beneficial to have identified the effects of the
campaigns by working, on the one hand, with a sample affected by them, on the other,
with a sample of municipalities that were unaffected or affected to a lesser degree. Yet,
the overall explanatory power of our model is high and we have not detected any
problems of multicollinearity of the control variables with the policy variables. As such,
we are able to claim that we have identified the specific effects of the drought variables.
While the results of our analysis suggest that the public communication campaigns
launched in response to the drought episode have been successful in reducing the
consumption of water, it is unlikely that future droughts can be addressed with similar
measures. After all, domestic consumption levels in the Metropolitan Area of Barcelona
would appear to be close to their minimum threshold if we bear in mind that indoor uses
are dominant. As an alternative, measures designed to increase water supply may be
needed to avoid future crises that threaten the supply for essential uses.
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19
TABLES AND FIGURES
Figure 1. Sample Municipalities within Catalonia, Barcelona Province and Metropolitan Area of
Barcelona.
Catalonia
Barcelona Province
Excluded and Included Municipalities
Excluded and Included Municipalities
Metropolitan Area of Barcelona
Excluded and Included Municipalities
Sant Just Desvern
Pallejà
Montcada i Reixac
Cerdanyola
Montgat
Sant Feliu
Papiol
Badalona
Santa Coloma de Cervelló
Barcelona
Torrelles
Santa Coloma de Gramenet
Sant Adrià de Besòs
Esplugues
Included
No data
Sant Climent
L'Hospitalet
Cornellà
Begues Gavà
Sant Joan Despí
Sant Boi
Castelldefels
Viladecans
2
4
(m3)
6
8
10
Figure 2. Residential water consumption per capita in sample Municipalities. Years 2004-2012.
2004
2006
2008
2005
2007
2009
Source: Aigües de Barcelona and Barcelona City Council
20
2010
2012
2011
Figure 3. Growth rate of residential water demand years 2004-2012, given initial consumption.
-10
Sant Adriá de Besòs
Barcelona
-15
Growth rate 2012-2004 (%)
Hospitalet de Llobregat
Cornella deBadalona
Llobregat
Montgat
Viladecans
Esplugues de Llobregat
Santa Coloma de Gramenet
Cerdanyola
del Vallès
Montcada
i Reixac
Sant Feliu de Llobregat
Sant Joan Despi
Sant Boi de Llobregat
-20
Sant Just Desvern
Gavà
El Papiol
Sant Climent de Llobregat
Santa Coloma de Cervelló
Castelldefels
-25
Palleja
Begues
-30
Torrelles de Llobregat
40
50
60
70
Consumption per capita 2004 (m3)
Source: Aigües de Barcelona and Barcelona City Council
Table 1. Descriptive Statistics. Dependent and Explanatory Variables
Mean
Variable
Std. Dev.
Variation
Min
Max
Coef.
Consumption
Population
Density
Income
overall
0.7197
0.202
2.501
8.869
between
0.5239
0.147
3.003
4.836
within
0.5053
0.142
1.777
7.5978
322666.1
2.612
3366
1621537
between
329834.6
2.67
3670.10
1607278
within
3263.895
0.026
94800.61
137791.6
5843.99
1.044
105
20858
between
5972.70
1.067
118.78
20483.78
within
128.15
0.023
5127.45
5973.454
2515.52
0.176
10504
23268
2404.3
0.169
11432.67
21703.89
overall
overall
overall
between
3.56
123533.1
5599.23
14252.2
21
within
892.33
0.063
10139.31
15988.75
0.04261
0.414
0.0379
0.22
between
0.02143
0.225
0.0680
0.1447
within
0.03704
0.361
0.0470
0.1917
0. 1036
0.040
2.28375
2.747
between
0.0978
0.038
2.335078
2.676
within
0.0399
0.015
2.430616
2.653
5.28
0.525
2.14
23.26
between
5.06
0.504
2.67
20.72
within
1.82
0.181
2.336667
13.93
2.485
0.145
12.45
23.33
between
2.434
0.142
12.66111
22.58
within
0.7098
0.041
15.00604
18.92
2.91
0.209
8.7
21.08
between
2.88
0.207
9.183333
20.69
within
0.716
0.051
12.17797
16.31
5.87
0.366
4.4
27.2
between
0.815
0.051
13.525
16.79
within
5.81
0.363
6.054257
27.35
43.906
0.961
0
223.6
between
3.711
0.081
40.41143
51.53
within
43.76
0.957
-5.635884
219.53
0.0897
0.962
0.0167
0.331
between
0
0
0.0933
0.0933
within
0.0897
0.962
0.0167
0.331
Unemployment overall
Household size overall
Foreign
Young
Old
Temperature
Rainfall
Price
overall
overall
overall
overall
overall
overall
0.1027
2.57
10.053
17.123
13.92
16.04
45.698
0.0933
Note: The total number of observations is 2484 in which the number of municipalities is
23 and the time periods are 108. The number of observations is only lower for the
variables of temperature and rainfall because of missing data; we have 2468 observations
for temperature and 2461 for rainfall.
22
Table 2. Correlation matrix of the variables used in the empirical analysis
Con.
Fore
Inc.
Une.
Old
Price
Dens.
Temp
Rain
Consumption
1
Foreign
-0.25
1
Income
0.29
0.27
1
Unemployment
-0.48
0.007
-0.19
1
Old
-0.48
0.58
0.02
0.37
1
Price
-0.19
0.11
0.13
0.46
0.14
1
Density
-0.40
0.72
-0.17
0.25
0.78
0.01
1
Temperature
0.16
-0.002
-0.01
0.02
0.02
0.02
0.003
1
Rainfall
-0.09
0.01
0.03
0.06
-0.01
-0.07
-0.02
-0.03
1
Household_size
Ddrought
-0.23
-0.19
-0.15
-0.06
0.13
-0.16
0.13
0.04
-0.05
1
drought
0.0007
-0.007
0.11
-0.33
-0.03
-0.06
-0.002
-0.04
0.002
-0.02
1
post-drought
-0.22
0.20
0.12
0.50
0.07
-0.18
0.01
0.04
0.12
-0.09
-0.34
D
D
house
23
Dp-drought
1
Table 3. Results of estimates of the water consumption equation (all sample)
Dependent variable: Water Consumption per capita
Explanatory variables
Municipality dummies
Panel corrected
standard errors (PraisWinsten Regression)
0.000032
(1.68e-06)***
0.85
(0.17)***
-0.32
(0.02)***
-5.44e-06
(8.19e-07)***
-0.022
(0.0023)***
0.004
(0.0007)***
-0.25
(0.07)***
0.0043
(0.0008)***
-0.00019
(0.00002)***
-0.024
(0.011)**
-0.049
(0.014)***
1.70
(0.07)***
NO
Panel corrected standard errors
(Prais-Winsten Regression) with
dummies of municipalities
0.000024
(6.07e-06)***
0.84
(0.17)***
-0.29
(0.05)***
-0.000011
(1.98e-06)***
-0.014
(0.003)***
0.005
(0.0014)***
-0.24
(0.06)***
0.0041
(0.0009)***
-0.0002
(0.00002)***
-0.022
(0.011)**
-0.046
(0.014)***
1.67
(0.15)***
YES
Year dummies
YES
YES
Month dummies
YES
YES
0.95
6602.95***
0.95
7201.87***
Income per capita
Unemployment_rate
Household_size
Density of population
Percentage of old population
Percentage of foreign population
Water_price_increases
Mean temperature
Rainfall
Ddrought
Dpost-drought
Intercept
2
R
Joint significance test (Ho: No overall
significance)
ADF test (Ho: nonstationarity I(1)
-0.21***
-0.21***
behavior)
Wooldridge test (Ho: No serial
99.498***
95.496***
autocorrelation)
Breusch-Pagan/Cook-Weisberg test
972.28***
1224.40***
(Ho: Constant variance)
Number observations
2459
2459
Note 1: Regressions use a panel-specific AR-1 autocorrelation structure and assume panellevel heteroskedastic errors.
Note 2: Statistical significance at 1% (***), 5% (**), 10% (*)
Table 4. Results for policy variables of estimates of the water consumption equation
(excluding the municipalities with higher outdoor use)
24
Dependent variable: Water Consumption per capita
Explanatory variables
Municipality dummies
Panel corrected
standard errors (PraisWinsten Regression)
-0.019
(0.007)***
-0.025
(0.009)***
NO
Panel corrected standard errors
(Prais-Winsten Regression) with
dummies of municipalities
-0.016
(0.007)**
-0.023
(0.009)***
YES
Year dummies
YES
YES
Month dummies
YES
YES
R2
Joint significance test (Ho: No overall
significance)
0.98
10342.13***
0.98
13833.86***
Ddrought
Dpost-drought
Number observations
1710
1710
Note 1: Regressions use a panel-specific AR-1 autocorrelation structure and assume panellevel heteroskedastic errors. Note 2: Statistical significance at 1% (***), 5% (**), 10% (*)
25
Appendix
Table A1. Chronology of main events and measures during the 2007-2008 drought episode
in Catalonia
Date
Main Events
Main measures
End 2006
First warning reports on
Establishment of the drought
Jan 2007
significant lack of
management plan and the drought
precipitation Reserves at 52% permanent committee
of capacity
Feb 2007
Persisting lack of
First public communication campaign
precipitation
for water saving
Mar-Apr 2007
Drought Decree by the
15% decrease of irrigation resources
Catalan Government
Cancellation of spillovers for purely
hydroelectric uses
Intensified user controls & waste-water
restrictions
All drought related information is
published in the river basin authority
website
May-Aug 2007
Reserves at 40.5% of capacity General water saving measures
(restrictions in public use of water:
gardening, swimming-pools, etc)
Public warning campaign +
communication campaign (letter, fax,
telephone) to households
Sept-Dec 2007
Reserves at 30% of capacity
Actions for groundwater use
Drought Decree prorogued
New communication campaign
Jan-Feb 2008
Reserves at 24% of capacity
Prohibition on the use of potable water
for municipal use (gardens,
recreational parks, etc)
Periodic press conferences by the
Catalan Minister of Environment to
inform on the drought
Distribution of 650.000 water-saving
kits among the population
Mar 2008
Reserves at 21% of capacity
Set up of an specific drought website
Organization and contracting (www.sequera.gencat.cat) + a
of water shipping from
telephone information system for users
Tarragona and Marseille
Apr 2008
Precipitations
Constitution of the Drought Committee
May 2008
June 2008
Precipitations. Reserves at
29% of capacity
Recovery of water reserves
(58.5% of capacity)
Source: Ortega and Markandya (2009)
26
Water shipping
Water shipping ends
Catalan drought derogated later (jan
2009) but not more water demand
measures since June 2008