Domestc Water Use and Values n Swazland: A Contngent Valuaton Analyss S Farolf 1, RE Mabugu 2 & SN Ntshngla 3 Abstract The paper reports on the use of the contngent valuaton method to study the determnants of Swaz households wllngness to pay (WTP) for an mprovement n ther water quantty and qualty. A sample of 374 households was surveyed and a Tobt model was appled to explan household preferences for qualty and quantty of domestc water supply and derve estmates of WTP for such a servce. The results confrm that household ncome had a postve and statstcally sgnfcant mpact on WTP for both qualty and quantty. Dstance to the water source s postvely assocated wth WTP regardless of the locaton (rural or urban) and of the household head s age, educaton, and gender. Current water consumpton was also statstcally sgnfcant for WTP for mproved quantty, but wth a negatve sgn, mplyng that the more a household consumes water, the less that household s WTP to have mproved water quantty. Conversely, the same household would be WTP for mproved water qualty. Rural households showed a much hgher WTP for mproved water provson servces than urban households. There s therefore scope to mprove water servce levels n Swazland even at a hgher water prce. More precsely, the estmates of WTP obtaned n ths study ndcate the possblty of ntroducng a demand-drven program to expand the coverage of rural tap water schemes. 1. Introducton Water s ncreasngly becomng a scarce resource n Swazland (World Bank, 1993). Despte the fact that Swazland s a country traversed by fve major rvers wth mean annual ranfall ranges between 550 and 625 mm n the lowveld, and between 850 and 1400 mm n the hghveld, water s one of the major constrants to development (Government of Swazland, 2003a). A hgh proporton of the populaton (47%), resdng n rural and per-urban areas, 1 CIRAD UMR G-Eau and Center for Envronmental Economcs and Polcy n Afrca (CEEPA), Department of Agrcultural Economcs, Extenson and Rural Development, Unversty of Pretora, 0002 Pretora, South Afrca. stefano.farolf@up.ac.za 2 Center for Envronmental Economcs and Polcy n Afrca (CEEPA), Department of Agrcultural Economcs, Extenson and Rural Development, Unversty of Pretora, 0002 Pretora, South Afrca. 3 Department of Agrcultural Economcs, Extenson and Rural Development, Unversty of Pretora, 0002 Pretora, South Afrca. 157
does not have access to safe and clean water (Government of Swazland, 2003b). Natonal health statstcs n the country show that some nfant mortalty s related to water borne dseases, whch s a reflecton of the poor qualty of water. Ths has been evdent by the 2003 outbreak of typhod n rural areas, whch resulted n the deaths of sx people, four of whom were chldren (World Health Organzaton, 2002). In addton, Swazland s avalable fresh water resources are already almost fully utlzed and under stress (Seetal and Qubell, 2003). As the populaton ncreases, both wthn Swazland and n the surroundng regons, better management of water resources s requred n order to ensure ts contnued avalablty. The total number of households n Swazland n 2001 was estmated at 233 843, of whch 79 205 (34%) lve n rural areas and 154 638 (66%) lve n urban areas (Statstcs Swazland, 2002). Wth regards to domestc water supples n the urban areas, 89% of the populaton s provded wth treated water and 60% of the populaton has access to water-borne sewage systems or septc tanks. In the rural areas, n spte of substantal nvestments, coverage levels reman low largely because of poor mantenance of exstng water systems (Government of Swazland, 2003a). Thus, real water coverage n these areas s approxmately 30%. The majorty of rver gaugng statons are not functonal and water equpment s outdated (World Health Organzaton, 2002). As a consequence, regular montorng of the levels of polluton s also poor. Publc or prvate nvestments for mproved water-related servces, partcularly n rural areas, are therefore essental f better lvelhood condtons for local resdents are envsaged. To mplement these nvestments, decson-makers need nformaton about the possblty of adoptng an mpartal, cost-recovery strategy resultng from the applcaton of water tarffs to domestc users. The man objectves of the study on whch ths paper s based were to determne how much Swaz households are wllng to pay (WTP) for an mprovement n ther water qualty and quantty as well as establshng the possble factors affectng ther WTP. Specfcally, the study s desgned to: 1. Quantfy the WTP for mproved water qualty and quantty by the Swaz households n both rural and urban areas; 2. Investgate the determnants of ther WTP. Ths s n order to determne, n monetary terms, the value of mproved qualty and quantty of domestc water n the country and to provde an understandng of the factors that affect ths monetary value. Ths exercse s 158
essental to produce quanttatve economc nformaton on domestc water uses and value that polcy-makers may fnd useful n mplementng the Natonal Water Act (Government of Swazland, 2004). The rest of the paper s organsed as follows: Secton 2 develops the methodology and llustrates the data. Secton 3 presents the results and ther dscusson whle secton 4 concludes. 2. Theoretcal framework, modelng and samplng procedure Ths secton presents the model, methods and procedures used to conduct the study on whch ths artcle s based. The Contngent Valuaton Method (CVM) was selected for ts approprateness when dealng wth estmaton of non-use values. The CVM can be used to elct consumers' WTP for almost any envronmental good or servce, ncludng more abundant and cleaner water (Mtchell and Carson, 1989). Whttngton et al. (1993) have carred out contngent valuaton studes of households' WTP for mproved santaton servces. Banda et al. (2004) appled a CVM to analyse determnants of qualty and quantty values of water for domestc uses n the Steelpoort sub-basn of South Afrca. A Tobt model was appled to household survey data, to explan household preferences for qualty and quantty of domestc water supply and to derve estmates of WTP for such a servce. The Tobt model takes the followng functonal form (Tobn, 1958): ˆ ' y = x β + ε (1) where: y = y f y f 0 (2) or: = 0 yˆ 0 (3) y f The varable y s the observed contngent valuaton bd by ndvdual, ŷ s a latent measure, x are the ndependent varables, β s a vector of parameters and ε s the error term dstrbuted as ndependent normal wth zero mean and constant varance (σ 2 ). The explanatory varables n the regresson model are a set of varables dealng wth demographc characterstcs, soco-economc characterstcs, a set of dummy varables concerned wth whether the household s practcng avodance measures aganst water-borne dseases and on the presence of small chldren n the household. Ths method elcts the probablty and not the actual value of WTP, whch s subsequently calculated through descrptve statstcs. Followng Greene (1997), the WTP probablty s computed as: 159
Z e PY ( = 1) = Z 1 + e where: ' ' E( Y/ X) = 0[1 F( β X)] + 1[ F( β X)] (5) (4) and F(.) s the cumulatve densty functon. Irrespectve of the dstrbuton used, the margnal effect s obtaned as follows (Greene, 1997): ' EY ( / X) df( β X) = β = ' X d( β X) ' ( ) f β X β (6) The response for WTP s a bnary varable that takes the value 1 f the response to the queston s Yes and 0 f the response s No. Let the bnary varable be WTP and the underlyng latent varable be WTP*. Then the general formulaton of the emprcal Tobt model s gven as: WTP = β X + ε (7) * ' where X s a vector of explanatory factors n the regresson for the ndvdual, β s a vector of ftted coeffcents and WTP* s the stated WTP for ndvdual. Snce WTP* s not observed, t s the underlyng latent varable that s related to the observed WTP as follows: WTP = > and: * 1 f WTP 0 (8) WTP = 0 f WTP 0 (9) * An econometrc analyss was used to test the relatonshp between WTP and soco-economc factors. Questons were asked n an ordered, categorcal form and then were transformed nto bnary varables. The respondents were asked f they were WTP for a better quantty and mprovement n the qualty of water. Constructng realstc and meanngful scenaros, n accordance wth the needs of the study, mnmsed hypothetcal/scenaro ms-specfcaton bas. Informaton was provded about the symptoms of contamnaton, the health rsks and the cost of treatment, both n the short-term and followng prolonged use of contamnated water. Informaton was also provded about the dfferent 160
types of treatment technologes that could be used n Swazland. Ths was all done verbally durng the course of the ntervews. WTP can be functonally expressed as follows: WTP = f (WATCON, HHINC, HHSZ, EDN, WATSOC, PAB, SML, CLT, LOC, AGE, GENDER) or, n a lnear regresson form: WTP = β0 + β1 WATCON + β2 HHINC + β3 HHSZ + β4 EDN +β5 WATSOC + β6 PAB + β7 SML + β8 CLT + β9 LOC + β10 AGE + β11 GENDER + ε where: WTP s the probablty that households wll be WTP for quantty or qualty; WATCON s water consumpton expressed n m 3 /month/household; HHINC s household s monthly ncome expressed n Emalangen (E) 1 ; HHSZ s household sze expressed n number of ndvduals; EDN s the household head s level of educaton expressed n number of years spent n educaton; WATSOC s the water source for the household (1 for n-dwellng, 2 for collectve taps and 3 for rver water); PAB s a dummy varable ndcatng that the household s practcng avodance measures aganst water-borne dseases 2 (1 = Yes, and 0 = No ); SML s a dummy varable ndcatng the presence of small chldren n the household (1 = households wth chldren; 0 = households wthout chldren); CLT s the tme n hours/month spent collectng water wthn the household; LOC s a dummy varable ndcatng household s locaton (1=urban; 0=rural); AGE s the age of household head (n years); GENDER a dummy varable ndcatng the sex of household s head (1=female; 0=male); and ε s the error term representng the unpredcted or unexplaned varaton n the dependent varable and s assumed to be regularly dstrbuted. The target populaton of ths study was defned as households that use water for domestc purposes n Swazland. The study was conducted n the eleven man centres of the country 3. The centers ncluded one cty, three towns and seven small towns. The frst four centres are urban and the remanng seven are rural (Department of Urban and Rural Development, 2002). Data on populaton and number of households was obtaned from Statstcs Swazland (2002). Snce the study defned two types of households n Swazland, the stratfed and random samplng method was selected, wth urban and rural households beng 161
the two strata. A sample of 374 households was surveyed categorsed nto rural and urban based on the geographc and soco-economc characterstcs of the resdental centres 4. Ths method was chosen to dentfy ssues that may be relevant n explanng the dfferences n water use between rural and urban households. These ssues ncluded the percentage of formal dwellngs n the area, servces delvered to the communty, dstance travelled to the source of water and level of lteracy. 3. Results The study ntervewed manly the heads of the households (87% of the sample). Any household member avalable who was old enough to answer the questons satsfactorly composed the remanng 13%. The results of the observed average household characterstcs are shown n Table 1. Table 1: Mean characterstcs of the ntervewed household. Varable Rural Urban Age of household s head (years) 52.3 49.8 Level of educaton of household s head* 1 3 Famly sze 9 6 Average household ncome (E/month) 2 352 15 846 *(Level of educaton 5= Degree, 4= Dploma, 3= O level, 2= Prmary, 1= None). Respondents resdng n urban areas are younger than those lvng n rural areas, have hgher educatonal levels and hgher ncome. Households n rural areas are larger than those resdng n urban areas. 3.1 Water use The dfferent types of water users n Swazland may be delneated accordng to the source of water used (Table 2). Most people n rural areas rely on rver and collectve tap water, whlst prvate tap s manly found n urban areas. Table 2: Source of water for the ntervewed households Rural Urban Source of water Frequency Percent Frequency Percent Prvate tap water 10 8 229 93 Collectve tap water 49 39 18 7.2 Rver water 68 53 - - Total 127 100 247 100 The per capta consumpton of water was sgnfcantly dfferent between the two surveyed areas (urban and rural) for all water sources (Table 3). There s a 162
clear correlaton between the household s ncome and source of water. The hgher the ncome, the hgher s the probablty to have prvate tap water. Table 3: Per capta ncome and per capta water consumpton by source (per month) Rural Urban Source of water Per capta ncome (E) Per capta water consumpton Per capta ncome (E) Per capta water consumpton (m 3 ) (m 3 ) Prvate tap water 1470.7 3.9 4951.9 5.4 Collectve tap water 100 2.3 123.9 1.3 Rver water 94 2.9 - - Average 261 2.7 2641 5.1 3.2 Wllngness to pay When estmatng the odds of WTP for quantty, households n the rural areas appeared more lkely to be WTP than those n the urban area (Table 4). Only 6% were WTP for an ncreased quantty of water n the urban areas and these households were exclusvely among the few recevng ther water from the collectve tap. In the rural areas, 58% of the ntervewed households were WTP for an mproved avalablty of water. In both areas, households were WTP for a better qualty of water. The fgure was nevertheless agan much hgher n the rural areas (67%) than n the urban areas (20%). It s noteworthy that n both areas, there was a hgher WTP for mproved water qualty than for ncreased water quantty. Table 4: WTP (yes or no) for mproved water quantty and qualty Rural Urban WTP for mproved quantty Percent Percent No 42.0 93.9 Yes 58.0 6.06 WTP for mproved qualty No 33.3 80.1 Yes 66.7 19.9 For the households that were WTP, the study nqured about the amount of money they declared to be WTP for mproved water quantty and qualty. As Fgure 1 shows, there s a clear correlaton between WTP (for mproved quantty n the fgure) and ncome. The correlaton coeffcent between WTP for quantty and ncome was 0.23. Ths was lower than the correlaton coeffcent between WTP for qualty and ncome (0.51). 163
100 WTP for quantty (E/ month) 8 0 6 0 4 0 2 0 0 0 5000 10000 15000 Household Income (E / Month) Fgure 1: Correlaton between WTP for quantty and ncome of households (E/ month) Many households seem to assocate the avalablty of prvate tap water wth the drect and ndrect benefts that they may receve from t. For nstance, good qualty water supply (as tap water s consdered to be by most domestc users) would ndrectly beneft served households n the case of outbreak of dseases such as cholera. Avodance of medcal costs could result n a consstent beneft, not mentonng the workng hours ganed n the case of dsease avodance (McConnell and Ducc, 1998). These aspects, among others, mght therefore nduce respondents to realze the economc mportance of water and thus contrbute to ther WTP for a good qualty and quantty of water. Table 5 provdes a synthess of the amounts households would be WTP n Emalangen/household/month. It s nterestng to note that rural households are WTP a hgher amount of money for an mproved water quantty despte ther much lower ncome. On the other sde, urban households are more concerned wth (and WTP more for) an mproved water qualty. Table 5: WTP n Emalangen/household/month for mproved quantty and qualty of water Rural Urban Mean St. Dev. Mean St. Dev. WTP for quantty 7.13 10.34 6.82 17.72 WTP for qualty 6.44 7.93 16.40 27.73 164
3.3 Contngent valuaton approach Two regresson analyses were conducted adoptng the model llustrated n the secton above, where the probablty that the household would be WTP for hgher water quantty was the dependent varable for the frst regresson, and the probablty that the household would be WTP for an mproved water qualty was the dependent varable for the second regresson. Probablty of WTP was then related to a set of explanatory varables, ncludng varables on demographc characterstcs, soco-economc characterstcs and water use/sources of the surveyed households. In estmatng the determnants of WTP for mproved water quantty and qualty, some of the varables were not statstcally sgnfcant, hence the decson to drop them from ether the quantty or the qualty regresson model was taken. The statstcally sgnfcant varables for both WTP regresson models were: ncome, water consumpton, source of water, age and gender of the head of the household. Varables excluded from one model but ncluded n the other were: collecton tme and practce of takng avodance measures aganst water-borne dseases (dummy). Results of the regresson llustratng the probablty of WTP for mproved water quantty are summarsed n Table 6. Table 6: Tobt results of WTP for mproved water quantty Tobt estmates Number of obs = 332 LR ch2 (4) = 89.74 Prob > ch2 = 0.0000 Log lkelhood = -562.25188 Pseudo R2 = 0.0739 WTP quantty Coeffcent Std. Err. t P> t HHINC 0.0023869 0.0006784 3.52 0.000*** WATCON -3.12434 0.918313-3.40 0.001*** CLT 0.5708033 0.0789491 7.23 0.000*** WATSOC -18.21501 5.284404-3.45 0.001*** AGE 0.2747466 2.275221 0.12 0.029** GENDER 1.759339 1.230838 1.43 0.061* Constant -18.97918 7.339519-2.59 0.010 Standard error 31.83606 2.577452 (Ancllary parameter) Obs. summary: 234 left-censored observatons at WTP quantty <=0 98 uncensored observatons One, two or three astersks (*) means statstcal sgnfcance at the 10%, 5% and 1% test levels respectvely. The varable Household Income (HHINC) had a postve and statstcally sgnfcant, mpact on WTP for quantty 5. Households wth hgher ncome are therefore more wllng to pay for mproved water servces. HHINC was perfectly collnear wth the varable educaton level of the household s head, and thus the latter was dropped from the regresson model. 165
Water Consumpton (WATCON), was also statstcally sgnfcant, but wth a negatve sgn when regressed on WTP for quantty. Ths result s qute ntutve too. The negatve sgn means that the more a household consumes water, the less that household s WTP to have an mproved water avalablty n terms of quantty. Households consumng lttle water are those lvng n rural areas, charactersed by large szes and lower ncome. They are more lkely to be WTP for mproved water avalablty than ther urban counterparts, who already have more relable and better water sources. Collecton Tme (CLT), was also statstcally sgnfcant at all levels wth a postve sgn, as expected from the lterature (Marrett, 2002). Ths suggests a negatve relatonshp between avalablty of water and the dstance or tme taken to collect the water. Households walkng long dstances to collect water on a daly bass (from collectve taps but partcularly from the rver) are more lkely to be WTP for a nearby source. The varable Source of Water (WATSOC), was statstcally sgnfcant wth a negatve coeffcent for WTP for quantty. Households that have a regular supply of prvate tap water were less wllng to pay for mprovements n the quantty. These households are more lkely to choose to mantan the status quo. Conversely, the worse the opnon of the household about the water avalablty s (e.g rver water users), the more a household would be WTP for ts mprovement. These results are consstent wth the fndngs by Kolstad (2002). AGE and GENDER of respondents both had a statstcally sgnfcant and postve effect on the household s WTP. Older heads of households have hgher WTP for quantty than ther younger counterparts, whle male household heads have lower WTP than female household heads. Ths result could be explaned by the fact that older women are usually nvolved n collectng water. They are the ones who are most lkely to perceve the stran of walkng long dstances when collectng water. Results of the model for WTP for mproved water qualty are summarsed n Table 7. 166
Table 7: Tobt results of WTP for mproved water qualty Log lkelhood = -585.16578 Number of obs = 226 LR ch2(5) = 89.47 Prob > ch2 = 0.0000 Tobt estmates Pseudo R2 = 0.0710 WTP qualty Coeffcent Std. Err. t P> t LOC -77.37195 11.69755-6.61 0.000*** PAB 38.68821 6.638338 5.83 0.000*** AGE 0.1444255 0.0818122 1.77 0.078* GENDER 0.7601581 1.320938 0.58 0.066* HHINC 0.005284 0.000762 6.93 0.000*** WATCON 0.5685311 0.1794684 3.17 0.002** Constant 15.47005 7.381161 2.10 0.037 Standard error 34.65609 2.607959 (Ancllary parameter) Obs. summary: 120 left-censored observatons at WTP qualty <=0 106 uncensored observatons One, two or three astersks (*) means statstcal sgnfcance at the 10%, 5% and 1% test levels respectvely. The Locaton of the Household (LOC) s an mportant varable explanng household s WTP for mproved water qualty. The regresson coeffcent was statstcally sgnfcant. Ths mples that the rural respondents are more lkely to be WTP for water qualty mprovement than urban households. Ths result s consstent wth the prevous fndngs and s a consequence of the serous water qualty problems due to poor provson servces n the rural areas. The vector of varables for Presence of Small Chldren n the Household was dropped from the model because of a multcollnearty problem. Ths varable was perfectly collnear wth the varable Household Practcng Avodance Measures. However households wth small chldren seem hghly concerned wth health rsks posed by usng contamnated water. As a consequence, the regresson coeffcent for Practcng Avodance Measures (PAB), was statstcally sgnfcant at all three test levels and postve. Current Water Consumpton (WATCON), was statstcally sgnfcant and postve when regressed on WTP for qualty. Ths s an nterestng result especally when compared to the earler fndng that the WATCON coeffcent for mproved water quantty was negatve. The nterpretaton s that the more a household consumes water, the more that household s WTP for a better qualty; n fact whle ts needs for quantty are satsfed, household s concerns shft towards qualty aspects. 167
Source of water (WATSOC) was statstcally sgnfcant and negatve. Ths means that as the users apprecaton of the water qualty ncreases (e.g for ndwellng tap users), ther WTP declnes. Varables HHINC, AGE and GENDER have the same sgns and sgnfcance as n the model llustrated n Table 6. 4. Conclusons Ths paper uses the contngent valuaton method to analyse the determnants of Swaz households wllngness to pay for an mprovement n ther avalable water quantty and qualty. The study was conducted on a sample of 374 households, of whch 127 (34%) were from the rural area and 247 (66%) were from the urban area. A Tobt model was appled to the data generated by the survey to explan the determnants of households WTP for mproved qualty and quantty of domestc water supply. Locaton of the households (urban/rural) was the most statstcally sgnfcant crteron to explan both the probablty to be WTP, and the amount of money a household s prepared to pay for mproved water servces. Rural respondents were more lkely to be WTP for water quantty mprovement and, surprsngly, ther bds were quanttatvely hgher than those comng from urban households, showng a real struggle for a better, closer and more relable source of water n rural areas. Rural households are also more lkely to be WTP for water qualty mprovements. Urban households are ready to propose hgher bds to mprove ther qualty of water, due to ther hgher ncome. Regressons results also show that, regardless of household locaton, ncome has a postve and statstcally sgnfcant mpact on WTP for both qualty and quantty. Smlarly, dstance to the water source s postvely assocated wth WTP for water quantty and qualty. Current water consumpton s also statstcally sgnfcant, but wth a negatve sgn when regressed on WTP for mproved water quantty. On the other hand, the more a household consumes water, the more that household s WTP for a better qualty; n fact, whle ts needs for quantty are satsfed, households concerns shft towards qualty aspects. The current source of water s also a statstcally sgnfcant determnant for households WTP for both mproved quantty and qualty. In ths case, households wth n-dwellng tap water are less WTP than households fetchng water at collectve taps or from the rver. Overall, results confrm that water servce levels are mportant to Swaz households, whch are wllng to pay for ncremental changes n servce levels. There s, therefore, scope to mprove water servce provson n Swazland even 168
at a hgher water prce. Ths was acknowledged for some tme n the context of other servces, such as electrcty provded n the country, but evdence n the water sector s stll lackng. More precsely, the estmates of WTP obtaned n ths study ndcate the possblty of ntroducng a demand-drven program to expand the coverage of rural tap water schemes. Acknowledgments Many thanks to the Edtor and the anonymous revewers for helpful comments on an earler draft. Remanng errors are entrely the responsblty of the authors. Notes: 1. 1 Llangen s equvalent to approxmately 15 US cents. 2. These ncluded bolng water, flterng and chlorfcaton. 3. Mbabane, Manzn, Nhlangano, Pggs Peak, Stek, Bg Bend, Mhlume, Hlatkulu, Lavumsa, Mhlume and Lobamba. 4. From a mother populaton of 233 843 households, a unform samplng fracton equal to 0.0016 was chosen, leadng to a total of 374 households, of whch, accordngly to the weght of the two strata, 127 (34%) were from the rural area and 247 (66%) were from the urban area. 5. The same mpact was observed for the varable HHINC on WTP for qualty. References Banda B, Farolf S & Hassan R (2004). Determnants of Qualty and Quantty Values of Water for Domestc Uses n the Steelpoort Sub-basn: A Contngent Valuaton Approach. Proceedngs of the conference: Water Management for Local Development, Loskop Dam, 8-11 November 2004. Department of Urban and Rural Development (2002). The Cty and Towns of Swazland. Annual Report, 2002. Government of Swazland (2003a). Swazland Government Year Publcatons. A Swazland Government Specal Report, Aprl 2003. Government of Swazland (2003b). Swazland Government Year Publcatons. A Swazland Government Specal Report, June 2003. Government of Swazland (2004). Swazland Year Book. Specal report prepared for the government of Swazland. May 2004. 169
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