Overconsumption of alcohol has a far-reaching adverse effect on the person and the larger society on various socio-economics aspects that have been the subject of debate and academic discourse for decades. One of the areas that alcohol has an impact is the work life of the alcoholic. This study seeks to assess the impact of alcohol consumption on labor outcomes.
MacDonald and Shields study the effects of alcohol consumption on wages and occupational attainment in England. They use a pooled sample from England Health survey for 1994, 1995 and 1996. They use an OLS regression to model wages and occupational attainment as a function of age, children, frequency of drinking, and quantity of alcohol, marital status, education and region (MacDonald and Shields 24). They reveal there is a negative effect on wages which is revealed through the hours worked.
Yoruk makes similar findings while studying the effects of alcoholism on young adults using national longitudinal data from a health survey. Yoruk controls for education, age, marital status and race (Yörük 1304).
Estimates the effect of alcoholism and alcohol abuse on wages earned as well as the number of hours worked. The author controls for age, gender, race, health, depression, marital status (Renna 99). Unlike, the other studies, this study distinguishes alcoholism and alcohol abuse. Renna reveals that alcoholism negative effect disappears but the effect on hours worked is persistent. Renna also applies a two-stage regression which is inconclusive.
This study seeks to assess the impact of alcohol on labor outcomes. The study uses national longitudinal data for one wave. The data contains 1600 observations. The labor outcome of interest is the hours worked. Hours worked will be the dependent variable. Alcohol consumption will be estimated by the number of pints taken per day. The other control variables that will be included are age, gender, marital status, the number of kids and race. The control variables are informed by theory.
An ordinary linear regression (OLS) model was applied. The choice of model was also informed by existing literature. Appendix 1 shows the regression output. The number of alcohol pints has a negative relationship with hours worked. Consumption of one alcohol pint per day reduced the number of hours worked by 4.78 hours. It is significant at 10 percent SL. All the other control variables were significant with the exception of the region. The model has an adjusted R-square of 0.1213: the model only explains 12 percent of the variation in hours worked. The other variables that would be relevant based on literature but were left out include wage rate and marital status.
Appendix 2 shows the Q-Q plot and residual vs. fitted plots that test the OLS assumptions. The residual vs. fitted plot does show a consistent pattern as x changes. Therefore, the variances are fairly homoscedastic/constant. The Q-Q plot shows that most data points are close to the dotted line. Therefore, the errors are normally distributed. The OLS assumptions hold. OLS is an appropriate fit for the data and the model.
Conclusion
The findings of this study are confirm existing literature. Alcohol consumption negatively affects the hours worked. The findings should guide policy making on alcohol. Taxes on alcohol should be increased to discourage consumption. Campaigns to sensitize the public should also be heightened. Further studies on the most effective remedies are necessary to identify the optimal solution to alcoholism and alcohol abuse.
Appendix 1
Call:
lm(formula = hrswrk ~ race + sex + perday + region + age + numkid)
Residuals:
Min 1Q Median 3Q Max
-2311.6 -598.0 155.5 610.8 4100.5
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1733.557 77.784 22.287 <2e-16 ***
race 106.788 9.672 11.040 <2e-16 ***
sex -534.585 14.906 -35.864 <2e-16 ***
perday -4.781 2.056 -2.325 0.0201 *
region 8.732 7.376 1.184 0.2365
age 20.703 2.209 9.371 <2e-16 ***
numkid -111.375 6.172 -18.045 <2e-16 ***
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Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 907.2 on 15993 degrees of freedom
Multiple R-squared: 0.1217, Adjusted R-squared: 0.1213
F-statistic: 369.2 on 6 and 15993 DF, p-value: < 2.2e-16
Appendix 2
Works Cited
MacDonald , Ziggy and Michael Shields. "The Impact of Alcohol Use on Occupational Attainment and Wages." Public Sector Economics Research Centre (1998): 1-49. Print.
Renna, Franscesco. "Alcohol Abuse, Alcoholism, and Labor Market Outcomes: Looking for the Missing Link." Industrial and Labor Relations Review (2008): 92-103. Print.
Yörük, Ertan Ceren . "The Effect of Alcohol Consumption on Labor Market Outcomes of Young Adults: Evidence from Minimum Legal Drinking Age Laws." The B.E. Journal of Economic Analysis & Policy (2015): 1297-1324. Print.
