Unemployment rates from 2005- 2014 will be used in order to compare it to our MMIC data. Referring again to Table 4.1, we observe a mean unemployment rate of 9.8. All data sets contain 560 total observations from the 56 counties used within the 10-year period. The mortality rates are divided into three categories: Alcohol-Induced Causes, Drug-Induced Causes, and All Other Causes. These rates are given per 100,000, as shown in 7.1.3 of the Appendix. Estimated population sizes per year are also included in the data set. Like the MMIC data, the crude rates are reported per county, per year from 2005-2014. Within this time period, these crude rates have ranged from 4.9 to 1328.6 per 100,000. Referring above to Table 4.1, the mean alcohol-induced, drug-induced, and other crude rates are 13.5, 15.8, and 759.4, respectively. In addition to the mortality data, arrest rates will be examined to determine if medical marijuana is a substitute for other drugs and alcohol. The arrest data comes from the State of California Department of Justice’s Criminal Justice Statistics Center and includes 76 arrest variables. Of these 76 variables, I will be using 7 of them in my data analysis. These variables include marijuana, drunk, felony drug offenses, narcotics, dangerous drugs, other drugs, and total arrests. Other drugs represent all misdemeanor drug arrests excluding marijuana. However, the marijuana variable used in our data is the sum of both misdemeanor and felony marijuana arrests. As stated by the CJSC, “A felony offense is defined as a crime which is punishable by death or by imprisonment in a state prison. A misdemeanor offense is a crime punishable by imprisonment in a county jail for up to one year.” 13 Full variable definitions are given in Table 7.2.1 in the Appendix. All variables in the data set were given as number of arrests per county, per year again from 2005-2014. As presented in part 7.1.2 of the Appendix, I converted these numbers into arrests per 100,000 so the analysis of all variables could be more easily interpreted. The CJSC has also provided crime data from 2005-2014 to be used in the regressions. Not to be confused with arrest data, pipp grow rack the crime data set contains all individuals convicted of a crime, whereas arrests occur when a person is simply taken into custody for a crime.

The crime data presented by the CJSC offers 66 variables, from which I selected the 10 main types of crime, including, violent crime, burglary, larceny/theft, property crime, aggravated assault, motor vehicle theft, robbery, forcible rape, homicide, and total crime. Property crime is the sum of burglaries, larceny/thefts, and motor-vehicle thefts and violent crime is the sum of forcible rapes, homicides, and robberies. For full definitions of crime variables, refer to Table 7.2.2 in the Appendix. The crime data set originally included city and county distinction, but I collapsed the data into strictly per county observations. Computed the same as the MMIC, crude, and arrest rates, the third calculation shown in 7.1.3 of the Appendix was used to convert the numbers into crimes per 100,000 people. Table 4.2 below offers summarized statistics of all data collected from the CJSC.To begin analyzing the effect of medical marijuana in California, all nine individual crime rates and total crime rates were regressed on MMIC rates and unemployment rates with county and year fixed effects. It is necessary to include county fixed effects in the model because there are unobservable factors that could affect crime rates. For example, high-income counties in California may have lower crime rates by being able to afford tighter security. It is also obligatory to include year fixed effects in the crime rates model. This type of fixed effect absorbs any event or time trend that could potentially adjust crime rates. Because the data ranges from 2005- 2014, the housing market crash could have affected crime rates. Referring to Graph 5.1, it is indicated that crime rates don’t necessarily have a linear time trend. Thus, the individual year dummy variables will be the best fit to combat the unobservable events that occur across time. Here we see that for every additional medical marijuana card issued, total crime decreases by one and a half crimes.

This appears to be a significantly large effect. However, looking at the average MMIC rate of 53 and the average total crime rate of 6,210, it is unlikely that medical marijuana could completely eradicate crime. The estimated results imply that if the mean of MMICs goes up to 54, crime rates will fall to an average of 6,208.5. This is only a decrease of 0.024% of total crime, which is a small, yet reasonable estimate. While this is a small effect on total crime, the 95% confidence level suggests the true estimate is between -2.46 and -0.55. Because these values are negative, it is acceptable to assume medical marijuana will not negatively impact society by increasing crime rates. After observing that medical marijuana has a negative effect on total crime, it can also be seen that medical marijuana also has negative effects on larceny-theft and property crime, with estimates shown in tables 5.4 and 5.5. Table 5.4 indicates that for every additional MMIC issued, larceny/theft declines by about half of a crime, while Table 5.5 suggests that for every additional MMIC issued, property crime decreases by ¾ a crime. Because property crime is defined as the sum of larceny/thefts, burglaries, and motor-vehicle thefts, the effect on larceny/theft is contained within the effect on overall property crime. Many individuals who argue against the legalization of marijuana claim that marijuana usage would increase crime, thereby negatively impacting society. By building a 95% confidence interval it is shown that the true estimates are negative and that 95% of the time, the estimate will fall between -1.18 and -0.33. Thus, medical marijuana will not increase overall property crimes, specifically larceny/thefts. This answers the common argument that marijuana use increases crime rates.The other seven crime variables regressed on MMIC, using Equation 5.2, showed no significant effects of medical marijuana on crime. However, vehicle theft showed a statistically significant negative effect at the 90% confidence level. This can be explained by the above regression results on property crime, given that vehicle theft is included in the overall property crime rates by definition. All other crimes displayed zero effect from medical marijuana. While we can comfortably say that medical marijuana does not increase crime rates, there needs to be an explanation for why it has a significantly negative effect on both total crime and property crime. One explanation is that allowing consumers to purchase legally decreases the amount of associated crime that comes with the illegal marijuana market. It is often true that individuals who enact in criminal activity participate in more than one crime. This means when individuals are purchasing marijuana illegally, they are more likely to commit other crimes. Thus, when additional MMICs are issued, individuals are purchasing marijuana legally and are less likely to be crime participants. This effect can be seen in the above regression results where additional MMICs lead to a slight fall in committed crimes. A second explanation could be that there are substitution effects for marijuana and other drugs and alcohol. With evidence of marijuana reducing violent behavior, as explained further below, individuals are less likely to commit crimes. Because many crimes are committed while drunk or intoxicated, an increase in marijuana use with significant substitution effects on other drugs or alcohol could lead to a slight decrease in crime.This brings us to the next two models, created to observe whether or not marijuana is a substitution drug for alcohol and/or other drugs. Equation 5.6 regresses every individual arrest rate on MMICs and unemployment rates, while Equation 5.7 regresses drug-induced, alcohol-induced, and all other mortality rates on MMICs and unemployment rates.

These two equations will allow us to examine any substitution effects going on between marijuana and other drugs and alcohol. Both equations are again controlled for county and time fixed effects.This means that 99.9% of the time medical marijuana has a negative effect on drunken arrests. While this indicates that there may be a substitution effect for alcohol, pipp horticulture racks cost it is a small effect with a 1:4 substitution ratio. For this effect to decrease drunken arrest rates by 1%, MMICs would have to increase by about 20 per 100,00. This could be a possible scenario, given that the standard deviation of MMICs is 95.34. In the likelihood of this event, medical marijuana could be a significant substitute for alcohol. As briefly mentioned earlier in this analysis, a substitution effect between marijuana and alcohol can justify why we see a decrease in crime. It has been observed by many studies that a large proportion of crimes are committed when an individual is intoxicated. According to the Huffington Post, the National Institute on Alcohol Abuse and Alcoholism “found that 25-30% of violent crimes are linked to alcohol use,” and the journal of Addictive Behaviors performed a study that suggested “cannabis reduces likelihood of violence during intoxication,” thus explaining why an increase in marijuana use can decrease crime rates.14 By finding a slight substitution effect between marijuana and alcohol, we are able to explain some of the negative effect that marijuana has on crime. After regressing all other arrest rates, drunken arrests remains the only significant category affected by MMICs. So with the given data, there is no evidence that marijuana is a substitute for dangerous drugs, other drugs, felony drugs, nor narcotics. It is particularly surprising that we see no effect on narcotics, considering most medical marijuana patients specifically use cannabis as a substitute for narcotics. An explanation for this can be that some medical marijuana users do not use for medical reasons many of the MMIC holders in this particular data base may only use for recreational purposes. To observe any further substitution effects, I used Equation 5.7 to regress alcohol induced crude rates, drug-induced crude rates, and all other crude rates on MMICs and unemployment still controlling for county and year fixed effects. Unlike the arrest rate data, no substitution effects were found. Referring to the regression output in Table 5.9 for alcohol-induced deaths, MMICs actually had a statistically significant positive effect on alcohol related deaths. The interpretation is that for every new medical marijuana user, the alcohol crude rate increases by 0.0068 deaths per 100,000. However, observing that zero is in the confidence interval and that the t-statistic is borderline significant, it is likely that there is no effect at all. While this is still a positive number, its suggested effect is so small, it becomes negligible. This can be determined by looking at the average crude rate for alcohol related deaths, which is 15.8. There would have to be an additional 147 MMICs per 100,000 to increase this crude rate by 1 death per 100,000. This is a highly unlikely scenario, and could therefore be dismissed. By applying this same model to drug-related deaths, we again get a statistically significant positive effect on the crude rate, shown in Table 5.10. While this would typically suggest that marijuana is a complement drug to other drugs, the effect is again, miniscule. With the average drug-induced crude rate of 13.4 deaths per 100,000, the number of medical marijuana cardholders would have to increase by 142 to cause 1 drug-related death. Similar to the effect on alcohol-induced mortality rates, this is a very unlikely event, and can be disregarded. While the drug and alcohol related deaths were affected slightly by medical marijuana, all other crude rates did not. There was no statistically significant effect when applying Equation 5.7 to all other crude rates. After implementing all regressions, there is evidence to suggest that medical marijuana has a negative effect on crime rates, decreasing total crime by 1.5 per 100,000 for every additional MMIC issued. It is also found that medical marijuana has a significantly negative effect on both property crime and larceny/theft rates. While medical marijuana could not completely alleviate crime all together because of the significantly higher crime rate average, there is no evidence that marijuana use would increase crime; thereby disproving the common argument that implementing marijuana legislation will increase crime rates.