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Newcomer Drinking Behavior and Immediate Post-College Earnings Growth: Does Occupational Social Intensity Make a Difference?

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Abstract

While some studies suggest that alcohol use reduces productivity and hence may reduce wages, others argue that it can enhance network relations and thus increase wages. The current study aims to unravel these equivocal findings by employing a prospective design focusing on young adults. Applying a social capital perspective, we posit that the relationship between alcohol use and earnings growth is positive for those whose vocational field places networking as more central to early career success (i.e., high social intensity occupations), but not for those whose vocational field emphasizes technical mastery as the basis for early career success (i.e., low social intensity occupations). Longitudinal data on 735 young adults entering career employment indicated that occupational social intensity indeed moderates the relationship between frequency of heavy episodic drinking (HED) and two-year earnings growth. As posited, whereas among those in low social intensity occupations the relationship between frequency of HED and earnings was not significant, among those in high social intensity occupations, this relationship was positive. Moreover, we posit and find this effect to be driven largely by first year’s earnings growth. Implications for research, practice and policy are discussed.

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Notes

  1. R2 was calculated for each of the multiple imputed data sets. Then, R2 values were pooled using simple averaging, following Van Ginkel (2019), which suggests that average of R2’s across imputed data sets is the preferred pooling method of R2. In order to test whether the \(\varDelta {R}^{2}\)in each stage of the hierarchical regression is significant, we used the macro by Van Ginkel (2010, 2019) for obtaining the F test for the complete model and for \(\varDelta {R}^{2}\).

  2. Analyses using list-wise deletion generated results that were the same as those reported with imputation, both with regard to statistical significance and the magnitude of parameter estimates.

  3. We use R2 calculation suggested by Liu et al., (2008) for repeated measures longitudinal data. As in the analyses conducted to test H1, R2 was calculated for each of the 100 multiply imputed data sets. Then, R2 values were pooled using simple averaging (Van Ginkel, 2019). Finally, as suggested by Van Ginkel (2019), we used the MULT option of the TEST statement to perform F test, jointly testing the null hypotheses regarding the significance of parameters added to models at each stage, based on the imputed data sets. This F test is used for testing the significance of \(\varDelta {R}^{2}\). Significance of whole model (which is equivalent to the significance of \({R}^{2}\)) was calculated by jointly testing the null hypotheses about the significance of all model parameters.

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Authors and Affiliations

  1. Hebrew University, Jerusalem, Israel

    Ronit Montal-Rosenberg

  2. Tel Aviv University, Coller School of Management, Department of Organizational Behavior, Tel Aviv, Israel

    Peter A. Bamberger

  3. University of Florida, Department of Management, Warrington College of Business Administration, Gainesville FL, USA

    Mo Wang

  4. University of Washington, Center for the Study of Health and Risk Behaviors, Seattle WA, USA

    Mary Larimer

  5. Cornell University, Smithers Institute, School of Industrial and Labor Relations, thaca NY, USA

    Peter A. Bamberger & Samuel B. Bacharach

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Montal-Rosenberg, R., Bamberger, P., Wang, M. et al. Newcomer Drinking Behavior and Immediate Post-College Earnings Growth: Does Occupational Social Intensity Make a Difference?. Occup Health Sci 7, 219–250 (2023). https://doi.org/10.1007/s41542-022-00126-8

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