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Exploratory analysis of crash determinants

Author

Listed:
  • Metz-Peeters, Maike
  • Patragst, Jil-Laurel

Abstract

This study presents an exploratory analysis of the key factors contributing to fatal and severe crashes on German motorways. We employ Poisson and Negative Binomial regression models, combined with Lasso regularization and stability selection, to explore model specifications incorporating potentially many interaction terms and polynomials. Utilizing an extensive data set including rich geo-spatial characteristics for 500-meter segments covering large parts of the German motorway network, key variables influencing crash frequency are uncovered. To obtain correct standard errors post variable selection, we split the data into separate samples for model selection and parameter estimation. Our results indicate that the inclusion of a limited number of higher-order terms significantly improves the regression formulation. Robustness checks confirm the stability of these findings. The results offer clearer insights into the key crash determinants and are more computationally feasible than simulation-based methods commonly used in accident research.

Suggested Citation

  • Metz-Peeters, Maike & Patragst, Jil-Laurel, 2025. "Exploratory analysis of crash determinants," Ruhr Economic Papers 1157, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    • Handle: RePEc:zbw:rwirep:319076
    DOI: 10.4419/96973341
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    References listed on IDEAS

    as
    1. Metz-Peeters, Maike, 2023. "The Effects of Mandatory Speed Limits on Crash Frequency - A Causal Machine Learning Approach," Ruhr Economic Papers 982, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen, revised 2023.
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      More about this item

      Keywords

      Road safety; crash frequency; lasso regression; machine learning; stability selection;
      All these keywords.

      JEL classification:

      • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
      • H10 - Public Economics - - Structure and Scope of Government - - - General
      • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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