Health Behaviors and Labor Market Status: The Impact of Substance Abuse Samuel Zuvekas and Philip F. Cooper and Thomas C. Buchmueller

Agency for Healthcare Research and Quality Working Paper No. 05013 April 2005

Suggested citation: Zuvekas S, Cooper PF, Buchmueller TC. Health Behaviors and Labor Market

Status: The Impact of Substance Abuse. Agency for Healthcare Research and Quality Working

Paper No. 05013, April 2005, http://gold.ahrq.gov.

AHRQ Working Papers provide preliminary analysis of substantive, technical, and methodological

issues. The papers have not undergone external peer review. They are distributed to share

valuable experience and research. Comments are welcome and should be directed to the

authors. The views expressed are those of the authors and no official endorsement by the

Agency for Healthcare Research and Quality or the Department of Health and Human Services is

intended or should be inferred.
 

Health Behaviors and Labor Market Status: 

The Impact of Substance Abuse 

Samuel H. Zuvekas; Philip F. Cooper; and Thomas C. Buchmueller 

February 2005 

ABSTRACT 

Previous studies on the effects of illicit drug and alcohol consumption on labor market 

outcomes have been mixed, with some studies even finding positive effects of drug and 

alcohol use on wages and employment status. Buchmueller and Zuvekas (1998) argue 

that it is necessary to separate out moderate use from more problematic use or abuse in 

understanding labor market impacts. We extend their work in two important directions. 

First, we use data from the 1992 National Longitudinal Alcohol Epidemiologic Survey 

(NLAES), which provides a larger (n=42,862) and nationally-representative survey, with 

improved labor market measures and similarly rich measures of alcohol and drug use and 

problems. Second, we jointly analyze the impacts of alcohol and drugs, whereas their 

previous work considered only drug use and abuse. Indeed, most of the previous 

literature focuses on either alcohol or drugs, but not both. Overall, we find that drug 

disorders are negatively associated with the probability of being employed but not 

earnings, while moderate drug use was not statistically associated with either outcome. 

We find no statistically significant effects of alcohol abuse on either employment or 

earnings. 

Samuel H. Zuvekas 

Senior Economist 

Center for Financing, Access, and Cost Trends 

Agency for Healthcare Research and Quality 

540 Gaither Road 

Rockville, MD 20850 

Email: szuvekas@ahrq.gov 

Philip F. Cooper 

Senior Economist 

Center for Financing, Access, and Cost Trends 

Agency for Healthcare Research and Quality 

540 Gaither Road 

Rockville, MD 20850 

Email: pcooper@ahrq.gov 

Thomas C. Buchmueller 

Graduate School of Management 

University of California-Irvine 
 

Acknowledgments 

The authors are grateful to Bridget Grant, National Institute on Alcohol Abuse and Alcoholism 

for providing us with the data for this study. This paper was previously presented at the Western 

Economic Association meetings, San Diego, July 1999 and the Southeastern Economic 

Association Meetings, Arlington, VA November 2000. The views expressed in this paper are 

those of the authors, and no official endorsement by the Agency for Healthcare Research and 

Quality or the Department of Health and Human Services is intended or should be inferred. 
INTRODUCTION 

Conventional public policy wisdom holds that illicit drug use has large negative effects 

on productivity and labor market outcomes. Estimates of the productivity losses due to drug 

abuse and addiction range from $9 billion (Rice et al. 1990) to $37 billion (Harwood et al 1984), 

with the most recent estimates placing the figure at about $23 billion (Office of National Drug 

Control Policy, 2001). In contrast, evidence from a number of econometric studies over the 

decade is mixed. Earlier studies not only failed to find adverse effects, but often found positive 

impacts of illicit drug use on labor market success (Kaestner 1991, 1994, Gill and Michaels 

1992, Register and Williams 1992). Buchmueller and Zuvekas (1998) suggest that these studies 

failed to adequately discriminate between moderate drug consumption and heavy drug 

consumption or abuse/addiction. When separating moderate drug users from more problematic 

users, they find the expected negative labor market effects of drug problems. 

Other more recent studies find that chronic use or substance abuse substantially reduces 

the probability of employment (Alexandre and French, 2004; French, Roebuck, and Alexandre, 

2001; Terza and Vechnak, 2001). DeSimone (2002) using instrumental variables methods, also 

finds drug use reduces employment, although the study does not distinguish between types of 

use. However, the recent evidence of negative impacts of chronic or heavy use on hours worked 

and productivity is much weaker (Zarkin et al. 1998a; French, Zarkin and Dunlap 1998). 

The distinction between moderate consumption and heavy consumption or 

abuse/addiction appears to be important in the parallel literature on the labor market effects of 

alcohol use, as well. French and Zarkin (1995) and Berger and Leigh (1988) find positive effects 

of moderate alcohol consumption on wages. In contrast, Mullahy and Sindelar (1993, 1991, 

1989) and Ettner, Frank and Kessler (1997) all find negative effects of alcoholism on wages and 
employment. Similarly, Mullahy and Sindelar (1996) and Terza (2002) find negative effects of 

problem drinking on employment (although Mullahy and Sindelar’s IV estimates were 

imprecisely estimated and not statistically significant). French and Zarkin (1995) also find 

negative effects of heavy alcohol use on wages. However, Zarkin et al (1998b) find positive 

effects of both moderate and heavy alcohol consumption. 

We examine the question of the impacts of drug and alcohol use on labor market 

outcomes by extending the work of Buchmueller and Zuvekas (1998) in two general directions. 

First, we use data from the 1992 National Longitudinal Alcohol Epidemiologic Survey (NLAES) 

which is a larger (n=42,862), nationally-representative data source with better labor market 

measures and similarly rich measures of alcohol and drug use and problems. Second, we jointly 

analyze the impacts of alcohol and drugs, whereas Buchmueller and Zuvekas considered only 

drug use and abuse. Indeed, most of the previous literature focuses on either alcohol or drugs, but 

not both. 

Section II describes the NLAES sample used in our analyses. We restrict our analyses to 

males because of their greater likelihood of labor force participation and substantially greater 

likelihood of drug use and drug-related problems. Section III describes our methods, where we 

incorporate drug and alcohol measures into standard wage and employment models. Section IV 

presents descriptive results and estimation results from the wage and employment models. We 

conclude, in Section V, with a discussion of the implications of our results and the need for 

better methods to control for endogeneity. 
II. DATA 

The data used in this study come from the first and only wave of the 1992 National 

Longitudinal Alcohol Epidemiologic Survey (NLAES).1

 The NLAES was sponsored by the 

National Institute on Alcohol Abuse and Alcoholism (NIAAA) and was designed to estimate the 

prevalence of alcohol and substance use disorders in the U.S. The major strength of the NLAES 

lies in its comprehensive measures of both alcohol and drug consumption and the disorders 

associated with their use. Respondents were asked not only about their alcohol and drug 

consumption, but detailed question about associated symptoms (e.g. shakes, inability to stop 

using, interference with social activities, etc.) using a clinically-based diagnostic instrument. 

Alcohol and drug use disorders were then classified using clinical-diagnostic criteria contained in 

the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders, 

4th edition (DSM-IV) based on the responses to the symptom-based questions. These clinical 

measures of alcohol and drug use disorders allow us to separate casual drug and alcohol use from 

substance abuse and dependence. 

The NLAES is a nationally representative sample of the civilian non-institutionalized 

population. The U.S. Census Bureau fielded the survey and collected data from October 1991 to 

November 1992. In addition to measures of substance use and disorder , the NLAES contains 

socio-demographic characteristics including age, race, sex, and marital status, and labor market 

characteristics such as employment, wage income, industry, and occupation. 

Overall, the NLAES sample contains data on 42,862 persons aged 18 and over. We focus 

our analyses on men for two main reasons. First, men tend to have much greater rates of both 

drug and alcohol use and problems compared to women (Kessler 1994; Regier et al 1993). 

Second, men traditionally have greater labor force attachment. We limit our analyses to men 
 

aged 25-54 to minimize potential problems that might result from retirement decision of older 

men, and differences in the timing of entry into the labor market for younger men. In addition, 

we exclude full-time students and persons who have never worked. Our final sample of men 

aged 25-54 includes 9,820 persons. 

Drug and Alcohol Measures 

We combine two sets of measures from the NLAES data to characterize each person’s 

drinking and drug use patterns. The first set defines whether a person currently (in the last 12 

months) uses, formerly used, or never used alcohol and drugs, respectively. Persons who used 

drugs less than 12 times in their lifetimes were classified as non-users in the NLAES survey. The 

second set defines whether the person met clinical criteria for either dependency or abuse for 

alcohol and drugs, respectively, and whether this was ever in their lifetime or in the last 12 

months. We then classify each person into three mutually exclusive categories of lifetime 

alcohol use: dependence or abuse ever in lifetime, moderate use in lifetime, or lifetime nonuser. 

We do the same for lifetime drug use patterns, as well as current alcohol and drug use patterns. 

The measures of clinical dependency as mentioned above come from the DSM-IV criteria 

which include symptoms such as not being able to stop or limit use, and delusions as a result of 

use. Symptoms of drug or alcohol abuse include occupational impairment, according to DSM-IV 

definitions which were the basis of the original NLAES abuse measures. This creates the 

potential for an obvious endogeneity problem when using a measure based, in part, on 

occupational impairment to look directly at labor market outcomes. Following previous analyses 

(Buchmueller and Zuvekas, 1998; Mullahy and Sindelar 1993, 1991, 1989), we eliminated this 

potential endogeneity by reconstructing the NLAES measures without using occupational 

1

 Despite it name, the NLAES only collected data for a single cross-section. 
impairment as a criterion. However, like these previous analyses, we found a high degree of 

association between occupational impairment due to drug and alcohol abuse so that our 

redefinition affected only 10 people in all. 

In Table 1, we report descriptive statistics of our drug and alcohol measures for our full 

sample of men age 25-54 (column 1), as well as separately for those who are currently employed 

(column 2) and those who are not (column 3). In the first panel, we see that a fairly high 

proportion, 29 percent, of men experienced either alcohol dependence or abuse at some point in 

their lifetime. Another 54 percent had used alcohol but did not have problematic use and 17 

percent reported never having used alcohol. Drug use and problems were less common. About 

10 percent of men had a problem with drug abuse or dependence at some point of their lives, 15 

percent had used drugs moderately, and 74 percent had either never used drugs or used them just 

a few times (less than 12). Some 7.5 percent of men had an alcohol and drug problem (either 

abuse or dependence) in their lifetime, which means that three-quarters of those with a drug 

problem also had an alcohol problem. 

Rates of current (in the last 12 months) alcohol and drug use, and especially problems, 

are much lower than lifetime rates. Only 2 percent of men had a drug problem in the last 12 

months, and a further 5 percent had used drugs without signs of a drug problem. About 11 

percent of men experienced dependence or abuse problems with alcohol in the last 12 months, 

while 38 percent reported no alcohol use in the last 12 months. For this reason and because of 

potential endogeneity problems that we will discuss later in the paper, we concentrate on lifetime 

effects of drug and alcohol abuse/dependence. 
 

Labor Market Outcomes 

We use two measures of labor market outcomes as dependent variables in our analyses, 

current employment status and annual earned income. Annual earnings is a product of hourly 

wages and hours work.2 While hourly wages would provide a more direct measure of 

productivity, it is not available in the NLAES. About 92 percent of the men in our sample 

currently worked with average annual reported earnings of $34,581 in 1992 dollars (see Table 2). 

Other variables 

In addition to our measures of substance use and disorders, we include standard 

determinants of labor market outcomes including age, race/ethnicity, sex, current marital status, 

education, and geographic indicators. Age squared is included along with age to account for any 

non-linear relationship between age and labor market outcomes. Mutually exclusive indicators 

for black and Hispanic are used to describe race and ethnicity, with white and other groups the 

omitted category. For education, we include mutually exclusive indicators of having a high 

school degree, associate degree or some college, bachelor’s degree, and advanced degree, with 

less than a high school degree as the omitted category. Geographic indicators include the 9 

census divisions and an indicator for residing in an urban versus a rural area. Descriptive 

statistics for these variables are reported in Table 2. 

2 We also examined an alternative measure of monthly earnings from a separate series of questions about labor 

market outcomes in the NLAES. Our results were not sensitive to whether we used the annual or monthly measure 

of earnings, but we opt for the annual measure because there are fewer missing responses and to maintain 

consistency within a single series of labor market questions. 
III. Econometric Specification 

We estimate a probit model of current employment status and an OLS model on log 

annual earnings. We include on the right-hand side of the equations age and age squared, 

race/ethnicity, education, marital status, and geographic indicators as described above in addition 

to drug and alcohol measures. The potential endogeneity of drug and alcohol use and associated 

problems is an importation consideration in estimating their impacts on labor market outcomes. 

In addition to the endogeneity problem we addressed in the data section concerning occupational 

impairment, endogeneity may come from two other sources. First, there are likely income effects 

related to the consumption of drugs and alcohol, which might lead to a positive bias on our drug 

and alcohol coefficients. Second, those with drug or alcohol problems, those using drugs or 

alcohol without problems, and nonusers may differ in unobserved ways, including preferences, 

that are correlated with labor market outcomes. The direction of this potential bias cannot be 

signed a priori. 

We rely on our clinical measures of drug and alcohol problems, which are based on a 

person’s physiological and psychological responses to drug and alcohol consumption, to help 

minimize potential endogeneity. Buchmueller and Zuvekas (1998) argue that these clinicallybased measures should be “much less influenced by income than simple measures of use 

frequency.” Furthermore, physiological responses to drug and alcohol use (for example, 

propensity to become dependent) are, in part, genetically determined in ways that are unlikely to 

be correlated with labor market outcomes. We also follow Buchmueller and Zuvekas and 

Mullahy and Sindelar (1993, 1991, 1989) in using lifetime measures of drug and alcohol use and 

disorders, rather than current consumption, to further minimize potential endogeneity problems. 
It is expected that the endogeneity bias will be less than if regressing current employment and 

income on current alcohol and drug consumption. For example, current drug problems may 

result from poor labor market success. 

We considered, but ultimately rejected, the use of an instrumental variables approach 

used in some of the literature on the effects of drug and alcohol use on labor market outcomes 

(see for example, Terza and Vechnak 2001; Terza 2001; Mullahy and Sindelar 1996; Kaestner 

1991 ). Recent work (Rashad and Kaestner 2004) points to many potential problems with the 

state-level instruments commonly used in these studies such as alcohol and cigarette tax rates 

and prices. Other instruments commonly used include whether a person’s mother and father were 

alcoholics. While parental history of alcoholism is strongly correlated with both drug and 

alcohol problems, there may be direct effects of growing up in a home with alcoholics that 

influences future labor market success. 

A second key issue with respect to estimation of the annual earnings equation conditional 

on employment is selectivity bias. The Heckman model or (other sample selection models) 

would be a natural choice for this problem. However, we lack adequate exclusion restrictions to 

identify sample selection models, and such models are well-known to be quite sensitive when 

relying on functional form alone to achieve identification. We thus present estimates of the wage 

equation without correcting for possible selectivity bias. 

We correct the standard errors of all estimates for the complex survey design of the 

NLAES . 

IV. RESULTS 

Descriptive 
We report descriptive statistics for the labor market outcomes in Table 3. The first 

column reports the probability that a male aged 25 to 54 was currently employed at the time they 

were interviewed along and the second column reports the mean annual earnings among those 

currently employed. There were little or differences in the probability of employment by 

lifetime alcohol and drug use patterns. Men who had an alcohol disorder at some point in their 

life were equally likely as men who had never drunk alcohol to be currently employed (.91) and 

only slightly less likely than moderate alcohol users (.91 vs. .92, p=.09). Similarly, men who had 

a drug disorder at some point in their life were somewhat less likely (.90 vs. 92, p=.07) to be 

currently employed, but there was no statistically difference between moderate drug users and 

non-users. Differences among men by their current (last 12 months) alcohol and, especially, 

drug use patterns were greater. Current moderate alcohol drinkers were actually more likely than 

those who had not drunk alcohol in the last year to be employed (.93 vs. 91), while those with a 

current alcohol problem were less likely to be employed than either moderate or nondrinkers 

(.89). In contrast to moderate alcohol users, current moderate drug users were less likely to be 

employed than nonusers (.88 vs. .92). Men with a current drug problem were substantially less 

likely to be employed (.82) than either moderate or non drug users. 

Differences in earnings among those employed were generally greater than differences in 

employment by alcohol and drug use patterns. Men who had never used alcohol had the lowest 

average annual earnings ($29.0 thousand), while men who had used in moderate amounts ($37.1 

thousand) had the highest earnings. Those with alcohol problems at some point in their lifetime 

($33.0 thousand) fell in between. Interestingly, those with current (last 12 months) alcohol 

problems had on average about the same annual earnings as non drinkers, but current moderate 

alcohol users had the highest annual earnings of any group ($38.0 thousand). It is implausible 
that moderate alcohol use (either current or in the past) would have a strong direct effects on 

productivity and earnings either positively or negatively, so the higher average earnings among 

these men more likely reflects differences in observed and unobserved characteristics, such as 

personal preferences for alcohol consumption. 

Men with moderate drug use during their lifetime had slightly higher average earnings 

than nonusers ($36.2 vs. $34.8 thousand), while those with drug problems at some point in their 

life had the lowest earnings ($30.6 thousand). In contrast, current moderate drug users had 

16% lower earnings on average than either lifetime or current nonusers. In addition to being the 

most likely to be unemployed, men with current drug problems earned substantially less than any 

other group of men ($25.5 thousand) and more than 25 percent less than non drug users. 

While the bivariate results reported in Table 3 reveal interesting differences in average 

employment and earnings by alcohol and drug use history, they cannot tell the whole story. 

There are several confounding factors that may be driving these differences. Education perhaps 

being the most relevant example. If the more educated are more likely to consume alcohol and 

drugs, then the positive association of alcohol use and problematic alcohol use on labor market 

outcomes reported in tables 2 and 3 may not be due to use of alcohol, but instead, may be a result 

of education being a positive correlate of drinking. We turn now to our multivariate regression 

results to control for education and other socioeconomic differences in understanding the impacts 

of drug and alcohol problems on labor market success. 

Multivariate 

We report results from the probit regression on probability of current employment and 

the OLS regression on logged annual earnings if employed in Table 4. As described in the 
 

 

econometric specification section, we focus on lifetime measures of alcohol and drug problems 

to minimize potential endogeneity bias. We find that having a drug problem (abuse and 

dependence) at any point during a man’s life is associated with a 2.6 percentage point reduction 

in the probability of being currently employed (p=.06). We find no effect on the probability of 

being employed associated with having an alcohol problem . Moderate drug use was not 

statistically associated with employment. Specifications where we dropped this moderate drug 

use and focused strictly on the clinically-based measures of drug and alcohol problems yielded 

nearly identical results. 

Although there were large differences in average annual earnings by lifetime alcohol and 

drug use patterns as seen in Table 3, these differences disappeared after controlling for education 

and other sociodemographic characteristics. No statistically significant effects of either lifetime 

drug or alcohol problems and moderate drug problems were apparent.3 

The other independent variables behave as expected. Men who are white, married, have 

higher levels of education and who live in urban areas are more likely to be employed and have 

higher earnings than men who are Hispanic or black, single, who did not possess a high school 

diploma, and who live in non-urban area. As expected, age has a significant nonlinear effect on 

the probability of being employed and annual earnings. 

Sensitivity Analyses 

We also performed separate analyses for men aged 25-34, 35-44, and 45-54, respectively. 

Not surprisingly, income increased with age and men aged 45-54 were slightly less likely to be 

in the labor force compared to younger men. Men aged 45-54 were also less likely to report any 
 

 

alcohol and, especially, drug abuse or dependence then their younger counterparts. However, the 

relationships between drug and alcohol problems and labor market outcomes were similar across 

all three age groups, both in the descriptive and regression analyses. For the sake of parsimony 

and to increase statistical power, we report only the results for the three age groups combined. 

V. DISCUSSION AND SUMMARY 

We find a negative association between having drug problems and employment but no 

effects of lifetime drug problems on annual earnings conditional on employment. The increase 

of 3 percentage points in the unemployment rate among males associates with a lifetime drug 

problem is rather substantial. This increased unemployment may results from the direct impacts 

of drug problems, as well as difficulties in obtaining employment because of a criminal record 

associated with drug problems. 

The lack of a negative impact of lifetime drug problems on earnings conditional on 

employment is puzzling. Buchmueller and Zuvekas (1998) found substantial negative impacts of 

problematic drug use, on the order of 12 to 13 percent lower earnings. Both that study and our 

current study use data from epidemiologic surveys and similar econometric methods. However, 

there are substantial differences in the labor market measures available, definitions of drug 

problems (because of ongoing revisions to the psychiatric profession’s Diagnostic and Statistical 

Manual), and in fielding methods between the two epidemiologic surveys used which may 

account for these differences. Most notably the ECA survey used in Buchmueller and Zuvekas 

(1998) was not nationally representative, but was collected from five sites (Eastern Baltimore, 

New Haven, St. Louis, Los Angeles, and Durham, NC) during the early 1980s. Local labor 

3

 Some studies (Mullahy and Sindelar 1989; 1993; French and Zarkin 1995) have run specifications without 

controlling for educational attainment and marital status because of the potential for indirect effects of drug or 
 

market conditions of these five sites, may not have been reflective of the U.S. as whole, and 

unmeasured market characteristics may have altered the association between drug problems and 

earnings. For example, drug problems may have been relatively concentrated in areas with 

poorer economic prospects. Still, we had expected to find a negative association between 

lifetime drug problems and labor market productivity. We note though that French, Zarkin and 

Dunlap (1998) also did not find significant impacts on productivity. 

The stronger association between current drug and alcohol problems and poor labor 

market outcomes noted in the descriptive results (Table 3) warrants closer investigation. The 

problem comes in sorting out whether current drug and alcohol problems are the result of poor 

labor market outcomes or vice versa, as well as omitted variables bias due to other unmeasured 

preferences and characteristics. While some studies have attempted to use instrumental variables 

to address these problems, there are substantial questions about the instruments that have been 

proposed to date as we discussed earlier. As a result, we did not attempt to estimate the 

relationship between current drug and alcohol problems and labor market outcomes here, but 

continue to investigate potential methods and data sources for future work. 

alcohol problems on education and marriage. However, employment and wage regressions without education are 

clearly misspecified 
 

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Table 1. Drug and Alcohol Measures by Labor Market Status 

Variable Currently Not 

In Labor Force Employed Employed 

Alcohol Use (Lifetime) 

Dependence or Abuse 29.4% 29.1% 31.9% 

Moderate use 53.9% 54.2% 50.7% 

No use ever 16.7% 16.7% 17.4% 

Drug Use (Lifetime) 

Dependence or Abuse 10.3% 10.2% 12.9% 

Moderate use 15.3% 15.3% 15.5% 

 No or minimal use ever 74.3% 74.5% 71.6% 

 (< 12 times) 

Any Alcohol or Drug Disorder 7.5% 7.3% 9.0% 

(Lifetime) 

Alcohol Use (last 12 months) 

Dependence or abuse 11.3% 10.9% 15.7% 

Moderate use 50.4% 51.1% 42.3% 

 No use in last 12 months 38.3% 38.0% 41.9% 

Illicit Drug Use (last 12 months) 

Dependence or Abuse 1.9% 1.7% 4.1% 

Moderate use 5.4% 5.2% 8.0% 

 No use last 12 months 92.7% 93.1% 87.9% 

N 9,820 9,018 802
 

 

 

 

 

 

 

 

 

 

Table 2 Descriptive Statistics 

Employment Regression Wage Regression 

Variable Mean Std. Err. Mean Std. Err 

Probability of Employment .918 (.004) 

Annual Earnings 34,581 (844) 

Log Annual Earnings 10.139 (.023) 

Age 38.016 (.100) 37.93 (.107) 

Age squared 1510.18 (7.75) 1502.44 (8.302) 

Black .106 (.007) .102 (.007) 

Hispanic .086 (.013) .083 (.012) 

Married .699 (.006) .711 (.006) 

High school diploma .294 (.009) .288 (.009) 

AA or some college .257 (.007) .259 (.007) 

BA .210 (.007) .217 (.007) 

Advanced degree .105 (.006) .110 (.006) 

Education missing .012 (.001) .012 (.001) 

Part-time student .008 (.001) .007 (.001) 

Urban .714 (.020) .717 (.021) 

Urban missing .021 (.002) .020 (.002) 

Census Division 1 .054 (.014) .053 (.014) 

Census Division 2 .152 (.050) .150 (.048) 

Census Division 3 .172 (.033) .172 (.033) 

Census Division 4 .063 (.012) .064 (.012) 

Census Division 5 .166 (.024) .168 (.025) 

Census Division 6 .054 (.010) .054 (.011) 

Census Division 7 .125 (.022) .124 (.022) 

Census Division 8 .059 (.009) .060 (.010) 

N 9,820 9,018 
 

 

 

 

 

Table 3. Employment and Earnings by Drug and Alcohol Use Characteristics 

Mean Annual Earnings 

If Employed 

(000s 1992 $) 

Variable Probability 

Employed 

Alcohol Use (Lifetime) 

Dependence or Abuse .91 (.006) 33.0 (0.7) 

Moderate use .92 (.005) 37.1 (1.2) 

No use ever .91 (.007) 29.0 (0.8) 

Drug Use (Lifetime) 

Dependence or Abuse .90 (.012) 30.6 (1.0) 

Moderate use .92 (.008) 36.2 (1.1) 

 No or minimal use ever 

 (< 12 times) 

.92 (.005) 34.8 (0.9) 

Any Alcohol or Drug Disorder 

(Lifetime) 

.90 (.013) 27.7 (1.0) 

Any Alcohol or Drug Disorder 

(Lifetime) 

.90 (.013) 27.7 (1.0) 

Alcohol Use (last 12 months) 

Dependence or abuse .89 (.011) 31.2 (0.7) 

Moderate use .93 (.005) 38.0 (1.1) 

 No use in last 12 months .91 (.005) 30.6 (0.9) 

Illicit Drug Use (last 12 months) 

Dependence or Abuse .82 (.026) 25.5 (1.6) 

Moderate use .88 (.014) 29.3 (1.3) 

 No use last 12 months .92 (.004) 35.0 (0.9) 

N 9,820 9,018 
 

Table 4. Regression Results 

Probit

Probability Currently 

Employed 

OLS

Log Annual Income 

if Employed 

Variable Coefficient Std. Err. Coefficient Std. Err 

Constant -0.200 0.249 7.813 *** 0.335 

Age 0.074 *** 0.025 0.077 *** 0.016 

Age squared -0.001 *** 0.000 -0.001 *** 0.000 

Black -0.194 ** 0.079 -0.227 *** 0.047 

Hispanic -0.157 ** 0.079 -0.131 *** 0.042 

Married 0.319 *** 0.040 0.232 *** 0.026 

High school diploma 0.163 *** 0.054 0.301 *** 0.050 

AA or some college 0.339 *** 0.066 0.474 *** 0.054 

BA 0.511 *** 0.073 0.720 *** 0.054 

Advanced degree 0.658 *** 0.102 0.844 *** 0.071 

Education missing 0.248 0.204 0.388 ** 0.166 

Part-time student -0.610 *** 0.170 -0.268 ** 0.129 

Urban 0.077 ** 0.054 0.067 ** 0.025 

Urban missing -0.133 0.126 0.097 0.129 

Census Division 1 -0.108 0.093 0.041 0.081 

Census Division 2 -0.069 0.098 0.059 0.067 

Census Division 3 0.064 0.094 0.031 0.050 

Census Division 4 0.140 0.127 -0.128 0.078 

Census Division 5 0.181 * 0.100 -0.016 0.058 

Census Division 6 0.110 0.098 -0.070 0.070 

Census Division 7 0.024 0.096 -0.193 *** 0.063 

Census Division 8 0.119 0.133 -0.131 0.073 

Drug disorder (lifetime) -0.167 * 0.088 0.001 0.042 

Moderate drug use (lifetime) -0.086 0.055 0.036 0.038 

Alcohol disorder (lifetime) -0.024 0.051 0.023 0.025 

R2 .103 

Sample size 9,820 9,018 

Standard errors are corrected for complex design of the NLAES survey. 

*p<.10,**p<.05,***p<.01