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Regulatory and Environmental Effects on Public Transit Efficiency. A Mixed DEA-SFA Approach

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Author Info
Buzzo Margari Beniamina () (HERMES, Center for Research on Regulated Services,Fondazione Collegio Carlo Alberto, Moncalieri (TO), Italy)
Erbetta Fabrizio () (University of Eastern Piedmont “Amedeo Avogadro”, Faculty of Economics, Novara, Italy; Ceris-Cnr and HERMES, Moncalieri, (TO), Italy;)
Petraglia Carmelo () (University of Naples “Federico II”, Department of Economic Theory and Applications, Napoli, Italy;)
Piacenza Massimiliano () (Ceris-Cnr and HERMES, Moncalieri, (TO), Italy)

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Abstract

The aim of this paper is to account for the impact of statistical noise and exogenous regulatory and environmental factors on the efficiency of public transit systems in a DEA-based framework. To this end, we implement a three-stage DEA-SFA mixed approach based on Fried et al. (2002) using a 1993-1999 panel of 42 Italian public transit companies. This allows us to decompose input-specific DEA inefficiency measures into three components: exogenous effects, pure managerial inefficiency, and statistical noise. First, the initial evaluation of producer performance is carried out using conventional variable returns to scale DEA (Banker et al., 1984). Second, a SFA approach (Battese and Coelli, 1992) is used to regress single input slacks on subsidies regulation (cost-plus versus fixed-price contracts) and a set of environmental variables including network speed and user density. Finally, third stage re-runs DEA on inputs purged of both exogenous effects and statistical noise. Results are such that adjusting for the type of regulatory scheme, environmental conditions, and statistical noise increases average efficiency in the industry and reduces dispersion among firms. Furthermore, the implementation of fixed-price subsidies is found to enhance efficiency in the usage of “drivers” and “materials and services” inputs. Such a result sheds some light on the determinants of input-specific efficiency differentials in the industry, improving the existing evidence on mean overall cost efficiency (e.g. Gagnepain e Ivaldi, 2002; Piacenza, 2006). As a policy implication, it is confirmed the relevance of regula tion aimed at replacing cost-plus subsidization mechanisms with high-powered incentive contracts as well as improving operating conditions of public transport networks.

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Publisher Info
Paper provided by Institute for Economic Research on Firms and Growth - Moncalieri (TO) in its series CERIS Working Paper with number 200613.

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Length: 25 pages
Date of creation: Dec 2006
Date of revision:
Handle: RePEc:csc:cerisp:200613

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Related research
Keywords: Public transit systems; Regulation; Environmental effects; Statistical noise; Data Envelopment Analysis (DEA); Stochastic Frontier Analysis (SFA);

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Find related papers by JEL classification:
C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Statistical Decision Theory; Operations Research
D21 - Microeconomics - - Production and Organizations - - - Firm Behavior
L50 - Industrial Organization - - Regulation and Industrial Policy - - - General
L92 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Railroads and Other Surface Transportation
R41 - Urban, Rural, and Regional Economics - - Transportation Systems - - - Transportation: Demand, Supply, and Congestion

References listed on IDEAS
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  1. Kerstens, K., 1996. "Technical efficiency measurement and explanation of French urban transit companies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 30(6), pages 431-452, November. [Downloadable!] (restricted)
  2. De Borger B. & Kerstens K. & Costa A., 2000. "Public transport performance: what do we learn from frontier studies?," Working Papers 2000019, University of Antwerp, Faculty of Applied Economics. [Downloadable!]
  3. Giovanni Fraquelli & Massimiliano Piacenza & Graziano Abrate, 2004. "Regulating Public Transit Networks: How do Urban-Intercity Diversification and Speed-up Measures Affect Firms' Cost Performance?," Annals of Public and Cooperative Economics, Blackwell Publishing, vol. 75(2), pages 193-225, 06. [Downloadable!] (restricted)
  4. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-32.
  5. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July. [Downloadable!] (restricted)
  6. Gagnepain, P. & Ivaldi, M., 1998. "Stochastic Frontiers and Asymmetric Information Models," Papers 98.503, Toulouse - GREMAQ.
  7. Philippe Gagnepain & Marc Ivaldi, 2002. "Incentive Regulatory Policies: The Case of Public Transit Systems in France," RAND Journal of Economics, The RAND Corporation, vol. 33(4), pages 605-629, Winter.
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  8. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November. [Downloadable!] (restricted)
  9. C. Cambini & M. Filippini, 2003. "Competitive Tendering and Optimal Size in the Regional Bus Transportation Industry: An Example from Italy," Annals of Public and Cooperative Economics, Blackwell Publishing, vol. 74(1), pages 163-182, 03. [Downloadable!] (restricted)
  10. Massimiliano Piacenza, 2006. "Regulatory Contracts and Cost Efficiency: Stochastic Frontier Evidence from the Italian Local Public Transport," Journal of Productivity Analysis, Springer, vol. 25(3), pages 257-277, 06. [Downloadable!] (restricted)
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  1. GAUTIER, Axel & YVRANDE-BILLON, Anne, 2008. "Contract renewal as an incentive device. An application to the French urban public transport sector," CORE Discussion Papers 2008068, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
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