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Explaining efficiency in municipal services providers

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Abstract

This paper considers the provision of some important municipal services and applies the non-parametric double bootstrap Simar and Wilson (J Econ 136(1):31–64, 2007) model based on a truncated-regression to estimate the effect of a group of relevant factors, which include the political sign of the governing party and the type of management, on robust DEA (Data Envelopment Analysis) estimates. Previous conditions, like separability, must hold for meaningful first- stage efficiency estimates and second-stage regression. After some confusion in the literature, Simar and Wilson (J Prod Anal 36(2):205–218, 2011b) clarify that their work of 2007 actually defines a statistical model where truncated (but not censored, i.e., Tobit, not Ordinary Least Square) regression yields a consistent estimation of model features. They demonstrate that conventional, likelihood-based approaches to inference are invalid, and they develop a bootstrap approach that yields valid inference in second stage regressions when these are appropriate. The results reveal a significant relation between efficiency and all the variables analysed and that municipalities governed by progressive parties are more efficient.

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Notes

  1. This means that the rate of convergence decreases when the dimension of the attainable set increases. The rate of convergence of the FDH estimator is \(n^{{{1 \mathord{\left/ {\vphantom {1 {p + q}}} \right. \kern-0pt} {p + q}}}}\)whereas for the DEA with the additional assumption of convexity, the achieved rate is \(n^{{{2 \mathord{\left/ {\vphantom {2 {p + q}}} \right. \kern-0pt} {p + q}} + 1}}\). See Simar and Zelenyuk (2011).

  2. For an extended and up-to-date review see c Simar and Wilson (2007), Cordero-Ferrera et al. (2008) or Bãdin et al. (2010b).

  3. See Bãdin et al. (2010b).

  4. The probabilistic framework will be of great help later on this paper to analyze the Simar and Wilson (2007) separability assumption.

  5. The asymptotics of the conditional order-m estimator was analyzed in Cazals et al. (2002) and recently in Jeong et al. (2010). As the conditional efficiency approach relies on the estimation of nonparametric kernel functions to select the appropriate reference partners, it relies on the choice of bandwidth parameters: although the estimates avoid the separability condition, their bandwidths rely on it.

  6. In their simulated examples, they illustrate how the standard DEA is very sensitive to outliers. Moreover, once the size of the noise increases, the DEA estimator behaves badly.

  7. See Sect. 1 in Wilson (1993, pp. 320–321). “S” is a set of n firms, S = (1,2,…,n); L ⊂ S contains i elements, i < n. \(R_{\hbox{min} }^{(i)}\)denote the observed minimum value of \(R_{L}^{(i)}\) for all \(\left( \begin{gathered} n \hfill \\ i \hfill \\ \end{gathered} \right)\) possible subsets L of size i. The numerator is the Andrews and Pregibon (1978) statistic that Wilson (1993) extends to the case for more than one. The denominator expresses the minimum value for a certain number of subsets of size i observations. As Wilson (1993) indicates for large data sets, Andrews and Pregibon (1978) suggest a graphical representation of the log ratios. Examination of the separation between the smallest ratios indicates possible outliers.

  8. There are 470 articles from 2010 to May 2012, of which 62 correspond to 2012.

  9. The DEA estimators to be computed in our case will have variable returns to scale and an input orientation that seems to be the most appropriate given that there is a demand minimization policy. The BCC model appeared first in Banker et al. (1984). Scales of returns to scale were also tested but rejected in favour of the VRS. For more details on the returns to scale test, refer to Simar and Wilson (2002). As regards traditional efficiency estimators we refer to section 2 in Wheelock and Wilson (2008). Since the command DEA of FEAR 1.15 computes estimates by Shephard (1970) distance function, efficiency has been measured in terms of Shephard’s input distance function, δi.

  10. For more details, see Simar and Wilson (2007) and Simar and Wilson (2011b).

  11. Daraio et al. (2010, p. 4): “In the empirical literature, researchers have typically assumed ψ(z i ,β) = z i ·β, where β is a vector of parameters. In addition to Assumptions 2.1–2.3, Simar and Wilson ( 2007 ) assume the error, ε, is distributed (truncated) normal in order to reflect the empirical literature. Alternatively, ψ(z i ) and the distribution of ε can be assumed to be nonparametric; see Park et al. ( 2008 ) for details”.

  12. For the steps and details refer to Simar and Wilson (2007). To this purpose, FEAR 1.15 (March 2010) includes DEA, boot.sw98, rnorm.trunc and treg among its routines.

  13. The statistic \(\hat{T}_{5n}\)results in significant p value of 0.0316, leading to rejection of the null hypothesis of independence.

  14. To understand the importance of the separability condition see Simar and Wilson (2011b).

  15. Only observations of the conditional DEA technology set are used for the construction of the DEA frontier for DMUi that lie within the chosen bandwidth, h, around zi. Efficiency scores for each observation can then be derived from this technology set. For a generalized approach of conditional efficiency measurement see Bãdin et al. (2010a). For the DEA conditional estimator, provided the elements of Z are continuous, the bandwidth parameter h can be optimized using the least-squares cross-validation (LSCV) technique discussed by Bãdin et al. (2010b). The appendix provides a Matlab routine that computes the bandwidth based on the LSCV criterion for the output oriented version. Following Daraio et al. (2010, p. 9): “if Z contains qualitative variables, then the sample observations must first be divided into groups defined by the qualitative variables”. Asymptotic results for DEA conditional estimators are given by Jeong et al. (2010).

  16. Efficiency is measured in terms of Shephard’s input distance function. Measure is hence one or larger.

  17. See Simar and Wilson (2000, p. 790). The authors advise that bias-correction should only be used when the ratio is well above unity, something which we will consider.

  18. For example, the municipality Vera, which is efficient when considering the estimation based on the initial distance function, has a corrected coefficient of 1.128, indicating that to obtain the same level of output it could reduce its input by about 10%. Specifically, the confidence interval at 95% for this unit indicates that it could reduce its inputs by between 3 and 27%.

  19. For more details See Zelenyuk and Zheka (2006) or Appendix 1 in Latruffe et al. (2008).

  20. We follow Simar and Wilson (2007, p. 44): the choice of the number of replications L1 in Algorithm #2 determines the number of bootstrap replications used to compute the bias-corrected estimates, \(\hat{\hat{\delta }}_{i} .\) They found that 100 replications are sufficient for this purpose. For L2 they use 2000 replications. The values of the variables are scaled appropriately; signs of estimated coefficients can be interpreted in a Farrell–Debreu direction.

References

  • Abizadeh S, Gray J (1993) Provincial government spending in Canada: an empirical analysis. Int Rew Appl Econ 7(1):69–90

    Google Scholar 

  • Ahmad IA, Li Q (1997) Testing Independence by Nonparametric Kernel Method. Stat Probab Lett 34(2):201–210

    Google Scholar 

  • Ancarani A, Capaldo G (2001) Management of standardized public services: acomprehensive approach to quality assessment. Manag Serv Qual 11(5):331–341

    Google Scholar 

  • Andersen P, Petersen NC (1993) A procedure for ranking efficient units in data envelopment analysis. Manage Sci 39(10):1261–1264

    Google Scholar 

  • Andrews DF, Pregibon D (1978) Finding the outliers that matter. J R Stat Soc 40(1):85–93

    Google Scholar 

  • Athanassopoulos AD (1998) Decision support for target-based resource allocation of public services in multiunit and multilevel systems. Manage Sci 44(2):173–189

    Google Scholar 

  • Bãdin L, Daraio C, Simar L (2010a) How to measure the impact of environmental factors in a nonparametric production model? IAP Stat Technical Report Series: Institut de Statistique, Universit′e Catholique de Louvain. Louvain-la-Neuve, Belgium

    Google Scholar 

  • Bãdin L, Daraio C, Simar L (2010b) Optimal bandwidth selection for conditional efficiency measures: a data-driven approach. Eur J Oper Res 201(2):633–640

    Google Scholar 

  • Balaguer MT (2004) La eficiencia en las Administraciones Locales ante diferentes especificaciones del output. Hacienda Pública Española 170:37–58

    Google Scholar 

  • Banker RD, Natarajan R (2008) Evaluating contextual variables affecting productivity using data envelopment analysis. Oper Res 56(1):48–58

    Google Scholar 

  • Banker RD, Charnes A, Cooper WW (1984) Some models for estimating technical y scale inefficiencies in data envelopment analysis. Manage Sci 30(9):1078–1092

    Google Scholar 

  • Becken S, Simmons DG (2002) Understanding energy consumption patterns of tourist attractions and activities in New Zealand. Tour Manag 23(4):343–354

    Google Scholar 

  • Bel G (2006) Un análisis de los gastos municipales por el servicio de residuos sólidos urbanos. Revista de Economía Aplicada 14:5–32

    Google Scholar 

  • Bel G, Costas A (2006) Do public sector reforms get rusty? Local privatization in Spain. J Public Reform 9(1):1–24

    Google Scholar 

  • Bel G, Fageda X (2010) Empirical analysis of solid management waste costs: some evidence from Galicia, Spain. Resour Conserv Recycl 54:187–193

    Google Scholar 

  • Bel G, Miralles A (2003) Factors influencing the privatization of urban solid waste collection in Spain. Urban Stud 40:1323–1334

    Google Scholar 

  • Benito B, Bastida F, García JA (2010) Explaining defferences in efficiency: an application to Spanish municipalities. Appl Econ 42(5):515–528

    Google Scholar 

  • Blank RM (2000) When can public policy makers rely on private markets? The effective provision of social services. Econ J 110:34–49

    Google Scholar 

  • Bloomfield P (2006) The challenging business of long-term public-private partnerships: reflections on local experience. Public Adm Rev 66:400–411

    Google Scholar 

  • Bosch N, Pedraja F, Suaréz-Pandiello J (2000) Measuring the efficiency in Spanish municipal refuse collection services. Local Govern Stud 26(3):71–90

    Google Scholar 

  • Bovea MD, Ibáñez-Forés V, Gallardo A, Colomer-Mendoza FJ (2010) Environmental assessment of alternative municipal solid waste management strategies& a Spanish case study. Waste Manag 30:2383–2395

    Google Scholar 

  • Callan SJ, Thomas JM (2001) Economies of scale and scope: a cost analysis of municipal solid waste services. Land Econ 77(4):548–560

    Google Scholar 

  • Cameron S (1989) Police cost function estimates for England and Wales. Appl Econ 21(10):1279–1289

    Google Scholar 

  • Carlson-Kanyama A, Linden AL (1999) Travel patterns and environmental effects now and in the future: implications of differences in energy consumption among socio-economic groups. Ecol Econ 30:405–417

    Google Scholar 

  • Carr-Hill R, Stern NH (1979) Crime, the police and criminal statistics. Academy Press, London

    Google Scholar 

  • Cazals C, Florens JP, Simar L (2002) Nonparametric frontier estimation: a robust approach. J Econ 106(1):1–25

    Google Scholar 

  • Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2(6):429–444

    Google Scholar 

  • Charnes A, Cooper WW, Rhodes E (1981) Evaluating program y managerial efficiency: an application of data envelopment analysis to program follow through. Manage Sci 27(6):668–697

    Google Scholar 

  • Charnes A, Cooper WW, Golany B, Seiford LM, Stutz J (1985) Foundation of data envelopment analysis for pareto-koopmans efficient empirical production functions. J Econ 30:91–107

    Google Scholar 

  • Contreras F, Ishii S, Kisuke-Hanaki TA, Connors S (2010) Drivers in current and future minicipal solid waste management systems: cases in Yokohama and Boston. Waste Manag Res 28:76–93

    Google Scholar 

  • Cook WD, Seiford LM (2009) Data envelopment analysis (DEA): thirty years on. Eur J Oper Res 192(1):1–17

    Google Scholar 

  • Cordero-Ferrera J, Pedraja-Chaparro F, Salinas-Jimenez J (2008) Measuring efficiency in education: an analysis of different approaches for incorporating non-discretionary inputs. Appl Econ 40(10–12):1323–1339

    Google Scholar 

  • Cusack TR (1997) Partisan politics and public finance: changes in public spending in the industrialized democracies, 1955–1989. Public Choice 91(3–4):375–395

    Google Scholar 

  • Daraio C, Simar L (2005) Introducing environmental variables in nonparametric frontier models: a probabilistic approach. J Prod Anal 24(1):93–121

    Google Scholar 

  • Daraio C, Simar L (2007) Conditional nonparametric frontier models for convex and nonconvex technologies: a unifying approach. J Prod Anal 28(1–2):13–32

    Google Scholar 

  • Daraio C, Simar L, Wilson PW (2010) Testing whether two-stage estimation is meaningful in non-parametric models of production IAP Stat Technical Report Series: Institut de Statistique, Universit′e Catholique de Louvain. Louvain-la-Neuve, Belgium

    Google Scholar 

  • Darrough M, Heineke JM (1979) Law enforcement agencies as multi-product firms: an econometric investigation of production cost. Public Financ 34(2):176–195

    Google Scholar 

  • De Borger B, Kerstens K (1996) Cost efficiency of Belgian local governments: a comparative analysis of FDH, DEA, and econometric approaches. Reg Sci Urban Econ 26(2):145–160

    Google Scholar 

  • De Borger B, Kerstens K, Moeseny W, Vanneste J (1994) Explaning differences in productive efficiency: an application to Belgian municipalities. Public Choice 80(3–4):339–358

    Google Scholar 

  • Debreu G (1951) The coefficient of resource utilization. Econometrica 19(3):273–292

    Google Scholar 

  • Demsetz H (1968) Why regulate utilities? J Law Econ 9:55–65

    Google Scholar 

  • Deprins D, Simar L, Tulkens H (1984) Measuring labour efficiency in post offices. In: Marchy M, Pestieau P, Tulkens H (eds) The performance of public enterprises: concepts y measurement. Elsevier, Amsterdam, pp 243–267

    Google Scholar 

  • Diaz-Meneses G, Palacio AB (2004) La jerarquía de efectos clísica de alta involucarión para la compresión de la conducta del reciclaje considerando los valores de los consumidores. Int R Public Nonpro Mark 1(1):89–109

    Google Scholar 

  • Diez-Ticio A, Mancebón MJ (2003) Análisis de la eficiencia de las instituciones encargadas de la seguridad ciudadana. Papeles de Economía Española 95:306–319

    Google Scholar 

  • Dijlgraaf E, Gradus RHJM (2007) Collusion in Dutch waste collection market. Local Govern Stud 33(4):573–588

    Google Scholar 

  • Doan LP (1998) Institutionalizing hosehold waste collection: the urban environmental management project in Cote d’ivoire. Habitat Inter 22(1):27–39

    Google Scholar 

  • Domberger S, Jensen P (1997) Contracting out by public sector: theory, envidence, prospects. Oxford. Rev Econ Pol 13(4):67–78

    Google Scholar 

  • Domberger S, Meadowcroft SA, Thompson DJ (1986) Competitive tendering and efficiency: the case of refuse collection. Fiscal Stud 7(4):69–87

    Google Scholar 

  • Drake L, Simper R (2003) The measurement of English and Welsh police force efficiency: a comparison of distance function models. Eur J Oper Res 147(1):165–186

    Google Scholar 

  • Dubin JA, Navarro P (1988) How markets for impure public goods organize: the case of household refuse collection. J Law Econ Organ 4(2):217–241

    Google Scholar 

  • Duffi A (2001) A trip too far. Ecotourism, politics and exploitation. Earthscan, London

    Google Scholar 

  • Efron B (1979) Bootstrap methods: another look at the jackknife. Annals Stat 7(1):1–26

    Google Scholar 

  • Emrouznejad A, Parker BR, Tavares G (2008) Evaluation of research in efficiency y productivity: a survey y analysis of the first 30 years of scholarly literature in DEA. Socio Econ Plann Sci 42(3):151–157

    Google Scholar 

  • Färe R, Grosskopfy S, Lovell C (1985) The measurement of efficiency of production. Kluwer Academic Publishers, Boston

    Google Scholar 

  • Farrell MJ (1957) The meaurement of productive efficiency. J R Stat Soc Series A 120(3):253–281

    Google Scholar 

  • Gamze-Turan N, Çoruh S, Akdemir A, Nuri Erguí O (2009) Municipal solid waste management strategies in Turkey. Waste Manag 29(1):465–469

    Google Scholar 

  • Giménez VM, Prior D (2003) Evaluación frontera de la eficiencia de costes. Aplicación a los municipios de Cataluña. Papeles de Economía Española 95:113–124

    Google Scholar 

  • Giménez VM, Prior D (2007) Long- and short-term cost efficiency frontier evaluation: evidence from Spanish local governments. Fiscal Stud 28(1):121–139

    Google Scholar 

  • Gyimah-Brempong K (1987) Elasticity for factor subsitution in police agencies. J Bus Econ Stat 5(2):257–265

    Google Scholar 

  • Gyimah-Brempong K (1989) Production of public safety: are socioeconomic characteristics of local communities important factors? Appl Econ 4(1):57–71

    Google Scholar 

  • Hagen TP, Vabo SL (2005) Political characteristics, institutional procedures and fiscal performance: panel data analyses of Norwegian local government 1991–1998. Eur J Politic Res 44:43–64

    Google Scholar 

  • Hoff A (2007) Second stage dea: comparison of approaches for modelling the dea score. Eur J Oper Res 181(1):425–435

    Google Scholar 

  • Jeong S-O, Park B, Simar L (2010) Nonparametric conditional efficiency measures: asymptotic properties. Annals Oper Res 173(1):105–122

    Google Scholar 

  • Karlaftis MG (2004) A DEA approach for evaluating the efficiency and effectiveness of urban transit systems. Eur J Oper Res 152(2):354–364

    Google Scholar 

  • Kneip A, Park BU, Simar L (1998) A note on the convergence of nonparametric DEA estimators for production efficiency scores. Econ Theory 14(6):783–793

    Google Scholar 

  • Kneip A, Simar L, Wilson PW (2008) Asymptotics and consistent bootstraps for dea estimators in nonparametric frontier models. Econo Theory 24(6):1663–1697

    Google Scholar 

  • Kuniyal JC, Jain AP, Shannigrahi AS (2003) Solid waste management in and around the Valley of Flowers and Hemkund Sahib. Waste Manag 23(9):807–816

    Google Scholar 

  • Lang JC (2005) Zero landfill zero waste: the greening of industry in Singapore. Int J Enviorn Sustain Dev 4:331–351

    Google Scholar 

  • Latruffe L, Davidova S, Balcombe K (2008) Application of a double bootstrap to investigation of determinants of technical efficiency of farms in central Europe. J Prod Anal 29(2):183–191

    Google Scholar 

  • Lieb CM (2004) The environmental Duznests curve and flow versus stock pollution: the neglect of future damges. Environ Resour Econ 29(4):483–506

    Google Scholar 

  • Magrinho A, Didelet F, Semiao V (2006) Municipal solid waste disposal in Portugal. Waste Manage 26(12):1477–1489

    Google Scholar 

  • Mathieson D, Passell P (1976) Homicide and robbery in New York City: an economic model. J Legal Stud 5(1):83–98

    Google Scholar 

  • Mazzanti M, Zoboli R (2009) Municipal Waste Kuznets curves: evidence on socio-economics drivers and policy effectiveness from EU. Environ Res Econ 44:203–230

    Google Scholar 

  • Mcdonald J (2009) Using least squares and tobit in second stage dea efficiency analyses. Euro J Oper Res 197(2):792–798

    Google Scholar 

  • Mugagga F (2006) The public private sector approach to municipal solid waste management: How does it work in Makindye division, Kampala district Uganda? Master of Philosophy in Development Studies thesis. Trondheim, Norway

  • Muñiz MA (2002) Separating managerial inefficiency y external conditions in data envelopment analysis. Eur J Oper Res 143(3):625–643

    Google Scholar 

  • Navarro A (1998) El control económico de la gestión municipal. Un modelo basado en indicadores. Sindicatura de Comptes, Valencia

    Google Scholar 

  • Neto F (2003) A new approach to sustainable tourism development: moving beyond environmental protection. Nat Resour Forum 27:212–222

    Google Scholar 

  • Nolan JF, Ritchie PC, Rowcrofts JR (2002) Identifying and measuring public policy goals: ISTEA and the US bus transit industry. J Econ Behav Organ 48(3):291–304

    Google Scholar 

  • Nyhan RC, Martin LL (1999) Assessing the performance of municipal police services using data envelopment analysis: an exploratory study. State Local Gov Rev 31(1):18–30

    Google Scholar 

  • Ohlsson H (2003) Ownership and production costs. Choosing between public production and contracting-out in the case of Swedish refuse collection. Fisc Stud 24(4):451–476

    Google Scholar 

  • Ortiz D (2003) Los indicadores como instrumentos para la evaluación de gestión pública. Una investigación empírica en el ámbito municipal. Tesis Doctoral, Universidad de Granada

  • Ozawa T (2005) Hotelling rule and the landfill exhaustion problem: case of Tokio city. Stud Reg Sci 35:215–230

    Google Scholar 

  • Park BU, Simar L, Weiner C (2000) The FDH estimator for productivity efficiency scores: asymptotic properties. Econ Theory 16(6):855–877

    Google Scholar 

  • Park BU, Simar L, Zelenyuk V (2008) Local likelihood estimation of truncated regression and its partial derivatives: theory and application. J Econ 146(1):185–198

    Google Scholar 

  • Patterson T, Niccolucci V, Marchettini N (2008) Adaptive environmental management of tourism in the Province of Siena, Italy using the ecological footprint. J Environ Manag 86(2):407–418

    Google Scholar 

  • Pina V, Torres L (2001) Analysis of the efficiency of local government services delivering. An application to public urban transport. Transp Res A 35:929–944

    Google Scholar 

  • Pommerehne W (1978) Institutional approaches to public expenditures: empirical evidence from swiss municipalities. J Public Econ 7:255–280

    Google Scholar 

  • Prado JM, García I (2007) Efficiency evaluation in municipal services: an application to the street lighting service in Spain. J Prod Anal 27(3):149–162

    Google Scholar 

  • Prior D, Balaguer MT, Vela JM (2002) Efficiency and quality in local government. The case of Spanish local authorities. Documents de Treball, Universitat Atónoma de Barcelona

  • Ramalho E, Ramalho J, Henriques P (2010) Fractional regression models for second stage dea efficiency analyses. J Prod Anal 34:239–255

    Google Scholar 

  • Reeves E, Barrow M (2000) The impact of contracting-out on the costs of refuse collection services: the case of Ireland. Econ Soc Rev 31(2):129–150

    Google Scholar 

  • Seiford LM (1996) Data envelopment analysis: the evolution of the state of the art (1978–1995). J Prod Anal 7:99–137

    Google Scholar 

  • Shephard RW (1953) Cost and production functions. Princeton University Press, Princeton

    Google Scholar 

  • Shephard RW (1970) Theory of cost and production functions. Princeton University Press, Princeton

    Google Scholar 

  • Silkman R, Young DR (1982) X-Efficiency and state formula grants. Natl Tax J 35(3):383–397

    Google Scholar 

  • Simar L (2003) Detecting outliers in frontier models: a simple approach. J Prod Anal 20(3):391–424

    Google Scholar 

  • Simar L, Wilson PW (1998) Sensivity analysis of efficiency scores: how to bootstrap in nonparametric frontier models. Manage Sci 44(4):49–61

    Google Scholar 

  • Simar L, Wilson PW (1999) Of course we can bootstrap dea scores! But does it mean anything? Logic trumps wishful thinking. J Prod Anal 11(1):93–97

    Google Scholar 

  • Simar L, Wilson PW (2000) A general methodology for bootstrapping in non-parametric frontier models. J Appl Stat 27(6):779–802

    Google Scholar 

  • Simar L, Wilson PW (2002) Non-parametric tests of returns to scale. Eur J Oper Res 139(1):115–132

    Google Scholar 

  • Simar L, Wilson PW (2004) Performance of the bootstrap for dea estimators and iterating the principle. Handbook of data envelopment analysis pp 265–298

  • Simar L, Wilson PW (2007) Estimation y inference in two-stage, semi-parametric models of production processes. J Econ 136(1):31–64

    Google Scholar 

  • Simar L, Wilson PW (2011a) Inference by the m out of n bootstrap in nonparametric frontier models. J Prod Anal 36(1):33–53

    Google Scholar 

  • Simar L, Wilson PW (2011b) Two-stage dea: caveat emptor. J Prod Anal 36(2):205–218

    Google Scholar 

  • Simar L, Zelenyuk V (2011) Stochastic fdh/dea estimators for frontier analysis. J Prod Anal 36(1):1–20

    Google Scholar 

  • Sjöström M, Östblom G (2010) Decouplin waste generation form economic growth: a CGE analyisi of Swedish case. Ecol Econom 69:1545–1552

    Google Scholar 

  • Spann R (1977) Public versus private provision of governmental services. In: Borcherding T (ed) Budgets and bureaucrats: the sources of government growth. Duke University Press, Durham, pp 71–89

    Google Scholar 

  • Stevens BJ (1978) Scale, market structure, and the cost of refuse collection. Rev Econ Stat 60(3):438–448

    Google Scholar 

  • Taïrou A (2000) Does inefficiency explain financial vulnerability of French municipalities? Paper presented to international conference on accounting, auditing and management in public sector reforms. EIASM, Zaragoza

  • Tavares G (2002) A bibliography of data envelopment analysis (1978–2001). Rutcor research report. Piscataway, New Jersey

  • Thanassoulis E (2000) The use of data envelopment analysis in the regulation of water utilities: water distribution. Eur J Oper Res 126(2):436–453

    Google Scholar 

  • Thanassoulis E (2002) Comparative performance measurement in regulation: the case of English and Welsh sewerage services. J Oper Res Soc 53(3):292–302

    Google Scholar 

  • Torgersen AM, Førsund FR, Kittelsen SAC (1996) Slack-adjusted efficiency measures and ranking of efficient units. J Prod Anals 7(4):379–398

    Google Scholar 

  • Tupper HC, Resende M (2004) Efficiency and regulatory issues in the Brazilian water and sewage sector: an empirical study. Utility Policy 12(1):29–40

    Google Scholar 

  • Viton PA (1998) Changes in multi-mode bus transit efficiency, 1988–1992. Transportation 25(1):1–21

    Google Scholar 

  • Wheelock DC, Wilson PW (2008) Non-parametric, unconditional quantile estimation for efficiency analysis with an application to Federal Reserve check processing operations. J Econ 145(1–2):209–225

    Google Scholar 

  • Wilson PW (1993) Detecting outliers in deterministic nonparametric frontier models with multiple outputs. J Bus Econ Stat 11(3):319–323

    Google Scholar 

  • Wilson PW (1995) Detecting influential observations in data envelopment analysis. J Prod Anal 6(1):27–45

    Google Scholar 

  • Wilson PW (2003) Testing independence in models of productive efficiency. J Prod Anal 20:361–390

    Google Scholar 

  • Wilson PW (2008) Fear: a software package for frontier efficiency analysis with r. Socioecon Plann Sci 42(4):247–254

    Google Scholar 

  • Worthington AC (2000) Cost efficiency in Australian local government: a comparative analysis of mathematical programming and econometric approaches. Finan Account Manage 16(3):201–227

    Google Scholar 

  • Worthington AC, Dollery BE (2001) Measuring efficiency in local government: an analysis of New South Wales Municipalities domestic waste management function. Policy Stud J 29(2):4–24

    Google Scholar 

  • Yang HL, Innes R (2007) Economic incentives and residential waste management in Taiwan: an empirical investigation. Environ Resour Econ 37:489–519

    Google Scholar 

  • Zamorano M, Molero E, Grindlay A, Rodríguez ML, Hurtado A, Calvo FJ (2009) A planning scenario for the application of gographical information systems in municipal waste collection: a case of Churriana de la Vega (Granada, Spain). Resour Conserv Recycl 54:123–133

    Google Scholar 

  • Zelenyuk V, Zheka V (2006) Corporate governance and firm’s efficiency: the case of a transitional country, Ukraine. J Prod Anal 25(1–2):143–157

    Google Scholar 

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Authors and Affiliations

  1. Department of Accounting and Finance, Faculty of Economics and Business, University of Murcia, Campus of Espinardo, 30100, Murcia, Spain

    Bernardino Benito & María-Rocío Moreno

  2. Department of Integration, Defense University Center, San Javier Air Base, 30720, San Javier, Spain

    José Solana

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  1. Bernardino Benito
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Benito, B., Solana, J. & Moreno, MR. Explaining efficiency in municipal services providers. J Prod Anal 42, 225–239 (2014). https://doi.org/10.1007/s11123-013-0358-7

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  • DOI: https://doi.org/10.1007/s11123-013-0358-7

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