This paper updates knowledge about the marginal cost of railway maintenance. Using a panel dataset comprising 16 years, we test whether more data makes a difference to conclusions. In contrast to previous estimates using a shorter panel, maintenance costs are now demonstrated to exhibit a positive dynamic effect; an increase in maintenance cost during one year indicates the need for more maintenance also the next year. Moreover, the marginal cost from the dynamic model is larger than its static counterpart. We conclude that the use of dynamic models on longer time series may have charging implications in several EU member states, considering that their track access charges are based on econometric studies that use static models and short panel datasets.
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Odolinski et al. (2017) studied this question.
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