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1 Elsever Edtoral System(tm) for Ecologcal Economcs Manuscrpt Draft Manuscrpt Number: ECOLEC-D Ttle: Assessng the wllngness to pay for relable domestc water supply: results from a contngent valuaton survey n Narob Cty, Kenya Artcle Type: Analyss Keywords: Market-based mechansms; contngent valuaton; wllngness to pay; Narob; PRESA; water; envronmental servces Correspondng Author: Dr. Bedru Babulo Balana, Ph.D. Correspondng Author's Insttuton: The Macaulay Insttute Frst Author: Bedru B Balana, PhD Order of Authors: Bedru B Balana, PhD; Dela Catacutan, PhD; Mka Mäkelä Abstract: Wth growng populaton and ncreasng demand for water, shortage of water has become a major problem n Narob. The Sasumua reservor, 50 km north of Narob, supples 20% of Narob's water. Human actvtes wthn the Sasumua catchment mpact the flow and qualty of water. However, landholders n the catchment have no ncentves to take nto account the mpact of ther decsons on the reservor. Recently, the World Agroforestry Centre has ntated the 'Pro-poor Reward for Envronmental Servces (ESs) n Afrca' project to examne the potental of market-based approach for the provson of ESs. The objectve of ths study was to estmate the WTP of Narob resdents for relable domestc water supply va catchment conservaton. Data were collected va contngent valuaton survey. A censored regresson model was employed to estmate the WTP. Results show that: (1) substantal WTP potentals exst among the resdents; (2) monthly mean WTP of an average household s about 275 Kenya shllngs; (3) household ncome, educaton, and age are the key varables explanng nterhousehold varatons n WTP; and (4) lack of approprate nsttutonal and admnstratve regmes are the major publc concerns. Thus, the nsttutonal and admnstratve aspects should be gven hgh prorty n desgnng market-based ESs provson.

2 *Hghlghts We assess the wllngness to pay of Narob resdents for relable water supply. Watershed servces va catchment conservaton are examned usng contngent valuaton. Resdents are wllng to pay an extra 25% of ther water bll f supply s relable. Key publc concern s lack of accountable and credble agency to mplement the scheme. Approprate nsttutonal/admnstratve regmes are vtal to mplement market-based schemes.

3 *Ttle Page Assessng the wllngness to pay for relable domestc water supply: results from a contngent valuaton survey n Narob Cty, Kenya Bedru Babulo Balana a, *, Dela Catacutan b, Mka Mäkelä b a The James Hutton Insttute, Soco-economc Research Group, Cragebuckler, Aberdeen AB15 8QH, Scotland, UK b World Agroforestry Centre (ICRAF), Unted Natons Avenue, Ggr, PO Box 30677, Narob, 00100, Kenya. * Correspondng author: E-mal: bedru.balana@hutton.ac.uk Telephone: +44 (0) Fax: +44 (0)

4 *Manuscrpt Clck here to download Manuscrpt: Balana_Ecol.Econ.doc Clck here to vew lnked References Assessng the wllngness to pay for relable domestc water supply: results from a contngent valuaton survey n Narob Cty, Kenya Bedru Babulo Balana a, *, Dela Catacutan b, Mka Mäkelä b a The James Hutton Insttute, Soco-economc Research Group, Cragebuckler, Aberdeen AB15 8QH, Scotland, UK; * Correspondng author: bedru.balana@hutton.ac.uk b World Agroforestry Centre (ICRAF), Unted Natons Avenue, Ggr, PO Box 30677, Narob, 00100, Kenya. Abstract Wth growng populaton and ncreasng demand for water, shortage of water has become a major problem n Narob. The Sasumua reservor, 50 km north of Narob, supples 20% of Narob s water. Human actvtes wthn the Sasumua catchment mpact the flow and qualty of water. However, landholders n the catchment have no ncentves to take nto account the mpact of ther decsons on the reservor. Recently, the World Agroforestry Centre has ntated the Pro-poor Reward for Envronmental Servces (ESs) n Afrca project to examne the potental of market-based approach for the provson of ESs. The objectve of ths study was to estmate the WTP of Narob resdents for relable domestc water supply va catchment conservaton. Data were collected va contngent valuaton survey. A censored regresson model was employed to estmate the WTP. Results show that: (1) substantal WTP potentals exst among the resdents; (2) monthly mean WTP of an average household s about 275 Kenya shllngs; (3) household ncome, educaton, and age are the key varables explanng nter-household varatons n WTP; and (4) lack of approprate nsttutonal and admnstratve regmes are the major publc concerns. Thus, the nsttutonal and admnstratve aspects should be gven hgh prorty n desgnng market-based ESs provson. Key words: Market-based mechansms; contngent valuaton; wllngness to pay; Narob; PRESA; water; envronmental servces

5 Introducton Wth growng populaton and ncreasng demand for water, shortages and ratonng of domestc water supply has become a common feature n many urban centres of developng countres (Thompson et al., 2000; Khatr and Varavamoorthy, 2007). The Kenyan captal, Narob, s a case n pont. Shortages and unrelable water supply s becomng a serous problem leadng to frequent water ratonng n many parts of Narob (UN-HABITAT, 2006). Resdents n some parts of the cty have to queue for long hours to get water. In March 2010, the Daly Naton, the country s most nfluental and largest newspaper, reported the serousness of water shortages n Narob. Accordng to the newspaper, although Ndakan Reservor, the man source of water for Narob, s operatng at nearly full capacty, cty resdents could contnue to experence water shortages. One major factor contrbutng to ths problem s consdered to be the degradaton of Sasumua catchment whch supples water to the Sasumua Reservor. The Sasumua reservor, located roughly 50 km north of Narob, supples 20% of Narob s water supply. The prmary land uses n the Sasumua catchment are grazng and ntensve arable croppng such as potatoes and vegetables. Such ntensve agrcultural practces affect water quantty and qualty avalable to benefcares further afeld, but upstream landholders have lttle or no ncentves to take nto account the mpacts of ther land use decsons. In recent years, payments for envronmental servces (PES) have emerged as mportant market-based mechansm for the provson of envronmental servces (ESs). PES can translate external, non-market values of ESs nto real ncentves for local actors to provde the requred ESs (Engel et al. 2008). Interest n PES as a tool for watershed management n developng countres has been growng. Among such ntatves n Afrca s the ICRAF s PRESA project. PRESA s a network that facltates PES mechansms n Kenya, Tanzana, Uganda and Gunea. It generates evdence on land use mpacts on ESs and lvelhoods and plays an ntermedary role n facltatng PES agreements between ESs provders and benefcares. The relaton between landholders n Sasumua and water users n Narob has been clearly establshed. Resdents of Narob would be the drect benefcares f water supply ncreases va catchment conservaton practces n Sasumua. For ths to happen, farmers at the catchment need to be ncentvsed to take actons that beneft downstream water users. If landholders n Sasumua adopt catchment conservaton, t could reduce reservor sedmentaton and ncrease water quantty n the reservor. In a PES scheme, landholders are the potental sellers of the watershed servces and hydroelectrc power generators, muncpal water companes, rrgators, and other downstream benefcares such as are potental buyers. Currently, PRESA s facltatng negotatons between producers and benefcares of ESs for ts Sasumua plot case. One of the key ssues n desgnng and mplementng a market-based provson of ESs s a thorough understandng of the demand.e., the wllngness to pay (WTP) of the benefcares for the

6 ESs. However, the benefcares WTP has not been properly assessed n any of PRESA s case study stes, ncludng Sasumua. Thus, the prncpal objectve of the present study was to assess the WTP of domestc water users n Narob for ncreased and relable supply of water va catchment conservaton n Sasumua. For ntatves such as PRESA and other smlar undertakngs, partcularly n the developng countres, knowledge of the WTP of potental benefcares for ESs s extremely mportant for desgnng and mplementng market-based methods. Ths study also ams to dentfy the key factors that nfluence the WTP of ESs benefcares. Based on the fndngs, the thrd objectve of the study was to suggest polcy relevant recommendatons related to PRESA s actvtes and other smlar market-based ntatves. The remander of the paper s organzed as follows. The next secton presents a bref descrpton of the contngent valuaton method. Secton 3 descrbes survey nstruments. Survey desgn ncludng samplng desgn and questonnare admnstraton s presented n Secton 4. Secton 5 presents the modellng of the CV data. Descrptve analyss and model results are presented n Sectons 6 and 7, followed by dscussons and polcy mplcatons The CV method CV method s a survey-based approach used to measure the non-market values of envronmental or publc goods based on how an ndvdual responds to a queston on hs/her WTP to envronmental changes (Hoevenagel, 1994; Stewart and Khan, 2006). The two prncpal assumptons underlyng ths method are: (1) that people have well-ordered, but hdden, preferences for all knds of envronmental goods; and (2) that people are capable of transformng these preferences nto monetary values (Hoevenagel, 1994). On the bass of these assumptons, the CV method elcts values for envronmental goods by presentng respondents wth a descrpton of a proposed hypothetcal scenaro or envronmental change and asks the respondents to express (n monetary terms) ther maxmum WTP to enjoy a postve change or the mnmum compensaton they would demand (wllngness to accept, WTA) for a negatve change. Generally, n CV surveys, there are three approaches to askng these questons (Cameron and James, 1986; Hoevenagel, 1994; Whtehead, 2006): () open-ended questons where respondents are asked to state ther maxmum WTP or mnmum WTA, () closed-ended questons where respondents are asked whether or not they would pay or accept a sngle sum of money., and () sequental bds or bddng games questons where respondents are asked whether or not they would pay or accept some specfed sum (repeatng the queston usng a hgher or lower amount dependng on the precedng response). In both () and (), the arbtrarly assgned values vary across respondents (Cameron and James, 1986).

7 Many early contngent valuatons asked open-ended questons, for nstance, What s the maxmum amount of money you would be wllng to pay for an ncrease n ar qualty n your cty? Despte ts drectness, the open-ended method has several dsadvantages. Most respondents may not have pror experence of valung envronmental changes. In daly lfe, people decde whether to purchase or not a good at a prevalng (or negotated) market prce, and do not state ther maxmum prce. Thus, demandng a maxmum WTP value may lead to hgh non-response rates and a large number of protest votes (.e. mplausble WTP values). Because of ths, t has been argued that value estmates produced through open-ended method are less relable than other elctaton methods. For example, studes usng both drect open-ended and bddng game methods found that the former consstently produced lower values (Cummngs et al., 1986). Such dffcultes n open-ended queston responses suggest that people need a certan degree of assstance to put values on envronmental goods. Ths has led to the popularty of closed-ended CV survey. Numerous applcatons of these methods now exst. Comprehensve assessments of CV survey nstruments and some specfc applcatons can be found n Cummngs et al. (1986) and Mtchell and Carson (1989). The attractveness of the closed-ended questonng strategy s that t generates a scenaro for each respondent n a manner smlar to that encountered n real market transactons. A hypothetcal prce s stated and the respondent decdes whether to say yes or no. However, challenges do arse n estmaton because the observed values are threshold levels of the respondent s WTP rather than the true value, whch s thus an unobserved random varable wth a value lower or hgher than the stated WTP. The challenge researchers face s n nferrng the magntude of the true WTP valuaton through an ndcator varable (the respondent s yes/no responses to the offered threshold) that tells whether ths underlyng value s greater or less than the offered value (Cameron, 1988). Wth the yes/no responses to closed-ended CV surveys, some varant of choce model s clearly mperatve (Stewart and Kahn, 2006) Survey nstruments 3.1 Elements of a CV survey As CV deals wth goods and servces wth no functonal markets, t should be desgned n such a way that a satsfactory (f hypothetcal) transacton s establshed n whch people are fully nformed and able to dentfy ther own best nterests. Ths wll result n vald and relable WTP estmates and wll only take place f the envronmental good under consderaton, the method of payment, and the hypothetcal market stuaton are well defned and understood by the respondents (Hoevenagel, 1994; Whtehead, 2006). Ths s mpled by the name of the method tself, whch produces values contngent upon the descrpton of the good and on the method of payment. Therefore, a great

8 deal of effort s requred to defne and clearly dsplay the current and proposed levels of changes. The CV questonnare should thus consst of the followng three key elements: 1. Descrpton of the change: Ths refers to descrpton of the envronmental resource under current condtons, as well as the proposed condtons f the respondent pays. 2. Descrpton of the constructed market: The organzaton that wll be nvolved n the provson of the proposed envronmental change has to be descrbed. For nstance, f the respondents do not trust the organzaton, ths wll affect ther belef n the certanty of the change and ther WTP value. 3. Payment vehcle: Respondents need to be told the means by whch they would pay for the proposed changes, e.g. n a hgher water bll or a tax ncrease. The payment schedule (monthly or yearly) and ts temporal lmts must be specfed. Fnally, the respondents are asked whether they would pay a certan amount, whch vares randomly across respondents. 3.2 The CV scenaro n ths study The CV scenaro was defned n terms of the current envronmental stuaton,.e. catchment degradaton due to ntensve human actvtes and the mpact of ths on flow of water nto the Sasumua reservor; the hypothetcal envronmental change through catchment management; the potental ncrease n quantty and relablty of water to downstream users; and the suggested method of payments. The valuaton scenaro was ntally drafted by the authors, substantally mproved by an expert workshop convened on 16 October 2010 at ICRAF n Narob. The experts, consstng of economsts, socal scentsts, engneers, hydrologsts, envronmentalsts and representatves from water companes, were drawn from ICRAF, Jomo Kenyatta Unversty of Agrculture and Technology, Kenafrc Industres Ltd., Ath Water Servces Board, the NCWSC, and the Ruru Water and Sewerage Company. After the scenaro descrpton, the CV questonnare captures how much a respondent s wllng to pay for ncreased and relable water supply through catchment conservaton n Sasumua. To fnd what an ndvdual s WTP s, a respondent was not drectly asked an open-ended queston (as descrbed n secton 2 above). Instead, a double-bounded CV survey procedure was appled whereby each ndvdual was provded wth a random ntal bd ( B ) (see Table 1) and asked whether he/she would be wllng to pay ths amount. Accordng to the double-bounded CV procedure, each person s asked a follow-up bd whch s lower or hgher dependng on the response to the frst bd.e., the follow-up bd s hgher f the frst bd was accepted and lower f the frst bd was rejected) 1. Thus, for each respondent we have an ntal bd ( B ) and one of the follow- I I 1 Conversely, for WTA survey the follow-up bd s lower f the response for the ntal bd was yes and s hgher f the frst bd was rejected.

9 6 171 up bds B and B, where B L U L B I B U. Each respondent was asked about a random ntal bd and the follow-up bd accordng to the schemes presented n Table 1. These bd values were chosen based on the water tarff structure n Narob and n consultaton wth the experts partcpatng n the expert workshop. The four possble outcomes for the two CV questons were: (1) both answers yes ; (2) both answers no ; (3) a yes followed by a no ; and (4) a no followed by a yes. >>> INSERT TABLE 1 HERE >>> Survey desgn and data 4.1 Samplng and Survey desgn The spatal coverage of the sample desgn for the survey targeted to parts of Narob whose prmary water source s the Sasumua reservor. Accordng to the water dstrbuton map of the NCWSC (see Fgure 1), these are the northern and western regons of Narob. The NCWSC map further ndcates the routes through whch Sasumua water s channelled and reaches these regons of the cty. For samplng purposes, the water dstrbuton boundary map provded by NCWSC was dgtzed and overlad n a GIS map wth admnstratve boundares. Orgnally, 15 sub-locatons (the smallest admnstratve unt n Kenya) were clustered nto three strata based on the ncome levels of resdental areas: hgh, medum, and low. Gven the nature of resdental occupancy n Narob, spatal clusterng of resdental areas on the bass of ncome level provdes adequate stratfcaton to serve the purpose of the survey. Generally n Narob cty, resdental areas are markedly separated by ncome levels. Low-ncome areas are often characterzed by hgher populaton densty than the hgh-ncome areas. Out of the ffteen sub-locatons, sx were randomly selected for the survey (Table 2 and Fgure 1). >>> INSERT TABLE 2 HERE >>> >>> INSERT FIGURE 1 HERE >>> As the sub-locatons vary n area and populaton sze, selecton of sample households was based on a spatal samplng technque referred to as the Systematc Unalgned Pattern by McCoy (2005). Accordngly, each sub-locaton was dvded wth a 250 by 250 meter grd and 1-2 random sample ponts (RSPs) were dentfed n each cell. Ths was to guarantee a spatal representaton of the sample set. Each RSP represents a survey respondent.

10 In the urban envronment, ths spatal samplng technque may exhbt some shortcomngs. For nstance, the RSP may end up n areas such as schools, hosptals, parks or busness or unoccuped premses, or the respondents may not be accessed due to commutng to work. To overcome such problems, a number of reserve RSPs (about 30% of the total sample sze) were generated. Table 3 presents the total and reserve RSPs generated and the target sze of respondents n each ncome category >>> INSERT TABLE 3 HERE >>> 4.2 Data collecton The data used n ths study were obtaned from expert workshops, key nformant ntervews, focus groups, and the CV survey Expert workshop The expert workshop was convened wth ten experts (economsts, envronmentalsts, hydrologst, engneers, socal scentsts, water companes and consumer groups) drawn from varous organzatons (see Secton 3.2). The major task of the workshop was to mprove the descrpton and desgn of the CV questonnare. Furthermore, useful nformaton was obtaned on the water tarff structure, water supply, techncal and mantenance problems, admnstratve, nsttutonal and polcy ssues, and potental short- and long-run remedal measures for the problem of water shortages n Narob. For example, nformaton on Narob water tarff was used to set the payment levels n the CV questonnare Focus group dscussons To obtan further qualtatve nformaton about the opnons, vews, atttudes, and experences of water users, two separate focus groups were convened at the ICRAF campus n Narob. Focus groups were drawn from resdents whose major water source s the Sasumua reservor. The focus questons were dentfed n consultaton wth the PRESA research team and local stakeholders n order to reflect the local condtons related to domestc water problems n Narob. Each focus group was moderated by two traned facltators a prncpal facltator and an assstant. Both facltators were resdents of Narob and possessed good knowledge about the ssue under the study CV survey admnstraton The contngent valuaton survey questonnare conssted of fve sectons: demographc, atttudnal and behavoural, valuaton, household ncome, and debrefng (Whtehead, 2006). The valuaton secton s presented n Appendx 1. In the debrefng, respondents were asked perceptons on the degree of uncertanty about the mpact of adopton of catchment conservaton n Sasumua on mprovng the relablty of water supply n the survey area. The questonnare was pre-tested and at

11 the end of the pretestng a debrefng sesson was held wth the enumerators and feld supervsors to obtan feedback. Consensus was reached that the scenaros presented n the fnal verson of the questonnare was credble. The survey was admnstered n October 2010 by a group of traned enumerators. Surveyng was rgorously supervsed to ensure that enumerators compled wth establshed procedures. A total of 202 sample households were ntervewed, out of whom 23 protested the CV survey,.e., were not wllng to answer the WTP queston CV Modellng Two broad modellng approaches can be pursued n analysng CV survey data: (1) relate the yes/no responses of the WTP queston to the monetary stmul.e., bds that nduced respondents to derve quanttatve measures of value (the random utlty theory (RUT) (McFadden, 1974; Tran, 2003), and (2) drectly relate threshold bd values to selected explanatory varables to estmate the actual WTP. 5.1 Bnary response models Logt, probt, and other bnary response models are routnely ftted to CV survey data to obtan estmates of the unobserved latent WTP. For nstance, earler analyses of closed-ended or sngle- bound CV data use logt models to derve ftted choce probabltes for yes y 1) and no ( y 0) responses to the valuaton questons (Bshop et al., 1983; Sellar et al., 1985; Sellar et al., 1986; Cameron and James, 1986). In the logt model, the choce probablty s gven ( by P y 1) (1 exp( x ' )) where the x ' s are the explanatory varables and ( s a vector of unknown parameters. In these studes, the threshold bd value was consdered as the sole explanatory varable and the resultng choce probabltes were nterpreted as the probablty that a randomly selected respondent would agree to pay the stated fee as a functon of the amount of money tendered. Then, cumulatve probabltes were used to estmate the expected value of the resource n queston. Apart from the threshold bd value, other explanatory varables could also be ncluded; but such models do not allow computaton of the margnal contrbuton of these other varables to the underlyng valuaton (Cameron and James, 1986). Hanemann et al. (1991) questoned the statstcal effcency of the sngle-bound dchotomous CV method and developed a more statstcally effcent WTP estmaton framework for double-bounded dchotomous choce contngent valuaton. Usng a logt modellng framework and a maxmum lkelhood (ML) estmaton technque on CV survey data obtaned from Calfornans on ther WTP for protecton of wetlands and wldlfe habtat n the San Joaqun Valley, Hanemann et al. (1991) showed the gan n effcency n the double-bounded model, and also found that the doublebounded data yelded a lower pont estmate of medan WTP than the sngle-bound data. Both the

12 gan n effcency and the drecton of change n the estmate of medan WTP were explaned by the fact that the follow-up bd n double-bounded approach mproves a poor choce of ntal bd. Double-bounded models are based on the assumpton that the dstrbutonal parameters for the underlyng latent WTP values are dentcal for both the frst and follow-up questons. However, Cameron and Quggn (1994) challenged ths assumpton and explctly assumed separate dstrbutonal parameters of WTP for the two CV questons,.e., they argued that respondents mght form two WTP values, one for the ntal bd and another for the follow-up bd, whch are lkely to be correlated, but need not be dentcal. Based on ths assumpton, they appled a bvarate bnary response model (bvarate probt) to a dchotomous choce wth follow-up CV survey conducted n Australa, and obtaned estmates of WTP that were sgnfcantly dfferent from the double-bounded model estmates. As suggested by Cameron and Quggn, the two WTP values for the respondent (for the frst and second CV questons), WTP 1 and WTP 2, mght be descrbed by the bvarate system as (equaton 1): 286 WPT WTP 1 2 x x (1) In equaton (1), the error terms are assumed to be jontly normally dstrbuted wth zero means and varances 2 and 2 1 2, and correlaton coeffcent. The bvarate probt model s applcable not only to modellng dchotomous choce CV questons wth follow-up, but also to a general parametrc model for two-response surveys. However, ths approach has created certan dlemma for CV researchers f estmates of means or varances, or both, dffer between the ntal bd and the follow- up bd. In such a stuaton, the researcher must decde whch estmate to use to calculate the WTP measure (Haab and McConnell, 2002). Addtonally, Albern (1995) nvestgated the relatve effcency and bas of the WTP estmates from bvarate and nterval-data models and found that mean WTP estmates and regresson coeffcents from nterval-data model are more effcent than those obtaned from bvarate probt model. She also showed that mean WTP estmated by nterval- data model remans unbased even f large dfferences between an ndvdual s two WTP values are allowed. 5.2 Interval data models 2 Data from a double-bounded CV survey can be analysed by usng a generalzaton of the models ftted by censored regresson (tobt models), known as nterval-data model. Ths model s a specal 2 2 case of the more general bvarate model wth 1 2; 1 2 ; and 1whch compels WTP WTP (Albern, 1995). Double-bounded CV data can be organzed n left-censored, rght Interval data model and nterval regresson were used nterchangeably.

13 censored and nterval-censored dataset format. For double-bounded WTP questons, those who answer yes, yes are rght-censored, those wth no, no are left-censored and those wth yes, no or no, yes fall wthn an nterval. Usng nterval data model, the bds can be explctly modelled and the mean WTP can be obtaned by post-estmaton predcton. Interval regresson fts models to data where each observaton represents nterval data, left-censored data, rght-censored data, or pont data. For nterval regresson models, the data should be stored wth two dependent varables (depvar1, depvar2).e., the end-ponts of the nterval (StataCorp, 2009). Table 4 shows how an emprcal CV survey data can be organzed n nterval dataset format. In ths study, to mplement nterval regresson, we created two dependent varables, LowerBound and UpperBound to represent the endponts or boundares of the bds. >>> INSERT TABLE 4 HERE >>> The lkelhood functon for nterval regresson regards that of the tobt models. Let y X be the model. The y represents contnuous outcomes the observed or unobserved underlyng latent varable values. We assume a normal dstrbuton of the error term ( 2 as ~ N (0, ). For observatons P we observe y (pont data); observatons ), dstrbuted L are left censored (we know only that the unobserved observatons equal to y s less than y L.e., a censorng value). Smlarly, R are rght-censored (we know only that the unobserved y s greater than or y R ). Observatons I are nterval (we know only that the unobserved y s n the nterval y, y ]). The lkelhood functon s (StataCorp, 2009): [ 1 2 ln L 1 2 P w y x' 2 log L R w log w log 1 y L y R x' x' log I w log y 2 x' y 1 X (2) where (.) s the standard cumulatve normal dstrbuton functon, w s the weght for the th 329 observaton, and x ' s a vector of explanatory varables. If no weghts are specfed, w 1. In our CV survey data analyss, we appled nterval-data model equaton (2). As sample respondents were randomly selected (see secton 4.1), w 1was attached n our emprcal model.

14 Emprcal mplementaton Models To compare the results of nterval data model, we ran probt and logt models for ntal and followup bds separately, and a vbvarate probt model (equaton 1) for both bds. However, the results of these models (not reported n the paper) were not as good as those of the nterval regresson n terms of explanng the WTP,.e. most of the parameter estmates turned out to be statstcally nsgnfcant. The falure of these models to explan WTP well may ndcate that the dstrbutons of error terms may be nether normal nor logstc, or that the underlyng WTP value may not be dfferent for the two bds. From the nterval-data model (equaton 2), the mean WTP value was estmated usng several post-estmaton technques (lnear predcton, condtonal expectaton and truncated methods) Explanatory varables (covarates) The covarates used n ths study were dentfed n the process of the questonnare desgn,.e. from lterature survey, workshops, expert consultaton, and questonnare pre-testng. As some of the nformaton, such as questons on ncome, s socally senstve, we employed a great deal of cauton n the wordng, level of detal, and style of presentaton of the questonnare. For nstance, nstead of askng the exact amount of household ncome, households were asked to select ther ncome class wthn a pre-defned lst defned on the bass of the ncome dstrbuton and occupatonal status of the survey dstrcts (see Secton 4.1). In total, nne covarates were dentfed to be ncluded n the CV models, n order to exhbt or proxy the demographc, atttudnal, economc, behavoural, human captal, and awareness characterstcs of the survey respondents. The proxy varables used were: Demographc: Respondent s age (n years) and sex (male=1; female=0) Atttudnal: Respondents percepton of the severty of the problem of water shortage n ther area (sub-locaton). The specfc queston was: Do you agree that shortage of water supply s a serous problem n your area? The response categores were: (1) Strongly agree; (2) Agree; (3) Dsagree; (4) strongly dsagree. In the analyss, responses (1) and (2) were labelled as agree and gven code 1, whle responses (3) and (4) were labelled as dsagree and were gven a code of 0. Economc: Ths was approxmated by two varables: (a) household s net ncome from all sources, and (b) whether water shortages have affected the household s ncome and avalable labour tme. The specfc queston n the questonnare for (a) was: How much net ncome (.e., after deductng tax or any other deductons), does your household earn from the man actvty and any supplementary actvtes per month? Respondents were also asked about any transfer ncome they may receve. In queston (b) we asked: Has water shortage affected the allocaton of your

15 household s ncome or labour tme for alternatve actvtes? wth response categores 1= Yes and 2= No. Behavour: The proxy varables used here were the actual problem the household faced n relaton to water shortage and whether the respondent s a member of a pro-envronment or conservaton organzaton or assocaton. The specfc queston wth regard to the frst ssue was: Have you ever faced any water shortage problem n the last 6 months? (1) Yes; (2) No. Respondents answered Yes were asked a further queston on the frequency of the problem. On the second ssue (.e., membershp or nvolvement n pro-envronmental actvtes), the queston was: Are you a member of any envronmental or conservaton group/assocaton/ programme? (1) Yes; (2) No. Human captal: The fve educaton classes used n the questonnare were: 0=never been to school; 1=prmary; 2=secondary;3= techncal or vocatonal or college dploma; and 4=unversty degree and above. These codes were used for the Edu_Class varable n Table 5. Awareness: Ths was to elct respondent s knowledge of the relatonshp between catchment management and water quantty or qualty. Each respondent was asked: Have you heard of or are you aware of how management of catchment areas upstream affects the flow of water avalable to downstream users? (1) Yes; (2) No. Table 5 presents the descrpton of the explanatory varables ncluded n the models. >>> INSERT TABLE 5 HERE >>> Descrptve analyss Table 6 summarzes the descrptve statstcs of the explanatory varables. Except the AgeRespondent varable, all the other varables n Table 6 should be nterpreted n percentages. For nstance, about 55% of the respondents are male; 54% responded that water shortages affected ther household ncome and labour tme; and 87% responded that they have faced water shortages problems n the last sx months. The summary of the two key explanatory varables, hhhncome and edu_class, (not ncluded n Table 6) s presented n Table 7. As these two varables are measured n more than two categores, we chose to present ther summary statstcs n each category or class n a separate table (Table 7). >>> INSERT TABLE 6 HERE >>> As can be seen from Table 7, about 65% of the respondents earn a monthly ncome of less than Ksh. 50,000. Only about 20% of survey respondents earn a monthly ncome of above Ksh. 100,000 of whch only 8% earn above Ksh. 300,000. In terms of educaton, about 24% of the respondents have a

16 unversty degree, and 26% have receved ether no educaton at all or have acheved only prmarylevel educaton. As ncome and educaton are the two mportant varables hypotheszed to affect WTP, the dstrbuton of these varables plays a sgnfcant role n the estmated mean WTP. >>> INSERT TABLE 7 HERE >>> Table 8 presents the summary of responses for the contngent valuaton bds, by ntal bd level (see Table 1). >>> INSERT TABLE 8 HERE >>> As shown n Table 8, 28.5% of the respondents provded two postve responses, and 10.6% gave two negatve responses, whereas 34.6% and 26.3% fell n the yes, no and no, yes categores respectvely. Table 8 also shows sgnfcant varaton n WTP of respondents wthn each ntal bd category. For nstance, wthn the left-censored group,.e. the no, no response category, about 6% of the respondents rejected the follow-up bd wth the mnmum payment amount offered (.e. Ksh. 50). Ths mples that these respondents are not wllng to pay even Ksh. 50 per month. On the other hand, among the rght-censored observatons,.e., response category yes, yes, about 4% of respondents stated that they are wllng to pay more than Ksh. 400 per month WTP Results The WTP estmates were obtaned usng the nterval-data model presented n equaton 2. The model wth the dependent varables of Lowerbound (depvar1) and Upperbound (depvar2) (see Secton 5.2 and Table4) was run usng the STATA (release 11) statstcal software on the varables descrbed n Table 5. Table 9 presents the results. As expected, atttudnal and awareness varables have postve coeffcents, whch mply that respondents who: (a) are aware of the contrbuton of catchment management for mprovng water quantty and qualty ( CatchAware ); (b) perceve water shortage as a serous problem ( AttWaterShortage ); and (c) are members of certan envronmental programmes ( MemberEnv ) are wllng to pay more for the proposed scenaro than those who do not possess these attrbutes. Gender dfferences (male and female respondents) do not exhbt sgnfcant dfferences n WTP for the scenaro presented. The three most mportant varables that explan varatons n WTP are household ncome, the respondent s level of educaton and age. Whle ncome and educaton are statstcally sgnfcant at 1% level (both wth postve coeffcents), age s sgnfcant at the 5% level (wth a negatve coeffcent). As expected, the hgher the level of household ncome and educaton, the

17 hgher the WTP. The negatve coeffcent of age ndcates that younger respondents are wllng to pay more than older respondents. >>> INSERT TABLE 9 HERE >>> >>> INSERT TABLE 10 HERE >>> Usng three dfferent post-estmaton methods (Table 10), mean WTP and standard devaton of estmates were obtaned. All predcton methods yelded very smlar mean WTP values. However, estmates of standard errors and the ranges generated by the three methods vary sgnfcantly. On the bass of the model predctons, the mean WTP s about Ksh. 275 per month, approxmately equvalent to US$3. Ths s almost 25% of the average survey household s monthly water bll. Ths apparently large WTP value (antcpated ncrease n water bll) may reflect the extent of water shortages n the survey area and people s preferences to pay for relable water supply. However, followng the ncome dstrbuton pattern of households n the area, large varablty n the households water blls was observed (from Ksh e., approxmately from US$ 1.5 to per month). Lkewse, the estmated mean WTP s smply an average predcton and ndvdual s actual WTP values could show wde varaton. Mean WTP estmates from the CV model need to be aggregated to reflect the total value of the ecosystem servce under consderaton. Two prncpal ssues n relaton to aggregaton are: (1) the relevant populaton (both geographcal scale and the proporton of the target populaton whose WTP s postve) over whch the value s to be aggregated, and (2) the length of perod (for nstance, for how many years) over whch the value s to be aggregated. In relaton to ths partcular study, both ssues were determned n the desgn stage of the study. The ecosystem servce under consderaton, the relevant populaton (scale ssue), and temporal ssues were clearly defned at the outset. The populaton sze of the sx sub-locatons was obtaned from the Kenya Natonal Bureau of Statstcs (KNBS, 2010). From ths data, the total number of households was estmated (assumng an average household sze of 6 persons). From the sample of 202 households, almost 12% protested, or declned to partcpate n scheme. From the estmated mean WTP of Ksh. 275 wth a standard error of 181, we calculated that about 8% of the populaton has a negatve wllngness to pay 3. As ths s not possble (.e., negatve WTP has no economc meanng), we renterpret ths as zero wllngness to pay (Verbeek, 2004). Thus, by excludng the 12% protest vote and 8% zero WTP, aggregaton was made over 80% of the populaton who are supposed to have some postve WTP. 3 Here the parameters of the model are assumed normally dstrbuted.

18 >>> INSERT TABLE 4 HERE >>> Usng the exchange rate of Ksh aganst US dollar (US$ 1=Ksh. 80) durng the survey perod, we estmated that the total annual WTP of the populaton dentfed to have been recevng water from Sasumua reservor s about US$ 575,657. It would be desrable to compare ths value wth the actual expendture on water treatment and mantenance of the reservor. Unfortunately, data s not avalable on ether the actual costs ncurred by NCWSC on water treatment, reservor sedment removal and other related actvtes or the compensaton demanded by landholders. However, a study by Pagola (2006) ndcates that about US$ 100,000 was spent at the Sasumua water treatment plant on treatment for contamnaton, and US$ 50,000 on clearng slts from water ntakes. Assumng that ths amount of money ($150,000) would motvate landholders to adopt catchment conservaton actvtes and supply watershed servces that could substtute the benefts from treatment and removal of slts, there appears to be a huge potental of users WTP to fnance catchment conservaton actvtes n Sasumua. Ths, however, requres approprate admnstratve and nsttutonal set-up, an ntermedary organzaton (at least n the ntal stages), and effectve desgn of a PES scheme Dscussons and mplcatons As ndcated earler, one of the key nterests of the PRESA project s to lnk landholders and downstream benefcares of envronmental servces through market-based mechansms. The project recognzes that understandng the demand (WTP) of the benefcares for ESs s a crucal component n desgnng market-based mechansms to the provson of ESs. As ndcated n Secton 3.1, the key components of a CV scenaro consst of descrptons of the envronmental change, the constructed markets, and the payment vehcle. However, Whttngton (1998) argues that, n the context of developng countres, one of the mportant ssues that should be explct n CV surveys s the nsttutonal regme and the agency mplementng the proposed scheme. Furthermore, Whttngton shows that publc percepton and dstrust of nsttutons and agences, and concerns about whether money would be properly used, substantally affect the WTP and publc partcpaton n any proposed scheme. Responses from our survey valdate Whttngton s argument. As part of the CV survey, we asked respondents to state ther vew on the sngle most mportant problem they perceved n realzng the proposed scenaro. The overwhelmng majorty of the respondents (nearly 90%) dentfed the lack of an accountable and honest admnstratve and nsttutonal regme for delverng the proposed schemes for enhancng relable water supply n Narob.

19 A fundamental publc concern that came across n ths study was the degree of general publc dstrust and suspcon on the utlzaton of funds f they were actually to contrbute to the proposed PES scheme. From experences of other schemes and of the prevalence of corrupton at varous levels n the Kenyan publc sector, respondents were very worred about the lack of credble nsttutons and an accountable and responsble agency to mplement the scheme and manage the funds. If PRESA s to play an ntermedary role, t must therefore ensure that accountable regmes are n place, and that publc trust among benefcares, scheme admnstrators and supplers s mantaned. Otherwse, t would be a steep challenge to mplement a market-based ESs provson scheme n the area. Most respondents ndcated that the current water provson system n Narob s neffcent n both techncal and manageral aspects. Corrupton, out-of-date ppes, poor mantenance servces, and napproprate water tarffs were some of the key problems ndcated by respondents. Because of these, respondents expressed dscontentment wth the NCWSC and concern that the money they are wllng to pay on top of current water bll may not be channelled to the stated purpose. If market-based catchment conservaton s to be mplemented n Sasumua, PRESA has to make sure that ether NCWSC has reganed publc trust or a payment scheme s desgned wthout NCWSC controllng or managng t. Otherwse, t would be a huge challenge to actually lnk the fnal benefcares, the landholders n Sasumua, and NCWSC through a market-based scheme. In summary, a key challenge n mplementng market-based catchment conservaton n Sasumua s not the lack of demand or wllngness to pay for securng water supply by Narob resdents, but the lack of a vable nsttutonal and admnstratve set-up to manage a PES scheme. The man argument runnng through ths s the need for greater attenton to the nsttutonal and admnstratve aspects of market-based mechansms. Where publc dstrust s nvolved, the role of an honest ntermedary who can medate between ES buyers and sellers s crucally mportant. The overall mplcaton s that, n stuatons where many supplers and many benefcares of ESs are nvolved, the mplementaton of market-based ESs provson s hampered greatly f the nsttutonal and admnstratve regmes of PES mplementaton lack publc trust. Acknowledgements We would lke to extend our heartfelt thanks to the experts who partcpated n the workshop. We would lke to thank Ken Thomson for hs valuable comments on the orgnal draft; John Mwang and John Gathenya for ther nputs n questonnare desgn and feld work; the respondents for ther wllngness to take part n the survey; and the enumerators for ther hard work n the feld data collecton. The vews expressed n ths paper are those of the authors and do not necessarly reflect those of the James Hutton Insttute or ICRAF.

20 References Albern, A., Effcency vs. Bas of wllngness to pay estmates: bvarate and nterval data models. J. Envron. Econ. Manag. 29, Bshop, R.C., Heberlen, T.A., Kealy. M.J., Contngent valuaton of envronmental assets: comparson wth a smulated market. Nat. Resour. J. 23, Cameron, T.A., A new paradgm for valung non-market goods usng referendum data: maxmum lkelhood estmaton by censored logstc regresson. J. Envron. Econ. Manag. 15: Cameron, T.A., James, M.A., Effcent estmaton methods for the closed-ended contngent valuaton surveys. Department of Economcs, Unversty of Calforna, Los Angeles, Workng paper #404. Cameron, T.A., Quggn, J., Estmaton usng contngent valuaton data from a dchotomous choce wth follow-up questonnare. J. Envron. Econ. Manag. 27, Cummngs, R.G., Brookshre, S., Schulze, W.D., (1986). Valung envronmental goods: an assessment of the contngent valuaton method. Rowman and Allanheld, Totowa, NJ. Engel, S., Pagola, S., Wunder, S., Desgnng payments for envronmental servces n theory and practce: An overvew of the ssues. Ecol. Econ. 65(4), Haab, T.C., and McConnell, K.E., Valung Envronmental and Natural Resources. Edward Elgar Publshng Inc., USA. Hanemann, M., Looms, J., Kannnen, B., Statstcal effcency of double-bonded dchotomous choce contngent valuaton. Am. J. Agr. Econ. 73(4), Hoevenagel, R., An assessment of the contngent valuaton, In: Pethng, E. (ed.), Valung the envronment: methodologcal and measurement ssues. Kluwer Academc Publshers. The Netherlands, pp Kenya Natonal Bureau of Statstcs, Narob (KNBS) (Kenya) Kenya populaton and housng census volume IA: populaton dstrbuton by admnstratve unts. Narob, Kenya: Kenya Natonal Bureau of Statstcs, Narob (KNBS) 217p. Khatr, K.B., Varavamoorthy K., Challenges for urban water supply and Santaton n the developng countres. Dscusson paper. UNESCO-IHE. The Netherlands. McCoy, R. M., Feld methods n remote sensng. The Gulford Press. New York. 159pp. McFadden, D., Condtonal logt analyss of qualtatve choce behavour, In: Zarembka, P. (ed.), Fronters n Econometrcs. Academc press, New York, pp Mtchell, R.C., Carson, R.T., Usng surveys to value publc goods: The contngent valuaton method. Resources for the Future, Washngton DC. Pagola, S., Payments for envronmental servces n Costa Rca. Ecol.Econ. 65:

21 Sellar, C., Chavas, J., Stoll, J., Contngent valuaton technques for assessng envronmental mpact: further evdence. J. Envron. Econ. Manag. 8, Sellar, C., Stoll, J., Chavas, J., Valdaton of emprcal measures of welfare changes: a comparson of non-market technques. Land Econ. 61(2), StataCorp Stata: Release 11. Statstcal Software. College Staton, TX: StataCorp LP. Stewart, S., Kahn, J.R., An ntroducton to choce modellng for non-market valuaton, In: Albern, A., Kahn, J.R. (eds.), Handbook on contngent valuaton. Edward Elgar Publshng Ltd. UK, pp Thompson, J., Porras, I.T., Wood, E., Tumwne, J.K., Mujwahuz, M.R., Katu-Katua, M., Johnstone, N., Watng at the tap: changes n urban water use n East Afrca over three decades. Envronment and Urbanzaton 12(2): Tran, K.E., Dscrete choce methods wth smulatons. Sprnger, Berkley, USA. UN-HABITAT, Rapd urban sector profle for sustanablty: Narob urban sector profle. Project Report, Narob, Kenya. Verbeek, M., A gude to modern econometrcs (2 nd ed.). John Wly and Sons Ltd. England. Whtehead, J.C., A practtoner s prmer on the contngent valuaton, In: Albern, A., Kahn, J.R. (eds.), Handbook on contngent valuaton. Edward Elgar Publshng Ltd. UK, pp Whttngton, D Admnsterng contngent valuaton surveys n developng countres. World Dev. 26(1), Appendx: Valuaton secton of the CV survey About the survey and background nformaton The am of ths survey s to assess domestc water user s wllngness to pay n Narob cty for relable water supply through catchment management measures n Sasumua catchment. Sasumua reservor provdes 20% of Narob s water. However, human actvtes wthn the Sasumua catchment compromse the quantty and qualty of water n the reservor. Implementng approprate reward schemes to landholders n the catchment could provde ncentves for the adopton of catchment conservaton measures whch could mtgate the problem. Recently, the World Agroforestry Centre (ICRAF) has ntated the Pro-poor Reward for Envronmental Servces n Afrca (PRESA) project to examne the potental of market-based approach to motvate landholders for catchment conservaton n Sasumua. As a resdent of Narob you wll be the benefcary f catchment conservaton results n relable water supply. You are sncerely requested to provde, as much as possble, accurate and true responses. The nformaton collected n ths survey wll be treated confdentally

22 Valuaton queston We are now gong to ask you a hypothetcal queston. Suppose you are told that the shortage and unrelable supply of water you have been experencng so far would be brought to an end by ncreasng the quantty of water at Sasumua reservor. Ths could be acheved f catchment conservaton measures are adopted at Sasumua. Landholders need to be compensated for the catchment conservaton measures they undertake. Suppose you and other benefcares are asked to cover the costs of mplementng the conservaton measures that wll ncrease water n the reservor and as a result water supply becomes relable to your household. The decson to contrbute s on voluntary bass. We want to know f you are wllng to pay for the proposed plan. You wll be requred to pay a certan amount on monthly bass for three consecutve years. The Payment amount wll be added to your monthly water bll, but PRESA wll facltate the actual mplementaton of the plan. Remember that you are payng to secure relable water supply to your household and f enough people are wllng to pay enough money the plan wll be mplemented; otherwse the current stuaton wll reman unchanged. But, bear n mnd that when you pay to enjoy relable water supply, that money s not avalable for other alternatve uses. 1) Would you lke to pay for the plan? Yes = 1; No = 2. 2) Would you be wllng to pay Ksh. for a relable water supply so that you wll no longer face water shortage or ratonng? Yes = 1; No =

23 Table Clck here to download Table: Tables.doc 1 Table 1. Random bd schemes used n the CV survey (n Ksh + ) Bd schemes Intal bd Follow-up bd (decreased) Follow-bd (ncreased) ( B ) I (f No for I B ) (f Yes for I B ) Scheme Scheme Scheme Ksh.= Kenyan Shllng; durng the survey perod, 80 Ksh. 1US$.

24 2 Table 2. Narob cty sub-locatons ncluded n the survey Sub-locaton Populaton densty Income level Ruthmtu Low Low Mountan Vew Hgh Hgh Loresho Low Hgh Gatna Hgh Low Mazwa Medum Medum Upper-Parklands Medum Hgh

25 3 Table 3. Desgn of the random sample ponts Income category Target sze Reserve RSPs Total RSPs Hgh Medum Low Total

26 4 Table 4. Structure of double-bound WTP bd data * for nterval regresson Data type Depvar1 Depvar2 I U Interval data (yes, no): [ B, B ] L I Interval data (no, yes): [ B, B ] I B L B U B I B L Left-censored data (no, no): (, B ]. L B U Rght-censored data (yes, yes): [ B, ) * I B = Intal bd; B = follow-up bd (f yes for B ); U I L U B. B =follow-up bd (f no for B ) I

27 5 Table 5. Explanatory varables Varable name Descrpton Hypotheszed effect on respondent s WTP AgeRespondent Age (n years) of the respondent (household head or spouse) Negatve but not mportant SexRespondent Sex of the respondent (male=1; female=0) Ambguous to hypothesze Edu_Class AttWatShortage Educaton level of the respondent (household head or spouse)head Do you agree that shortage of water supply s a serous problem n your area (cty dstrct)? (Agree=1; Dsagree=0) Postve and mportant Postve CatchAware MemberEnv hhwatershort HHLabInc hhhncome Are you aware of the effect of catchment management on downstream water users? (yes=1; No=0) Are you member of any envronmental group? (yes=1; No=0) Has the household faced any water shortage n the last 6 months? (yes=1; No=0) Has water shortage affected the household s labour tme or ncome?(yes=1; No=0) Net monthly household ncome (fve ncome classes: 1= Ksh. 0 10,000; 2= Ksh. 10,001 50,000; 3= Ksh. 50, ,000; 4= Ksh. 100, ,000; and 5= Above Ksh. 300,000) Postve Postve Postve; but depends on the frequency of the shortage Postve; but depends on the degree of severty Postve and mportant

28 6 Table 6. Summary statstcs of the explanatory varables Varable Name # obs. Mean Std. Dev. Mn. Max AgeRespondent SexRespondent CatchAware AttWatShortage MamberEnv HHLabInc hhwatshort

29 7 Table 7. Summary of household ncome and educaton Income Class + or Educaton level class + Varable hhhincome (%) NA* hhhincome( cum. %) NA Edu_class (%) NA Edu_class Cum. %) NA + See Table 5 for educaton and ncome class defntons; *NA= not applcable

30 8 Table 8. Responses to double-bounded bds Intal bd (n Ksh) (Yes, Yes) (Yes, No) (No, Yes) (No, No) Total Total Percent (%) The percent s calculated n relaton to the 179 respondents who responded the WTP queston.

31 9 Table 9. Results of Interval data model Varable name Coeffcent Std. error z P> z AgeRespondent -2.08** SexRespondent edu_class 53.33*** CatchAware AttWatShortage * MemberEnv HHLabInc hhhncome 69.64*** hhwatshort -1.37* /lnsgma sgma *= sgnfcant at 10%; **= sgnfcant at 5%; ***= sgnfcant at 1% Wald ch2(9) = ; Log lkelhood = ; Prob > ch2= Observaton summary: 19 left-censored observatons 0 uncensored observatons 51 rght-censored observatons 109 nterval observatons

32 10 Table 9. Predcted WTP usng varous post estmaton methods Predcton method # observaton Mean Std. Mn. Max. Lnear predcton e ( a, b) : condtonal expected value method ystar ( a, b) : truncated method e(a, b)calculates E(xb + u a < xb + u < b), the expected value of y x condtonal on y x beng n the nterval (a, b), meanng that y x s censored. a and b are specfed as they are for pr(.). 2 ystar(a,b) calculates E(y*), where y* = a f xb + u < a, y* = b f xb + u > b, and y* = xb + u otherwse, meanng that y* s truncated. a and b are specfed as they are for pr(.).

33 11 Table 10. Populaton sze of survey sub-locatons Sub-locaton Male Female Total Ruthmtu 7,493 7,776 15,269 Mt. Vew 8,439 8,242 16,681 Loresho 9,449 8,561 18,010 Gatna 24,747 21,125 45,872 Mazwa 6,470 7,720 14,190 Upper Parklands 3,015 3,023 6,038 Total 59,613 56, ,060 Source: Kenya Natonal Bureau of Statstcs (KNBS, 2010). Kenya populaton and housng census volume IA: populaton dstrbuton by admnstratve unts. Narob, Kenya: Kenya Natonal Bureau of Statstcs, Narob (KNBS) 217p.

34 Fgure Clck here to download Fgure: fgure.doc Page 1 of 1 Fgure 1. Map of the study stes (cty sub-locatons)