The Impact Of Marijuana Legalization On Crime Trends Literature Review
In today’s political climate, much discussion centers around the facts of marijuana policy in national discussions and debates. On the one hand are the scientific and medical policy discussion which consider continuously whether marijuana is in fact detrimental to your health or whether there are some if any benefits. On the other side of the fence are the social policy wonks who argue continuously over marijuana policy and its legal status in contemporary American jurisprudence. Marijuana legalization discussions are not simply a question of whether the law should permit the use and possession of marijuana (however, this is one type of discussion with respect to legalization). In the United States, marijuana policy differs across states and even nations, as the United States along with the international community continue to evolve drug policy laws as experiments are tested in the social laboratory of life. Marijuana decriminalization is a second option underneath that of marijuana legalization which differs in that it does not make marijuana use or possession legal under the law but it does offer reduced penalties if one is detained for possession or personal use of small amounts..(Shepard & Blackley 2007) A third domain of marijuana legal discussion is medical marijuana, which continues to find passage ongoing in more and more states.(Shepard & Blackley 2007) Medical marijuana law with statutory authority makes it legal for a physician to place a patient under a medical marijuana prescription as long as they have registered with the state authorities and attained a proper license. Medical marijuana recipients still remain vulnerable to criminal prosecution in the event a law enforcement officer finds them in possession or use of marijuana, even if the marijuana is from their own personal prescription.(Shepard & Blackley 2007)
The federal government continues to criminalize marijuana primarily because it has been found to have high risk for abuse potential as well as having no clear and compelling evidence for its use in medical procedure and treatment. On the basis of marijuana’s high potential for abuse and no accepted evidence in medical treatment.(Shepard & Blackley 2007) Notably, this view is endorsed and supported by medical organizations nationwide. On the other hand, marijuana legalization maintains a strong case that should not go unheard. The public conversation concerning marijuana law and policy in the United States is at its peak as states increasingly liberalize their marijuana legislation over the past 15 years. Since 1996, over 20 states have passed Medical Marijuana Legislation and now 3 states have legalized recreational sale as well, of which Colorado is one. Experts across both domains of social as well as scientific policy conduct individual focused debates, reflecting the issue’s heated relevancy in lawmaker’s agendas.(Shepard & Blackley 2016)
These two areas cover the overarching issues at the front of marijuana discussions: concerning the fair assessments of marijuana’s health effects on the human body and related risks and benefits as well as its legal status, specifically with reference to progressive measures for decriminalization and legalization, which Colorado achieved in 2013.(Shepard & Blackley 2016) This idea is also distinct from medical marijuana, in which a person may defend themselves against any criminal charge if caught possessing or using marijuana and that they can prove that they have a medical need to do so under state laws. Proponents of marijuana legalization advocate its taxation and sale based on anticipated gains in revenues which would return significant tax revenues as well as reduce policing costs.(Shepard & Blackley 2016) Nevertheless, the federal government still maintains that distribution of marijuana is unlawful and considers it a serious crime. Furthermore, in Gonzales vs. Raich (2005), the United States Supreme Court found that federal authority acting in accord with statutory law, may seek criminal prosecution against any person who takes marijuana under a doctor’s prescriptions in the event law enforcement finds the illicit substance in the person’s control.(Mazeika et al. 2010) This ruling reinforced the fact that state rulings on marijuana do not work to change federal law.
Explanation of Study
Despite the fact that marijuana has had a long history of use in treatment for medicinal purposes legitimized outside of Western history, policymakers and even some members of the scientific community remain stridently opposed, seizing opportunities to unravel any hint of potential problem in social outcome of legalization. In spite of these political discussions, Medical Marijuana Laws (MML) have passed in over 20 states since 1995.(Shepard & Blackley 2016) And, most recently, Colorado and Washington each have legalized its use in their states within the past 3 years. Concern and interest in how these laws might affect and shape society has inspired an increase in research activity and discussion among social science practitioners and policy theorists. This paper wishes to explore this topic on the issue of marijuana legalization and whether increase in crime is an effect of marijuana legalization or not. The effect of crime rates is indeed one of the most widespread concerns in the decision to push legislation in progressive directions.
The most obvious reason for this is because legalization (whether as a Medical designation or Recreational) has the effect of bringing marijuana to a public storefront and making it an item of commerce, thereby increasing access to reliable sources of plant for members of a community whether they are purchasing it as recreational product or with a medical marijuana card. One issue some police forces have seen and warned of is the opening of dispensaries and the associated crime potential.(Shepard & Blackley 2007) Dispensaries are ideal operations for criminal groups to target because of the illicit recreational product on hand as well as the presence of large amounts of cash.(Shepard & Blackley 2007) In California, law enforcement officials have stated publicly in announcements of observed trends in the area through press meetings and releases. One such police chief in the state noted during a live taped press statement of a rise in armed robberies and home invasions with marijuana cultivators being the explicit target.(Shepard & Blackley 2007) The combination of a cash-only business as well as the attraction of huge amounts of illicit substance are aspects which seem intuitively attractive to a ruthless or violent criminal gang as candy in a candy store. Dispensaries then become automatically associated with sites of crime.
For this project we will collect data from the Uniform Crime Reporting Program (UCR) which is available to the public in published form on line under the title Crime in the United States. We will collect data for all 7 offenses contained in part 1 of the UCR which includes homicide, rape, robbery, burglary, auto theft, larceny and assault.(Biderman & Lynch 2012) These figures will be gathered from all 50 states between the years 1996 and 2006. Data from all 50 states over a period of 10 years resulted in a N=500. Each value reported captures the instance of the rate of crime per 100,000 people. Our next task with this data was to figure out the dates that states passed MML legislation within this time frame, and which. Searching the 20 states’ websites with known and active MML legislation, we recorded each year’s passage for our study. Each state and the year in which MML legislation was passed is noted to the right of the colon as the following: California: 1996, Montana: 2004, Nevada: 2000, Oregon: 1998, Rhode Island: 2006, Vermont: 2004,Washington: 1998, Hawaii: 2000, Colorado: 2000, Alaska: 1998.
We use this information in our modeling by including a variable that captures the effect post-law, called a trend variable.(Woolridge 2010) This variable ope rationalizes by giving representation to the number of years law has been in effect while assigning a value of zero for all years before law was encoded.(Woolridge 2010) As a trend variable, it also accepts an assigned value of 1 for all years before the law was passed and a value of 1+k where k=number of years after the initial passage of the law. What is excellent about the use of this variable is that it is able to capture changes in a linear trend pattern after the law has taken effect.(Woolridge 2010) This has obvious explanatory advantages over the dummy variable technique that assigns a binary (0 = no law ,1 = law).(Woodlridge 2010) The dummy variable technique captures only discreetly an impact on crime. What we wish to look at here more closely, however, is what kind of changes may have happened possibly within a dynamic linear movement over time.
This approach allows us to draw some powerful conclusions and topple speculative arguments about the interaction of marijuana in one’s youth and its association with later criminal acts and behaviors.. People who are strong against marijuana legalization raise one of the more powerful concerns that its increasing access will harm the vulnerable youth in our society and put greater numbers at risk for deviancy in adulthood vis a vis addiction and crime. The hypothesis indicated here is challenging for those interested in pushing for legalization because of its intuitive possibility. Being able to analyze the data, in particular the trend effect on how crime rates moved over time following the passage of laws across states will give us robust means by which to answer this argument in a scientific and conclusive fashion.(Woolridge 2010) To complete our model we add a number of control variables that can account for potential countervailing forces occurring over the period of time we are studying. These are our independent variables that characterize and reflect sociodemographic status. Borrowing directly from the model presented in criminal justice researchers Kovardzic, Vieraitis, and Paquette-Boots (as cited in Shepard & Blackley 2016 ), we include an equivalent list in our model of these control variables. They include real per-capita income, unemployment rate, total employment rate, percent living below poverty line, percent of residents living groups by decades of 10, fraction of residents who hold a minimum of a bachelor’s degree and percent of state residents living in urban or metropolitan area. These data have various sources. Unemployment and employment figures are gathered from the Bureau of Labor Statistics.(Biderman & Lynch 2012) The U.S. Census Bureau provides data for poverty levels, age.(Biderman & Lynch 2012)
The goal for our model is to analyze the in-state variation following passage of MML legislation and to compare these effects across states for the time period of 1996 – 2006. From here, the goal is to analyze and assess whether crime rates changed following MML passage by looking at the changes of crime within states over time and comparing those patterns to the effects other states experienced analogously before and after their own passage and then last to compare the trends viewed in this step to the trends observed across the 30 other states who did not pass any medical marijuana legislation in this time. Our dependent variable in this model is therefore the natural log of each state’s variable crime rate captured from the Uniform Crime Report that incorporates the 7 offenses, as mentioned previously. The model we use for this is an ordinary least square regression model using fixed-effects. Our dependent variable therefore fits the requirement that it is measured a minimum of twice for each state.(Woolridge 2010) Our independent variable also changes across time with respect to dynamic forces. Fixed effects modeling is especially appropriate here for its specialty in looking at variables that change over and across time. (Woolridge 2010) Our estimates also are adequate for organizing the panel data as individual states, since it isolates heavily on the individual differences that exist between dependent state crime rate variable. It puts less focus on the differences within differences of individuals and allows for the differences across individuals to take stage.
Limitations exist in fixed effects that include sensitive and unobserved variables. Failure to include any one variable may result in skewed coefficients.(Stock & Watson 2003; Woolridge 2010) In general, fixed effects models are considered generous for their ability to produce results against risk of omitted variable bias. However, this all depends on how small or great the differences within differences variation really is.(Stock & Watson 2003; Woolridge 2010) If the within variation becomes small with respect to between person variation, the result will create problems with standard errors of fixed effects coefficients. If they are extremely large, this is a good indicator that something has gone wrong (Stock & Watson 2003).
Legal changes in any dynamically operating community justice system will necessarily bring with it observable empirical differences indicating this shift in policy. Criminal justice is a broadly comprehensive term that includes not only the corrections system, parole, probation, jail, as well as state run prisons, drug court and certified treatment centers, mandatory community service programs, juvenile justice sectors, policing, as well as the community and county circuit courts. question which is the subject of the study of this paper. Our methodological approach therefore is geared to data used in law enforcement statistics in order to capture all instances of the event in question which in our case is all 7 of level 1 offenses in the UCR.(Biderman & Lynch 2012) Our data instrument may be understood as existing in the same category as other aggregate reporting that similarly rely on government, hospital, court and police records. The one caveat to these kinds of data as information sources is each may be subject to certain constraints such as limited or full coverage as well as the practices used in reporting that may include specific procedures or delays.(Biderman & Lynch 2012) In our present study we therefore utilized arrest records taken from years 1996 – 2006 for a comparison of states with MML and 30 states without MML, all data made available by the Federal Bureau of Investigation’s Uniform Crime Report.(Biderman & Lynch 2012) The Uniform Crime Report is released yearly, on an annual basis. It includes compiled data on volume levels and rates of violent and other property crimes organized by nation country and state.(Biderman & Lynch 2012) Law enforcement agencies on an individual level are also granted access to this data set by supplying 12 months total of complete data. This report also includes miscellaneous data about arrests within law enforcement agencies.
Limitations and Discussion
The focus of this project was to conduct a preliminary study into and understand some of the consequences involved with Drug law changes. One of the most interesting study design patterns available under this topic is the evaluation method,which may use one or more design patterns. Evaluation designs can achieve what is sought after in the literature review, by isolating clearly the change before and after, in evaluating the intended effects of a legal change but also giving insight into explaining what may be the unintended effects of a legal change.
There also exist some caveats with the data set used for this study. There are certain aspects of the Uniform Crime Report dataset. For one, the UCR is not a dataset that includes juvenile reporting.(Biderman & Lynch 2012) This aspect may be significant with respect to the question over the relationship between juvenile use of marijuana and juvenile offending, as well as juvenile offending and factors influencing criminality over the lifespan. The UCR does not collect all crimes reported to police in the reporting period because the report itself only collect those which are written into an official arrest record, which is a Uniform Crime Report measure itself.(Mazeika et al. 2010); Biderman & Lynch 2012) The UCR also may not reveal the full import of the charge underlying the arrest. An arrest may include charges not collected by the 7 offenses listed in the Level 1 category of inclusion on the UCR.(Biderman & Lynch 2012)
Biderman, A. D., & Lynch, J. P. (2012). Understanding crime incidence statistics. Springer Science & Business Media. Retrieved from https://books.google.com/books? id=YLghBQAAQBAJ&lpg=PT7&ots=0cgNMv6EcE&dq=UCR&lr&pg=PT11#v=onepage&q=UCR&f=false
Mazeika, D., Bartholomew, B., Distler, M., Thomas, K., Greenman, S., & Pratt, S. (2010).
Trends in police research: a cross‐sectional analysis of the 2000–2007 literature. Police
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Shepard, E. M., & Blackley, P. R. (2016). Medical Marijuana and Crime Further Evidence From
the Western States. Journal of Drug Issues, 0022042615623983
Shepard, E. M., & Blackley, P. R. (2007). The impact of marijuana law enforcement in an
economic model of crime. Journal of Drug Issues, 37(2), 403-424.
Stock, J. H., & Watson, M. W. (2003). Introduction to econometrics (Vol. 104). Boston: Addison
Woolridge, J. M. (2010). Econometric analysis of cross section and panel data. MIT press.
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