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Railway (De-)Regulation – A European Comparison

Railway (De-)Regulation – A European Comparison. Guido Friebel, Marc Ivaldi, Catherine Vibes November 2003 Railroad Conference, Toulouse. Subject of the study. Intensive reform discussion: how to increase European railroad efficiency? Three types of reforms (Directive 91/440):

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Railway (De-)Regulation – A European Comparison

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  1. Railway (De-)Regulation – A European Comparison Guido Friebel, Marc Ivaldi, Catherine Vibes November 2003 Railroad Conference, Toulouse

  2. Subject of the study • Intensive reform discussion: how to increase European railroad efficiency? • Three types of reforms (Directive 91/440): • Separation infrastructure/operations • Independent regulatory body • Third-party access • Large variation across time and countries in adopting these reforms • Main question: What does the experience in EU countries teach us about the effect of reforms on railway efficiency?

  3. Approach • Production function • Measure of efficiency: closeness of a given railway firm to “production frontier”? • Efficiency = residual that is not explained by: • Technological elements • Reforms in the law book • For instance: • quality of management, • implementation of reforms... • Our specific interest: what is the impact of reforms on productivity trends? • Approach allows to look at • Effects of reforms • Efficiency of railways: over time and across countries

  4. Main results • Reforms increase output • More reforms are not necessarily better than less reforms • It depends on sequencing: • packages of reforms are neutral or even bad • sequential reforms improve efficiency • More favorable efficiency development for smaller countries than for larger countries, • except for Sweden and Germany.

  5. Data • Worldbank: information about physical inputs and outputs • Inputs: route kilometers, staff • Outputs: total kilometers (freight and passenger), passenger kilometers • Reforms: date of adoption of three reforms: • Separation • Regulatory institution • Third-party access

  6. Data strengths and weaknesses Strengths: • Physical data: most comprehensive data set available • Institutional data: variation over time and across countries Weaknesses: • Lacking data of UK during reform period: clearer (better) results without UK • Institutional data: • Problem of compatibility across countries • Very different types of reform implementation

  7. Deregulation events, three main aspects

  8. The model • Cobb-Douglas production function • After log-linearization • Country fixed effects and time trend • y=output, K=Capital, L=Labor • OLS Estimation, robustness check: LISREL

  9. Result 1: Reforms increase productivity

  10. Distinguishing reforms • Result 1 does not take into account: • Intensity of reforms • Type of reform • Regression on quantity of reforms only: more than one reform does not improve efficiency  • Distinguish sequencing of reforms: • Partial • Sequential • Package

  11. Result 2: Sequencing matters

  12. Efficiency measure Global efficiency: Passenger traffic efficiency:

  13. Efficiency development over time, total traffic, larger countries

  14. Efficiency development over time, total traffic, smaller countries

  15. Efficiency development over time, passenger traffic, larger countries

  16. Efficiency development over time, passenger traffic, smaller countries

  17. Relative efficiency among larger countries, five-year periods, total traffic

  18. Relative efficiency, larger countries, five-year periods, passenger traffic

  19. Summary and implications • First detailed test of effect of reforms on railroad efficiency • Reforms help increase efficiency • More reforms are not necessarily better: sequencing seems to matter • Additional result: Institutional/full separation of infrastructure do not score better than organizational reforms (when including UK) • Much need to dig deeper into differences in implementation

  20. Backup slides

  21. Advantage of the method: it allows to solve the potential problem of correlations between input quantities and individual effects. The theoretical model: η= latent variables z=observed variables Estimation of the model entails choosing values for the parameters so that the predicted covariance matrix fits the empirical one. The mean-and-covariance structure analysis: the LISREL model

  22. Efficiency comparison, total traffic

  23. Efficiency comparison, total traffic

  24. Intensity of reforms

  25. Separation of infrastructure from operations

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