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The Economic Costs of Alcohol and Drug Abuse in the United States - 1992

Table 5.7

Studies of the Impact of Alcohol and Drug Abuse on Productivity

Study Data and Sample Principal Findings
Alcohol Studies
Berger and Leigh 1988 Quality of Employment Survey (1972-73), males and females age 18+ Positive effect of current alcohol consumption on wages. Estimated wages of drinkers exceed those of nondrinkers by 8-57% for men and 26-40% for women.
Heien and Pittman 1989 National alcohol survey (1979) Problem-drinking status endogenous. No significant effect of alcohol consumption on family income after accounting for this endogeneity.
Mullahy and Sindelar 1989 ECA (New Haven site only), males ages 25 to 59 Symptoms of alcohol abuse at young ages are associated with a 1.5-year reduction in educational attainment. No significant effect of current symptoms on current earnings.
Rice et al. 1990 ECA (multiple sites), males and females ages 18 to 64 Lifetime diagnosis of alcohol abuse is associated with a 1-9% reduction in personal income for males and a 1-19% reduction for females. Magnitude depends on age.
Mullahy and Sindelar 1991a,b ECA (multiple sites), males and females ages 18 to 64 Lifetime diagnosis of alcohol abuse/dependence is associated with reductions in the likelihood of working full time (7-19%) and personal income (3-23%).
Mullahy and Sindelar 1991a ECA (New Haven only), males ages 22 to 64 (mainly ages 30 to 59) Lifetime diagnosis of alcoholism is associated with reductions in the likelihood of working full time and in household income (17-31%). The magnitude of the estimates are sensitive to the model specification.
Drug Studies
Rice et al. 1990 ECA (multiple sites), males and females ages 18 to 64 Lifetime diagnosis of drug abuse/dependence associated with a 1-9% reduction in personal income for males (not significant) and positively associated with personal income for females (not significant).
Kandel and Davies 1990 NLSY (1984 and 1985), males ages 18 to 27 Use of marijuana is associated with an increase in employment gaps and the number of weeks unemployed. Use of cocaine increases job mobility, gaps, and unemployment. No effect of recent drug use on current wages controlling for previous years' wages.
Kaestner 1991 NLSY (1984) males and females ages 18 to 27 Use of cocaine and/or marijuana has positive effect on the wages of males and females after controlling for selectivity and endogeneity of drug use.
Register and Williams 1992 NLSY (1984), males ages 18 to 27 Predicted use of marijuana or cocaine negatively associated with employment, but long-term and on-the-job use are positively associated. Overall positive effect of marijuana use on wages. No significant effect of cocaine use on wages.
Gill and Michaels 1992 NLSY (1980 and 1984), males and females ages 18 to 27 Use of drugs significantly reduces the probability of employment. No significant effect of "hard" drugs on employment. Drug users have higher wages but lower returns to human capital characteristics than nonusers.
Kaestner 1994b NLSY (1984 and 1988), males and females ages 23 to 30 Positive effect of drug use on wages in cross-sectional model for males and females. Negative effect of drug use on wages for males (not significant) and positive effect (significant) for females in longitudinal fixed-effects model.
Kaestner 1994a NLSY (1984 and 1988), males and females ages 21 to 30 Marijuana and cocaine use have negative impact on labor supply in a cross-sectional analysis, particularly among males. Longitudinal analysis indicates no effect of illicit drug use on labor supply for males or females.
Buchmueller and Zuvekas 1994 ECA (multiple sites), males ages 18 to 45 Drug abuse has a significant negative impact on the likelihood of employment and on the income of males ages 30 to 45 but no effect on the employment or income of males ages 18 to 29.
Buchmueller and Zuvekas 1996 ECA (multiple sites), males ages 18 to 45 Drug abuse or dependence has a significant negative impact on income among young and prime-age males. Although moderate drug use is associated with higher income among young males, this disappears among older males.

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