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Warning, Learning and Compliance: Evidence from Micro-data on Driving Behavior

Author

Listed:
  • Marcello Basili
  • Filippo Belloc
  • Simona Benedettini
  • Antonio Nicita

Abstract

In many contexts, warning systems of law enforcement are used to let uninformed individuals learn what is illegal, while sanctions are applied only after a number of repeated violations. Surprisingly no em- pirical evidence is available so far, over the learning impact of warnings. This paper is a first attempt to empirically investigate the warning’s effect on individuals’ behavior employing a unique database on a traffic law enforcement system, which constitutes an extraordinary nat- ural laboratory to test whether experience warning induces learning. Specifically, we use six-year longitudinal data on about 50000 drivers under the Italian point-record system of traffic law. Our statistical re- sults show that warned drivers become more compliant. To the extent individuals learn through their repeated behavior, a warning system makes it possible to apply sanctions only to (presumably) informed violators.

Suggested Citation

  • Marcello Basili & Filippo Belloc & Simona Benedettini & Antonio Nicita, 2012. "Warning, Learning and Compliance: Evidence from Micro-data on Driving Behavior," Department of Economics University of Siena 639, Department of Economics, University of Siena.
    • Handle: RePEc:usi:wpaper:639
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    File URL: http://repec.deps.unisi.it/quaderni/639.pdf
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    References listed on IDEAS

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    Cited by:

    1. Josef Montag, 2013. "A radical change in traffic law: effects on fatalities in the Czech Republic," MENDELU Working Papers in Business and Economics 2013-39, Mendel University in Brno, Faculty of Business and Economics.

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    More about this item

    Keywords

    warning; law enforcement; mixture models;
    All these keywords.

    JEL classification:

    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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