The findings by Register & Williams , who use the 1984 wave of the NLSY, concur in that general marijuana-use to have a positive effect on wages. These results, in conjunction with less extreme conclusions by Kaestner and Burgess & Propper , who conclude that illicit drug use does not have a significant adverse impact on employment, reveal how the widely accepted perceptions on the effect of illicit drug use on labor market outcomes is, in fact, far from conclusive. One factor contributing to this apparent heterogeneity among study findings may be the widespread presumption that substance abuse is strictly an exogenous factor predicting labor market outcomes. Rather than treating both as bivariate markers of a complex change process over time , prior studies have often been quick to designate elicit drug use as a predictor for labor market outcomes, without sufficient justification to rule out the possible need to consider the effect in the opposite direction . Indeed, despite the recognition for the need to statistically model the fully dynamic and reciprocal nature of these multivariate longitudinal outcomes , attempts to implement such analyses is a relatively recent development . Needless to say, failing to account for the simultaneity between the bivariate responses of repeated measures data may impact the conclusions reached in comparison to a joint model that concurrently analyze both outcomes within a single analytic framework . To simultaneously analyze the joint processes between the two markers of change – developmental pathway of marijuana-use and employment – the bivariate random intercept and slope model is applied in the present study.
Building on the multilevel modeling framework to study the relationship between change and initial value in a linear growth curve setting,vertical racking system the main advantage of BRISM lies in its ability to utilize the inherent cross-correlated structure of truly multivariate repeated measures outcomes. The approach allows for the assessment of the association between one growth curve coefficient and another after adjusting for key covariates for all of the response variables, as well as estimation of cross-correlations between two, or more, slopes and intercepts . In addition to accounting for the potential confounding influence of reverse causality , joint modeling of multivariate longitudinal outcomes also encapsulates the upshot issue that the life-course trajectory of illicit drug use as well as employment is dynamic . Levels of illicit drug use and labor market outcomes tend to vary over ages especially during the transition period from adolescence to young adulthood. Substance abuse behaviors may undergo dramatic changes as adolescents mature physically and mentally, develop better decision-making skills, and take on new roles and responsibilities as they transition into adulthood . Concurrently, levels of employment may fluctuate substantially during this transitional period as these individuals complete their education, begin initiating into the workforce, and enter into marriage and parenthood . With the magnitudes and direction of correlation between longitudinal illicit drug use and labor market outcomes presumably varying at each life stage, it is essential to treat an individual’s drug use trajectory as an interdependent outcome measure.
The present study contributes to the literature by examining the bidirectional longitudinal effects of substance use and employment outcomes while properly accounting for dynamic interdependencies between two concurrent repeated-measures outcomes and important covariates such as gender. Previous studies have found that males and females differ considerably in terms of their illicit drug use patterns as well as in labor market outcomes . French et al. , for example, found that when the “ever in lifetime” drug use measure was decomposed into marijuana-use and other drug use, females who used marijuana in their lifetime were more likely to be absent during the past year than female employees who had never used drugs. Buchmueller & Zuvekas concur with strong evidence that problematic drug use is negatively related to income, particularly for primeage males. Application of bivariate random intercept and slope modeling framework allows for cross-correlation among the initial status and longitudinal trajectories of the two outcomes to be quantified, while simultaneously accounting for unobserved person-specific variation across multiple time-points. The central purpose of the study is to construct estimates of the impact of drug use on the employment status for men and women, as well as assesses whether longitudinal employment trajectory is systematically related to marijuana-use trajectory, and to what extent the interdependence between the two longitudinal outcomes is confounded by gender. The data used in the analysis come from the National Longitudinal Survey of Youth , which is a longitudinal survey of a nationally representative sample of young men and women who were between 14 and 22 years old at the time of the first survey in 1979.
Annual follow-up surveys were conducted from 1979 through 1994, and biennially since 1996. These surveys collect extensive information on labor market behavior, educational experiences, and training investments over time, as well as detailed demographic information on participants’ military experience, income and assets, health conditions, attitudes and aspirations, geographic residence, family background, household composition, marital and fertility histories, child care, criminal behavior, and alcohol and drug use. For the present study, a total of 7,661 subjects who completed the follow-up in 2004 were included for the analysis . At each wave of the survey, respondents provided detailed information on their workforce participation in the past calendar year, including occupations of the jobs, number of weeks worked, hours usually worked per week, weeks out of the labor force, as well as start and end dates for each position held. The main outcome variable used for the analysis is percent of weeks worked per year, which was computed as the number of weeks worked during a year divided by number of weeks in the year, and ranges from 0 to 100%. To create a comprehensive picture of participants’ developmental trajectory of employment from the initiation of their formal career, this study examined employment status over a 17-year period starting at age 23, thereby excluding periods when many survey participants were full-time students and/or part-time workers. The latter cut-off of age 39 is due, in part, to the excessive missing data beyond this point. While some information on survey participants’ illicit drug use has been collected since the first survey in 1979 , more detailed data collection on substance use activities began with the 1984 survey. Among the fields included in the revised instrument were the types of drug used , age of first drug use , frequency of drug use within a participant’s lifetime, time period of most recent drug use, number of times drugs had been used in the past 30 days, whether the participant used drugs at work, and if so,indoor grow facility the frequency of drug use at work. Table 2 provides a descriptive overview of when illicit drug use begins for both genders, illustrating the gender-gap in substance abuse persistent across drug types. Adopting the life-course perspective drug use trajectory framework , the analysis for the present study focuses on marijuana-use from age 23 to 39, as one of the two longitudinal outcome variables. As summarized in Table 1, the average age of the 7,661 subjects at intake was 17.5 for males and 17.6 for females, and the majority were not and had never been married at intake . Ethnicity composition was similar between males and females with about 50% non-Hispanic Caucasians, 31% African American, and 19% Hispanic. Average years of education at intake were 10 years for both genders. Notably, one area where males and females significantly differ is in the age when they first used two of the illicit drugs: Marijuana and Cocaine. The difference is particularly pronounced for marijuana, where the average age of first-time use is 15.32 for males and 16.12 for females. Figure 1 shows the empirical mean employment for male and female survey participants respectively, and contrasts the longitudinal trajectories for each gender by those who had ever used marijuana to those who had never used.
While an upward trend in employment is evident in both genders, a closer comparison of the longitudinal trajectories reveals that the male employment trajectories are persistently higher than those of females, reflecting the distinctly gendered patterns of employment – for men, full-time workforce participation is often initiated in early adulthood and remains relatively uninterrupted throughout the prime income earning years . Meanwhile, Figure 2 depicts the concurrent marijuana-use rate for each gender, with a gradual decline in usage in both groups as participants fully transition into adulthood . The empirical usage rate is consistently higher for males over females during the age range specified for the present study , indicating that the higher rate of marijuana consumption observed among adolescent males persist well into adulthood.Table 3 summarizes the parameter estimates for the variance covariance matrix D – corresponding to Equation – for both males and females from fitting the bivariate random intercept and slope model , while Table 4 expresses the same interdependence between the two repeated measures outcomes as a correlation matrix. Meanwhile, Table 5 provides residual variance-covariance matrix – corresponding to Equation – for both males and females. The covariance between the slope and intercept for the employment trajectories are substantial for both genders, with significant correlation for males as well as for females – see Table 4. The positive correlation coefficient estimates indicate that participants with a higher number of weeks worked at age 23 are more likely to maintain their productive employment status over subsequent years. However, the same cannot be said about their longitudinal marijuana-use trajectory. The slope-intercept covariance parameter estimate for the repeated measures outcome is almost non-existent, with non-significant negative correlation for both male and female participants. In other words, unlike the employment trajectories, a person’s marijuana-use status at age 23 is uncorrelated with marijuana-use trajectory during early adulthood. In addition to slope-intercept covariance specific to each of the two outcomes, BRISM estimates the cross-correlations among the four longitudinal growth parameters. As summarized in Table 3, the covariance between the two intercepts is significant for both genders. The negative correlation between the two random effects , indicates that survey participants with higher marijuana-use at age 23 tend to be less participatory in the workforce at that time. The covariance between the slope of marijuana-use and the employment intercept is also negative for the two groups , suggesting that those who were less participatory in the workforce at age 23 are increasingly likely to develop an illicit drug use habit in later years. While the covariance estimate between the intercept for marijuana-use and the employment slope are negative for both groups, the correlation is statistically significant for males but non-significant for females . While higher marijuana-use at age 23 is correlated with lower workforce productivity in later life for males, this relationship is not significant for their female counterparts. The genders also diverge in terms of their residual covariance between the two longitudinal outcomes . While the correlation is negative and statistically significant for males , it is non-significant for females . In other words, males with higher level of workforce participation are less likely to engage in marijuana-use, while this pattern does not hold for females. This study examined the association of marijuana-use and percent of weeks worked per year over time, and contributes to the growing body of literature by incorporating methodological analytic strategies that examine long-term patterns of employment in relation to drug-use trajectory. Adoption of a life-course perspective for the analysis of longitudinal substance abuse patterns facilitates a comprehensive examination of changes in workforce participation and drug use as cross-correlated repeated measures over age that more closely align with the multifaceted and dynamic nature of substance abuse in early adulthood. The key findings of the study can be summarized as follows: first, a negative correlation of marijuana-use with level of employment was initially observed for both genders. Concurring with the pool of empirical evidence from cross-sectional analyses , the present study suggests how current marijuana-use is negatively associated with contemporaneous measures of employment. Second, the parameter estimates from the BRISM revealed that employment at early adulthood was negatively associated with slope of marijuana-use trajectory.