Compared to the national data, the WSU sample pre-RML appears to be more white, more likely to be in a fraternity or sorority, more likely to live off campus or in a fraternity/sorority house, and less likely to live with parents. We will see based on the regressions that although these variables are associated with higher likelihood of marijuana use, they are also associated with a lower likelihood of increasing use after RML. To the extent that differences in composition between the WSU and national samples affect differences in the trend of marijuana use, we expect that such differences are likely to bias against an observed relative increase in use at WSU. We also compare pre-RML marijuana use between the WSU sample and the two national samples. Fig. 2 shows the percentage of respondents each year who have used marijuana in the past 30 days for all three samples. The NCHA national data is only through 2011.For the national NCHA data after 2011 and for the WSU data after 2012, we forecast each series based on the data through 2012. Forecasts are generated using best-fit double exponential smoothing to account both for levels and for changing trends.Both the national NCHA and NSDUH data show an increase over the period before 2012 and are consistently within 1 and 4 percentage points of each other. The WSU series starts out slightly lower than both national series but with a nearly parallel trend and remains in the range of both national series through 2012. Readers will note the relatively large increase in the WSU series between 2008 and 2010, which corresponds to changes in Washington’s MML laws. Though the magnitude is smaller, we observe an increase at this same time in both the national samples. It may be the case that national changes affected students both in and out of Washington. Any long-term effects of such national changes are reflected in the NSDUH data. The forecasts for both the WSU and the national NCHA samples are almost parallel to the actual trend in the NSDUH and the 95-percent confidence interval for each forecast contains the other forecast as well as the NSDUH actual values. It appears that the increase in marijuana use at WSU after 2008 may have been a one-time jump,grow tent indoor a proposition more fully examined in the conclusion of the paper.

It is also relevant to note that both national samples are “contaminated” with observations from WSU and from others in Washington and Colorado.9 If RML increases marijuana use for college students, as we expect, then including Washington and Colorado students in the national samples biases against finding an effect in the difference-in differences analysis.Estimates for the logit regressions on the probability of having used marijuana in the past 30 days are reported in Table 3. The far-left column shows the basic regression, controlling only for a linear trend. Column 2 shows the results of the regression with demographic controls added. Columns 3 and 4 show the results with more co-variates added, some potentially endogenous. Controlling for a predicted increase of about 1.2 percentage points each year, we find that marijuana use among WSU students increased between 2.0 and 3.5 percentage points after RML and remained higher through 2015. Each estimate across specifications is statistically different from zero with at least 95-percent confidence. We find no evidence that legal sales had an additional impact on the proportion of marijuana users. The additional change after legal sales is consistently positive but not statistically different from zero at conventional levels; t-scores for these differences range from 0.43 to 0.88 . This regression model also provides estimates of relative marijuana use among WSU students. Male students are between 2 and 7 percentage points more likely to have used marijuana than females. Black and white students are the most likely to use marijuana compared to other races with Asian students being the least likely. In results not shown , we also see a decreasing likelihood of marijuana use with age of about 3 percentage points per year after age 20. After controlling for GPA, Greek membership, residence, and international status, 1st-year undergraduates are the most likely to use marijuana by between 3 and 5 percentage points over students of other years. International students are between 4 and 7 percentage points less likely to use marijuana than domestic students. Students with a 4.0 GPA are between 3 and 10 percentage points less likely to use than other students. Students in fraternities or sororities are between 4 and 12 percentage points more likely than other students.

Finally, the likelihood of marijuana use is positively correlated with the use of tobacco, alcohol, and illegal drugs.different subgroups and present the results in To better understand the impact of RML, we repeat the analysis for Table 4. Results of these regressions are generally consistent across all four specifications for each group. For brevity, we report only the results that include controls for age, sex, race, and year in school . The proportion of each group that reported having used marijuana before 2014 is included at the bottom of each column. Though the estimates differ greatly in magnitude, and only a few of the estimates are statistically significant at conventional levels, all groups are associated with a positive increase above the trend in marijuana use after RML. The results suggest marijuana use by underage students increased at least as much as that by legal-age students after RML. The estimates for the increase in underage students’ likelihood of using marijuana are large and statistically significant with a p-value < .01, while the estimates for legal-age students are smaller and not statistically different from zero. Using a chi-squared test after estimation, the differences between the two groups’ estimates for 2014 and 2015 have p-values of 0.206 and 0.955, respectively. We also note that the difference between the estimates for 2015 and 2014 for legal-age students is marginally statistically significant with a p-value=0.081, indicating that legal-age students waited to use marijuana until after they could obtain it from authorized distributors. The subgroup analysis provides insight into which groups are driving the changes overall. There is a relatively large increase in likelihood of marijuana use for Black and Hispanic Students, although only Hispanic students showed changes that are statistically significant with a p-value < 0.05. The likelihood of marijuana use among Black and Hispanic students increased in 2014 by 15.8 and 14 percentage points, respectively. This change represents an 88-percent increase in recent users for Black students and a 93-percent increase for Hispanic students. This is 8–9 times the estimated effect for Asian and white students. This relatively large increase is made more significant by the fact that it occurs over a previously non-increasing trend for both groups. In fact, though not statistically different from zero, Black and Hispanic students are the only groups with estimated negative trends over this time.

In other words, both groups started out with a proportion of marijuana users that remained essentially constant since 2005 until RML, after which Black and Hispanic students were among the most likely students to have used marijuana. Females are the group with the next highest increase after RML that is statistically significant with a p-value < 0.05.Results from the logit regressions on the likelihood of using tobacco, alcohol, or illegal drugs are reported in Table 5. Again for brevity, we report only the results for the regressions that include controls only for age, sex, race, and year in school. For convenience, we report again the estimates for marijuana use from column 2 of Table 3. On average, the yearly trends in the likelihood of use for tobacco, alcohol, and illegal drugs are in the opposite direction and significantly smaller in magnitude than the yearly increase of 1.2 percentage points in marijuana use. No significant changes occur in 2014. In 2015, the only significant changes include a 2.4-percentage-point decrease in the likelihood of using tobacco and a 2.2-percentage-point increase in the likelihood of using other illegal drugs. These results imply a possible substitute/complement effect or a spillover effect on norms against other illegal drugs, though the changes did not occur until a full year after the major changes in marijuana use. Additionally, relative to the changes for marijuana, the changes for tobacco and illegal drugs are not as robust to alternative specifications and estimation methods . We see no evidence that RML or legal sales affected the use of alcohol. Overall, grow tent hydroponic our results do not support any systematic changes in other substances that occur parallel with changes in marijuana use. This supports a conjecture that RML was the cause of the changes we find for marijuana.Results of the OLS regressions with respect to regularity of marijuana use are presented in Table 6. In 2014, we find an increase of about 0.5 days in the past 30 days above a linear trend of between 0.13 and 0.16 days per year.This increase is statistically significant across specifications with at least 95-percent confidence. The estimates for after legal sales are smaller than for after RML and are not statistically significant at conventional levels. Though the magnitude of the estimates in 2015 are not significantly lower than in 2014, the lack of a significant increase in 2015 could indicate that the effect of RML on frequency is short-lived and the equilibrium trends in frequency are unaffected by legalization. Alternatively, this may indicate that a proportion of students who began using before legal sales of marijuana are more likely to use it more frequently than those who waited.

The calculation of the difference-in-differences estimations are reported in Table 7. Using the national NCHA forecast as a counterfactual, the estimated effect of RML is an increase of 8.6 percentage points. Using the NSDUH, the estimated effect is 9.6 percentage points. These estimates are both statistically significant with over 99-percent confidence and are 3–5 times larger than the estimated increase over a linear trend in the regressions. Although limited by not accounting for covariate changes over time, the difference-in-differences estimations suggest that the increase over a linear trend in the regressions may be a conservative estimate of the effect of RML on the likelihood of using marijuana.Substance use among young adults is a major public health concern and is associated with academic problems. The bulk of research in this area has focused on undergraduate students, as alcohol and marijuana use among this population are fairly common . In addition to academic difficulties, alcohol and marijuana use are associated with other negative consequences during the college years, including risky sexual behaviors, social and interpersonal problems, injury, and impaired driving . Longitudinal research has shown that alcohol and marijuana use during college might have long-term consequences after college graduation. Heavy drinking and marijuana use during college are associated with post-college substance abuse and dependence, unemployment, less prestigious employment, and lower income . Marijuana use during college and the immediate post-college years, particularly heavy use, is associated with several negative health outcomes at ages 24 and 27, including emotional problems, injury, illness, decreased quality of life, and less service utilization for physical and mental health problems . Degree non-completion as a consequence of substance use has been found in longitudinal studies of high school and college students. Adolescents who use alcohol, tobacco, and marijuana during ninth grade are less likely to complete high school than non-drug users . One study integrated data from three longitudinal studies and found that daily marijuana use during adolescence was significantly associated with decreased odds of both high school and college completion . In a study of college students, frequent marijuana use during the course of college was associated with increased likelihood of dropping out . Despite evidence of associations between alcohol and marijuana use and high school and undergraduate degree non-completion, the possible impact on graduate degree completion has not been explored. An increasing number of college graduates are enrolling in graduate school, with almost 40% of college graduates pursing a graduate degree within four years of graduation . However, only 50% to about 75% of those who enter graduate school ultimately complete their degree, with differences by degree type and academic discipline .