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Demand for household water in Buon Ma Thuot, Viet Nam evidence from households’ revealed and stated preferences ESTIMATING HOUSEHOLD WATER DEMAND USING REVEALED AND CONTINGENT BEHAVIORS EVIDENCE FROM[.]

ESTIMATING HOUSEHOLD WATER DEMAND USING REVEALED AND CONTINGENT BEHAVIORS: EVIDENCE FROM VIET NAM Jeremy Cheesman 1, Jeff Bennett and Tran Vo Hung Son Abstract: This article separately estimates water demand by households utilizing (i) municipal water exclusively and (ii) municipal water and household well water in Buon Ma Thuot, Viet Nam Demand estimates are obtained from a panel dataset formed by pooling household-level data on observed municipal water purchases and stated intended water usage contingent on hypothetical water prices Estimates show households using municipal water exclusively have very price inelastic demand, whereas households using both municipal and household well water have more price elastic, but still inelastic, simultaneous water demands and readily substitute between water sources in response to increasing prices Household water usage is conditioned by water storage and supply infrastructure, income and socio-economic attributes The demand estimates are used for forecasting municipal water usage as well as the municipal water supply company’s likely revenue stream following an increase to the municipal water tariff and also for modeling consumer surplus losses from municipal water supply disruptions Keywords: urban water demand, household production function, revealed preference, contingent behavior Research Associate, Crawford School of Economics and Government, Australian National University, Canberra 0200 AUSTRALIA Professor, Crawford School of Economics and Government, Australian National University, Canberra 0200 AUSTRALIA Head, Environmental Economics Unit, University of Economics Ho Chi Minh City, Ho Chi Minh City, VIET NAM Household water INTRODUCTION demand analyses are an economic cornerstone for demand side water management, developing efficient water tariff schedules and water infrastructure cost benefit analyses Meta-analyses profiling the household water demand literature concentrate on developed country applications (Espey et al 1997, Arbues et al 2003, Dalhuisen et al 2003) These applied studies from developed countries mainly estimate demand from households’ observed water purchases from a single municipal water supplier, municipal water’s multi-part block tariff, household income, socio-economic attributes and sometimes climatic and structural factors, typically finding household water demand is both price and income inelastic Household water’s price and income inelasticity is normally linked to water being a non-substitutable input in many household uses and also because household water expenditures only account for a small percentage of most households’ budgets (Arbues et al 2003) Less work has been directed towards estimating household water demand in less developed countries (LDC’s) Strand and Walker (2005) estimated a –0.32 household own price elasticity using a survey dataset from 17 cities in Central America and Venezuela Their analysis shows households drawing water from more than one source have source specific water demand and also that in-household water infrastructure is a stronger demand determinant than water price Using data from seven Cambodian towns, Basani, Isham et al (2008 forthcoming) estimated households’ own price elasticity for municipal water supplies between -0.40 and -0.50 Combining household data from El Salvador and Honduras, Nauges and Strand (2007) estimated non-tap water demand elasticities as a function of water cost, defined as the sum of water’s purchase price and hauling costs, between -0.40 and -0.70 Rietveld, Rouwendal et al (2000) estimated an own price elasticity of -1.2 for a cross-section of Indonesian households Acharya and Barbier (2002) estimated linear water demands for Nigerian households that (i) exclusively collected water, (ii) exclusively purchased water from vendors, or (iii) hauled and purchased water Households purchasing water exclusively had an estimated own price elasticity of –0.067, whereas collecting and purchasing households’ own price elasticity for purchased water was –0.073 Estimating price elasticity requires that water’s price varies However, water may be purchased at a constant price, as is the case when a municipal water supplier charges the same tariff for every cubic meter of water it delivers, or unpriced, in the sense of not having a tariff, as occurs when a household draws its water from a private well Both of these situations complicate household water demand estimation, but both, and especially the latter, are frequently features of household water use in LDC’s Stated preference techniques can be applied for constructing the price usage relationships needed for estimating household water demand functions in both these situations (Freeman 2003) Stated preference techniques construct hypothetical markets, using these for simulating respondents’ preferences for scarce resource allocation When available, households’ real water purchasing histories, such as their water bills, can be used as an empirical anchor point for investigating each household’s likely water usage in novel water pricing situations Confirming convergent validity between a household’s observed water purchases and stated preferences shows the same underlying preference structure is being used for making actual and hypothetical water purchases Analyses pooling revealed and stated preference data (Adamowicz et al 1994, Ben-Akiva et al 1994, Englin and Cameron 1996, Adamowicz et al 1997, Huang et al 1997, Acharya and Barbier 2002, Boxall et al 2002, Earnhart 2002, Hanley et al 2003) generally show pooling increases estimated parameters’ efficiency and robustness, especially when estimates are based on small datasets (Englin and Cameron 1996, Haab and McConnell 2003, Hanley et al 2003, Birol et al 2006) This article households estimates using (i) demand municipal for water delivered exclusively water by and (ii) municipal water and household well water in Buon Ma Thuot (BMT), Viet Nam Buon Ma Thuot is located in Viet Nam’s Central Highlands region and is Dak Lak Province’s largest town The municipal water supply system was upgraded and expanded in 2003, resulting in connected households increasing their municipal water usage, and thereby diverting scarce water away from the region’s irrigated agriculture sector The Buon Ma Thuot Water Supply Company (BMTWSC), the autonomous State agency responsible for operating the municipal water supply system, is meant to operate at full cost recovery The fixed VND2,250 (USD1  VND15,500) per cubic meter tariff it charges is less than the VND4,000 per cubic meter average cost it estimates it incurs for delivering water to BMT’s households however All households receiving municipal water supplies in BMT are metered and have their monthly household water bills calculated from their metered usage Approximately 75 percent of all permanent households in BMT are now connected to the municipal water supply system A percentage of households already connected to the municipal system combine municipal water and water from at least one alternative source, such as private wells or water vendors Little is known about households’ usage patterns from non-municipal water sources in BMT nor why households may prefer these sources’ water to municipal water Madanat and Humplick (1993) found that households had preferences for water by source in specific uses and it is reasonable to expect the same thing here For example, BMT’s households may prefer using municipal water for cooking and well water for drinking because they believe municipal water tastes and smells of chemicals Nothing is known about how households using secondary water sources would alter usage between sources when responding to changes in the attributes of either the municipal or secondary source’s water These substitution strategies carry important economic and water planning implications in BMT however, meaning a system of conditional water demands for households not using the municipal water source exclusively must be estimated This article’s main contributions lie first in developing the sparse literature on single and multiple source household water demand in Southeast Asia and second in the novel revealed and stated preference approach the article applies for estimating own and cross price elasticities for water when faced with an invariant municipal water price and unpriced household well water Household water demand estimates are constructed from a survey dataset pooling households’ actual observed water usage at the existing municipal water tariff and their stated water usage preferences contingent on hypothetical water prices The stated preference approach is based in the contingent behavior method, which works by eliciting individuals’ intended behavioral response to a hypothetical situation occurring, such as an increase in water price (Hanley et al 2003) Acharya and Barbier (2002) have previously employed a contingent behavior approach in estimating Nigerian households’ water demand as a function of real and hypothetical vendor water prices and water hauling times In the remainder of this article the conceptual household water demand model, estimation and survey approaches are first described Following a brief descriptive analysis of the survey data, household water demands are estimated from the panel dataset Policy implications are discussed in section five and the demand estimates are used to forecast household municipal water usage and the BMTWSC’s revenue following an increase to the municipal water price The consumer surplus losses imposed by binding water supply constraints are evaluated in section six in light of dry season water shortages that have historically plagued BMT Section seven concludes SPECIFICATION AND ESTIMATION TECHNIQUE 2.1 M ODELING HOUSEHOLD WATER USAGE Household water usage is a function of an underlying decision making process that takes water usage preferences and constraints on acquiring water into account (Larson et al 2006) When household labor is needed for collecting and preparing water, a household water demand model accounting for having to choose between allocating scarce household labor between water collecting and preparing usages and income generating work is required Acharya and Barbier (2002) formally model the joint consumer producer household’s decision making when two water sources are available, with one source being free but requiring labor input and the other priced and not requiring labor input The household seeks to maximize utility from water given the water sources available and the household’s income and labor constraints The end result is the household water demand function, conditional on water source: Q j Q j  p p , sc , A p , , A c , , Z  (1) where Q j is the water quantity used from source j, p p is the purchased water’s price, sc is the collected water’s shadow price, which is the marginal opportunity cost of foregone income from work, A p , , A c , are two vectors describing water quality attributes such as turbidity, smell and taste of priced and collected water respectively and Z is a vector of household specific characteristics, including income and labor potential When water is perfectly substitutable between sources, the utility maximizing household consumes water from both sources until the marginal rate of substitution from purchasing water and collecting water are equal, meaning the marginal opportunity cost of foregone work income equals the marginal water price This household decision framework includes two corner solutions: firstly, when the opportunity cost of foregone work income due to water collection and preparation always exceeds water’s marginal price the household consumes priced water only and secondly, when the marginal water price always exceeds labor’s marginal opportunity cost then the household always collects water 2.2 D EMAND 2.2.1 ESTIMATION H OUSEHOLD WELL STATUS Obtaining unbiased water demand estimates requires that households drawing water from wells in BMT so as a result of a random selection process It is possible however that latent variables determine whether a household has a well or not This potential source of sample selection bias is controlled for using Heckman’s (1979) two step estimation procedure In the first step the discrete choice dependent variable (di ) equals one if the household has a private well and zero if they not Assuming a normal probability distribution for the error term ( ui), the decision model in probit form is: Pr  d i 1 Pr  x i β u i   x i β  (2 ) where x i is a matrix vector of explanatory variables describing the household’s well status, β a vector of unknown coefficients to be estimated and   x i β  is the cumulative normal distribution The inverse Mill’s ratio is calculated with the probit model’s estimated parameters and included in the second stage household water demand estimates The inverse Mill’s ratio is: Mi   (3 )    are respectively the univariate standard where  . and normal      x i βˆ   x i βˆ cumulative distribution and the probability density functions 2.2.2 C ONDITIONAL HOUSEHOLD WATER DEMAND FUNCTIONS For households using the municipal water supply only, their conditional household demand function is assumed to be: (4 ) Whereas the households using water from both municipal and ln Qm c1  a1 ln pm  a2 Z  1 private well sources have the conditional simultaneous demands:  ln Qm c  bm1 ln p m  bm ln s w  bm3 Z     ln Qw c3  bw1 ln p m  bw ln s w  bw3 Z   Where the municipal water price is shadow price, Z describes pm , s w household (5 ) (6 ) is well water’s socio-economic characteristics including water supply infrastructure such as storage tanks and booster pumps and also the household’s inverse Mill’s ratio,  i the normally distributed idiosyncratic error term and the remainder are coefficients for estimating These demand specifications exclude costs from preparing water for use, such as filtering or boiling water before drinking, because descriptive analyses, to be discussed subsequently, suggest these are likely immaterial The demand equations also exclude water quality attributes, again because descriptive analyses showed BMT’s survey respondents viewed water quality as being near equal between municipal and household well sources and also because water quality perceptions are likely correlated with income and education (Whitehead 2005) EMPIRICAL APPLICATION Schedules of household water usage as a function of water prices are constructed in this analysis by pooling observed and contingent behavior data from Buon Ma Thuot’s urban and periurban households The observed behavior data is municipal water usage by households at the existing municipal water tariff The contingent behavior data is estimated by constructing how each household changes its water usage following hypothetical changes in water pricing Because all households receiving the BMTWSC’s municipal water are metered, this data can be used for cross-validating households’ own water usage estimates and also for anchoring the contingent behaviour scenarios Survey development is discussed in detail in Cheesman, Son et al (2007) The survey’s main objective was collecting household background data, including details on in-household water supply infrastructure, and estimating actual and contingent household water usage for BMT households’ seven main water usages, with these defined in pre-testing: (i) bathing and washing; (ii) preparing meals; (iii) drinking; (iv) cleaning; (v) laundry; (vi) outside (generally gardening); and (vii) home business For preferences estimating for water households’ by household revealed and stated usage, the survey enumerator first assisted the respondents in estimating their average daily household water usage by source for the seven household usages To this, the enumerator walked through the respondents’ household, identifying with the respondents where activities using water were occurring Following this initial identification, the enumerator worked with the respondents to estimate the amount of water used in each activity during a normal day Because different household members are generally responsible for specific water usages, both the male and female household heads participated where possible Having both household heads responding may reduce the potential for strategic behaviour because the respondents audited the other’s answers and there was open discussion on points of difference (Thomas and Syme 1988) The household members estimated their daily water usage via observation and demonstration For water usages that were not daily, weekly usage figures were estimated After household daily or weekly water usages in the seven main household extrapolated usages monthly were estimated, household water the usage enumerator and water expenditure by water source As a first step, the household’s estimated municipal water usage was compared to their latest available municipal water bill to check whether the respondents accurately estimated their monthly municipal water usage Then, for estimating the monthly municipal water cost by usage, each usage’s estimated monthly municipal water usage was multiplied by the VND2,250 per cubic meter tariff charged by the BMTWSC For calculating well water’s monthly cost by the seven household usages, estimated well water usage was multiplied by a volumetric shadow price of VND450 per cubic meter, which was the representative household’s calculated well water extraction cost defined by pre-testing The shadow price was constructed using labor and pumping fuel costs only, with these being constructed from the average daily wage and fuel price observed per month from this subgroup The same price increase would cause households with wells to increase well water usage by around 4.9 cubic meters per month and reduce municipal water usage from around 9.1 to 5.5 cubic meters, resulting in their average monthly municipal water bill rising from VND20,520 to VND22,041 Assuming these households account for 25 percent of the population with municipal connections, the BMTWSC’s monthly revenue stream increases from VND103 million to VND110 million from this subgroup This re-pricing scenario’s impact on municipal water expenditure as a percentage of total household budget is modest Municipal water expenditure as a percentage of average monthly income for households using municipal water exclusively rises from 1.4 to 2.3 percent in this scenario, and from 0.08 to 0.09 percent for households using municipal and household well water CONSUMER SURPLUS EFFECTS FROM QUANTITY RESTRICTIONS This final section considers the welfare impacts of municipal water supply shortages on Buon Ma Thuot’s households The analysis’ pertinence lies in the rolling dry season municipal water supply disruptions that have plagued BMT in recent years and also because Viet Nam’s Law on Water Resources requires priority based water allocations during times of regional shortage (Socialist Republic of Vietnam 1998) As long as constant elasticity does not equal –1.0, a consumer’s gross value of an increase in water supply from Q and Q1 is exactly defined by (Gibbons 1986: 17):    P *Q V  0   1      1 1  Q   Q         (9 ) P and Q define the initial price quantity locus,  is the own price elasticity of demand estimate, and Q is the incremented supply quantity Subtracting the water price paid isolates consumer surplus:  S V  p p  Q0  Q1   (10 ) Estimating with this approach shows consumer surplus losses from reducing total monthly household municipal supplies are more pronounced in households using municipal water only, which is to be expected (Table 5) More inelastic own price demand and the lack of source substitution opportunities result in greater consumer surplus losses for these households For example, reducing total monthly municipal supplies by three cubic meters to these households results in consumer surplus falling by around VND58,500, whereas the consumer surplus loss for households using municipal and household well water is VND3,600 CONCLUSION This article contributes to the limited but growing literature estimating household water demands by pooling revealed and stated preference data and also to the literature estimating household water demand in less developed countries Research estimates and related policy analysis are based on households’ observed municipal water purchases and contingent behavior data that extends understanding about household water usage to novel water pricing situations This article’s results suggest this approach can be used for recovering estimates of households’ (shadow) price elasticities for water from municipal and nonmunicipal water sources in developing countries Compared to other stated preference approaches, the contingent behavior method this article develops has the advantage of setting households’ responses in the familiar behavioral context of actual household water usage, which may reduce potential for hypothetical response bias When the contingent behavior approach is structured for allowing behavior revisions based on outcome feedback, as was the case in this research, the Discovered Preference Hypothesis (Plott 1996) and its supporting literature (Bateman et al 2004) predicts increasingly valid and stable preference estimates should be forthcoming Several limitations should be noted in this analysis First, the low percentage of respondents correctly stating the municipal water price shows it is clear that most responding households were learning water prices and their water demands as the survey proceeded The implication is that if a new water tariff schedule were implemented in BMT, most households’ actual behavioral changes following water tariff increases may not perfectly reflect their stated contingent behaviors One would expect actual demand to be more inelastic relative to stated demand in this case (Gaudin 2006) The research’s second limitation was the artificial well water shadow price used Because well water’s extraction costs will clearly differ between households that use well water, using a common shadow price may have sacrificed some incentive compatibility, implying respondents were simply playing by the rules of the game when estimating their household demands In Buon Ma Thuot, developing the municipal water supply system has resulted in urban and peri-urban households’ increasing their municipal water usage at smallholder irrigators’ deprivation As Rural Water Supply and Sanitation programs are implemented in other regional centers around Dak Lak Province, this pattern of rural-urban water transfers will likely be replicated When increasing urban water usage diverts scarce water from other uses, opportunity costs are created raising questions about the extent to which these transfers are