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The effect of tourism on crime in Italy: A dynamic panel approach

Author

Listed:
  • Biagi, Bianca
  • Brandono, Maria Giovanna
  • Detotto, Claudio

Abstract

The purpose of this paper is to demonstrate that, for the case of Italy, ceteris paribus, tourist areas tend to have a greater amount of crime than non-tourist ones in the short and long run. Following the literature of the economics of crime à la Becker (Crime and Punishment: An Economic Approach, 1968) and Enrlich (Participation in Illegitimate Activities: A Theoretical and Empirical Investigation, 1973) and using a System GMM approach for the time span 19852003, the authors empirically test whether total crime in Italy is affected by the presence of tourists. Findings confirm the initial intuition of a positive relationship between tourism and crime in destinations. When using the level rather than the rate of total crime and controlling for the equivalent tourists (i.e. the number of tourists per day in a given destination) the effect of the tourist variable is confirmed. Overall results indicate however that the resident population has a greater effect on crime than the tourist population. Therefore, the main explanation for the impact of tourism on crime seems to be agglomeration effects.

Suggested Citation

  • Biagi, Bianca & Brandono, Maria Giovanna & Detotto, Claudio, 2012. "The effect of tourism on crime in Italy: A dynamic panel approach," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 6, pages 1-24.
  • Handle: RePEc:zbw:ifweej:201225
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    File URL: http://dx.doi.org/10.5018/economics-ejournal.ja.2012-25
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Mantobaye Moundigbaye & William Rea & W. Robert Reed, 2016. "More Evidence On “Which Panel Data Estimator Should I Use?”," Working Papers in Economics 16/18, University of Canterbury, Department of Economics and Finance.
    2. Moundigbaye, Mantobaye & Rea, William S. & Reed, W. Robert, 2018. "Which panel data estimator should I use? A corrigendum and extension," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 12, pages 1-31.
    3. Mantobaye Moundigbaye & Clarisse Messemer & Richard W. Parks & W. Robert Reed, 2016. "Bootstrap Methods for Inference in the Parks Model," Working Papers in Economics 16/22, University of Canterbury, Department of Economics and Finance.
    4. repec:eee:touman:v:54:y:2016:i:c:p:383-392 is not listed on IDEAS
    5. Brida, Juan Gabriel & Del Chiappa, Giacomo & Meleddu, Marta & Pulina, Manuela, 2012. "Cruise tourism exteralities and residents' support: A mixed approach," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 6, pages 1-26.
    6. Daniel Montolio & Simón Planells, 2013. "Does tourism boost criminal activity? Evidence from a top touristic country," Working Papers 2013/4, Institut d'Economia de Barcelona (IEB).
    7. repec:jtr:journl:v:11:y:2015:i:1:p:61-70 is not listed on IDEAS
    8. B. Biagi & MG. Brandano & D. Lambiri, 2012. "Does tourism affect house prices? Some evidence from Italy," Working Paper CRENoS 201227, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    9. repec:jtr:journl:v:8:y:2014:i:1:p:97-111 is not listed on IDEAS

    More about this item

    Keywords

    tourism; crime; externalities;

    JEL classification:

    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • K00 - Law and Economics - - General - - - General (including Data Sources and Description)
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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