Regulation and Efficiency Incentives: Evidence from the England and Wales Water and Sewerage Industry. Abstract

Transcription

1 Unversty of Warwck nsttutonal repostory Ths paper s made avalable onlne n accordance wth publsher polces. Please scroll down to vew the document tself. Please refer to the repostory record for ths tem and our polcy nformaton avalable from the repostory home page for further nformaton. To see the fnal verson of ths paper please vst the publsher s webste. Access to the publshed verson may requre a subscrpton. Author(s): FABRIZIO ERBETTA and MARTIN CAVE Artcle Ttle: Regulaton and Effcency Incentves: Evdence from the England and Wales Water and Sewerage Industry Year of publcaton: 2009 Lnk to publshed verson : Publsher statement: None

2 Regulaton and Effcency Incentves: Evdence from the England and Wales Water and Sewerage Industry FABRIZIO ERBETTA * Unversty of Pemonte Orentale, Faculty of Economcs HERMES, Centre for Research on Regulated Servces MARTIN CAVE Warwck Busness School, Unversty of Warwck Abstract Ths paper evaluates the mpact of the tghtenng n prce cap by OFWAT and of other operatonal factors on the effcency of water and sewerage companes n England and Wales usng a mxture of data envelopment analyss and stochastc fronter analyss. Prevous emprcal results suggest that the regulatory system ntroduced at prvatzaton was lax. The 1999 prce revew sgnaled a tghtenng n regulaton whch s shown to have led to a sgnfcant reducton n techncal neffcency. The new economc envronment set by prce-cap regulaton acted to brng nputs closer to ther cost-mnmzng levels from both a techncal and allocatve perspectve. 1 Introducton The England and Wales water and sewerage ndustry was prvatzed n 1989 and thenceforth has been subject to a sequence of fve-year prce controls n the form of prce caps. Prce-cap regulaton s set out to be a hgh-powered ncentve scheme. However, prevous emprcal fndngs have shown that the cap ntroduced at prvatzaton n 1989 had been lax (Saal and Parker, 2000), n the sense of allowng real prce ncreases and the evdence that the frst prce revew n 1994 produced effcency gans s weak (Saal and Parker, 2001 and 2004). Ths may be explaned by the double duty of the regulator to encourage a hgher level of effcency and provde the companes wth the fnancal resources to support ther nvestment programs. The 1999 prce revew sgnaled a change n the mplementaton of regulatory polcy by mposng for the frst tme a real prce reducton. * Contact Author. Faculty of Economcs, Unversty of Pemonte Orentale, Va Perrone 18, Novara, Italy, Tel +39 (0) , Fax +39 (0) , Emal: fabrzo.erbetta@eco.unpmn.t. We apprecated the useful comments from Ian Byatt, Govann Fraquell, Mark Stewart and semnar partcpants at OFWAT, although of course we are solely responsble for any errors. 425

3 As noted by Weyman-Jones et al (2006), ncentve regulaton has many attractve propertes but a number of practcal concerns may arse when a regulaton model has to be mplemented n practce. Therefore, t appears that the attanablty of many of the desrable propertes of ncentve regulaton s an emprcal ssue (Ur, 2003). Our paper ams at explorng whether ncentve regulaton (namely, the tghtenng of regulaton n 1999) actually resulted n an ncrease n performance. In partcular, ssues we wsh to deal wth and that may be of nterest to regulators n a broader perspectve are: how s t possble to account for dfferent envronmental condtons when mplementng a yardstck competton model? Is ncentve regulaton able to drve to mproved effcency under both a techncal and allocatve perspectve? Does ncentve regulaton (and other envronmental varables) dfferently mpact on the effcent use of ndvdual nputs? In facng these questons, we used a DEA-based two stage approach derved from Fred et al (2002). In the frst stage, DEA (Data Envelopment Analyss) s run over a balanced panel data of the ten water and sewerage companes for the perod from to In ths stage, estmates of techncal and allocatve effcency are obtaned. In the second stage, we calculate nput-specfc excess utlzaton and allocatve dstorton measures, and regress them on a set of envronmental varables usng Stochastc Fronter Approach (SFA). These explanatory varables are chosen to represent both the operatonal and regulatory envronment under whch the frms operate. In ths way, we provde a decomposton of the DEA-based overall techncal and allocatve neffcency nto three components: envronmental mpact, pure manageral neffcency and statstcal nose. Ths approach has several advantages, whch may be regarded as attractve propertes by regulators. Frst, t makes t possble to ncorporate envronmental effects and statstcal nose nto a DEA-based model. Second, t allows us to evaluate the mpact of operatonal and regulatory envronment on both techncal and allocatve effcency of regulated frms. Thrd, t provdes nput-specfc effcency measures, whch can be decomposed n order to dentfy the pure manageral effcency separately from envronmental effects and nose. The remander of the paper s organzed as follows. Secton 2 provdes a general descrpton of the regulatory regme for the Englsh and Welsh water and sewerage ndustry, whch offers a context to the research queston ths paper deals wth. Secton 3 s a revew of the exstng lterature dealng wth effcency n the water ndustry n England and Wales as well as abroad. The model specfcaton s set out n secton 4. Secton 5 focuses on the nput and output varables along wth the arguments that support ther choce, whle secton 6 specfes the envronmental and regulatory factors. Emprcal results are presented and dscussed n secton 7. Secton 8 concludes and brefly notes some polcy mplcatons. 2 Regulaton of the water ndustry At the prvatzaton of the ndustry n 1989, the ten Regonal Water Authortes (RWA) were transferred to the prvate sector wth the functons of water supply, sewerage collecton and sewage dsposal, and they became Water and Sewerage Companes (WaSCs). The responsblty for drnkng qualty and envronment regulaton was passed to ndependent agences, respectvely, the Drnkng Water Inspectorate (DWI) and the Natonal Rvers Authorty, the latter absorbed nto the Envronment Agency (EA) n The then current ntegrated structure of the water and sewerage ndustry was thus almost 426

4 entrely preserved, wth the excepton of qualty regulaton functons whch were consdered more opportunely managed by publc agences (Hunt and Lynk, 1995). These ten prvatzed companes, along wth the 29 already prvately-owned water only companes, formed the England and Wales water and sewerage ndustry. The ndustry structure s concentrated, wth the ten WaSCs provdng both water and sewerage servces n England and Wales, and accountng for 78% n terms of water suppled to the populaton and 85% n terms of served area (Saal and Parker, 2000). Gven the large amount of the assets transferred to the prvate sector, and the (then) monopolstc nature of the establshed companes, the functon of regulatng prces was gven to an ndependent agency, the Offce of Water Servces (OFWAT), whose man task s to set prce n a way that encourages the companes to generate nvestment funds, enhance ther effcency level and fulfll programs for achevng hgh qualty and envronmental standards. Snce prvatzaton n 1989, the England and Wales water and sewerage ndustry has been subject to a regulatory regme based on prce-cap regulaton. Ths s a substtute for competton and s mplemented by allowng companes to change prces accordng to the nflaton rate (RPI, Retal Prce Index), plus or mnus a K factor decded by the regulator (OFWAT). 1 Ths factor s composed of a negatve component that accounts for the potental ncrease n effcency that the regulator judges to be achevable (X-effcency) and a postve component that s set to accommodate the large captal nvestment program of the companes. The prce determnatons are also based on a comparatve performance assessment (yardstck competton). Ths system allows the regulator partally to crcumvent the lack of nformaton that typcally characterzes the relatonshp between regulator and regulatees. Once prces are set, f frms manage to delver servce at a lower average cost than that assumed by the regulator, they keep the resultng benefts. The regulator can thus provde frms wth the ncentve to ncrease ther effcency and then return part of the realzed cost savngs to the customers through a subsequent reducton n prces. Prce cap regulaton s regarded as a hgher-powered ncentve scheme than rate of return regulaton. The attempt to ncrease effcency should lead to a reducton n the use of the resources to produce a specfed output (that s, ncreased techncal effcency), and/or to a change n nput mx, gven the relatve nput prces, n order to mnmze overall cost (that s, ncreased allocatve effcency). The am of the paper s to analyze the trend of both the effcency components durng the regulated perod from to and nvestgate whether the regulatory prce revews succeeded n the purpose of encouragng convergence towards hgher effcency. Followng the frst prce control set by the Government at prvatzaton n 1989, new prce revews have been set n 1994, 1999 and 2004 at ntervals of fve years. 2 Gven the data avalable, we wll be able to analyze the mpact of the 1994 and 1999 prce revews. 1 The frst prce control, for the perod 1989 to 1994, was set by the Government. OFWAT has set the subsequent ones. 2 In realty, the prce cap n 1989 was set for a ten-year perod, wth an opportunty for the regulator to hold an nterm determnaton after fve years, whch the regulator mplemented. A debate rose regardng the desrablty of mantanng a fve-year cyclcal revew as the frms may have greater ncentve to outperform the regulatory targets n the ntal years of the fve-year prce control perod n order to keep the benefts for a longer tme before passng them to the customers through the successve prce regulaton. A longer prce settng perod mght nduce the frms to outperform the regulatory assumptons for a hgher number of years. In 1999, OFWAT proposed a rollng ncentve mechansm whch t beleved would have strengthened the frms ncentve to cost reducton, allowng them keepng the benefts for a full-fve years perod, rrespectve of when the target outperform was made. 427

5 Followng prvatzaton, prces for the water and sewerage servce rose, on average, by almost 30% durng the years up to the 1994 prce revew (Saal and Parker, 2000), thus provdng frms wth the fnancal resources necessary to sustan ther captal nvestments. The 1994 prce revew set an average real annual ncrease of 1.5% up to 1999, wth the expectaton of a further real ncrease by 0.6% per year over the followng fve years (OFWAT, 1994). However, wth the 1999 prce revew, the regulator reduced prces by 12.3%, on average, for the frst year of the new perod. The average annual real reducton over the fve years as a whole was 2%. 3 The 2004 prce revew, however, dd not contnue n ths way, as t allowed an average annual ncrease over the whole fve-year perod of 4.3%. The 1999 revew thus, sgnaled a change n regulatory polcy and concentrated the greatest part of the prce reducton n one year. Ths rases the queston of whether ths would motvate frms to acheve hgher levels of effcency growth. 4 A standard answer to ths queston may be that a prce cap, whch makes prces exogenous for a specfed perod, should provde broadly smlar ncentves for cost reducton however challengng the targets. However, t s also known that a fxed term prce control furnshes weaker ncentves for effcency towards the end of the control perod, as a result of the so-called ratchet effect the tendency for regulators to use cost performance at the end of the control perod as a bass for settng prces for the next perod. If the regulator not only extrapolates from the level of costs when settng the next prce cap but also notes ther rate of declne, a frm may be reluctant to put n a very sparklng performance n any prce control perod n case t receves tougher cost reducton targets n the next perod. More demandng targets may elct dfferent behavor n ths regard, by removng the opton on pan of the frm falng to make a proft of ekng out cost reductons over tme. At the same tme, prvatzaton should have removed the mplct dstorton found n publc frms, such as the overuse of employment for socal and poltcal reasons, so allowng the regulaton polcy beng more effectve. We examne what the data tell us about the mportance of these varous effects. 3 Prevous emprcal lterature In ths secton, we present a bref descrpton of prevous emprcal studes that have been conducted on the economc analyss of the water and the ntegrated water and sewerage ndustry, n both the UK and other countres. The frst pont of nterest concerns the analyss of cost effcency. As far as the UK experence s concerned, a few early papers attempted to evaluate the frms cost effcency and total factor productvty after the prvatzaton of the ndustry, as well as to establsh the mpact of regulaton. Stewart (1993, 1994) nvestgated water and sewerage costs separately, usng an econometrc fronter approach. The results are shown to depend on the dstrbutonal assumpton employed n the econometrc specfcaton. 3 After the frst prce reducton, the regulator set a further decrease by 0.4% for the fnancal year and ncreases by +0.2%, +1.3% and +1.7% for the last three years. These fgures are averages across the ndustry. 4 For a dscusson of the mpact of prce controls, see Armstrong and Sappngton (2007). 428

6 Ashton (2000a) analyzed the frm-specfc cost effcency condtons of the UK water and sewerage prvatzed companes as combned enttes over the perod between 1987 and 1997, usng a translog varable cost specfcaton. Ths study fnds a moderate level of dsperson of average neffcency, whch could be ndcatve of the dversty both of operatng envronment and of performance n the sector. In another contrbuton, Ashton (2000b) dentfed the dynamc aspects of performance of the prvatzed WaSCs between 1989 and 1997, explorng the characterstcs of the total factor productvty growth. The results hghlght a declne n total factor productvty and techncal change, thus drawng the attenton to the modest mpact of prvatzaton snce A jont consderaton of the effect of prvatzaton and regulaton on economc effcency was carred out by Saal and Parker (2000). Ths study modeled the ten WaSCs, usng observatons between 1985 and 1999, usng a mult-output translog total cost functon. The fndngs suggest that technologcal change has been labor-savng and captalaugmentng. The hypotheses of dfferent total cost growth rate after prvatzaton and the 1994 prce revew were tested. Whle the former hypothess was rejected, revealng that no effect could be found due to prvatzaton, the second one was not, suggestng that the man source of cost effcency mght be found n ndustry regulaton. In another contrbuton, Saal and Parker (2001) employed labor and total factor productvty (TFP) ndces and rejected the hypothess of ncreasng overall productvty due to prvatzaton, even though labor productvty showed a sgnfcant growth rate. As they argued, ths may be ascrbed to a decreasng trend n captal productvty, due to captal for labor substtuton n the post-prvatzaton perod and the falure of the regulator to counteract the tendency towards over-nvestment. 5 They also found that, although gans n labor productvty manly took place after the 1994 prce revew, the overall productvty growth declned after Further results are found n Saal and Parker (2004), where no evdence s found that prvatzaton led to a TFP growth but there s some evdence of mprovng TFP owng to the 1994 prce control. In a more extensve study, Saal and Red (2004), employng a qualty adjusted translog varable cost functon, showed that whle the 1994 prce revew mproved operatng cost productvty, the 1999 prce revew dd not provde evdence of a further productvty growth rate. Saal et al (forthcomng) adopt an nput dstance functon approach n order to decompose productvty growth nto techncal change, effcency change and scale effcency change. Ths study clams that whle techncal change occurred as a consequence of prvatzaton, effcency mprovements dd not come about because the regulatory prce control was lax. Bottasso and Cont (2003) also found evdence that operatng cost neffcency was decreasng and that the neffcency dfferentals were narrowng for the whole Englsh and Welsh water ndustry between 1995 and Lookng elsewhere the role of regulatory polcy has been recently examned by Aubert and Reynaud (2005) for the Wsconsn water system. The partcular Wsconsn regulaton scheme, based on the smultaneous presence of prce-cap and rate-of-return schemes n the same regon at the same tme, allowed the authors to compare the effect of the two dfferent regulatory regmes. Usng a stochastc cost fronter approach (where the neffcency error term s modeled as a functon of the regulatory type), they surprsngly conclude that the most effcent utltes are those operatng under a rate-of-return regme 6 5 Ths process s manly explaned by the authors n terms of the envronmental constrants that forced the prvatsed companes nto extensve nvestment programmes. 6 Rate-of-return regulaton emerged for lmtng the profts of franchsed monopoles. It conssts n lettng the frms to freely choose ther prce under the constrant that return on captal should be far but below a pre- 429

7 and subject to extensve nformaton gatherng by the regulator. Prce-cap regulaton was shown to be a hgher-powered ncentve mechansm than a hybrd regulatory scheme wth less nformaton avalable for the regulator. The need for the regulator to gather nformaton n order to enforce an effectve yardstck competton system s also emphaszed by Anwandter and Ozuna (2002), n the context of the publc water ndustry reform n Mexco. Evdence of poor results of prvate ownershp, gven the monopolstc nature of the servce, can be found n other studes. Fegenbaum and Teeples (1983), usng a sample of government and prvately-owned U.S. water supplers suggest that, contrary to publc choce or property rghts theores, no evdence could be found of sgnfcant dfferences n the cost functons of publc versus prvate utltes. Bhattacharyya et al (1994) and Bhattacharyya et al (1995a and 1995b) modeled the cost structure of a sample of U.S. water utltes embodyng the potental nput allocatve dstorton attrbutable to the ownershp nature. 7 The man results hghlght a better effcency performance of the publc frms at least when they are large. Lambert et al (1993) examned the queston of the ownershp structure for U.S. water system usng a lnear programmng approach. They found no dfference between prvate and publc categores n selectng the least cost combnaton of nputs. An alternatve method for modelng the technology and assessng effcency performance s va DEA (Data Envelopment Analyss), although DEA was crtczed by OFWAT n 1994 as a means of settng prce lmts. A comprehensve descrpton of the use of DEA for regulatory purposes s provded n Thanassouls (2000a and 2000b), where DEA methodology has been employed wth the am of estmatng the potental operatng cost savngs for the water functon. These studes also address the ssue of how to represent the technology. Other applcatons of DEA can be found n Tupper and Resende (2004) n the context of the Brazlan water and sewerage system and n Coell and Waldng (2006) n the context of the Australan water ndustry. The former, n partcular, provdes a second stage correcton of the DEA effcency scores n order to account for regonal operatonal heterogenetes (densty effects and water losses). Cubbn and Tzandaks (1998) carred out a comparson between regresson analyss and DEA for the UK water ndustry usng data. Ths study concludes that DEA analyss could be useful n dentfyng possble reasons for poor performance but t s to be used wth cauton where large datasets are not avalable. Summarzng, as far as the UK context s concerned, analyss of the mpact of regulaton has been generally lmted to the 1994 prce revew wth the excepton of the study by Saal and Red (2004) and the fndngs show a scant evdence of effcency growth. The 1999 prce revew tghtened the regulaton scheme, mposng for the frst tme a prce reducton. The dataset used n ths study covers the perod from to for the ten WaSCs, and although t does not allow us drectly to consder the mpact of specfed level. Ths method allows prces to ncrease for coverng costs and, n such a way, t s expected to provde less ncentves to pursue cost effcency. 7 In these studes, the authors employed a generalsed or shadow cost functon approach (Kumbhakar, 1992; Parker, 1995, Maetta, 2000; Kumbhakar and Sarkar, 2003) whch accommodates the possble volaton that arses when costs are mnmsed wth respect to nternal (shadow) prces rather than market nput prces. The nput prce dstortons brng about allocatve neffcency. The applcaton of ths methodology may be partcularly sutable for publc utltes, as they are often subject to the publc control. It s also to be noted that an alternatve soluton to the problem of not exogenous nput prces conssts n the use of an nputdstance functon (see Saal and Parker, 2004), snce ths method does not requre nformaton on prces. 430

8 prvatzaton on effcency, t allows us to test the effects of two subsequent prce revews. Ths makes t possble to address the queston of whether tghtenng the regulatory regme succeeded n mprovng the cost effcency of the ndustry. Furthermore, from a methodologcal vewpont, ths study seeks to shed some lght on allocatve effcency, whch has receved so far lmted attenton n the emprcal lterature. 4 Model specfcaton In 1957, Farrell ntroduced a methodology for the measurement of the economc effcency, as well as ts decomposton nto both techncal and allocatve components. From an nput-orented perspectve 8, techncal effcency (TE) s assocated wth the ablty to produce on the effcency boundary of the producton possblty set gven a predetermned quantty of output (pont E n fgure 1), whereas allocatve effcency (AE) reflects the ablty to produce at a gven output level usng the optmal nput mx (pont E n fgure 1). X 2 Effcent soquant lne E D Isocost lnes F E 0 X 1 Fgure 1: Global, techncal and allocatve measures of cost effcency Note: Two nputs (x 1 and x 2 ) and one output technology. Techncal effcency OE/OD; Allocatve effcency OF/OE; Economc effcency OF/OD (OF/OE) (OE/OD) Let N [wth n 1,, N] be the number of Decson Makng Unts (DMUs), x the -th nput [ 1 I] and y j the j-th output [j 1 J]. Then, the nput-orented radal measure of techncal effcency (TE I ) s calculated by solvng, for each DMU, the followng lnear programmng problem (Charnes, Cooper and Rhodes, 1978; Banker, Charnes and Cooper 1984), under the assumpton of varable returns to scale (VRS) 9 : 8 In prncple, the economc effcency may be measured usng an nput or an output-orented approach. In the frst case, the nput use s mnmzed gven a certan amount of output, whle n the second the output s maxmzed for a gven level of nputs. Generally, the adopton of an nput-orented framework s preferred when publc utltes are consdered as the demand of servce the supplers must provde may be seen as exogenous (see Torres and Morrson Paul, 2006, for an applcaton wth endogenous output). 9 For a comprehensve descrpton of DEA models, see Thanassouls (2001) and Coell et al (2005). The VRS (Varable Returns to Scale) model here adopted ensures through the convexty constrant that a DMU 431

9 0 S, S, λ 1 λ 1...J j y λ S y 1...I x λ S x TE S S ε TE j n N 1 n n N 1 n jn n j j N 1 n n n I J 1 j j I 1 I + + mn (1) where S and S j ndcate the slacks (that s, non-radal nput reducton measures) for -th nput and j-th output respectvely, ε s an nfntesmal and λ n s an ntensty varable assgned to each DMU, whch assumes non-zero value for the effcent DMUs (that s, those lyng on the effcency fronter) whch are the peers for the neffcent ones. The scalar TE I ranges from 0 to 1, beng equal to unty when full techncal effcency occurs. The allocatve effcency measure allows us to assess the potental to reduce costs further by means of a varaton n the nput mx, consstently wth the exstng technology. The DMU s cost-mnmsng nput demand (x * ) may be calculated by solvng, for each DMU, the followng VRS lnear programmng problem (Coell et al, 2005): 0 x, λ 1 λ 1...J j y λ y 1...I x λ x w x n N 1 n n N 1 n jn n j N 1 n n n I 1 mn (2) Hence, the allocatve effcency measure s calculated as the rato of mnmum attanable cost to the cost correspondng to a stuaton wheren all nputs are contracted by the same proporton (1-TE I ) n order to elmnate techncal neffcency, as follows: ( ) I 1 I I 1 x TE w w x AE (3) s compared wth unts operatng at a smlar sze. In ths way, ths model allows separatng the pure manageral neffcency from the neffcency entrely due to an ncorrect sze settng. 432

10 The basc DEA model descrbed here evaluates economc effcency usng tradtonal nput and output varables but t does not consder the potental role that envronmental factors may have on producers performance. 10 Several models have been developed n order to ncorporate envronmental effects nto a DEA-based performance evaluaton. 11 One possble approach s to nclude the envronmental varables drectly nto the lnear programmng formulaton ether as nondscretonary nputs, outputs or neutral varables, accordng to the crcumstances (Ferrer and Lovell, 1990). Ths requres that further lnear programmng constrants be ncluded. As a consequence, only few envronmental varables can smultaneously be taken nto account to avod excessve restrcton of the reference set, hence reducton of the dscrmnatory power of DEA. Another possble approach s to adopt a mult-stage DEA analyss amed at ensurng that the comparson s made among unts whch operate under smlar envronmental condtons, so elmnatng the envronmental effects from the sngle producer s performance assessment. In ths way, the evaluaton of the mpact of the envronmental effects may be carred out ether when an a pror drecton of the nfluence of the envronmental varable upon effcency s known (Banker and Morey, 1986) or not (Charnes et al, 1981). Both these approaches are, however, determnstc and so they fal to take nto consderaton the effects of statstcal nose on effcency performance. Another group of models s based on two-stage mxed approaches, whch nvolve solvng a DEA problem n a frst stage usng tradtonal nput and output varables, n order to calculate ntal effcency measures. The effcency scores are then regressed upon a set of envronmental varables n a second stage, the objectve beng to determne the sgns, as well as the sgnfcance of the coeffcents of the envronmental varables and to consder the mpact of nose. McCarty and Yasawarng (1993) and Bhattacharyya et al (1997) tred to account for nose usng the resduals of the regresson to adjust the frst-stage DEA effcency scores. Fred et al (1999) ntroduced a three-stage approach where the ntal DEA effcency scores are regressed upon a vector of envronmental factors. Predcted values of the mpact of the envronmental effects can be then computed. In a thrd stage, the orgnal data are adjusted to account for the effect of envronmental varables and DEA s re-run n order to obtan new DEA scores unaffected by envronmental characterstcs. Ths approach, however, s unable to account for the role of statstcal nose on effcency. 12 In order to embody the acton of both envronmental varables and statstcal nose upon effcency, we adopted a novel three-stage approach proposed by Fred et al (2002). By adoptng, a mxed approach whch combnes DEA and Stochastc Fronter Approach (SFA), ther model makes t possble to obtan a measure of the ntrnsc manageral ablty 10 Some examples of envronmental factors that may affect frms performance nclude characterstcs, such as ownershp nature, geographcal locaton, regulatory regme and so on (Fred et al, 1999). 11 See Coell et al (2005) for wde detals on these models. 12 In general, t s mportant to recognze that as noted n the DEA lterature all the mult-stage mxed approaches may present problems f the varables used n the frst stage (nputs and outputs) were hghly correlated wth the set of varables used n the second stage; the resultng second-stage coeffcents would then be based. Moreover, whether n the frst DEA stage some relevant nputs or outputs were omtted, the technology would be ncorrectly specfed and the effcency scores napproprate for use n the second-stage regresson. 433

11 shown n organzng frms operatons, separately both from the mpacts of the envronmental characterstcs n whch producton takes place and from random nose. Note that, although the Fred et al (2002) approach was orgnally proposed to model DEA-based techncal neffcency measures, t has been extended n ths study to ncorporate also allocatve neffcency. The model s brefly summarzed here. Accordng to Fred et al (2002), the dfference between the observed nput-specfc usage, x ( 1,, I), and the optmal projected value onto the effcent boundary, TE I x (where the techncal effcency score, TE I, s derved from the DEA lnear programmng (1)), s vewed as the excess use (or over-use) of the -th nput. Such excess use may be explaned by pure manageral techncal neffcency, envronmental effects and random nose. In ths lght, these nput-specfc overuse measures derved for all the observatons from the frst stage have been regressed over a set of envronmental varables usng SFA, as descrbed below 13 : ( x TE x ) f ( z; β) + u v 1,..., I (4) I + where z [z 1n,, z Kn ] s a vector of K envronmental varables outsde the control of managers, β s a vector of parameters to be estmated, u s a non-negatve half-normal dstrbuted N + (0,σ u 2 ) error term 14, whch captures the over-use of the -th nput brought about by pure manageral neffcency, and v s the usual normally dstrbuted N(0,σ v 2 ) error term. 15 As n equaton (4), the -th nput allocatve dstorton, obtaned as dfference between the techncally optmum nput level and the cost-mnmzng nput demand (x * ), has been regressed usng SFA on a set of varables whch enable to control for the mpact of envronmental factors. In ths case, as the nput dstorton could be ether postve or negatve, we consdered, on the left-hand sde of equaton (5), the absolute value of the dfference 16, as follows: ( z; β) + u v TE I x x f + 1,..., I (5) 13 It should be noted that n the Fred et al (2002) method total (radal plus non-radal) measures of nput slacks (nterpreted as nput over-use measures) are regressed aganst a set of observable envronmental varables usng SFA, where total nput slacks are calculated, followng the lnear programmng problem (1), as x (TE I x - S ) x (1-TE I )+S ( 1,, I). Dfferently, our second stage estmates are solely based on radal rather than total nput slacks, expressed as x - TE I x ( 1,, I). The attempt to dsentangle techncal from allocatve neffcency led us to nclude non-radal nput slacks, S, nto the allocatve dstorton equatons, as the potental non-radal contracton of specfc nputs reflects the adjustment of an napproprate nput mx (Coell et al, 2005; Ferrer and Lovell, 1990). 14 In ths paper, a half-normal dstrbuton has been adopted rather than a more general truncated-normal specfcaton of the neffcency term, n order to mnmse computatonal problems. Although the truncatednormal specfcaton s more general, we do not thnk that ths assumpton creates serous problems. 15 For completeness, n Fred et al (2002), a thrd stage s defned n whch DEA s re-run once orgnal data are adjusted n order to remove the mpact of envronmental varables and nose. Snce the calculaton of frms rankng s beyond the am of ths paper, we decded to skp ths stage. 16 The left-hand sde dfference n equaton (5) should be consdered as a mere dstorton measure as t only allows consderng f dstorton s systematcally explaned by external or nternal factors, wthout dstngushng between nput-specfc over or under-utlsaton. 434

12 where z, β and v have the same meanng as above. In ths case, the neffcency term u 0 should be nterpreted as the ntrnsc nablty of the managers to arrange the nput mx, gven the relatve nput prces, n order to attan mnmum cost. One advantage of ths methodology wth respect to the stochastc cost fronter approach s that t allows separatng the techncal and the allocatve effcency components n an easy way. For each component then, t nvolves the estmaton of I separate secondstage equatons, thus lettng features of operatng envronment, pure manageral neffcency and statstcal nose exert dfferent mpact across nputs. In addton, t allows separatng the techncal from the allocatve effcency. In order to capture the (techncal and allocatve) neffcency trend over tme, the neffcency error terms, u, have been modeled, ether n equatons (4) or (5), accordng to the tme-varyng neffcency model defned n Battese and Coell (1992): nt ( t T ) ( ) η e unt u (6) where n 1,, N denotes the frm, t 1 T denotes the tme, T ndcates the fnal year of the tme seres for each frm, η s a parameter to be estmated and u T s assumed to have an..d. half-normal dstrbuton N + (0,σ u 2 ). A postve value of η mples a downward trend n the manageral effcency term over tme whle a negatve value mples an upward trend. Thus, the trend of the manageral neffcency for each nput, along wth ts statstcal sgnfcance, s drectly derved from the data once both envronmental factors and nose have been removed. As regards ths pont, t should be acknowledged that a restrctve assumpton apples n the sense that all the frms are assumed to be characterzed by a smlar trend of the neffcency term over tme. Ths could be seen as a regrettable restrcton of the model. Nonetheless, t may be argued that all the England and Wales WaSCs share very smlar regulatory condtons and, as a consequence, the restrctons enforced by the central regulator are lkely to gude frms n a common drecton. 5 Specfcaton of the technology usng DEA A fundamental stage n DEA s the correct dentfcaton of the multple-nput multpleoutput bundles, so that frms can be compared takng nto consderaton all the actvtes they carry out (Thanassouls, 2001). Wth respect to the ndustry under nvestgaton, the frst actvty concerns the extracton and treatment of water from rvers or boreholes. Once water has been abstracted and treated to meet qualty parameters, t s pumped nto the mans and delvered to household or non-household customers through the dstrbuton network. A second set of actvtes deals wth the collecton of waste water through the sewage network and the dsposal of the effluent n the sewage treatment works so that water can be returned to ts natural envronment. There s a body of lterature that attempts to model water and sewerage technology and cost structure (among the others, see the studes of Fabbr and Fraquell, 2000; Garca and Thomas, 2001; Mzutan and Urakam, 2001; Torres and Morrson Paul, 2006). The choce of nputs and outputs descrbed below s generally consstent wth ths lterature. 435

13 Usng ths scheme, we dentfed four outputs, each of them able to capture a specfc resource-consumng phase of the overall transformaton process. Frst, the total volume of delvered potable plus non potable water (WDEL) has been used as the output of the abstracton and treatment phase. Ths s a conventonal measure of the water producton actvty. An alternatve measure, also tested n ths work wthout sgnfcant changes n the results, s the dstrbuton nput, whch s defned as the amount of water enterng the dstrbuton system, ncludng the water losses along the dstrbuton network. Second, the total number of household and non-household water servce-connected propertes (WPROP) has been adopted as proxy for the scale of the dstrbuton actvty. Thrd, the total number of household and non-household sewerage servce-connected propertes (SPROP) has been used as to capture the scope of the waste water collecton actvty. Fnally, the physcal amount of waste water (WASTW) has been ncluded as output of the effluent dsposal and treatment actvty. One mportant characterstc of water companes s that they must comply wth drnkng water qualty standards (ssued by DWI) and rver qualty standards (ssued by EA). Thus, water qualty could be regarded as an addtonal output snce the fulfllment of qualty programs s usually hghly expensve. However, nstead of consderng water qualty as a separate output we adopted the soluton, suggested by Saal and Parker (2000), of adjustng the WDEL varable by a frm-specfc complance ndex wth drnkng water qualty standards and WASTW by a frm-specfc water qualty complance ndex wth rver qualty standards. Both complance ndces have been standardzed wth respect to the average England and Wales complance levels. 17 In order to model the producton process, we used three nputs: labour, other operatng expendtures and captal. All the varables have been expressed n prces. Labour nput (EMPL) s measured by the total cost of non-manual and manual manpower whch s drectly attrbutable to the water and sewerage busnesses. In order to obtan a proxy for the physcal use of labour, we adjusted ths varable by a frm-specfc labour prce ndex. 18 The other operatng expendtures varable (OTHEX) has been calculated by subtractng the cost of labour from the total operatng expendtures (OPEX) for the apponted water and sewerage busnesses, and t ncludes the cost of materals and consumables, hred servces and energy (see Ashton 2000a and 2000b for a smlar approach). Snce the prce of energy followed a decreasng trend both n real and nomnal terms the fall n the prce of energy for the ndustral sector s about 20% n current terms and 60% n nomnal terms from 1993 to 2005 t was mpossble to deflate ths aggregate value usng a common prce ndex. Therefore, we deflated the materals and servces cost and the energy cost through two dfferent ndces. The former has been adjusted by the conventonal RPI 17 Consstent tme seres of drnkng water and rver qualty complance ndces have been taken from the DWI and the EA annual reports. 18 The labour prce ndex s based on the trend of the average wage for each frm. In turn, the average wage has been calculated dvdng the total employment cost by the number of full total equvalent employees (the nformaton has been taken from the annual reports of the companes). Ths s the best avalable proxy of the yearly average wage for the water and sewerage ndustry. The resultng wages have been then compared wth the data from the New Earnngs Survey and ths confrmed ther valdty. We preferred to use ths specfcaton of the labour nput nstead of drectly usng the number of employees snce the latter sometmes relates to the whole group, so ncludng workers of non apponted busnesses. 436

14 ndex; the latter by an energy prce ndex for the ndustral sector derved from the Department for Trade and Industry (DTI). 19 Captal expendture (CAPEX) has been ncluded n the DEA specfcaton because of the captal-ntensve nature of the water and sewerage ndustry (Saal and Parker, 2000, 2001; Saal et al, forthcomng; Coell and Waldng, 2006). The annual captal consumpton has been calculated by multplyng the yearly monetary value of captal, gven by the annual average modern equvalent asset (MEA) estmaton of the replacement cost of fxed tangble assets 20, by a deprecaton rate. Ths latter was derved on the bass of the current deprecaton and nfrastructure renewal charges 21, drectly attrbuted to water and sewerage busnesses, dvded by the average MEA gross captal value n the same year. In ths way, the consumpton of captal, as captured by CAPEX, s proportonal to the stock of captal. Some descrptve statstcs on output and nput varables are presented n Table 1. Varable Mean Standard Varaton devaton coeffcent Mn Max WDEL (Ml/d) WPROP (000) SPROP (000) WASTW (Ml/d) EMPL ( m) OTHEX ( m) CAPEX ( m) Table 1: Descrptve statstcs In order to derve the contrbuton of allocatve effcency to overall economc effcency, nput prce data are needed. A deflaton procedure based on has been followed, n order to solate the real movements of prces. A prce of labor has been calculated by dvdng the overall cost of employment by the number of full tme equvalent employees (see note 18) and then deflatng the resultng values by the RPI ndex. A prce for other operatng expendtures s problematc, gven the heterogeneous nature of ths nput. We adopted a weghted average of RPI and a real prce ndex of energy for 19 Dfferent energy prce ndces are avalable. We consdered the energy prce ndex for ndustral use expressed n current terms and ncludng the clmate levy charge for UK. 20 Followng Stone and Webster (2004), the MEA values avalable n the OFWAT dataset have been deflated usng the Constructon Prce Index (COPI) as deflaton ndex nstead of the RPI ndex. Furthermore, the MEA annual values have been corrected n order to elmnate the mpact due to AMP adjustments that s, perodc captal value adjustments to brng assets to ther current values accordng to ther operatonal standards. Ths smoothng of the captal stock tme seres has been carred out consderng the MEA value n the fnancal year as base and then addng (for the successve years) or subtractng (for the prevous years) the amount of the annual net nvestments, calculated for each year at prces. 21 The deprecaton regme s dfferent accordng to the type of asset. Whle above ground assets (lke treatment plants, pumps, reservors, sewage dsposal works) are deprecated, the underground assets are not drectly deprecated but an nfrastructure renewals charge s computed and ncluded n the Proft and Loss statement. 437

15 the ndustral sector, taken from DTI, where the weghts are represented by the respectve cost shares. 22 Fnally, the prce of captal has been computed as the percentage rate resultng from the sum of the above descrbed deprecaton (and nfrastructure renewal) rate and the opportunty cost of captal. 23 The latter has been drectly mputed from the regulatory assessment of the far rate of return on the captal employed. Accordng to OFWAT, the cost of captal cost was equal 5.5% up to 1999 and 4.75% for the subsequent years. In addton, t should be noted that the ncluson of four output varables ensures that the comparson s made among frms wth smlar customer densty (where customer densty s measured as volumes per customer) and smlar relatons between water and sewerage actvtes. Furthermore, comparson between frms whch are smlar n terms of network densty (where network densty s measured as customers per klometre of network) s also ndrectly accommodated. Low network densty frms are generally more captal-ntensve than hgh network densty frms. Therefore, the jont consderaton of operatng and captal expendtures ensures that the comparson s made among frms wth smlar nput ratos, that s, wth comparable network densty condtons (Coell and Waldng, 2006). 6 Envronmental and regulatory varables The effcency of a frm could be affected by exogenous condtons that are not under the drect control of managers. These effects should be removed n an effcency assessment. The exogenous varables we used n the second stage are of two types: envronmental varables and polcy varables. The former take account of the mpact of the dfferent characterstcs of the network and of the area where the servce s provded, thus control for heterogenety among frms. The latter relate to regulatory polcy and more specfcally, the change n the economc envronment that occurs after the ntroducton of new regulatory constrants. These varables are not dfferentated by frms snce the regulatory framework s common for the whole ndustry but they vary over tme. The set of envronmental varables should be such as to represent the exogenous characterstcs of the whole range of actvtes. Our set of envronmental varables s consstent wth many of the above mentoned emprcal studes. We now brefly descrbe these varables. 22 A better soluton may have been to dsentangle materal and servces from energy. In ths latter case, the frst choce for the energy prce would have been a measure calculated by dvdng the cost of power by the consumpton of energy but unfortunately, no consumpton value s avalable n the OFWAT dataset. The most natural alternatve would have been to use an energy prce ndex but n ths case, we must have employed two prce ndces (the RPI ndex and the DTI energy prce ndex) nvarant across frms. On the contrary, the weghted average prce ndex here adopted s varant, gven that the cost shares vary across frms and years. The DTI real energy prce ndex has been deflated usng the GDP deflator. We recomputed the energy prce tme seres ndex usng the RPI ndex but no sgnfcant dfference emerged. 23 The noton of user cost of captal s based on the vew that captal should be consdered under both a physcal and fnancal perspectve. Indeed the captal cost the frm truly ncurs s an mplct rental prce, whch s the nterest rate on the nvestment prce, plus the deteroraton nvolved, (Morrson Paul, 1999, p.286). For a smlar approach see also Mzutan and Urakam (2001). 438

16 The proporton of water abstracted from underground sources (SOURCE) reflects the dfferent condtons of water producton. A larger amount of abstracton from boreholes than from surface sources requres hgher power consumpton but at the same tme, less treatment cost because of the hgher purty of underground water. Wth regard to captal, a hgher proporton of underground water requres more pumps whle a hgher proporton of surface water s assocated to a larger number of treatment plants. For these reasons, we assgn no a pror mpact to ths varable. The percentage of water losses (WLOSS) wth respect to the overall dstrbuton nput s a general proxy for the operatonal condton of the dstrbuton network. A hgher proporton of losses mples more crtcal condtons of the network, thus a hgher nput use s expected. The water populaton densty (WDENS) s calculated as the rato between the populaton provded wth water and the length of water dstrbuton network. In a rough way, a hgher densty could also be assocated to a greater proporton of household propertes. In general, provdng servce to a more concentrated populaton s cheaper per connecton than servng a dspersed populaton, snce n ths latter case more dversons of the network, more frequent mantenance and more energy are needed. The sewerage populaton densty (SDENS) s calculated as the rato between the equvalent sewerage populaton and the length of the sewerage network. A hgher densty could be assocated to a hgh proporton of household propertes connected. Analogous economes of densty arguments, as descrbed above for the water actvty, apply even though a more ambguous effect has been emprcally found (see Tupper and Resende, 2004). 24 Snce sewerage populaton densty could not entrely capture the effect due to the users composton, we also consdered the trade effluent varable (TREFFL), whch represents the proporton of ndustral effluent n total waste water. In general, we would expect that more ndustral effluent would mpose hgher nput requrements, especally wth respect to treatment cost and energy. Tme trend (TIME) s ncluded to account for technologcal progress/regress. The TIME varable s nterpreted as a proxy for technologcal changes but not for changes n techncal effcency condtons, whch are emboded n the one-sded dstrbuted error component. Furthermore, as prvately-owned frms are proft-maxmzng agents, we would expect that techncal progress was encouraged after prvatzaton. Fnally, regulatory varables have been ntroduced to take nto account the potental mpact of changes n the economc envronment. Because there have been two prce controls durng the perod under observaton, we ntroduced n the model two dstnct dummy varables, REG94 and REG99, whch assume a value of one for the fve years after respectvely, 1994 and As noted above, the second regulatory nterventon was more severe. Hence, we may expect a stronger nput-reducng mpact assocated wth the REG99 varable. The manageral (techncal and allocatve) neffcency s emboded nto the one-sded neffcency error terms (u) n equatons (4) and (5). The undrectonal effcency trend s 24 The WDENS and SDENS varables are expected to capture more effects than those ones already accommodated by the mult-nput DEA specfcaton. WDENS and SDENS use the populaton rather than the number of customers and they are ncluded to reflect the dfferent operatonal characterstcs assocated to the network conformaton. 25 It should be noted that the allowed prce changes took effect on 1 Aprl 1995 and 1 Aprl

17 drectly estmated by the model. Ths neffcency error component should be nterpreted as the resdual neffcency of the frms f they faced the same envronmental and nose condtons, and they operated n a neutral context wth respect to regulatory polcy and techncal progress/regress. Thus, another reason has to be sought to explan the neffcency terms level and trend. Snce the water and sewerage companes were subjected to a prvatzaton process n 1989, the change n ownershp regme could be nterpreted as drver of the manageral neffcency trend. As stated above, prvate frms are usually vewed as focusng more on proft-maxmzng (or cost-mnmzng) behavor than publc frms, so that they can be expected to make more effort for the ratonalzaton of the nput consumpton. Moreover, the ntroducton of a yardstck competton regme n the perod after prvatzaton could have well worked as an ncentve mechansm as t allowed a frm s performance to be judged n relaton to the performance of the other unts. 26 At least n the long run, ths could be expected to narrow the effcency dfferentals and to nduce the frms to reduce costs. For these reasons, we should expect a postve effcency trend that s, a convergence towards an optmal use of nputs from both a techncal and an allocatve vewpont Emprcal results 7.1 DEA techncal and allocatve effcency results The frst stage DEA results are shown n Table 2. The mean techncal effcency score s equal to 0.909, whch ndcates that the average frm could reduce all nputs smultaneously by 9.1%, stll producng the same amount of output. The mnmum value s 0.657, ndcatng that there were substantal dfferences among frms. The mean allocatve effcency score s 0.810, a very low level, whch ndcates that, even f techncal effcency were acheved, a 19.0% excess of total operatng (captal plus non captal) cost over mnmum cost there would stll exst, whch could be elmnated by adjustng the napproprate nput mx. The mnmum score s 0.349, revealng the presence of very large allocatve dstortons. 28 Moreover, the varablty of the allocatve scores s hgher that that of techncal effcency. These results ndcate that a major part of the 26 OFWAT has placed consderable emphass on yardstck competton n prce cap settng. By usng the results of econometrc studes of the regulated frms whch relate costs to nternal nput organsaton and envronmental varables, OFWAT s able to set out catch-up effcency targets that contrbute to the determnaton of the prce cap for ndvdual companes. The determnaton process also makes adjustments for events that are beyond the companes control and rewards or penalses servce qualty performance. The fnal decson on prce caps thus reflects OFWAT s assessment of each company s performance relatve to the ndustry as a whole. 27 Whle the regulaton and tme varables have been used as explanatory factors for both the techncal and allocatve frameworks, the set of operatonal characterstcs have been consder to have only a techncal nature. Ths s consstent wth several papers wthn the shadow cost functon approach lterature stream whch only use regulaton, ownershp and tme as potental explanatory factors for allocatve dstortons. 28 Actually, ths value appears very low but when we move to the frst decle the allocatve effcency level ncreases to 0.622, thus revealng a more credble assessment of the allocatve neffcency n such extreme stuatons. Anyway, very low level of allocatve (as well as techncal) effcency could also be found n many emprcal researches usng DEA (see, for nstance, Coell et al (2002)). 440