Unit-pricing: Minimising Christchurch Domestic Waste

Transcription

1 Unt-prcng: Mnmsng Chrstchurch Domestc Waste Peter R. Tat Commerce Dverson, Lncoln Unversty Paper presented at the 2004 NZARES Conference Blenhem Country Hotel, Blenhem, New Zealand. June 25-26, Copyrght by author(s). Readers may make copes of ths document for non-commercal purposes only, provded that ths copyrght notce appears on all such copes.

2 Unt-prcng: Mnmsng Chrstchurch Domestc Waste Peter R. Tat, Commerce Dverson, Lncoln Unversty Summary One economc tool that can ad n the achevement of waste mnmsaton targets s unt-prcng. Unt-prcng n the waste management sector refers to a prcng system that charges households for ther collecton and dsposal servce relatve to the amount of waste dsposed by the household. Ths research nvestgates the potental mpact of mplementng a unt-prcng polcy for domestc waste collecton and dsposal servces n Chrstchurch. Data s collected usng a Contngent Valuaton survey. A Posson Quas-Maxmum Lkelhood count model s specfed for econometrc analyss of demand for Chrstchurch Cty Councl domestc collecton servces. Key words: Demand for domestc waste servce, unt-prcng, Contngent valuaton methodology, PQML count model. Chrstchurch Domestc Waste Servces The Chrstchurch Cty Councl (C.C.C.) supples the cty s major domestc waste and dsposal servce to households by way of a weekly kerbsde collecton. There are also a number of small prvate supplers, and they account for approxmately 15% of the market. The councl servce requres waste to be placed n a councl approved bag that has a ffty ltre, 15 klogram capacty. Untl recently each rateable property was suppled wth 52 bags per year. Ths has now been halved. Collecton and dsposal of these bags s presently funded by a flat rate of $43 leved on households as part of general annual rates. Resdents can buy as many addtonal bags as they requre n a mnmum pack sze of 5 for around $6 a pack from retal outlets. Hazardous waste and lquds are prohbted but anythng else can be put n the bag. The councl servce accounts for 85% of the Chrstchurch domestc waste collecton market, collectng and dsposng of approxmately 37,818 tonnes n Burwood landfll durng 2001 (C.C.C. 2003). Ths s 17 percent of Chrstchurch refuse gong to Burwood landfll. Wth 123,000 households, the average Chrstchurch household dsposes of 307 klograms per year by ths servce. The lfe-span of Burwood landfll, currently Chrstchurch s only landfll, has exceeded ts planned duraton and the Councl antcpates the openng of a new regonal landfll at Kate Valley n the near future. The lfe span of Burwood has been just over twenty years and Kate Valley s expected to have a comparable lfespan. At ths rate potental stes wll become very scarce wthn decades. The Chrstchurch Cty Councl recognses responsblty for ensurng that Chrstchurch has a sustanable future and have mplemented programmes to help reduce waste gong to the landfll ncludng kerbsde recyclng, compostng of some garden waste brought drectly to landfll, recyclng centres at the Refuse Transfer Statons, and the sortng of refuse at the Transfer Statons (mostly metals and nert materal lke sol and rubble). In 2001 kerbsde collecton amounted to 14,374 tonnes, and 31,157 tonnes of green waste was collected at Transfer Statons (C.C.C., 2003).

3 Fgure 1: Composton of refuse n domestc black bags Source: C.C.C. (2003) Glass 3% Metal 3% Textles/Rubber 4% Other 6% Ktchen 30% Plastc 10% Paper 28% Garden 16% Fgure 1 reveals that almost three-quarters (74%) of the contents of an average black bag has the potental to be dverted from landfll. Almost all paper types are now collected from household kerbsdes as part of recyclng. Ktchen and garden waste make up nearly half of an average bag, even though Chrstchurch Cty Councl estmates that approxmately 60% of households compost at home or take green waste to transfer statons. Sustanable development n Chrstchurch The mandate and plan for Chrstchurch s domestc waste management s contaned n three mportant documents: the Chrstchurch Cty Plan (C.C.C., 1995) whch dscusses sustanable development and ts mplcatons for waste management, the Waste Management Plan for Sold and Hazardous Waste (C.C.C., 1998) whch drects current polcy, and The New Zealand Waste Strategy (M.F.E., 2002) whch ams to coordnate actons and polcy natonally. The Natural Envronment secton of the Cty Plan emphaszes a strategy of waste mnmsaton for the cty that promotes the sustanable management of resources. The plan recognses that a prmary ndcator of sustanable development s the dsposal rate of domestc muncpal sold waste. Reducton of waste generaton wll prolong the lfe of waste management facltes, partcularly landflls, and adds to the effcent use of resources. Polcy drectly applcable to the domestc sold waste sector should be formulated so as to mnmse the dsposal of waste nto the envronment. In relaton to councl provded domestc waste collecton and dsposal servces, the Waste Management Plan for Sold and Hazardous Waste recommends that n order to promote the objectves of ths plan, costs must be allocated such that they establsh economc ncentves to reduce waste and that an element of deterrent prcng for producng excessve waste s ncluded n such a system (C.C.C., 1998). The New Zealand Waste Strategy comprses of fve core polces that form the bass for acton, one of these s effcent prcng (M.F.E., 2002). Ths means creatng an ncentve structure that encourages households and ndvduals to mnmse waste. Ths s consstent wth Chrstchurch s waste management plan. Falure to provde

4 such an ncentve structure s untenable n communtes that strve to mplement modern waste management. The vson of the Waste Management Plan for Sold and Hazardous Waste s to mnmse the mpact of sold waste on the envronment. The reducton target for domestc kerbsde waste collecton s 80% less than 1994/95 levels by As the 1994/95 level was approxmately 126 klograms per person per year, ths target equates to approxmately 26 klograms per person per year. Fgure 2: Per person domestc waste, recyclng and green waste Source: C.C.C. (2003) kg/person/year 60 Domestc kerbsde waste Green waste Domestc kerbsde recyclng / / / / / / /01 Year endng 30 June Fgure 2 shows current trends for councl collected domestc waste and recyclng, and green waste at transfer statons. The almost horzontal dashed lne at the top shows that domestc kerbsde waste per person gong to the landfll has remaned vrtually constant snce 1995, wth only a very slght downward trend. The ntroducton of kerbsde recyclng n 1997 has done lttle to decrease the quantty of domestc black bag waste gong to the landfll. Chrstchurch Cty Councl (C.C.C. 2003) suggests that ths low mpact s due to resdents fndng new bts and peces to throw out, now that recyclng means there s more capacty for the same amount of bags. If ths s the case then resdents would have had to store waste over some tme accumulatng a sgnfcant amount. As recyclng ncreased households found more and more thngs to dspose of, so that the amount of waste sent to the landfll remaned relatvely stable. The zero prce for recyclng may be a reason. Ths s because the zero prce can create a perverse ncentve structure n that households can now purchase larger tems or more of an tem, for example, f those tems can be recycled. They face no ncrease n dsposal costs (drectly, that s, recyclng must be funded from somewhere and so other servces prces may ncrease) for the ncrease n volume as they can use the free recyclng servce. Ths s the opposte of source reducton, and may be mtgated by chargng a postve prce for recyclng servces n the same way as waste servce (.e. unt-prcng). However the recyclng servce prce must be set below the waste servce prce to decrease the volume of waste gong to landfll. Another possble explanaton may be that household s have reduced the amount of waste that they take drectly to refuse statons themselves. The ntroducton of green waste separaton at landfll, to be composted, has also done lttle to decrease the amount of domestc waste enterng the landfll va kerbsde collecton. Ths may ndcate that collecton of green waste s not a substtute for

5 kerbsde collecton. Implyng that the ncrease n green waste collected can be attrbuted to separaton of waste by households already gong to transfer statons. Flat-rate neffcency Many communtes have tradtonally charged households for ther waste servce by a flat-rate, as has Chrstchurch. A flat-rate charge s the prce of a servce leved n one lump sum, whch s the same for all households. The charge does not reflect the amount of waste that a household generates. Flat-rate chargng creates a perverse ncentve structure that does not motvate sustanable practce and leads to an neffcently hgh level of servce demanded. The economc argument s relatvely straghtforward and s llustrated below n Fgure 3. Ths secton s adapted from Mranda et. al. (1994 pp 683-5).The fgure shows demand (margnal beneft) and supply (margnal cost) of councl servce as measured by the number of black bags. Waste collecton servces are assumed to be a normal good and so the demand curve s downward slopng. Q * s the effcent quantty of servce snce at ths quantty the margnal beneft from the last unt consumed s equal to the margnal cost of supplyng t. Ths quantty of servce can be acheved wth the rght prce of P *. In contrast, wth a fxed charge households face a cost of zero for each addtonal unt (bag) of servce demanded, that s, the margnal prce to users s $0.00. The result s that households demand servce untl the margnal beneft of the last unt consumed s also equal to zero, gvng quantty of Q Flat Rate. At ths level of servce the margnal cost of provdng the last unt s greater than the margnal beneft obtaned from consumng t. If nstead of chargng a flat-rate a unt-prcng polcy s adopted, then settng the unt-prce at margnal cost wll acheve economc effcency. In applcaton t can be dffcult to estmate margnal cost and so average cost (AC) prcng s often used nstead. Ths would result n a level of demand greater than Q * but less than Q Flat Rate. Two-ter prcng can also be appled. Resdents are charged two fees, the frst fee s flat and covers some mnmum level of servce. The second fee s unt-based and vares wth any addtonal bags collected. The smaller s the level of servce provded by the flat-rate, and the closer the unt-prce s set to margnal cost, the closer we come to achevng economc effcency.

6 Fgure 3: Illustratve MC and MB for domestc waste servces $Prce per bag Demand = MB Supply = MC AC P * = MC = MB P AC MB = $0.00 Q * Q AC Flat Rate Q Quantty of bags Unt-prcng Unt-prcng n the waste management sector refers to a prcng system that charges households for ther collecton and dsposal servce relatve to the amount of waste dsposed by the household. At present n the Unted States of Amerca, over 4,000 communtes use unt prcng programs for domestc waste servce prcng, whch serve over 27 mllon U.S. resdents (Gordon, 1999). Ths makes Amerca the number one mplementer globally. However communtes n many natons around the world have adopted the approach. Unt-prcng has been shown to reduce waste generaton and dsposal, and to ncrease dverson opton such as recyclng and compostng. Convncng evdence of the mpacts of unt-prcng on a households waste management decsons comes from case studes of communtes who have mplemented the program. Data on waste flows both before after mplementaton provde opportuntes to make sound comparsons between programs usng flat-rate chargng and those wth unt-prcng. Such studes typcally categorse the effects of unt-prcng nto fve factors: decreased rates of waste generaton, decreased rates of waste dsposal, ncreased recyclng, ncreased llegal dsposal and ncreased source reducton behavour (see for example: USEPA, 1991; Fullerton and Knnaman, 1994; Mranda et al, 1994; Mranda et al, 1996a; Mranda and Bauer, 1996; Reschovsky and Stone, 1994; Choe and Fraser, 1999) Contngent Valuaton Survey To gan nsght nto the possble effect of a unt-prce on quantty, demand for domestc waste servces s modelled. CVM was ncorporated nto a self-admnstered questonnare sent to Chrstchurch households n February and March of The survey nstrument was pretested usng the cogntve ntervew method (Dllman, 1998). The ntent of ths method s for the ntervewer to prompt the ntervewee to verbalse comments and thoughts that would otherwse go unnotced. A proportonate-stratfed random sample of 1500 Chrstchurch resdents on the electoral role was conducted, the desgn varable beng household ncome. Ths samplng procedure was employed because a secondary objectve of the study s to

7 analyse how dfferent ncome groups react to changes n prce. Wth 121 respondents gone-no-address, and 448 usable responses a 32% response rate results. The survey conssted of four components, the frst s based on substtutes for the councl servce and asks questons measurng alternatve dsposal optons such as the volume of prvate servce that the household subscrbes, and the number of recyclng bns put out for collecton. The second component s the hypothetcal market scenaro for rubbsh bags. Respondents were asked to ndcate the quantty of bags that they would put out, for dfferent prces per bag under a unt-prcng system. The elctaton method can best be descrbed as teratve bddng and s gven n fgure 4. The thrd component sought to dentfy atttudnal motvatons for household waste mnmsaton. Respondents were asked to ndcate agreement on a lkert scale, wth statements representng motvatons for waste mnmsaton such as: concern for the natural envronment. The scale ranges from one (strongly agree) to fve (strongly dsagree). Ths data was recoded nto a dummy varable for each statement, by ncludng only those that agree or strongly agree wth the statement. The forth component of the survey focused on the generaton of waste n the household. Ths took the form of demographc questons such as the number of adults and chldren n the household, and f households consder the cost of dsposng of a product at the end of ts lfetme or dsposng of ts packagng, n the purchase decson, behavour known as source reducton. Fgure 4: Wllngness-to-pay elctaton 12 Currently n Chrstchurch, each rateable property s suppled wth 52 rubbsh bags per year that enttle the household to waste collecton and dsposal servces. These are pad for by an amount n the rates that s the same for every household, regardless of the number of people n the household or the volume of waste put out at the gate, currently ths amount s $43 per year. Any addtonal bags can be purchased separately from retalers at around $5 for a pack of 5; a cost of $1 per bag The next few questons relate to how the amount of waste put out for collecton by your household would change gven a certan scenaro. The scenaro s hypothetcal, and there s no suggeston that t wll occur n Chrstchurch. Imagne that your household had to purchase all of ts rubbsh bags from a retal outlet at a prce per bag, ths would mean that no money would be taken out of rates to fund the servce. For each addtonal unt of rubbsh dsposal needed, the household would purchase another bag. If the household generates very lttle waste then costs wll be low. Ths s a stuaton that occurs n many communtes around the world. For each queston there s a table provded that wll help you to answer. The tables provde nformaton on the total costs of dsposal dependng on prces per bag, and the number of bags put out for collecton each fortnght.usng the frst table below for example, f rubbsh bags cost $0.50 each and your household put 4 bags per fortnght out for collecton, then the cost to the household would be $2.00 per fortnght, whch s $52.00 per year. Please consder each alternatve carefully. A If rubbsh bags were to cost $0.50 each, how much would your households rubbsh collecton cost? (get fgures from table below) $0.50 per bag 1 bag per fortnght 2 bags per fortnght 3 bags per fortnght 4 bags per fortnght 6 bags per fortnght Cost per fortnght $0.50 $1.00 $1.50 $2.00 $3.00 Cost per year $13.00 $26.00 $39.00 $52.00 $78.00 Would ths cost mean that your household would change the number of bags put out? If yes, then how many bags would be put out per fortnght? B If rubbsh bags were to cost $2.00 each, how much would your households rubbsh collecton cost? (get fgures from table below) $2.00 per bag 1 bag per fortnght 2 bags per fortnght 3 bags per fortnght 4 bags per fortnght 6 bags per fortnght Cost per fortnght $2.00 $4.00 $6.00 $8.00 $12.00 Cost per year $52.00 $ $ $ $ Would ths cost mean that your household would change the number of bags put out? If yes, then how many bags would be put out per fortnght?

8 C If rubbsh bags were to cost $3.00 each, how much would your households rubbsh collecton cost? (get fgures from table below) $3.00 per bag 1 bag per fortnght Cost per fortnght Would ths cost mean that your household would change the number of bags put out? If yes, then how many bags would be put out per fortnght? 2 bags per fortnght 3 bags per fortnght 4 bags per fortnght 6 bags per fortnght $3.00 $6.00 $9.00 $12.00 $18.00 Cost per year $78.00 $ $ $ $ D If any of your answers to questons 12A 12C resulted n a reducton n the number of bags put out for collecton, then how do you thnk the household wll acheve ths? Data Descrpton The followng table descrbes the varables used n the modellng procedure. Table 1: Data descrpton Dependent varable the number of C.C.C. domestc rubbsh bags put out for collecton and dsposal each fortnght. Explanatory varables Prce per bag CVM WTP estmates Adults the number of people n the household aged 16 years or over Chldren the number of people n the household aged 16 years or under Compost dummy varable: 1 f household uses compostng to dspose of food waste, 0 otherwse. Prvate the volume (ltres) of weekly prvate servce Source reducton dummy varable: 1 f practces source reducton behavour, 0 otherwse Recycle ftted values of the number of recyclng bns put out for collecton fortnghtly Income Household annual ncome, n categores 1-9 Atttudnal varables dummy varable: 1 f household agrees or strongly wth statement as motvaton to mnmse waste, 0 otherwse. Concern for the natural envronment Other peoples vews of oneself Prce of waste servce Tme and effort managng waste Negatve attrbutes of waste Desre for effcency Member of envronmental organsaton

9 < Not Stated A ch-squared test s used to test the null hypothess that there s no assocaton between the dstrbutons of demographc varables of the sample and 2001 Census data, the relevant dstrbutons and p-values are reported n Fgures 5. We can see that the null s rejected n all but one case, at a 1 percent sgnfcance level. The dstrbuton of age for the sample s skewed towards older age and away from younger age. Ths results from drawng the sample from the electoral role as ths excludes those aged 17 years and under. It s consdered that excludng ths age group would not bas the results as these ndvduals would seldom be responsble for decsons on household waste management. Fgure 5: Sample characterstcs 50% 40% 30% 20% 10% Number of household members 90% 70% 50% 30% Ethncty 10% One Two Three Four Fve Sx Seven Eght Not Stated P< European Maor Pacfc Asan Other Not stated P < % Employment 60% Gender 50% 40% 30% 20% 10% Employed full and part tme Unemployed and actvely seekng work Not n Labour Force Undentfed Male Female Not Stated P < P < % 80% 60% 40% 20% Educaton 30% 25% 20% 15% 10% 5% Age Degree No degree P < P < 0.001

10 Loss 0 - $10,000 $10,001 - $20,000 $20,001 - $30,000 $30,001 - $40,000 $40,001 - $50,000 $50,001 - $70,000 $70,001 - $100,000 $100,001 Not Stated Household ncome 20% 16% 12% 8% 4% P < Model specfcaton The dependent varable exhbted nonnegatve nteger propertes, to take advantage of ths a Posson count data model was deemed an approprate specfcaton for the modellng procedure. For a detaled and comprehensve analyss of count data models see Cameron and Trved (1998). The Posson regresson model s the smplest and perhaps most common count data model. The Posson parametersaton explots the dscrete characterstc of the dependent varable. For a dscrete random varable, y, wth observed frequences, y, = 1,..., N, where y 0, the Posson regresson model specfes that y gven x s Posson dstrbuted wth densty f y x y e, y 1, 2, 3... (1) y The dstrbuton s determned by the sngle parameter, the mean. Ths parameter s gven by the condtonal mean functon E y x (2) whch s determned by the regresson equaton. Ths study specfes an exponental condton mean functon, as s common practce. Ths mmcs the nonnegatve nature of the dependent varable, ensurng that none of the ftted values of the model wll be negatve. x y x e E (3) The method of Maxmum Lkelhood s used to estmate the model. All emprcal model estmaton s carred out usng LIMDEP econometrc software. The loglkelhood functon takes the followng form

11 n ( x ) y x e ln y ln L (4) 1 The maxmum lkelhood prncple s to choose values of the parameter vector ˆ that maxmses the lkelhood functon gven the sample data (.e. the vector of parameter values that gves the greatest probablty of obtanng the observed data). The Posson MLE ˆ P s the soluton to the frst-order condtons n 1 ( x ) y e x 0. (5) The method for computaton of ˆ s the Newton-Raphson teratve method. Convergence s guaranteed because the log-lkelhood functon s globally concave For emprcal estmaton one of the most mportant restrctons of the Posson assumpton s the equalty of the (condtonal) mean and varance E y x Vary x (6) The raw data suggest that there s under-dsperson present, that s, the varance s less than the mean for the dependent varable, however we need to test the condtonal mean and varance equalty. Ths restrcton, referred to as equ-desperson, s formally tested usng a regresson based test proposed by Cameron and Trved 2 2 (1990). The test s based on an auxlary regresson of e y on o y ˆ where the errors and ftted values are obtaned from an ntal estmaton of the Posson model. The test statstc s hghly sgnfcant leadng to rejecton of the equ-dsperson assumpton. In settngs of under-dsperson an alternatve s to use Posson quasmaxmum lkelhood (PQML). The estmator s lke the Posson MLE n that the Posson model s used to motvate the frst-order condton defnng the estmator, but t s unlke the Posson MLE n that the data generatng process used to obtan the dstrbuton of the estmator need not be the Posson. Ths means that the same loglkelhood functon s used but a dfferent estmator of the covarance matrx s adopted. Ths study uses the estmator proposed by Huber (1967) and Whte (1982). Provded the condtonal mean functon s correctly specfed and the condtonal dstrbuton of y s Posson, the PQML ˆ s consstent, effcent, and asymptotcally normally dstrbuted. Table 2 presents the prelmnary estmaton as estmaton (1) whch ncludes all varables. The explanatory varables collectvely are statstcally sgnfcant n explanng the varaton of the dependent varable.none of the atttudnal varables are ndvdually statstcally sgnfcant although concern for the natural envronment, other peoples vews of oneself, and prce of waste servce all have envsaged sgns. Nether burnng nor llegal dsposal are statstcally sgnfcant. All other varables have the antcpated sgn except recyclng. The coeffcent for recyclng s postve, suggestng that the expected number of bags would be ncreasng n the amount of recyclng the household does. The opposte result s theorsed.

12 Table 2: Model estmaton Varable descrpton Estmaton Estmaton Estmaton (1) (2) (3) Constant 0.59 a 0.57 a 2.92 a Unt-prce proxy CVM WTP estmates ($ per bag) a a a Questons concernng waste generaton Adults 0.22 a 0.22 a 0.96 a Chldren 0.20 a 0.20 a 0.49 a Source reducton a a a Household ncome 0.02 b 0.02 b 0.09 a Questons concernng waste dverson Recyclng 0.16 a 0.31 a a Prvate servce a a a Compostng a a a Burnng Illegal Atttudnal questons Concern for the natural envronment Other peoples vews of oneself Prce of waste servce Tme and effort managng waste 0.05 Negatve attrbutes of waste 0.06 Desre for effcency 0.03 Member of envronmental organsaton 0.00 RsqD Ch squared Prob [ > value] a sgnfcant at 99% confdence level. b sgnfcant at 95% confdence level. Droppng non-sgnfcant varables from the model, yelds estmaton (2). It was determned that the ncorrect sgn for the recyclng coeffcent results from the quantty of recyclng beng endogenous to the model, and therefore correlated wth the error term. A standard approach n cases where rght-hand sde varables are correlated wth the resduals s to estmate the equaton usng nstrumental varables regresson. The general dea behnd nstrumental varables s to fnd a set of varables, termed nstruments, whch are both correlated wth the explanatory varables n the equaton, and uncorrelated wth the errors. These nstruments are used to elmnate the correlaton between rght-hand sde varables and the dsturbances. One technque s to model the varable of concern and use the ftted values of that regresson to act as the nstrument n the orgnal model. Ths s the procedure adopted presently. A Posson ML model s specfed for the number of recyclng bns put out per fortnght. The regressors are number of adults, number of chldren and household ncome. The equ-dsperson assumpton s rejected and so Posson QML estmaton s employed. The estmates from ths model are gven n Table 3. The varables collectvely and

13 ndvdually are hghly sgnfcant. The ftted values for the dependent varable from ths model are used as the nstrument. Table 3: Instrumental varable estmaton for recyclng Adults Chldren Income 0.24 a 0.10 a 0.03 a RsqD 0.10 Ch-squared Prob [ > value] 0.00 a sgnfcant at 99% confdence level. b sgnfcant at 95% confdence level The fnal model wth the ncluson of the recyclng nstrumental varable s presented as estmaton (3) n Table 2. We can see that the use of nstrumental varable has corrected the sgn of the recyclng coeffcent. The ch-squared test ndcates that the explanatory varables as a whole are sgnfcant n explanng the dependent varable. Each explanatory varable s sgnfcant ndvdually at the 1% level. All sgns of the estmated coeffcents are consstent wth economc theory. The value of RsqD, the sum of the squared devance resduals, consdered by Cameron and Trved (1998) to be the most approprate measure of ft for ths model, could be consdered low, however cross-sectonal data often suffer from ths result. Interpretaton The margnal effect of a regressor ndcates the change n the expected value of the dependent varable, gven a unt change n that regressor. The margnal effect of the j th regressor s E y x n n 1 1 x je n 1 xj n 1 because the frst-order condtons mply 1 n n 1 E y x j x y j (7) x e y ths smplfes to Ths procedure nvolves assessng the condtonal mean for each observaton and then E y x wth averagng, to yeld an average response. The partal dervatves of respect to each varable are computed at the means of the explanatory varables. Ths hghlghts the non-lnear nature of the estmaton, and as coeffcent estmates are senstve to the values at whch they are computed, they are not constant. Interpretaton of each explanatory varable n the model follows. The margnal effect of prce n Table 2 s Ths s calculated at the average of all prces (all other varables are at ther averages also), whch s $1.64. Ths s nterpreted as a one unt ncrease n prce (.e. $1.00), from the average prce, leadng (8)

14 Expected number of bags Margnal effect of prce to a decrease n the expected number of bags by 0.21 bags per fortnght. To nvestgate how the margnal effect of prce changes across prce levels, we can change the value at whch the margnal effect of prce s computed. Frst we compute the margnal effect of prce, wth prce set at zero, and all other varable set at ther means. Ths gves the margnal effect of a one unt ncrease n prce from zero dollars. Then we repeat the estmaton wth hgher prces of $1.00, $2.00, $3.00 and $4.00. Plottng the resultng condtonal means aganst prce results n Fgure 6. The slope of a tangent to the curve at a gven prce s the margnal effect of that prce, holdng all else n the regresson equaton constant. Fgure 6, whch s essentally a demand curve, llustrates how the condtonal mean falls as prce ncreases and that the margnal effect of prce s dmnshng as prce ncreases, the curve s steeper at low prces and flatter at hgh prces. Ths s more easly seen f the magntude of the margnal effect s plotted aganst prce as n Fgure 7. Fgure 6: Margnal prce effects curve Fgure 7: Magntude of margnal prce effect $Prce per bag $Prce per bag We can see that the magntude of the margnal effect of prce s decreasng as prce ncreases. Households respond more strongly to ntal ncreases n prce than they do to ncreases once the prce s set. The theorsed prce per bag facng households under flat-rate chargng s $0.00 per bag. Ths s qute dfferent from the average prce at whch the margnal effect presented n Table 2 s computed. Table 3 shows that the margnal effect of prce at $0.00 s -0.25, ncreasng prce one unt from $0.00 leads to a decrease n the expected number of bags by 0.25 bags per fortnght. It s ths value of the margnal effect that should be used n assessng reductons n demand for servce. Because the mean functon s nonlnear, t s theoretcally naccurate to talk of a margnal effect across several unts. If we want to look at the effect of ncreasng prce from $0.00 to a prce greater than a one unt ncrease (.e. $1.00) then we need to compute an accumulatve or total effect. For example, consder an ncrease from $0.00 to $3.00 per bag. Usng the condtonal means provded n Table 4 the accumulatve effect s a decrease n the expected number of bags (condtonal mean) of 0.61 per fortnght (= ).

15 Table 3: Margnal prce effects Prce Condtonal mean Margnal effect of prce $ $ $ $ $ Consder the followng numercal example. For ths sample, the status quo average number of bags put out for collecton s 2.04 per fortnght for each household. Ths equates to bags a year. If a unt-prce of $1.00 per bag was ntroduced the model predcts a reducton of 0.25 bags for the average household per fortnght. In Chrstchurch wth approxmately 123,000 households ths equates to a reducton of 799,500 bags per year. The average weght of a domestc black bag has been estmated at 8.3kg (C.C.C. 2003), ndcatng a possble weght reducton of around 6,636 tonnes. Gven that approxmately 37,818 tonnes of waste goes to landfll from councl domestc servce ths equates to a percent reducton. Table 4 provdes some more examples. Table 4: Numercal examples of waste reducton Change n prce Tonnes per year percent of councl domestc servce $0.00 to $1.00 6, $0.00 to $ , $0.00 to $ , $0.00 to $ , The margnal effects dscussed next, adults, chldren, prvate servce, and recyclng are computed at the means of all varables. For the average household, the effect of the number of adults on the quantty of bags put out s gven by 0.964, whch ndcates that for each addtonal adult n the household above the average (2.11) the expected number of bags ncreases by bags. Each chld contrbutes approxmately half as much waste as each adult. Each chld n the household ncreases the expected number of bags by bags. Each ltre of prvate servce that the household uses decreases the expected number of bags by bags. Ths means that f a household subscrbes to 140 ltres of prvate servce a week then they wll put out 1.2 bags less per fortnght on average. Each bn of recyclng put out by the household reduces the expected number of bags by per fortnght. For the bnary choce varables, compost and source reducton, nterpretaton s slghtly dfferent. The negatve coeffcents mply that the condtonal mean s e smaller when the dummy varable s unty rather than zero. Table 5 shows the results of these computatons. If the household uses compost to dspose of food waste then the expected number of bags put out per fortnght falls by 0.83 bags. If the household purchases products wth relatvely less packagng or otherwse relatvely low dsposal costs, behavour referred to as source reducton, then ths reduces the expected number of bags by 0.78 bags per fortnght.

16 Expected number Of bags Margnal effect Of prce Table 6: Bnary choce varable coeffcent nterpretaton ˆ e Compost Source reducton The margnal effect of household ncome on the number of bags put out as presented n Table 2 s estmated as Agan ths s computed at the means of all varables. As the ncome varable s measured n categores, the coeffcent estmate s nterpreted as an ncrease n ncome from one category to the next ncreases the number of bags put out by bags per fortnght. Do dfferent ncome groups react dfferently to changes n prce? Income dstrbuton concerns should be nvestgated as part of an effort to recognse socal sustanablty as a requrement for domestc waste management polcy. One mght expect the margnal effect of prce to be greater for lower ncome groups who face a relatvely tghter budget constrant. Analysng ths effect could hghlght whch ncome groups mght reduce ther demand more than others. To do ths we wll compute the margnal effects of varyng prce levels across dfferent household ncome groups. Frst we compute the margnal effect of prce, wth prce set at zero, ncome set at nne (the hghest ncome category) and all other varables set at ther means. Ths gves us the frst margnal effect for the hgh ncome group. Then we repeat the estmaton wth hgher prces of $1.00, $2.00, $3.00 and $4.00. Ths procedure s then repeated for two other ncome groups, medum (category 5) and low (category 1). Ths wll reveal whether ncome affects a household s reacton to the prce level. Fgure 8: Margnal prce effect curves Fgure 9: Magntude of margnal prce effect across household ncome groups Hgh Medum 0.15 Low Hgh Medum Low $ Prce per bag $ Prce per bag Frst we can see that the prce effect s greatest when movng from a prce of zero to $1.00, and that the effect of prce s dmnshng as the prce per bag ncreases. Ths s the same for all ncome groups. A more nterestng observaton s the hgher ncome

17 groups react more strongly to the prce, and the prce effect s convergng between ncome groups as prce ncreases. Ths can be more easly seen n Fgure 9. The margnal effect at prce equal to zero s -0.22, and for the low ncome, medum and hgh ncome groups respectvely. Ths gves a range of When the margnal effect s evaluated at a prce of $4.00 then the effects are -0.13, and , gvng a range of Ths suggests that as an autonomous level s reached the ablty of a household to reduce waste further s lmted. Fgure 8 also remnds us that, holdng all else constant, hgher ncome groups have a hgher condtonal mean relatve to low ncome households. That s, holdng all else constant, a wealthy household wll produce more waste than a relatvely low ncome household. At each prce level the hgh ncome groups have a relatvely greater opportunty to decrease the amount of bags used because the magntude of ther waste s greater. The lower ncome groups are closer to the autonomous level of waste generaton and dsposal. They do not generate or dspose of a lot to start wth and therefore they do not have as much opportunty to decrease the use of bags. Reducton achevement How households acheve any reducton s crucal to the success of the waste management program. The followng table gves the optons that respondents ndcated they would use to acheve the reducton n bags. The survey asked respondents to ndcate how they would acheve any reducton n the number of bags put out. The queston was open-ended but could be categorsed as n Table 7. The percentages gven are of the number of households actually reducng the number of bags put out, n = 247. Table 5: Waste reducton achevement optons (n = 247) Varable descrpton Percentage Prvate 24.3 Compost 19.8 Compacton 19.4 Recycle 18.2 Burn 12.1 Source reducton 10.1 Illegal 4.9 Can not do any more 5.7 Insnkerator 2.0 The sum of the percentages s more than 100 because some households ndcated several optons. All households that would reduce ndcated at least one opton. Subscrpton to a prvate servce s the most popular opton, wth almost 25 percent of households choosng ths opton to help obtan reductons n the number of councl bags used. Ths s perhaps the most serous threat to achevng waste targets n a untprcng programme as t results n no reducton n the amount of waste gong to the landfll. Compostng, compacton and recyclng are also major reducton optons for households. Compacton reduces the volume of but not the actual amount of waste

18 Compost Prvate Recyclng Source reducton Burn Illegal Compacton Insnkerator and so does not contrbute to waste reducton goals. Some households consdered that they would decrease the number of bags that ther household put out but dd not know how they would acheve ths. Ths group s measured by can not do any more. Ths group of households may be dong all they can to mnmse waste. Has the ntroducton of unt-prcng ncreased the number of households usng dverson optons? Ths queston s answered n the Fgure 10. Fgure 10: Increases n household dverson Percent of sample Pre unt-prcng Post unt-prcng 10 Dverson optons We can see that there has been a relatvely even ncrease for most dverson optons, wth no sngle opton beng favoured sgnfcantly more than others. Ths hghlghts the dverse nature of ndvdual household s waste management strateges. Households dd not ndcate that they compact waste untl after the ntroducton of unt-prcng, so all compacton behavour s attrbuted to the unt-prcng polcy. Wth ths n mnd, t s burnng that has the largest percentage ncrease compared to the preunt-prce level. Conclusons Ths research demonstrates that there s a sgnfcant opportunty for unt-prcng to decrease the amount of waste that Chrstchurch households send to landfll. Substtuton towards prvate servce and compacton are the greatest threats to the ablty of a unt-prcng system to decrease waste gong to landfll. Compacton can only successfully be eradcated f the weght of rubbsh s measured and used from prcng. Respondents who practce source reducton are an ndcaton of the growng ncentve for manufacturers and producers to take some accountablty for the waste component of the goods they sell. In ths way the responsblty for mnmsng waste s not only that of consumers, although t s them that must sgnal to manufacturers that products wth mnmal dsposal costs wll be favoured. Ths mples a role for polces that explctly ncorporate frms nto the management of waste from ther products, post sale. Mnmum recyclable component requrements and buy-back systems are

19 examples that need to be nvestgated as possble tools n a comprehensve waste mnmsaton strategy. The major lmtatons of ths research stem from the nablty to form a quanttatve estmate of respondent s use of dverson optons such as recyclng post-mplementaton of a unt-prcng programme. Ths research s able to present a qualtatve measure. To estmate a quanttatve response would requre data descrbng observed measurable changes n the levels of dverson optons such as the number of recyclng bns ncreasng. Ths s not usually possble as a unt-prcng programme has not actually been mplemented. Some communtes have conducted experments, or trals that can provde the necessary data. One possble lmtaton stems from the data collecton process. The number of bags put out provdes the measure of the level of waste dsposed of va councl servce. However the volume and weght of a councl rubbsh bag vares across households, but s treated as constant, that s, one bag. Ths study has focused on the applcaton of a market based nstrument at the household level. Instruments appled at ndustry level also play an mportant role n mnmsng waste generaton. Research nto the nteracton of nstruments at ths, and the household level n New Zealand, s an essental part of waste mnmsaton debate that provdes ground for future research. References Cameron, A.C., and Trved, P.K. (1990). Regresson Based Tests for Overdsperson n the Posson Model. Journal of Econometrcs, 46, Cameron, A.C., and Trved, P.K. (1998). Regresson Analyss of Count Data. Cambrdge: Cambrdge Unversty Press. Choe, C., and Fraser, I. (1999). An Economc Analyss of Household Waste Management. Journal of Envronmental Economcs and Management 38, Chrstchurch Cty Councl (1995). Cty of Chrstchurch Plan. Chrstchurch Cty Councl. Chrstchurch. Chrstchurch Cty Councl. (1998). Waste Management Plan for Sold and Hazardous Waste Chrstchurch Cty Councl. Chrstchurch. Chrstchurch Cty Councl. (2003). Sold Waste and Recyclng Statstcs for Chrstchurch. Chrstchurch Cty Councl. Retreved August 1, 2003 from Dllman, D.A. (1998). Mal and Telephone Surveys: the Total Desgn Method. New York: Wley.

20 Fullerton, D. and Knnaman, T.C. (1994). Household Demand for Garbage and Recyclng Collecton wth the Start of a Prce per Bag. U.S. Natonal Bureau of Economc Research Workng Paper No Gordon, H. Jr. (1999). PAYT Contnues to Grow. Waste Age. Hong, S. (1999). The Effects of Unt Prcng System upon Household Waste Management: The Korean experence. Journal of Envronmental Management, 57, Hong, S. and Adams, R.M. (1999). Household Responses to Prce Incentves for Recyclng: Some Further Evdence. Land Economcs, 75(4), Huber, P.J. (1967). The Behavour of Maxmum Lkelhood Estmates Under Nonstandard Condtons. In L.LeCam and J.Neyman, eds., Proceedngs of the Ffth Berkeley Symposum on Mathematcal Statstcs and Probablty. Berkeley: Unversty of Calforna Press, Mnstry for the Envronment. (2002). The New Zealand Waste Strategy. New Zealand Mnstry for the Envronment. Wellngton. Mranda, M.L., Everett, J.W., Blume, D. and Roy, B.A. Jr. (1994). Market-Based Incentves and Resdental Muncpal Sold Waste. Journal of Polcy Analyss and Management, Vol. 13, No. 4, (1994). Mranda, M.L. and Bauer, S.D. (1996). The Urban Performance of Unt Prcng: An Analyss of Varable Rates for Resdental Garbage Collecton n Urban Areas. School of the Envronment Duke Unversty. Report prepared for: Offce of Polcy, Plannng and Evaluaton U.S. Envronmental Protecton Agency, Washngton D Mranda, M.L., Bauer, S.D. and Aldy, J.E. (1996a). Unt-Prcng Programmes for Resdental Muncpal Sold Waste: An Assessment of the Lterature. School of the Envronment Duke Unversty. Report prepared for: Offce of Polcy, Plannng and Evaluaton U.S. Envronmental Protecton Agency, Washngton D.C. Mranda, M.L. and Aldy, J.E. (1996b). Unt Prcng of Resdental Muncpal Sold Waste: Lessons Learned from Nne Case Study Communtes. School of the Envronment Duke Unversty. Report prepared for: Offce of Polcy, Plannng and Evaluaton U.S. Envronmental Protecton Agency, Washngton D.C. Reschovsky, J.D. and Stone, S.E. (1994). Market Incentves to Encourage Household Waste Recyclng: Payng for What You Throw Away. Journal of Polcy Analyss and Management, 13(1), Unted States Envronmental Protecton Agency. (1991). Unt Prcng Provdng an Incentve to Reduce Muncpal Sold Waste. U.S. EPA. Washngton D.C. Whte, H. (1982). Maxmum Lkelhood Estmaton of Msspecfed Models. Econometrca, 50, 1-25.