Should Marijuana be Legalized?
Introduction
Supporters of decriminalization debate that, at most, decriminalization is anticipated to source a small increase in the sum of people who use marijuana. Decriminalization of marijuana would also have at most a small optimistic effect on the occurrence of its use. The supporters of decriminalization regard alcohol, marijuana and cocaine, comparatively, as the substitute drugs for getting high. On the other hand, if decriminalization cuts down the total costs, which includes the money price and legal risks, of marijuana, it will transfer the requirement for drugs to marijuana from alcohol and cocaine. For that reason, recriminalization of marijuana is likely to lessen the employment of alcohol and cocaine.
In the anti-decriminalization point of view, this would cause a large increase in marijuana users as this process gives people, in particularly young ones, a negative signal about marijuana (Martin, 2008).
The future of these two ones stands on marijuana, concerning the effects of decriminalization of this drug on the kind of a drug usage being fairly diverse. As these forecasts are so discrete, an experiential analysis can potentially distinguish between these two opposing views.
Changes in Use upon Decriminalization
There has been a little evidence concerning the effect of decriminalization of marijuana on the drug use. Arnold S. Trebach argues that the drug usage fell in Holland following that the country's decriminalization of this drug in 1976. G. Sylbing and J.M.G. Persoon have presented the findings of a 1983-year survey of the marijuana use among young people in Holland. The current users, not including those that report of its usage "less than once a month," were 3.0 % of the sample. Those reporting of its usage "less than once a month" were 2.4 percent, which is low comparing to the use of this drug by the American youth. Admittedly, it is difficult to draw some conclusions from a cross-cultural comparison such as this. In addition, it must be pointed out that the decriminalization of marijuana in Holland is a part of the strategy to curtail the use of dangerous drugs. Thus, the law enforcement officers there do not consider themselves "soft" on drugs (Morrissey, Keogh, & Doyle, 2008).
There is also another way to determine what impact marijuana’s decriminalization would have on the drug usage: non-users can be asked if they would start using marijuana upon its legalization. During 1972 and 1973, the National Commission on Marihuana and Drug Abuse conducted a survey. Those who said that they did not use the drug were asked whether decriminalization of marijuana would make them use it. Surprisingly, only 12 and 8 % of non-using young people and 4 % of non-using adults claimed that they would try the drug if it was legalized.
A third approach to ascertaining the effect of decriminalization of marijuana upon drug use is to conduct a before-and-after study, or even a full-blown trend analysis of drug usage within a state that has decriminalized. Following Oregon's 1973 decriminalization of marijuana, a survey of marijuana use in that state was conducted annually, from 1974 to 1977. "Current use," defined as use within the past month, rose from 24 to 30 percent among 18-29 year olds. Thus, current use went up in Oregon during this period. However, current use was also going up nationwide during this period (Nash, 1997).
Lloyd D. Johnston, Patrick M. O'Malley and Jerald G. Bachman systematically track the marijuana use in decriminalization states relatively to other states using the data of an annual survey of high school seniors. While its usage was somewhat higher in the states that had decriminalized it, this was true both before as well as after they decriminalized it. Significantly, given the national trend at the time of rising marijuana use, the difference between decriminalizing and other states did not increase. The researchers concluded that decriminalization had had virtually no effect on the marijuana use among American young people in this age group (Weill & Rosen, 2004).
The fourth approach, and the one we have employed in this study, involves the use of an econometric analysis to identify the contribution of legal sanctions for the marijuana use to the individual reported drug usage. While multiple regression analysis and related statistical methods have been used to identify the variety of sociological and psychological determinants of a drug usage, ours is the first attempt to use this methodology to identify the contribution of individuals' state legal sanctions for marijuana usage.
The data set used in the analysis is derived from the National Longitudinal Survey of Youth. Started in 1979, the NLSY is an ongoing and annual survey of the work experienced and socioeconomic conditions of 12,686 individuals being between the ages of 14 and 21 during 1979. In 1984 and 1988, the supplementary questions on the drug use were included. The samples we have abstracted are males for whom the complete data are available (Simons & Carey, 2006).
Results report of the current use of alcohol, marijuana and cocaine based on the 1984- year and 1988-year responses. The rates of use roughly correspond with those obtained by the National Institutes for Drug Abuse for 18-25 year old males in the surveys of 1985 and 1988. States that have decriminalized marijuana are found to have the slightly higher rates of the drug use than other ones. Because of the possible differences in these states' populations these small differences in the drug use cannot be automatically attributed to decriminalization.
It should be noted that we are analyzing a reported drug usage, which may differ from an actual usage. Barbara S. Mensch and Denise B. Kandel have identified some underreporting, especially with the reference to the cocaine use. The regressions pertaining to it may, therefore, be suspect. Finally, the substantial difference, in the alcohol intake of those having marijuana at least once during the past month taken six or more drinks at one time versus the alcohol intake of other users of alcohol motivates our separate analysis of the former one.
The Regression Models
Our regression models posit that an individual's reported drug usage for each of three drugs, i.e. alcohol, marijuana and cocaine that are the functions of legal sanctions imposed by that individual's state for possession of small amounts of marijuana. This comes along with two other measures of the state control for drugs and a set of demographic, economic, sociological and psychological factors.
One of the two other measures of state control for drugs identifies whether an individual is not at the legal age to purchase beer, wine or other forms of alcohol. This variable is operative only in the 1984-year equation when the number of persons in the sample was between 18 and 20 years old and when the legal drinking ages varied across the states.
The other control of a supply variable is the ratio, in 1984 and 1988, of the total number of arrests, excluding those for minor traffic violations. Such arrests end up with those for violent crimes such as murder, assault and robbery in the individual's state. This variable attempts to control the variation among states at their levels of enforcement of "common crimes". This includes the so-called victimless crime laws. We do not have the data specifically on victimless crimes and arrests. That is why we use the broader "common crimes", the arrest data.
Furthermore, we have two sets of regression models. The first set pertains to the dichotomous choice of being a current user or not. The other set being restricted to current users pertains to the frequency of the current use. The dichotomous choice equations are structured as logistic ones. The parameters being estimated are not themselves easily interpreted. Due to the way the data are coded, the frequency of using equations is structured as truncated Tobit models. The parameters, estimated by this model, are directly interpreted as partial derivatives.
In addition to the drug policy variables, a number of other control variables is included in regression models. These ones include a usual list of variables included by econometricians analyzing the behavior while using the survey data, i.e. age, education, a marital status, ethnicity and urbanization. In addition, we include the parents' education, a religious participation, an income and wealth measure, as well as a measure of failure and of the subjective well-being. We have experimented with various combinations of these control variables. The reported estimates of coefficients of the drug policy variables are not materially dependent on the particular set of control variables employed.
Discussion of Results
The estimates of the greatest interest pertain to the effects of decriminalization of marijuana. They are mostly insignificant. That is, there is no evidence that would prove that decriminalization has an effect either on the frequency of use or the choice of drugs, regardless whether it is a legal drug (alcohol) or an illegal one (marijuana or cocaine). The few exceptions are interesting.
In the 1984-year survey, when cocaine was a "hot" drug, the states that had decriminalized marijuana had more users of cocaine. This can be taken as the evidence that this is a "gateway drug" to more dangerous ones. However, from the results we have found that those that used cocaine in these states had used it less frequently. A larger number of users of the small amount of cocaine in decriminalization states may be taken as refuting the argument that the decriminalizing process leads to a compulsive use of more dangerous drugs (Morrissey, Jenm & Doyle, 2008). In addition, in 1988, decriminalization states featured fewer people taking "six or more" drinks of alcohol at the time. This may be the proof e of the substitution effects discussed above.
Enforcement efforts as proxied by the total number of arrests relatively to the number of arrests for violent crimes appear to lower the number of drug users. The state with as many arrests for “common crimes" as it had such for a violent crime, as opposed to the state with no arrests for other than a violent crime, would have had about 1.5 percent less marijuana users in 1988. Somewhat curiously, due to the fact that alcohol is a legal drug, this index of enforcement also appears to lower the alcohol use.
The third drug policy, not a legal drinking age, operating only in the 1984 sample, appears to have been effective in persuading young people not to experiment with cocaine when it was the "hot" drug. Other effects are insignificant but suggestive, i.e., the high legal drinking ages that may reduce the use of alcohol and increase the use of marijuana.
Among the set of control variables, the most consistently significant ones are religious activities, a marital status and education. Persons who report of the more frequent attendance of religious services also report of the less usage of drugs. In addition, religious people that use alcohol use less of it. These findings contrast sharply with those of Robin Sickles and Paul Taubman. They have found out that "no religion" had a significant and negative impact on marijuana and cocaine usage. The probable reason for the difference is the use of the person's self-identification with religious denominations and our use of the person's attendance of religious services.
Being married, like being religious, decreases the probabilities of using each of these three drugs. Among those drinking alcohol, the frequency of alcohol use decreases. It could be that the negative impact of marriage on the drug use by young men is due to maturity not reflected at the physical age (Feltenstein, 2008).
The more years of education the person has, the less likely is to use any of illegal drugs. However, there is some evidence that additional years of education increase the probability that the person consumes alcohol. However, not six or more drinks at a time may be drunk. In addition, more educated people using drugs report of consuming less.
The more years of education of these young people's parents, the more likely are they are going to use drugs. This result may be cohort specific. Given the ages of young people in the sample, many of their parents were at the college age during the 1960s, when many of those who were at college experimented with marijuana and other illegal drugs.
Less consistently significant are the wealth and failure variables. The wealth variable represents the sum of the human and financial capital. Wealth appears to shift the demand for drugs from marijuana to cocaine in 1984 as well as from marijuana to alcohol in 1988. Marijuana appears to be a cheap drug, so that as the wealth increases the demand for the shifts from it to other drugs appears. The reason that marijuana is not expensive may be in the heavy taxation of alcohol and the severity of criminal sanctions applied to cocaine use relatively to marijuana one.
The failure index is constructed from the variables denoting unemployment, being on the public assistance, fired, feeling discriminated against, and being unsatisfied with the job. It is designed to capture in one variable the influences on the demand for drugs presumed in the underlying variables. Gary S. Becker and Kevin M. Murphy, for example, have developed a theoretic model in which the temporary stress plays a very important role in addiction. The failure, as we have measured it, results in fewer people using alcohol. However, this does increase the frequency of using alcohol.
In unreported regressions, in which the underlying variables have been entered directly into the model, some of them were found to contribute to the demand for drugs. Having been convicted, fired, feeling discriminated against and not being satisfied with the job were each found to have increased the number of marijuana users in both the 1984-year and 1988-year samples. However, these results were not achieved for either the number of alcohol or cocaine users, nor were they achieved in any of the frequency of use models. Thus, Becker’s and Murphy's theory appears to be verified in so far as the failure leads to an increased use of marijuana and the frequency of consuming alcohol (Nash, 1997).
The coefficient on the variable block may appear unusual and implying as it does that young black men use drugs less than the white youth. In fact, the self-reported drug use by African Americans is lower than it is for European and Asiatic Americans in these surveys. Furthermore, Sickles and Taubman find that the contribution of being black to use drugs is highly sensitive to include a variable. The latter one has been constructed from the deviations of respondents' wages predicted by a human capital model estimated.
As already noted, the changes in the set of control variables did not materially affect the estimates pertaining to the drug policy variables. Nevertheless, the additional work would seem to be in order to quantify the influence of such as the failure and wealth on a drug use. In particular, it may be useful to investigate the extent to which the demand for drugs differs among identifiable subgroups of the population.
It is also interesting that the frequency of drug use models for illegal drugs, i.e., marijuana and cocaine, is not very well estimated, as reflected in their paucity of significant variables. This could simply reflect their small sample sizes. Alternately, this could display a difficulty in forecasting the frequency of the illegal behavior.
Conclusion
To be sure, we have not found a strong evidence of the substitution effects hypothesized by some advocates of decriminalization. Also, we have not found the good proof of the drug gateway effects hypothesized by some advocates of decriminalization. “States that have decriminalized marijuana did not suffer epidemics of marijuana use, or epidemics of other drugs, relative to states that continued to apply criminal sanctions to possession of small amounts of marijuana” (Martin, 2008).
The one statistically significant evidence of the increased drug use associated with decriminalization is the higher number of cocaine users. They were apparently using small amounts of —this drug in 1984. While not indicating that decriminalization of marijuana leads to a compulsive use of more dangerous drugs. It does indicate that the decriminalization of marijuana can lead to an increased experimentation with more powerful drugs.
With the 1988-year sample, about the only effect of the continued criminal sanctions on marijuana appears to be somewhat a lower use of marijuana in conjunction with somewhat greater "six or more" uses of alcohol. This constitutes a weak support of the drug substitution argument advanced by the advocates of decriminalization.
Our findings can, therefore, be said to lean to the direction of the pro-decriminalization view of the effects of decriminalization. Stated conversely, recriminalization of marijuana is unlikely to yield a significant reduction in the use of this drug or, for that matter, other legal or illegal ones (Feltenstein, 2008).
Certain findings can be cited as supporting a pro-active role for law and social institutions in reducing the use of drugs. States with many arrests for "common crimes" have a lower incidence of the drug use, including the consumption of legal as well as illegal drugs. Furthermore, the person's education and participation in the family and religious activities lower the use of illegal drugs and the frequency of use of them. This is not to say that there is the strong evidence that criminal sanctions for possession of small amounts of marijuana have been effective in reducing the drug abuse. It says that economic incentives and society's expectations of self-responsibility have taken place (Simons, Gaher, Correia & Bush, 2005).
