Abstract
This paper leverages the timing of a ban on the purchase of sex to assess its impact on rape offenses. Relying on Swedish high-frequency data from 1997 to 2014, I find that the ban increases the number of rapes by around 44–62%. The results are robust to several econometric specifications that exploit different identification assumptions. The increase reflects a boost in completed rapes both in the short- and long-run. However, it is not accompanied by a decrease in the number of pimps. Taken together, the empirical evidence hints at the notion that the rise in rapes is not connected to the supply of prostitution but rather to changes in the demand for prostitution due to the ban. The results here have the opposite sign but larger magnitudes in absolute value than results in the literature on the decriminalization of prostitution.
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Data availibility
All the data sets used in this article might be accessed publicly contacting the corresponding websites mentioned in Section 3.
Notes
As for regions I refer to any of the self-governing local authorities, also known as regional councils. Currently and in the years analyzed in this article, there are 21 regions of this sort in Sweden.
The precise figures are 1.8% of women and 0.3% of men.
Sexualbrottslagstiftningen Uppsala University and the National Centre for Knowledge on Men’s Violence against Women. Retrieved on 12-August-2023 https://www.nck.uu.se/kunskapsbanken/amnesguider/sexuellt-vald/sexualbrottslagstiftningen/
For further information, see Svanström (2005).
In this framework I assume these three types of sex are imperfect substitutes between them. Clearly, assuming perfect substitutability does not change the results.
In this data base, data in 2005 for a few airports are missing.
Namely, \(\log (rape_{rmy})\) is either the number of reported cases of rape in logs \(+1\) (i.e., \(\log (1+rape_{rmy})\)) or the inverse hyperbolic sine transformation of rapes, since rape might take value 0.
Supplementary material S.2.5 offers further information on the size of these estimators.
Supplementary material S.9 considers additional specifications that might be useful to shed further light on the mechanisms analyzed here.
In particular, with respect to the years before 1999, at that time prostitution was not regulated in Sweden (Ciacci, 2021).
A pimp (or procurer) denotes a person, especially a man, who controls prostitutes and arrange customers for them, usually in return for a share of the earnings. In Sweden, even if selling sex is not penalized, making money out of prostitutes (e.g., pimping) is a crime. For this reason, Brå also collects data on the number of convicted pimps. Pimping is also closely related to coercive exploitation of prostitution and human trafficking (Elrod, 2015).
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Acknowledgements
I would like to thank Juan J. Dolado, Andrea Ichino, and Dominik Sachs for invaluable guidance and support. I am thankful to Manisha Shah for her inestimable suggestions to improve this article. I am also very grateful to Ludvig Lundstedt who helped me in collecting the data and gathering information about prostitution laws in Sweden. I would like to express my gratitude to Brais Álvarez Pereira, Giovanni Andreottola, Andreu Arenas, Elena Esposito, Gabriel Facchini, Antoni I. Moragas, Krzysztof Pytka, María Micaela Sviatschi and participants to the EUI students’ workshops, to the online seminar on the economics of crime organized by Jennifer Doleac, to the 4th alumni EUI conference, and to the Royal Economic Society conference of 2023. I would also like to thank editor Klaus F. Zimmermann, as well as three anonymous referees for their comments and guidance. All remaining errors are my own.
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Financial support from the Spanish Ministry of Science (PGC2018-093506-B-I00) is gratefully acknowledged.
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Ciacci, R. Banning the purchase of sex increases cases of rape: evidence from Sweden. J Popul Econ 37, 37 (2024). https://doi.org/10.1007/s00148-024-00984-2
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DOI: https://doi.org/10.1007/s00148-024-00984-2
Keywords
- Rape
- Sex crimes
- Prostitution
- Prostitution law
- Prostitution regulation
- Criminalizing purchase of prostitution
- Nordic model
- Fuzzy difference-in-differences
- Event study analysis
- Instrumental variables estimation