Households Willingness to Pay for Improved Solid Waste Collection Services in Kampala City, Uganda

Transcription

1 Workng Paper Seres No. 07/11 Households Wllngness to Pay for Improved Sold Waste Collecton Servces n Kampala Cty, Uganda by Margaret Banga, Razack Lokna, Adolf Mkenda and Kassm Kulndwa Abstract Ths study dentfes the determnants of households wllngness to pay for an mprovement n sold waste collecton servces basng on 381 households n Kampala. Employng the doublebounded contngent valuaton method, households mean wllngness to pay for mproved sold waste collecton servce was estmated to be Ushs 2439 per month. Both the decson to pay and the amount households are wllng to pay for mproved sold waste collecton servces are nfluenced by ncome, educaton, age and home ownershp. A socally acceptable fee whch the majorty of people are wllng to pay should be set n order to avod the free rder problem. JEL Classfcaton: Keywords: Department of Economcs Workng Paper Seres Unversty of Dar es Salaam

2 Workng Paper Seres No. 07/11 Households Wllngness to Pay for Improved Sold Waste Collecton Servces n Kampala Cty, Uganda by Margaret Banga, Razack Lokna Adolf Mkenda and Kassm Kulndwa Outlne 1. Introducton 2. Data 3. Emprcal Desgn and Methodology 4. Theoretcal Model 5. Results and Dscusson 6. Conclusons References The Authors Margaret Banga s currently a lecturer, Insttute of Statstcs and Appled Economcs, Makerere Unversty, Box 7062, Kampala, Uganda; durng the wrtng of ths paper she was a Post-doc n the Department of Economcs, Unversty of Dar es Salaam. Razack Lokna and Adolf F. Mkenda are both Senor Lecturers n the Department of Economcs, Unversty of Dar-es-Salaam. Correspondng Author: rlokna@udsm.ac.tz Acknowledgements Fnancal support from Swedsh Internatonal Development Agency (Sda) through the Envronment for Development (EfD) programme s acknowledged Workng Papers at

3 1. Introducton The economc and demographc growth of ctes n Uganda, s posng serous challenges to the urban local authortes. Wth rapdly swellng urban populaton, the requrement for nfrastructure and servces ncrease manfold. Sold Waste Management (SWM) s one such servce that needs to be adequately provded to ensure an urban envronment conducve to the well-beng and productvty of the resdents. The sold waste problem s due to hgh waste generaton, nadequate waste collecton and poor dsposal habts by the households/ndvduals. In Uganda, the local government authortes are responsble for SWM servces, but these servces are only at secondary level (collecton from dumpng grounds/skps). Prmary collecton (waste removal from houses) s neglected by Kampala Cty Councl (KCC) and yet a poor prmary collecton means exposed waste n the vcnty and an unhealthy envronment. Lack of nfrastructure, an neffcent nsttutonal setup, and lmted fnancal and techncal resources, have led to an nadequate and neffcent level of provson of servces even at the secondary level and yet the rate of waste generaton s ncreasng each day. Kampala cty, wth a populaton of about 2 mllon people (projected from the 2002 census), generates about 1580 tones of sold waste per day. Of the total waste generated, about 53% s resdental sold waste (Banga, 2008). However, only 40 percent of the total waste generated s collected by both KCC and the prvate sector 1. Therefore, the sgnfcant amount of sold waste generated s ether burnt on the streets or ends up n dranage channels, marshy areas and empty plots. In addton to the low collecton rate, there s nequalty n the geographcal dstrbuton of the servce. Hgh-ncome resdental areas and the cty center receve better servces from both KCC and prvate companes, whle low-ncome areas and the nformal settlements receve lttle (and n some areas) no waste collecton servces. In an attempt to reduce the burden facng KCC n sold waste management, KCC has decded to explore the alternatve of prvatzng sold waste management servces, whereby, people pay for the servces,.e the collecton of the waste that they themselves generate. Indeed, n 1999, followng the establshment of the sold waste management ordnance, whch empowers the partcpaton of the prvate sector n sold waste management servces, KCC started contractng prvate frms n order to mprove on sold waste collecton servces. Whle prvatzaton may be a vable opton to the sold waste 1 Cty Mayor, Personal communcaton

4 problem, n most cases t s done hurredly and not gven much thought and as a result ts ntended purpose may not be acheved. There s lack of nformaton on whether households are wllng to pay for the servces that prvate frms provde, and f so, how much they are wllng to pay to have the servces provded to them. To answer these questons, ths study undertook a contngent valuaton (CVM) survey to assess the households wllngness to pay for sold waste collecton servces n Kampala. Contngent Valuaton method s a non-market valuaton method commonly used to fnd the economc value of envronmental commodtes. It s a method that uses hypothetcal survey questons to elct people s preferences for publc goods by fndng out what they are wllng to pay for specfed mprovements n them (Mtchell and Carson, 1989). The contngent valuaton method has been used by several scholars to study wllngness to pay for sold waste management servces (Altaf et al., 1996; Zan, 1999; Fonta et al., 2008, Jn et al., 2006, Basl et al.,2006). These studes used the random Utlty approach proposed by Hanemann (1984) and dd not go further to re-parameterze the coeffcents n order to explan the margnal contrbutons of the ndependent varables to the underlyng WTP. Ths study takes the approach proposed by Cameron and James (1987) and Cameroon (1988), whch gve two separate estmates for the locaton and scale varable, and the coeffcents of the explanatory varables can be easly nterpreted as margnal contrbutons to the dependent varable. 2. Data Kampala s dvded nto fve admnstratve unts (Dvsons). However, only four dvsons (Nakawa, Kawempe, Rubaga and Makndye) were consdered for ths study because the ffth dvson (Central Dvson) s better servced by both Kampala Cty Councl (KCC) and a prvate company. 2 From each of the four dvsons, one parsh was chosen to partcpate n the survey, each wth an equal allocaton of 100 households. Wthn each parsh, 5 Local Councls (LCs) were sampled from whch households for ntervews were randomly selected. 3 The enumerators were nstructed to ntervew household heads, and n cases where the household head was not around, they 2 It s also the admnstratve dvson and houses most of the wealther households, ncludng the Statehouse. 3 Samplng frames were obtaned from the local councl leaders.

5 ntervewed someone who s nvolved n decson-makng or one wth knowledge about household expendtures and commtments. The survey was carred out usng a face-to-face ntervew approach n accordance wth the NOAA Panel recommendaton (Arrow et al., 1993). Fve graduates were recruted and thoroughly traned to carry out the survey. To ensure qualty control, the enumerators were not splt nto groups; they all vsted each parsh together. Ths was done to prevent the respondents who had been ntervewed from dscussng the content of the questonnare wth other respondents who were yet to be ntervewed. 3. Emprcal Desgn and Methodology The elctaton method used n ths study was a close-ended format (double-bounded) and the payment vehcle was a monthly garbage fee to be pad drectly to the prvate company (the servce provder). In desgnng the questonnare used n ths study, focus group dscussons and a plot survey of 80 respondents were frst conducted. The am of the focus groups was to help determne how much nformaton to present, as well as to refne the questons used n the valuaton secton. Four focus group sessons of eght people were organsed and conducted n July The fndngs from the focus groups were used n the development of a draft contngent valuaton survey questonnare, whch was subsequently used n the plot survey. The draft questonnare was pre-tested on a sample of 80 respondents. The pretest was dvded nto two; the frst 50 respondents were presented wth an open-ended queston n order to get the bd desgn, and snce the fnal survey was to be carred out usng the close-ended elctaton format, the last 30 respondents were presented wth a closeended valuaton queston. The fnal verson of the questonnare was based on the results from the plot survey. Informaton from the focus group and plot survey exercses suggested a bd vector of 1000, 2000, 3000 and 4000 Uganda Shllngs (Ushs). 5 Followng on from the plot testng of the questonnare, the man survey was carred out for a perod of 8 weeks on a sample of 400 households from four dvsons of Kampala Cty. These dvsons ncluded Nakawa, Naguru, Kawempe and Rubaga. 4 Four parshes (Naguru, Nakulabye, Mulago and Nsambya) were used n the study. Therefore, there was one focus group for each parsh. 5 At the tme of the survey, 1 USD = 1820 Ushs

6 Recent research (Fujta et al., 2005) ndcates that at least 600 samples are needed for a sngle-bounded format and at least 400 samples for a double-bounded format n order to ensure statstcal relablty of WTP estmatons. Also, for each type of communty or area to be surveyed, a sample of between 100 and 200 respondents s desred (Contreau-Levne et al., 2000). Takng ths nto account and gven the budget constrant, we decded to take a sample of 400 households. The households were frst nformed about the current waste management stuaton before the scenaro for the planned mprovement n waste management was presented. The respondents were also remnded about ther budget constrant n relaton to the responses they gve to the valuaton questons. In dong so, t s assumed that the respondents would take nto consderaton ther ablty to pay f the descrbed mprovement s mplemented. To reduce the hypothetcal bas, whch s nherent n the CVM survey mechansm, a cheap talk 6 secton that remnds respondents about the mportance of truthfulness n ther answers was ncluded. Cummngs and Taylor (1999), Lst (2001), and Lusk (2003) have found cheap talk to effectvely remove hypothetcal bas for respondents. In ths study, respondents were frst asked f they would be wllng to pay anythng, even a small amount for the mprovement explaned to them n the scenaro. For those who sad yes to the partcpaton queston, a dchotomous format (doublebounded) of the valuaton queston was asked. In ths case, the respondent was presented wth an ntal bd and asked whether he/she was wllng to pay that amount or not. If the response to the ntal bd was yes, the respondent was then presented wth a hgher bd (twce the ntal bd) and asked f she/he was wllng to pay the offered amount. If the response to the ntal bd was no, the respondent was presented wth a lower bd (half the ntal amount) and asked f he was wllng to pay that amount. The double-bounded format was fnally followed by an open-ended follow-up queston solctng the maxmum amount that the household was wllng to pay. The follow-up queston helps n dentfyng nconsstent responses and outlers. Four dfferent bds (1000, 2000, 3000 and 4000) were used n ths study and households were assgned randomly to any one of these bds. For those who sad no 6 Cheap talk s a non-bndng communcaton between a researcher and the respondent pror to admnstraton of the CVM valuaton questons.

7 to the partcpaton queston, they were asked to gve reasons why they were not wllng to pay anythng. 4. Theoretcal Model Dchotomous choce CVM s based on random utlty theory, whch assumes that choces are based on utlty comparsons between the avalable alternatves, and the alternatve that provdes the hghest utlty wll be the preferred choce (McFadden, 1974; Louvere et al., 2000). Ths study follows the approach to modellng CV data by Cameron et al. (1987) and Cameron (1988) whch bypasses the underlyng utlty model and estmates the parameters of the latent WTP dstrbuton drectly. Ths approach permts the straghtforward calculaton of margnal values for all arguments n the WTP functon and are easy to nterpret. Cameron s approach s derved from the expendture functon as follows: WTP z, z, u ; s e( z, u, s) e( z, u, s)... (4.1) where z 1 s the stuaton wth mprovement n sold waste management, z 0 s the current sold waste management stuaton, s s a vector of soco-economc varables and u 0 s the utlty level before the ntroducton of mproved sold waste management servce. Assumng a lnear functonal form for the WTP, the econometrc model s Y ',... (4.2) x where Y s the unobserved true ndvdual wllngness to pay (WTP) for the envronmental resource n queston at the moment the dchotomous choce queston s posed. Y s assumed to depend on ndvdual soco-economc characterstcs contaned n the vector x plus an unobservable random component ε (dstrbuted N(0, σ 2 )), whch absorbs all unmeasured determnants of the value of the resource to ths ndvdual. Y s consdered a latent contnuous censored varable: the observed varable s the answer yes or no regardng whether or not the ndvdual would be wllng to pay a gven amount t. The ndvdual wll state that he s wllng to pay the offered amount I 1 f Y and unwllng to pay the offered amount 0 t I f Y t. The dscrete response ndcator varable I s the sngle endogenous (dependent) varable n ths framework.

8 Let P 1 be the probablty that Y t and P 0 be the complementary probablty. In the double-bounded model, we have four response probabltes because each partcpant s presented wth two bds. The level of the second bd s contngent upon the response to the frst bd. If the respondent says yes to the frst bd ( t I ), meanng that he s wllng to pay the amount of the frst bd, he s presented wth a second bd ( t H ) that s some I H amount greater than the frst bd ( t t ). If the ndvdual responds wth a no to the frst bd, the second bd ( L I L t ) s some amount smaller than the frst bd ( t t ). In ths case we observe two dchotomous varables; the answers to the frst queston and ts follow-up. The outcomes to ths method are () no to both bds; () a no followed by a yes ; () a yes followed by a no ; (v) yes to both bds. The second offered threshold s clearly not ndependent of valuaton nformaton, whch the respondent has revealed n answerng the frst WTP queston. The sequence of questons solates the range n whch the respondent s true WTP les, placng t nto one of the followng four L L I I H u ntervals: (, ), ( t, t ),( t, t ) or ( t, ). t The second bd, n conjuncton wth the response to the ntal preference decson, allows both an upper and a lower bound to be placed on the respondent s unobservable true WTP. If the second decson s n the same drecton as the frst (yes, yes; no, no), t rases the lower bound or lowers the upper bound, respectvely. We therefore have the followng response probabltes: H I H Pr(yes, yes) = Pr( Y t t ) 1 F( t )... (4.3) I H H I Pr(yes, no) = P ( t Y t ) F( t ) F( t )... (4.4) r L I I L Pr(no, yes) = P ( t Y t ) F( t ) F( t )... (4.5) r L I L Pr(no, no) = P ( Y t t ) F( t )... (4.6) r Gven ths data, a log-lkelhood formulaton of the double-bounded model s applcable. n LogL 1 H H ' I I log F t x / H H ' I ' + I 1 I log F t x / F t x B /

9 L I ' L ' + I 1 I log F t x / F t xb L L ' + 1 I 1 I log F t x / where /... (4.7) I t s the bd offered n the frst queston; I, I, I are dchotomous varables wth value one f the answer to the ntal bd or the correspondng follow-up has been postve, and zero otherwse. Maxmsaton of the log-lkelhood wll yeld separate estmates of and and ther ndvdual asymptotc standard errors. Ths s made possble because of the presence of t n the lkelhood functon. The estmated parameters of Cameron s approach can be nterpreted n the same way Ordnary Least Squares (OLS) results are nterpreted. In other words, the s can be nterpreted as the margnal contrbuton to change n WTP resultng from a one unt change n the explanatory varable. In the same way, the transformatons of Y commonly used n OLS models can readly be employed by applyng them to t. Ths method also produces asymptotc standard error estmates drectly, and no addtonal computatons are requred (Cameron and James, 1987). The advantage wth ths approach s that one s able to determne (systematcally and easly) the effect upon the condtonal expectatons of WTP of changes n the levels of each explanatory varable (Cameron 1988). As suggested by Krström (1997), a partcpaton queston ntroduces a spke n the model, and ths allows for a non-zero probablty of zero WTP. If the respondent answers no to the partcpaton queston then hs/her WTP s assumed to be zero wth a postve nonzero probablty a. If the response s postve, the second queston asks whether the ndvdual s wllng to contrbute t, where t s one of the possble bds n the study. For household, let S =1(0) f the response to the frst queston s yes (no) and let I=1(0) f the response to the bd t s yes (no). Therefore, (S, I) can take on the values (1, 1), (1, 0) and (0, 0). The sample log lkelhood functon correspondng to these possbltes s: H L N ln L [ S I ln(1 G( t )) SI ln( G( t )) (1 S )ln(1 G(0))]... (4.8) 1 where N s the sample sze, G( 0) a (0,1 ) and the probablty of a yes response (.e. that the household accepts the bd (t ) s assumed to be normally dstrbuted N (0, σ 2 ). In order to allow for the estmaton of a double-bounded model wth a spke and the ncorporaton of explanatory varables, we use the method proposed by Reser et al. (1999) whch suggests breakng up the lkelhood functon n (4.8) nto two separate

10 parts. In the frst part, the spke s estmated usng a probt regresson, where the dependent varable w for each household s 1 or 0 accordng to whether the WTP s greater or equal to zero. probt w x... (4.9) where x s the vector of household characterstcs. The second part conssts of optmzng the cumulatve dstrbuton functon F(t ) of the sub-populaton that s wllng to pay. In ths estmaton, the log-lkelhood functon n equaton (4.7) s estmated. The WTP dstrbuton s assumed to be log-normal. The Mean WTP wth a spke (uncondtonal mean.e. takng nto account those wth zero WTP) s then calculated as E ( WTP ) E( WTP WTP 0) * Pr( WTP 0) 0*(Pr( WTP 0))...(4.10) 5. Results and Dscusson 5.1 Socoeconomc characterstcs of respondents Of the 400 questonnares used n the survey, 381 were vald (wth complete nformaton). The sample characterstcs are gven n Table 5.1. Frstly, the majorty of respondents (66.2 percent) were females and ths was manly because they were the ones found at home at the tme of the ntervew. Secondly, even n cases where both husband and wfe were at home, the husbands preferred ther wves to be ntervewed clamng that they are the ones concerned wth handlng waste. The average age of respondents was 36.7 years, and the average famly sze was 6 people (the natonal fgure stands at 5). Educaton wse, 15% had at least a dploma. The monthly average ncome per household was Ushs , wth the majorty of households (65.1%) havng one person contrbutng to household ncome. In terms of ownershp of the houses, 52.2% were stayng n ther own houses, 45.2% were rentng normally, whle only 2.6% were stayng n houses rented by a relatve or suppled free by the employer. About 41% of the houses had compounds. Households who stay n houses wth compounds have alternatve ways of dsposng of waste such as dggng pts or throwng t n ther backyards.

11 Table 5.1: Descrpton and Summary Statstcs of Varables Varables Descrpton Mean Std devaton Age Actual age of respondent n years Hhsze Household sze measured by number of adults and chldren feedng from the same source Educaton Educaton level of the respondent; 1=Dploma and above, 0 otherwse Income Monthly household expendture (n Uganda Shllngs) Gender 1=Male; 0 = Female Pay Whether household has ever pad for waste collecton n any form(1= Yes, 0=No) Tenure Home ownershp(1=owned, 0= Rentng) Yard Whether the house has a compound (yard) or not. (1= presence of a yard, 0= No yard) Problem Whether household reported sold waste as a major problem (1=Yes; =No) Separate Whether household separates sold waste or not (1=Yes, 2=No) Source: Author s Computaton from Survey Data. 5.2 Current Waste Management Practces Respondents were asked how they store ther household waste before dsposal. Most of the respondents (81.1%) reported to be havng contaners where they store ther sold waste before dsposal. The contaners are usually durable plastc bags ( kg capacty) and the practce s to throw away the sold waste and re-use the plastc bags. The remanng 18.9 % who do not have contaners throw ther waste n the backyard, n pts or burn t n ther compounds. In terms of the waste collecton servce to ther households, 22.8% reported that a collecton vehcle goes around and they take ther waste at a partcular pck-up pont. The largest percentage (34.9%) however take ther waste to communal contaners suppled by Kampala Cty Councl (KCC), 7 whle 23.3% empty ther waste onto an open ple. The results also show that 4% of the respondents hre nformal prvate waste collectors who carry away the waste but they do not know where t s dsposed of. Table 5.2 shows the dfferent ways households dspose off sold waste. 7 We found communal contaners n two of the parshes surveyed (Naguru and Nsambya). KCC had wthdrawn the contaners from the other areas studed.

12 Table 5.2: Current Major Waste Management (Collecton Servces) n the Surveyed Areas Management Practces No of respondents Percentage Collecton vehcle at a pck-up pont Throwng n a communal contaner Throwng n open feld (llegal ple) Throwng n backyard/pt or buryng n own land Don t know 15 4 Total Source: Author s Computaton from Survey Data. The households whch do not burn or throw ther waste n ther backyards were further asked who normally takes the waste bns out to be empted. The results ndcate that 32.4% of the households make use of prvate nformal waste collectors wthn the communty to take the waste bns out. Ths s followed by the housewves (20.7%) and by chldren between the age of 13 and 18 who consttute 17.5% (see Table 5.3). Ths result shows that the nformal prvate sector plays a major role n sold waste management, and therefore, there s a need to ntegrate them nto waste management plannng. Table 5.3: Who Normally Takes the Waste Bn Out to be Empted? Poston n the household Frequency Percentage Head of household Spouse (female) Any member of the household Mad/Houseboy Any chld between the age of 6 and Any chld between the age of 13 and Informal garbage collector (scavenger) Don t know Total Source: Author s Computaton from Survey Data. Respondents were also asked about ther percepton towards the present garbage collecton systems. Only 24% of the respondents were satsfed wth the present waste collecton systems. Ths result mples that there s an urgent need for mprovement n sold waste management servces n the study areas. The man reasons why people were not satsfed wth the current waste collecton servces n order of mportance were; the nterval between collectons s too long (40.3%), persstent squalor at the

13 communal contaners/llegal ples (27.1%), servce beng unrelable (12.5%) and the locaton of the communal contaner or pckup pont s unsatsfactory (11.1%). Some of those who take ther sold waste to the garbage collecton truck complaned of the rregularty of the truck, whch results nto t gettng too full whenever t comes to collect garbage. Ths s what one of the respondents had to say: The vehcle takes long to come. Some tmes t comes after 2 weeks and at tmes even after a month. When t comes, everyone rushes to have her waste taken. Unfortunately the vehcle cannot take all the waste. They over fll t such that even as t moves some waste falls off back to the road. In fact some people reman at the pckup pont wth ther waste. So what do you expect? Do you expect me to carry back the waste and keep t n my home for another two or three weeks? All I can do s leave t at the pck up pont. 5.3 Valuaton Results The majorty (79.8%) of the 381 households consdered n ths study were wllng to pay for a door-to-door waste collecton servce (ther WTP>0). The man reasons gven by the 20.2% who were not wllng to pay (WTP=0) were; they could not afford to pay for garbage collecton (40.5%), t s a responsblty of KCC (29.1%), satsfed wth the current way they dspose of ther garbage (16.3%), and they do not beleve the servce wll be relable (13.9%). Of the 77 respondents wth a zero valuaton for WTP, thrty two (41.6%) were consdered to be protest responses to the valuaton queston, consttutng 8.4% of the whole sample. Two nconsstent responses were also dentfed. Thus, n total we had 34 nvald responses. Ordnarly, n estmatng the determnants of wllngness to pay for a project, the most convenent approach would be to dscard the nvald responses and use the vald ones. However, smply dscardng the nvald responses could lead to sample selecton bas, whch may possbly affect the valdty of the estmates obtaned from the gven sample for the purpose of polcy nference. Ths s because the sample remanng after excludng the nvald responses may not be a random sample (although the ntal sample was a random one) (see Mekonnen, 2000; Cala and Strazzera, 2000; Strazzera et al., 2003a and 2003b; Fonta and Ichoku, 2005).

14 Removal of nvald responses can be justfed f the group of respondents wth nvald responses s not sgnfcantly dfferent from the remander of the sample, at least n terms of the covarates employed n the WTP model. The means of the varables of the vald and nvald response groups are compared and any sgnfcant dfference between these two groups of respondents s an ndcator of the presence of sample selecton bas and justfes the use of a sample selecton WTP model (Vella, 1998; Strazzera et al., 2003a, 2003b). Vella (1992, 1998) argues that once there s no sgnfcant dfference n the characterstcs of the two sub-samples, then there s no need of usng a sample selecton model. To test whether the respondents wth vald responses and those wth nvald responses dffer sgnfcantly n characterstcs, the ndvdual t-test s used. The null hypothess s that there s no dfference n means of varables between the vald responses and nvald responses. That s, the t-statstc s calculated for the null hypothess vald nvald x x =0, where wth vald responses and vald x s the mean characterstc of respondents nvald x s the mean characterstc of those wth nvald responses. All the absolute values of t-statstcs for the varables dd not exceed the crtcal value (1.96) at the 5% level, thus the null hypotheses could not be rejected. Ths study therefore uses only the vald responses snce there s no sgnfcant dfference between the characterstcs of the vald sub-sample from the nvald subsample Sample Frequences to Wllngness to Pay Table 5.4 column 2 shows that the share of yes responses decreases as the bd amount ncreases rangng between 93% and 14%. Nnety three percent of the respondents who were asked a bd amount of 1000/= answered yes, at bd amount 2000/=, the percentage of those who sad yes decreased to 56.8 percent, and at the hghest bd amount 4000/=, only 13.9 percent answered yes. In a well developed CVM survey, the number of yes answers should declne as the bd amount ncreases (Carson, 2000).

15 Table 5.4: Sample Frequences to the WTP Questons for Door-to-Door Sold Waste Collecton 8 (n = 302) Intal Bd (UGX) Yes a Yes-Yes b Yes-No No-Yes No-No Number asked (50.7) 29 (42) 5 (7.2) (20.3) 27 (36.5) 26 (35.1) 6 (8.1) (11.3) 18 (22.5) 30 (37.5) 23 (28.8) (8.9) 4 (5.1) 34 (43.0) 34 (43.0) 79 Source: Authors Computaton Notes: a: Column two refers to a yes response to the ntal bd only b: In parenthess are percentages Furthermore, the proporton of yes-yes answerng pattern falls as the bd amount s ncreased. For example, of those who were asked an ntal bd of 1000/=, around 50.7% were wllng to pay at least 2000/= for a door-to-door sold waste collecton system, whle only 8.9% were wllng to pay at least 8000/=. The proporton of no-no answers ncreases as the bd amounts on the WTP queston are ncreased. At bd amount 1000/=, there s no no-no respondents, mplyng that all the households (who are wllng to pay somethng) are wllng to pay at least 500/= 9 for door-to-door sold waste collecton servce, whle 43% answered no-no to the hghest bd. The remanng answerng patterns, yes-no and no-yes responses ndcate that the respondents maxmum WTP les between the ntal bd amount and the ncreased, and decreased, bd amounts respectvely. These results can therefore be nterpreted as a sgnal of the nternal valdty of the CVM answers, confrmng the selecton of an effcent bd desgn. Table 5.5 and Fgure 5.1 show the survval probabltes from the non-parametrc analyss of the double-bounded responses. 8 Ths table shows only those who were wllng to pay. Snce there was a partcpaton queston, the bd values were presented to only those respondents who were wllng to contrbute somethng. 9 Snce 1000/= was the lowest bd n the bd desgn and the follow-up bd was halved f the response to the ntal bd was no, then the lowest follow up bd asked was 500/=.

16 Percentage of yes responses Table 5.5: Survval Probabltes Estmated for Double-Bounded Responses 10 Bd (Ushs) Number of Avalable Subjects Number of subjects who are wllng to pay the Bd Source: Author s Computatons Probablty of sayng yes Fg. 5.1: Survval Functon for the Double-Bounded Responses Offer bds. Source: Authors own complaton The dstrbuton of the WTP helps us to know the percentage of the sample that would be wllng to pay for the servce at each partcular bd value. For example, from Fg 5.1, t can be seen that at bd amount 500, all the sample respondents (who are ready to partcpate n the programme) are wllng to pay for the servce. At bd amount 1000, 92% of the respondents would be wllng to pay to have the servce. At 1500, only 71% of the households wll be wllng to pay for the servce. The medan WTP s 2100/= and 10 We use Terawak s (2003) Second Nonparametrc Approach for Double- Bounded Dchotomous Contngent Valuaton. For an extensve dscusson of the method, see Terawak (2003).

17 at ths prce, 50% of the households would be wllng to pay. 11 Ths nformaton s necessary for the polcy makers and prvate companes when decdng on tarffs Determnants of wllngness to pay Before estmaton of the WTP functon, a startng pont bas test was performed to check f the double-bounded model was the most approprate model to estmate. Albern (1995a) and Albern et al. (2005) show that when there s no startng pont bas, the double-bounded model s the correct model, and the estmates of the mean WTP are vrtually unbased. To test for the presence of startng pont bas, 3 bd set dummy varables 12 were ncluded among the regressors of the double-bounded model, and then the null hypothess that the coeffcents on these dummes are jontly equal to zero was tested. 13 Usng the Wald test statstc, the null hypothess that all the coeffcents of the bd set dummes n the model are not sgnfcantly dfferent from zero could not be rejected, mplyng that there s no evdence of startng pont bas on the bd amounts. The fnal results of the estmatons are shown n Table 5.6. Column two presents the results of the spke probt n whch the dependent varable s ether 1 or 0 correspondng to whether the household s wllngness to pay s greater than or equal to zero. The thrd column shows the results of the double-bounded estmaton for only those wth a postve wllngness to pay. The hypothess that all coeffcents except the constant terms (n the two models) are smultaneously equal to zero was tested usng the Wald statstc. The calculated Wald ch-squares are and n column 2 and column 3 respectvely, leadng to the rejecton of the hypothess at a 0.01 probablty level wth 11 and 10 degrees of freedom respectvely. Ths ndcates the capablty of the models to explan the varaton n WTP for mproved sold waste management servces. 11 The medan s the value of the WTP at whch the survval functon equates to Bd set dummes mean a set of dummes where the frst dummy takes on a value of one f the respondent was assgned to the frst bd set used n the survey, and 0 otherwse etc. 13 Ths method was also used by Whttngton et al, 1990; Green and Tunstall, 1991; Cameron and Quggn, 1994; Altaf et al, 1996 and Chen et al, 2005

18 Table 5.6: Estmaton Results for the Double-Bounded Model. Varables a The Spke Partcpants (Double- (Probt) Bounded) Constant (-0.04) 3.49 (3.26)*** Lncome 0.26 (2.70)** 0.36 (4.10)*** Gender 0.16 (0.55) 0.16 (1.18) Tenure 0.52 (1.99)** 0.21 (1.88)* Educaton 0.58 (1.71)* 0.25 (1.90)* Age (-3.17)*** (-3.05)*** Pay 0.64 (2.77)** 0.18 (1.63) Problem 0.44 (2.06)** (-0.83) Waste (-0.79) Household sze (-0.12) Separate (-0.03) (-2.33)** Kawempe 0.73 (2.11)** Makndye 0.09 (0.30) Rubaga 0.01 (0.03) Log pseudo-lkelhood Sample sze Wald Ch2 (11) Wald Ch2 (10) = Prob>Ch Pseudo R Notes: a The dependent varable n column 2 s 1 or 0 resultng from the partcpaton queston. b The dependent varable n column 3 s the nterval n whch the WTP falls. c The numbers n Parentheses are z-statstcs. d *, ** and *** ndcate sgnfcance at the 10%, 5% and 1% levels respectvely. e Kawempe, Makndye, and Rubaga are locaton dummes. Nakawa s the reference. These are the four dvsons that were surveyed. From the results n Column 2, t can be seen that household ncome, tenure, educaton level of the respondent, age of the respondent, whether the household has ever pad for garbage collecton, whether sold waste s vewed by the household as a major problem, and household beng located n Kawempe are the man factors determnng the household s decson of whether to pay or not to pay for the proposed door-to-door sold waste collecton servce. The negatve coeffcent on the age varable mples that the young respondents are more wllng to pay for the mprovement than the old. Income, educaton and whether sold waste s vewed by the household as a major problem, tenure, and pay postvely affect the decson to pay for the mproved sold waste management servce, mplyng that rcher households, the educated, those who perceve sold waste as a major problem and those who have ever pad for sold waste collecton

19 are more wllng to pay for the mprovement than the poorer, the less educated and those household who perceve sold waste as not beng a major problem to them. The more educated beng more wllng to pay may be explaned by the fact that educated people can access nformaton about the envronment and health more easly than the less educated. Educated people are more lkely to read newspapers and magaznes, and therefore have a hgher awareness of the dangers of poor waste management and the benefts of proper waste dsposal. From the coeffcents of the locaton dummes, only Kawempe has a postve and sgnfcant coeffcent mplyng that households n Kawempe Dvson are more wllng to pay for sold waste collecton servce than those n Nakawa. There s no sgnfcant dfference between Makndye, Rubanga and Nakawa. Ths result s not surprsng gven the fact that among all the dvsons, there were no KCC communal contaners n Kawempe. Thus, the households depended on the garbage trucks (whch were rregular) and the nformal waste collectors. Despte the fact that sold waste related ssues are handled by females n the home, the results show that gender does not sgnfcantly nfluence wllngness to pay. Fonta et al. (2008) found gender to sgnfcantly nfluence household s wllngness to pay. Also, the amount of waste generated by a household and whether the household practces some form of waste separaton at source have no sgnfcant nfluence on the decson to pay for sold waste collecton. Column 3 gves the results of the double-bounded estmaton for only those respondents who have a postve wllngness to pay. Household ncome has a statstcally sgnfcant and postve effect on the amount a household s wllngness to pay; the amount of money a household s wllng to pay for door-to-door sold waste collecton servce ncreases wth household ncome. For example, f monthly household ncome ncreases by 10%, the amount of money a household s wllng to pay for door-to-door sold waste collecton wll ncrease by 3.6% per month. 14 The coeffcent on the age varable has a negatve sgn, whch means that monetary valuaton decreases wth age of the respondent. Younger respondents are found to be wllng to pay more for door-to-door sold waste collecton servce. Ths could be 14 As explaned n secton 4, when the Cameron Approach s used, the resultng coeffcents can be nterpreted n the same way OLS estmates are nterpreted. Snce we have assumed a log-normal dstrbuton and the ncome varable s n logs, the ncome coeffcent can be nterpreted as a percentage change.

20 explaned by the fact that older people are more resstant to changng the ways of dong thngs around ther houses, and snce payng for waste collecton servce s relatvely new n Kampala, older respondents are less lkely to be wllng to pay more. For each addtonal year n age, the wllngness to pay for door-to-door sold waste collecton decreases by 1.4%. Altaf et al. (1996) also found a negatve relatonshp between age of respondent and wllngness to pay for mproved sold waste management for Gujranwala (Pakstan). As expected, households who are stayng n ther own homes (Tenure) are wllng to pay more than those who are rentng. Ths may reflect a securty aspect of wllngness to pay, where the homeowners know that they wll be stayng n ther homes for long, or f they decde to move, the waste collecton servce n the area wll have ncreased the value of the home. Homeowners are wllng to pay 21% more for sold waste collecton servce than those who are rentng. The mplcaton of ths result s that snce those who are rentng are wllng to pay less for door-to-door sold waste collecton servce, the garbage fee can be ncluded n ther house rent so that t becomes the responsblty of the landlord to pay to the servce provder. In ths model, the reference educaton level s those wth below dploma. The sgn on the educaton varable s postve and sgnfcant. Ths mples that the hgher the educaton level of the respondent, the more amount he s wllng to pay for door-to-door sold waste collecton servce. The fndng that a hgher educatonal level ncreases the amount that a household s wllngness to pay for sold waste management s not surprsng as more educaton enhances an ndvdual s wllngness to take responsblty for hs/her own health. Those who have attaned at least a dploma are wllng to pay 25% more than those wth an educaton level below dploma. As antcpated, households who do separate ther waste are wllng to pay less than those who do not separate. They are wllng to pay 17% less than ther counterparts. Ths fndng s not surprsng because households fnd other uses for the separated waste. For example, they gve peelngs to domestc anmals, some metals are sold, and plastc contaners are used as flowerpots. In ths way, the amount of waste avalable for dsposal reduces and therefore the household wll not be wllng to pay more for the avalable sold waste. The varables Problem, Pay, Gender, Waste and Hsze are found not to sgnfcantly affect the amount a household s wllng to pay for sold waste collecton servces.

21 The results n Column 2 and column 3 show that some varables may not nfluence a household s decson to pay, but do nfluence the amount that the household s wllng to pay for a door-to-door sold waste collecton servce, for example separate. On the other hand, some varables may nfluence the decson to pay for sold waste collecton but not the amount the household s wllng to pay, for example, problem and pay. 5.4 Welfare Analyss The man purpose of conductng a CVM study s to obtan a welfare measure, such as mean or medan WTP. In ths study, the welfare measure refers to the amount that households are wllng to pay monthly for a door-to-door sold waste collecton servce. The results can be used as a gude for polcy makers concernng ssues such as tarff and s also an ndcaton of the benefts of mprovng sold waste management. For the openended queston, the mean s obtaned as Ushs Table 5.7 presents the welfare estmates wth the correspondng 95% confdence nterval. The uncondtonal mean WTP estmate was obtaned usng equaton (4.10) and s Ushs Ths mples that on average, each household s wllng to pay 2439/= ($1.34) per month to have a door-todoor sold waste collecton servce. Also, the mean WTP of the double-bounded model s greater than the mean WTP from the open-ended queston. Table 5.7: Mean WTP per Household per Month and ther Confdence Intervals (n Uganda Shllngs) Double bounded wthout a Spke Double bounded wth a spke Mean wthout covarates [2796.4, ] a [2181.2, ] Mean wth covarates [2366.9, 2990] [2154.9, ] Source: Author s own computaton. Note: a: the confdence ntervals are estmated usng the delta method. 5.5 Analyss of Cost and Revenue Generated from Garbage Fees In ths secton, the revenues and costs of resdental garbage collecton are dscussed. The cost of 100% collecton of sold waste from Kampala s sad to be about Ushs 500 mllons per month (Kasoz, 2008). Resdental sold waste generaton s estmated to be 840 tonnes per day, whch s about 53% of the total sold waste generated n Kampala

22 (Banga, 2008). Therefore, the cost of collecton of resdental sold waste would be Ushs 265 mllons. The total number of households n the surveyed dvsons s Takng the bd value as the amount to be charged and the percentage of households wllng to pay at each bd value as the complance rate, we fnd that the least amount of revenue wll be generated when the garbage fee s Ushs 500, and the hghest revenue wll be generated when the fee s Ushs At Ushs 500, there s total complance, but the revenue generated does not cover the cost of collecton. At Ushs 2000, the revenue and thus the profts are maxmum, but wth only 55% complance. At the mean WTP of Ushs 2439, the complance rate would be 45%. The frm wll break even f the fee s between Ushs 500 and Ushs At Ushs 1000, there wll be profts realzed and the complance rate s also hgh (92%). 6. Concluson The results show that a hgh percentage of households are wllng to pay for a doorto-door sold waste collecton servce. Ths s contrary to the common belef that people are opposed to payng for sold waste management servces, and that t s the responsblty of government. The mean WTP obtaned s 2439 ($1.3), and s an ndcator of what people are wllng to pay on average, for a door-to-door sold waste collecton servce per month. However, although t s mportant to calculate the mean WTP, the mean alone does not convey much nformaton to the polcy maker. From the dstrbuton of the WTP values, we see that at the mean WTP, about 45% of the sample (those wllng to pay somethng) would be wllng to pay that amount. Ths would mply that the garbage problem s not solved. The queston s, should the garbage charge be based on the mean WTP? To avod the free rder problem, a socally acceptable fee should be set n whch the majorty of people are wllng to pay. The government could then come n to subsdze the prvate company f need be.

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