Methodology Conclusions References (selected) Bhattacharyya, A., Kumbhakar, S., Bhattacharyya, A., Ownership structure and cost efficiency: A study of publicly owned passenger-bus transportation companies in India. Journal of Productivity Analysis 6 (1), 47–61. Destatis, Preise und Preisindizes für gewerbliche Produkte (Erzeugerpreise) – Juni Statistisches Bundesamt Fachserie 17 Reihe 2. Wiesbaden. Deutsche Bundesbank, Monatsbericht August On the Internet: retrieved 27 April Farsi, M., Filippini, M., Greene, W., Efficiency measurement in network industries: Application to the Swiss railway companies. Journal of Regulatory Economics 28 (1), 69–90. Farsi, M., Filippini, M., An analysis of cost efficiency in Swiss multi-utilities. Energy Economics 31 (2), 306–315. Greene, W., Limdep Version 9.0 Reference Guide. Econometric Software, Plainview. Greene, W. H., Reconsidering heterogeneity in panel data estimators of the Stochastic Frontier model. Journal of Econometrics 126 (2), 269–303. Greene, W., Distinguishing between heterogeneity and inefficiency: Stochastic Frontier Analysis of the World Health Organization’s panel data on national health care systems. Health Economics 13 (10), 959–980. Hadri, K., Guermat, C., Whittaker, J., Estimation of technical inefficiency effects using panel data and doubly heteroscedastic stochastic production frontiers. Empirical Economics 28 (1), 203–222. Pitt, M., Lee, L., The measurement and sources of technical inefficiency in Indonesian weaving industry. Journal of Development Economics 9 (1), 43–64. Saal, D. S., Parker, D., Weyman Jones, T., Determining the contribution of technical change, efficiency change and scale change to productivity growth in the privatized English and Welsh water and sewerage industry: Journal of Productivity Analysis 28 (1-2), 127–139. Verband Deutscher Verkehrsunternehmen, VDV Statistik Köln. Motivation Results Unbalanced panel: 254 observations for 39 multi- output companies from 1997 until 2006 Physical data from VDV statistics, monetary data from annual reports Monetary data in 2006 prices inflated by the German producer-price- index (Destatis, 2008) Capital price including material costs, other operating expenses, depreciations, interests on borrowed capital and the opportunity cost of capital (equity base x interest rates for corporate bonds (Deutsche Bundesbank (2007) plus 2% risk premium) Chair of Energy Economics and Public Sector Management Outsourcing in Local Public Transport: A Hidden Efficiency Determinant? Matthias Walter 15 May 2009 Optimization of outsourcing as positive efficiency determinant should be in focus for the industry Vast differences in the vehicle utilization rate for railcars determines efficiency predictions -Improvement options can be related to enhancing speed through infrastructure measures (separate rail embankments, prioritization at traffic lights, tunnels in inner-city areas, new tracks, express trains, etc.) -Furthermore maintenance times could be reduced and procurement optimized Profit and cost efficiency -Relatively high mean efficiencies suggest that the problem is likely to be not only on the cost side, where improvements through wage reductions have happened in the past -Cost saving potential for the dataset: bn EUR based on bn EUR total costs (in 2006 prices) - The revenue side should bear further optimization potential and should be analyzed in the future Data Descriptive Statistics Data Correlations Regression Results Descriptive Efficiencies Efficiency Rank Correlations Historically Organized Market Characterized by the Substantial Need for Transfers High fragmentation of the market: several 100 operators Integrated operators of bus and tram or light railway or metro in medium-sized and larger cities Very low level of cost coverage with mean of 73.8% (Verband Deutscher Verkehrsunternehmen, 2008) Mostly municipal ownership with high degree of political intervention (Public service obligation, decision over new lines, …) High fragmentation of the market: several 100 operators Integrated operators of bus and tram or light railway or metro in medium-sized and larger cities Very low level of cost coverage with mean of 73.8% (Verband Deutscher Verkehrsunternehmen, 2008) Mostly municipal ownership with high degree of political intervention (Public service obligation, decision over new lines, …) Several Measures to Increase Efficiency Several Measures to Increase Efficiency Facts ID = (population in the supplied area) / (bus line and length rail-bound track length) not dependent on congestion Outsourcing (part of material costs) moves personnel costs to 3rd parties Translog Cost Function Heteroscedastic Stochastic Cost Frontier Models Function Design Local point of approximation: Mean Time dummies with neutral technical change following Farsi et al. (2005) and Farsi and Filippini (2009) No reliable results with linear time trend and time trend varying with input and output levels (Saal et al., 2007) Use of random effects model to exploit the panel data structure and because of low within variation (at most 6% based on overall variation for costs, outputs and the remaining factor price) 1) Random Effects Model (ML estimation) as suggested by Pitt and Lee (1981): Heteroscedastic inefficiency determinants (ID, UR), revealing management quality following Bhattacharyya et al. (1995), Hadri et al. (2003) and Greene (2007): 2) True Random Effects Model (Simulated ML) based on Greene, 2004 and 2005: 3) Random Parameter Model allowing for heterogeneity in the outputs Heteroscedastic inefficiency term for the Random Parameter Models as for the Random Effects Model, except for the time-variant inefficiency determinants:, Tests on Variable Specification Kernel Density of Efficiency Predictions LR-Tests on Random Effects Model - Model w UR better than model w/o OUT & UR (p = 0.014) - Model w UR better than model w OUT & UR (q = 0.009) Wald Tests on Random Parameter Models - Model w OUT & UR better than model w OUT only (p = each) - Model w OUT & UR better than model w UR only (p = 0.073, 0.067) Significant cost decreases over 10 years (up to 25%) Significant modeling results for unobserved heterogeneity and heterogeneous output characteristics Negative skewness of all curves Similar distributions for True Random Effects and Random Parameter Models Bimodal distribution in the Random Effects Model against the expectation, Farsi and Filippinis’ (2009) explanation: “cost differences that are not due to inefficiencies but to other external factors” Mergers and acquisitions, especially for companies operating on a network with connecting lines, e.g. Mannheim, Heidelberg and Ludwigshafen Tenders: so far only for bus services in Hesse and for regional bus services around Hamburg and Munich, maybe in the future also for other services Efficiency Analysis for incentive regulation for sunshine regulation (“naming and shaming”) Mergers and acquisitions, especially for companies operating on a network with connecting lines, e.g. Mannheim, Heidelberg and Ludwigshafen Tenders: so far only for bus services in Hesse and for regional bus services around Hamburg and Munich, maybe in the future also for other services Efficiency Analysis for incentive regulation for sunshine regulation (“naming and shaming”)