Marginal cost of road maintenance and operation: Swedish estimates based on data from 2004 to 2014

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In this study, we estimated the marginal costs of road operation and maintenance by using the cost function approach with Swedish road network data from 2004 to 2014. The results of this study suggest a marginal cost of 0.07 SEK per vehicle kilometre for maintenance and operation of gravel roads, but none for paved roads. The data consist of traffic volume, costs, and road attributes for the Swedish national road network. The observational unit is the road maintenance delivery unit (MDU), and there were 109 such MDUs in Sweden in 2014. We estimated models separately for paved road operation and maintenance, gravel road operation and maintenance, and winter road operations. In paved road maintenance, reinvestment is excluded.

The data are given in panel format and the models are estimated with random effects. A logarithmic functional form has been used, and this means that the estimated parameter can be interpreted as an elasticity. This elasticity together with the average cost yields the marginal cost. The results of this study suggest a marginal cost of 0.07 SEK per vehicle kilometre for maintenance and operation of gravel roads. The estimated marginal cost for winter road operation is less than 0.01 SEK per vehicle kilometre, and this marginal cost estimate is statistically significant. We do not find a statistically significant marginal cost for maintenance and operation of paved roads.

Our estimates of marginal costs for road maintenance and operation are generally lower compared to previous Swedish estimates. An important reason for this is that the definition of an MDU has changed over time, but we used the current classification for each year of data in this report. The lack of a significant marginal cost for paved roads is most likely explained by the fact that reinvestment costs were not included in our analysis. We have tested other model specifications to check the robustness of our results. The estimates are robust with respect to different time periods, the choice of measure of traffic volume, and new explanatory variables, except in the case of the gravel roads.

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