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More Tourism, More Crime: Evidence from Croatia

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Abstract

For all its benefits, mainly through contributing to economic growth, tourism can cause certain negative externalities, increased crime incidence being one of them. More crime leads to immediate costs to residents, tourists and the host country, but can also imperil the destination’s image and fend off tourists in the future. We study the impact of tourism on crime in Croatia by estimating the elasticity of property crime with respect to tourist arrivals on monthly panel data at the county level over the period 1998–2016. We find robust evidence that tourism increases property crime. The elasticity varies spatially and by type of property crime, being higher in coastal than in continental counties, and higher for theft than for larceny. The estimates are used for counter-factual calculations which show that, had tourism been the only factor affecting property crime, the number of crimes would have evolved over 2006–2016 to a much higher level than it actually has. The elasticities are large enough that, absent sufficiently strong countervailing factors, even a moderately paced tourism growth can bring a sizeable increase in property crime over a decade. From the policy perspective, it is important to understand the countervailing factors and to consider the costs of tourism-induced crime in social cost-benefit assessments of tourism growth.

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Notes

  1. Figure S1, panel a, in Supplementary Material displays a map of Croatia and the neighbouring countries.

  2. In references, the titles of media articles are translated from Croatian by the authors.

  3. Figure S1, panel b, in Supplementary Material displays a map of Croatia with county borders. It is also indicated which counties are coastal and which are continental.

  4. For details, see Croatian Criminal Act, Articles 229–231.

  5. Hereafter, we will use just ‘average’ to mean ‘average compound’.

  6. Note also that it can be interpreted as the effect of the number of tourist arrivals per square kilometre on the number of crimes per square kilometre of the county surface area, owing to the fact that we control for county fixed effects.

  7. In all tables with regression results, the coefficient estimates are displayed with four decimals, but in text we round them to two decimals. We do so throughout the whole text.

  8. Recall that Zagreb comprises two counties, namely the City of Zagreb and County of Zagreb.

  9. Full results are provided in Table S1 in Supplementary Material.

  10. Full results are provided in Table S1 in Supplementary Material.

  11. With one exception, where one of the controls is appropriately redefined (see next paragraph).

  12. Full results are provided in Table S2 in Supplementary Material.

  13. Full results are provided in Table S3 in Supplementary Material.

  14. It might be that for theft the clear-up rate better measures deterrence, though it is admittedly hard to know what might be the reasons for that.

  15. Note that it would not make a substantial difference if it were included as the share of the unemployed in population instead, given that we control for population (as previously discussed in the cases crime vs. crime per 100,000 inhabitants and tourist arrivals vs. tourist arrivals per 100,000 population). Unfortunately, there are no monthly data on the number of active population at the county level, so we are not able to control for the unemployment rate.

  16. Full results are provided in Table S4 in Supplementary Material.

  17. Here ’full sample’ refers to the sample covering all counties and all months for which the number of unemployed persons at the county level is available, namely from January 2004 to December 2016.

  18. Full results are provided in Table S5 in Supplementary Material.

  19. Unemployment is regularly at its lowest point over a year during the summer months, when the tourist season is peaking. In addition, besides tourism, other important sectors, most notably construction, employ more during summer months, though more so outside the areas with most tourists.

  20. We have also tried controlling for (the natural logarithm of) gross domestic product, on which we have only annual, rather than monthly, county-level data. These data are not available for 1998 and 1999. The results—available on request—show that the coefficient on ln(GDP) is never statistically significant and the crime elasticity estimate hardly changes.

  21. The evolution of tourist arrivals was depicted in Fig. 1.

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Funding

Funding was provided by TvojGrant@EIZ.

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  1. Institute of Economics, Zagreb, Croatia

    Vedran Recher & Ivica Rubil

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  1. Vedran Recher
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  2. Ivica Rubil
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Correspondence to Vedran Recher.

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Recher, V., Rubil, I. More Tourism, More Crime: Evidence from Croatia. Soc Indic Res 147, 651–675 (2020). https://doi.org/10.1007/s11205-019-02160-6

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