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Difference-in-Difference models to estimate causal effects on auto insurers behavior

Author

Listed:
  • Catalina Bolancé

    (Department of Econometrics Riskcenter-IREA, Universitat de Barcelona, Spain.)

  • Montserrat Guillen

    (Department of Econometrics Riskcenter-IREA, Universitat de Barcelona, Spain.)

  • Ana M. Pérez-Marín

    (Department of Econometrics Riskcenter-IREA, Universitat de Barcelona, Spain.)

  • Anna-Patrícia Orteu

    (Department of Econometrics Riskcenter-IREA, Universitat de Barcelona, Spain.)

Abstract

The Difference-in-Difference (DiD) method is useful to test if an event has effects in a given outcome using non-experimental data. Based on DiD method, we propose alternative panel models to estimate the causal effects of the traffic accidents on driving behavior patterns: the total annual driving distance in km, the percent of km circulated above the speed limits, in urban areas and at night. We use a data set provided by an ”insurtech” company that uses car sensors to measure driving data over a period of three years. The estimation results show as the causal effects of accidents are different if we consider frequency of accidents, type of damages and whose fault is the accident. Furthermore, different profiles of policyholders in function of drivers and cars characteristics are associated with specific causal effects.

Suggested Citation

  • Catalina Bolancé & Montserrat Guillen & Ana M. Pérez-Marín & Anna-Patrícia Orteu, 2024. "Difference-in-Difference models to estimate causal effects on auto insurers behavior," IREA Working Papers 202411, University of Barcelona, Research Institute of Applied Economics, revised Feb 2024.
    • Handle: RePEc:ira:wpaper:202411
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    File URL: http://www.ub.edu/irea/working_papers/2024/202411.pdf
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    More about this item

    Keywords

    Telematics; average treatment effect; panel data; damages; fault; drivers heterogeneity. JEL classification: C21; C55; G22.;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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