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The impact of recreational marijuana dispensaries on crime: evidence from a lottery experiment

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Abstract

Many North American jurisdictions have legalized the operation of recreational marijuana dispensaries. A common concern is that dispensaries may contribute to local crime. Identifying the effect of dispensaries on crime is confounded by the spatial endogeneity of dispensary locations. Washington State allocated dispensary licenses through a lottery, providing a natural experiment to estimate the causal effect of dispensaries on neighborhood-level crime. Combining lottery data with detailed geocoded crime data, we estimate that the presence of a dispensary has no significant impact on local crime in the average neighborhood. We estimate a small rise in property crime in low-income neighborhoods specifically.

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Notes

  1. The federal government regulates drugs through the Controlled Substances Act (21 U.S.C. §811), which does not recognize the difference between the medical and recreational use of marijuana.

  2. “Marijuana producer” means a person licensed by the WSLCB to produce and sell marijuana at wholesale to marijuana processors and other marijuana producers. “Marijuana processor” means a person licensed by the WSLCB to process marijuana into usable marijuana and marijuana-infused products, package and label usable marijuana and marijuana-infused products for sale in retail outlets, and sell usable marijuana and marijuana-infused products at wholesale to marijuana retailers. “Marijuana retailer” means a person licensed by the WSLCB to sell usable marijuana and marijuana-infused products in a retail outlet.

  3. Rape incidents constitute only 0.2% of reported crimes within jurisdictions in our sample where data is available.

  4. To further clarify the calculation of \(D_{it}^d\) and \(W_{it}^d\) in cases where treatment circles overlap, we provide an example in Fig. 8.

  5. We allow \(D_{it}^d\) and \(W_{it}^d\) to exceed one in order to capture treatment intensity. The choice implies that the partial effect of being treated by two dispensaries is twice that of being treated by a single dispensary. We test robustness to alternate constructions of \(D_{it}^d\) and \(W_{it}^d\) in Table 14 and find results are consistent.

  6. We test for finite sample bias by estimating the Cragg–Donald Wald F statistic. We estimate the F statistic at over 500 for all treatment radii, strongly rejecting the presence of significant bias.

  7. For example: Surveillance video shows pot shop owner use bear spray to thwart armed robbery, Fox 13, Seattle, 02/17/2020; Violent pot shop robbers wanted in Seattle, Fox 13, Seattle, 02/07/2020; ‘They held a gun to my head’: Armed robbers hit S. Seattle pot shop, KOMO News, 11/19/2019.

References

  • Abadie A, Athey S, Imbens GW, Wooldridge J (2017) When should you adjust standard errors for clustering? Technical report, National Bureau of Economic Research

  • Adda J, McConnell B, Rasul I (2014) Crime and the depenalization of cannabis possession: evidence from a policing experiment. J Polit Econ 122(5):1130–1202

    Article  Google Scholar 

  • Anderson DM, Rees DI (2014) The legalization of recreational marijuana: How likely is the worst-case scenario? J Policy Anal Manage, pp 221–232

  • Angrist JD (1990) Lifetime earnings and the Vietnam era draft lottery: Evidence from social security administrative records. Am Econ Rev, pp 313–336

  • Barrios T, Diamond R, Imbens GW, Kolesár M (2012) Clustering, spatial correlations, and randomization inference. J Am Stat Assoc 107(498):578–591

    Article  Google Scholar 

  • Becker GS, Murphy KM (2013) Have we lost the war on drugs? Wall Street J, 4

  • Brinkman J, Mok-Lamme D (2019) Not in my backyard? Not so fast. The effect of marijuana legalization on neighborhood crime. Regional Sci Urban Econ 78:103460

    Article  Google Scholar 

  • Burkhardt J, Goemans C (2019) The short-run effects of marijuana dispensary openings on local crime. Ann Regional Sci 63(1):163–189

    Article  Google Scholar 

  • Callaway B, Goodman-Bacon A, Sant’Anna PH (2021) Difference-in-differences with a continuous treatment. Working Paper

  • Callaway B, Sant’Anna PH (2021) Difference-in-differences with multiple time periods. J Economet 225(2):200–230

    Article  Google Scholar 

  • Carrieri V, Madio L, Principe F (2019) Light cannabis and organized crime: evidence from (unintended) liberalization in italy. Eur Econ Rev 113:63–76

    Article  Google Scholar 

  • Chang TY, Jacobson M (2017) Going to pot? The impact of dispensary closures on crime. J Urban Econ 100:120–136

    Article  Google Scholar 

  • Chu Y-WL, Townsend W (2019) Joint culpability: the effects of medical marijuana laws on crime. J Econ Behav Org 159:502–525

    Article  Google Scholar 

  • Cook PJ, MacDonald J (2011) Public safety through private action: an economic assessment of bids. Econ J 121(552):445–462

    Article  Google Scholar 

  • De Chaisemartin C, d’Haultfoeuille X (2018) Fuzzy differences-in-differences. Rev Econ Stud 85(2):999–1028

    Article  Google Scholar 

  • De Chaisemartin C, d’Haultfoeuille X (2020) Two-way fixed effects estimators with heterogeneous treatment effects. Am Econ Rev 110(9):2964–2996

    Article  Google Scholar 

  • Dong X (2022) Recreational marijuana sales legalization and monday work injury claims. BE J Econ Anal Policy 22(1):99–121

    Article  Google Scholar 

  • Dragone D, Prarolo G, Vanin P, Zanella G (2019) Crime and the legalization of recreational marijuana. J Econ Behav Org 159:488–501

    Article  Google Scholar 

  • Freedman M, Owens EG (2011) Low-income housing development and crime. J Urban Econ 70(2–3):115–131

    Article  Google Scholar 

  • Ghosh T, Van Dyke M, Maffey A, Whitley E, Gillim-Ross L, Wolk L (2016) The public health framework of legalized marijuana in colorado. Am J Public Health 106(1):21–27

    Article  Google Scholar 

  • Goodman-Bacon A (2021) Difference-in-differences with variation in treatment timing. J Econ 225(2):254–277

    Article  Google Scholar 

  • Green T (2021) Americans overwhelmingly say marijuana should be legal for recreational or medical use. Pew Research Center, April 16, 2021

  • Hansen B, Miller K, Weber C (2017) The grass is greener on the other side: How extensive is the interstate trafficking of recreational marijuana? Technical report, National Bureau of Economic Research

  • Hansen B, Miller K, Weber C (2020) Early evidence on recreational marijuana legalization and traffic fatalities. Econ Inquiry 58(2):547–568

    Article  Google Scholar 

  • Hollenbeck B, Uetake K (2021) Taxation and market power in the legal marijuana industry. RAND J Econ 52(3):559–595

    Article  Google Scholar 

  • Huber A III, Newman R, LaFave D (2016) Cannabis control and crime: medicinal use, depenalization and the war on drugs. BE J Econ Anal policy, 16(4)

  • Jacob BA, Ludwig J (2012) The effects of housing assistance on labor supply: evidence from a voucher lottery. Am Econ Rev 102(1):272–304

    Article  Google Scholar 

  • Kau JB, Rubin PH (1975) New estimates of the determinants of urban crime. Ann Regional Sci 9(1):68–76

    Article  Google Scholar 

  • Morris RG, TenEyck M, Barnes JC, Kovandzic TV (2014) The effect of medical marijuana laws on crime: evidence from state panel data, 1990–2006. PloS One 9(3):e92816

    Article  Google Scholar 

  • Nicholas LH, Maclean JC (2019) The effect of medical marijuana laws on the health and labor supply of older adults: evidence from the health and retirement study. J Policy Anal Manage 38(2):455–480

    Article  Google Scholar 

  • Rephann TJ (2009) Rental housing and crime: the role of property ownership and management. Annals Regional Sci 43(2):435–451

    Article  Google Scholar 

  • Thomas D, Tian L (2021) Hits from the bong: The impact of recreational marijuana dispensaries on property values. Regional Sci Urban Econ 87:103655

    Article  Google Scholar 

  • Tyndall J (2019) Getting high and low prices: Marijuana dispensaries and home values. Real Estate Econ

Download references

Acknowledgment

We thank Gary Engelhardt, Simona Fabrizi, Alfonso Flores-lagunes, Ryan Greenaway-McGrevy, Ross Jestrab, Je.rey Kubik, Ste.en Lippert, David Neumark, Peter Phillips, Alex Rothenberg, Perry Singleton, Asha Sundaram, James Tremewan, Emily Wiemers, and seminar participants at the University of Auckland, Midwest Economics Association Conference, and Southern Economic Conference for their helpful comments and valuable suggestions. We appreciate the Pierce County Sheri. Department, the City of Tacoma Police Department, the Seattle Police Department, and the Washington State Liquor and Cannabis Board for their data support. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Declarations of interest: none. All errors are our own.

Author information

Authors and Affiliations

  1. Krieger School of Arts and Sciences, Advanced Academic Programs, Johns Hopkins University, 555 Pennsylvania Ave NW, Washington, DC, 20001, USA

    Xiuming Dong

  2. University of Hawaii Economic Research Organization and Department of Economics, University of Hawaii at Manoa, 2424 Maile Way, Saunders Hall 540, Honolulu, HI, 96822, USA

    Justin Tyndall

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  1. Xiuming Dong
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Appendices

Appendix tables

See Tables 9, 10, 11, 12, 13, 14, 15.

Table 9 Effect of dispensaries on overall number of local crimes, combined areal unit approach
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Table 10 Effect of dispensaries on overall number of local crimes, outcome in crimes per 10,000 residents
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Table 11 Effect of dispensaries on local crime by disaggregated crime type
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Table 12 Effect of dispensaries on local crime by crime type, using log-transformed crime measure
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Table 13 Effect of winning the lottery on local crime, Poisson regression
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Table 14 Effect of dispensaries on overall number of local crimes, alternative definitions of D and W
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Table 15 Effect of winning the lottery on local crime by crime type and neighborhood characteristics, alternative neighborhood type definitions
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Appendix figures

See Figures 6, 7, and 8.

Fig. 6
figure 6

Mean Monthly Crime Counts by Lottery Status. Mean monthly crime counts with a 95% confidence interval at 200 ms around dispensaries for a all crimes, b property crimes, c violent crimes, and d drug crimes by lottery result from 2010 to 2016. The vertical red line indicates the time of the lottery drawing. Month 0 is equal to January 2010. A significant threat to the identification would be the presence of differential crime trends between treatment and control areas. Visual inspection suggests the pre-treatment trends are parallel

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Fig. 7
figure 7

Crime Heat Maps. The figure displays the frequency of crime occurring in a particular square unit, within a month, relative to the location of a dispensary applicant, averaged across applicants. Panel a shows the average crime activity before the lottery event, across all applicant locations. We compare lottery compliers (those winners who opened a dispensary at their application address) before (b) and after (c) the lottery event. We do not find a strong spatial correlation between applicant sites and pre-lottery crime rates when examining the immediate areas

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Fig. 8
figure 8

Calculating W and D When Treatment Areas Overlap. The figure and table illustrate a hypothetical case of calculating values of W and D in a case where the treatment areas of three applicants overlap. In this example, at a specific time (t) lottery applicants X and Y have won the dispensary lottery but only applicant X is operating a dispensary. a-d represent areas as a share of a unit circle. For example, if a covers 20% of a circle, a=0.2

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Dong, X., Tyndall, J. The impact of recreational marijuana dispensaries on crime: evidence from a lottery experiment. Ann Reg Sci 72, 1383–1414 (2024). https://doi.org/10.1007/s00168-023-01246-x

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