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  • 1.
    Forsstedt, Sara
    et al.
    Transportstyrelsen.
    Hultkrantz, Lars
    Örebro Universitet.
    Nilsson, Jan-Eric
    Swedish National Road and Transport Research Institute, Society, environment and transport, Transport economics, TEK.
    Yarmuchamedov, Sherzod
    Swedish National Road and Transport Research Institute, Society, environment and transport, Transport economics, TEK.
    Hur väl fungerar försäkringsbranschen?2015In: Ekonomisk Debatt, ISSN 0345-2646, no 6, p. 7p. 40-47Article in journal (Other (popular science, discussion, etc.))
    Abstract [sv]

    Ekonomisk teori visar hur försäkringssystem kan bidra till ökad välfärd. Men den visar också att det finns gränser för hur mycket trygghet vi kan eller bör skaffa oss genom försäkringar. Med unika mikrodata undersöker vi i denna artikel ett antal frågeställningar om försäkringsmarknadens effektivitet. Resultaten har betydelse för förståelsen av hur informationsasymmetrier hanteras av försäkringsbranschen, samt underlag för vissa policyrekommendationer när det gäller trafiksäkerhet och fordonsförsäkringar.

  • 2.
    Odolinski, Kristofer
    et al.
    Swedish National Road and Transport Research Institute, Society, environment and transport, Transport economics.
    Yarmukhamedov, Sherzod
    Riksrevisionen.
    Nilsson, Jan-Eric
    Swedish National Road and Transport Research Institute, Society, environment and transport, Transport economics.
    Haraldsson, Mattias
    Swedish National Road and Transport Research Institute, Society, environment and transport, Transport economics.
    The marginal cost of track reinvestments in the Swedish railway network: using data to compare methods2018Report (Other academic)
    Abstract [en]

    In this study, we analyze the difference between survival and corner solution models in estimating the marginal cost of reinvestments. Both approaches describe the reinvestment process in rather intuitively similar ways but have several methodological distinctions. We use Swedish railway data on track segment and section levels over the period 1999-2016 and focus on reinvestments in track superstructure. Results suggest the marginal costs from survival and corner solution models are SEK 0.0041 and SEK 0.0103, respectively. The conclusion is that the corner solution model is more appropriate, as this method consider the impact traffic has on the risk of reinvestment as well as on the size of the reinvestment cost. The survival approach does not consider the latter, which is problematic when we have systematic variations in costs due to traffic and infrastructure characteristics.

  • 3.
    Yarmuchamedov, Sherzod
    Swedish National Road and Transport Research Institute, Society, environment and transport, Transport economics.
    How risky are uninsured drivers?2018In: Journal of Transportation Safety and Security, ISSN 1943-9962, p. 1-12Article in journal (Refereed)
    Abstract [en]

    Obtaining insurance is expected to have disincentive effects on driver behavior, and as such on accident probabilities due to the adverse selection and/or moral hazard effects, though empirical studies provide mixed evidence. The risks of an accident incurred by uninsured drivers are, however, indeterminate as well, because of the unavailability of individual level data on uninsured drivers. Therefore, the purpose of this article is to empirically analyze whether insured or uninsured drivers pose greater accident risks. It uses unique individual level data on privately owned insured and uninsured passenger vehicles in Sweden for the period 2006 to 2010. The results show that the accident probability of uninsured drivers is 34 percentage points higher than for insured drivers, with uninsured drivers age 25 to 34 years posing the highest risk of an accident. This implies that uninsured drivers are a high-risk group and a significant threat to traffic safety. Possible solutions and policy implications are discussed at the end of the article.

  • 4.
    Yarmukhamedov, Sherzod
    et al.
    Swedish National Road and Transport Research Institute, Society, environment and transport, Transport economics, TEK.
    Swärdh, Jan-Erik
    Swedish National Road and Transport Research Institute, Society, environment and transport, Transport economics, TEK.
    Marginal cost of road maintenance and operation: Swedish estimates based on data from 2004 to 20142016Report (Other academic)
    Abstract [en]

    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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