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This study presents an innovative methodology for estimating the distance travelled by vehicles, both on national and foreign territories, based on data derived from roadworthiness tests. By integrating data from the Ministry of Infrastructure and Transport’s (MIT) vehicle inspection archives and the Public Vehicle Register (PRA), this research addresses the methodological challenges associated with estimating vehicle kilometres (VKM) travelled by the active fleet of vehicles registered in Italy. The methodology is grounded in the concept of “average daily distance”, with estimations varying according to the frequency of inspections. A key aspect of this study is the transformation of administrative data into reliable statistical indicators, dealing with issues such as missing or inconsistent odometer readings and outlier values. Missing values are imputed using a non-parametric HotDeck method. The results will provide valuable insights for analyzing road congestion, energy consumption, and the environmental impact of Italy’s vehicle fleet, contributing to evidence-based policy-making in transport and environmental studies.

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An Innovative Methodological Contribution to Transport Statistics: Transforming Administrative Data into Statistical Measure of Vehicle Travel Distance

  • 会议论文

  • 发表日期：

    2025年

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  • Andrea Amico,
  • Marica D’Elia,
  • Chiara Riccobono

摘要

This study presents an innovative methodology for estimating the distance travelled by vehicles, both on national and foreign territories, based on data derived from roadworthiness tests. By integrating data from the Ministry of Infrastructure and Transport’s (MIT) vehicle inspection archives and the Public Vehicle Register (PRA), this research addresses the methodological challenges associated with estimating vehicle kilometres (VKM) travelled by the active fleet of vehicles registered in Italy. The methodology is grounded in the concept of “average daily distance”, with estimations varying according to the frequency of inspections. A key aspect of this study is the transformation of administrative data into reliable statistical indicators, dealing with issues such as missing or inconsistent odometer readings and outlier values. Missing values are imputed using a non-parametric HotDeck method. The results will provide valuable insights for analyzing road congestion, energy consumption, and the environmental impact of Italy’s vehicle fleet, contributing to evidence-based policy-making in transport and environmental studies.