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Does performance pay increase alcohol and drug use?

Abstract

Using US panel data on young workers, we demonstrate that those who receive performance pay are more likely to consume alcohol and illicit drugs. Recognizing that this likely reflects worker sorting, we first control for risk, ability, and personality proxies. We further mitigate sorting concerns by introducing worker fixed effects, worker-employer match fixed effects, and worker-employer-occupation match fixed effects. Finally, we present fixed effect IV estimates. All of these estimates continue to indicate a greater likelihood of substance use when a worker receives performance pay. The results support conjectures that stress and effort increase with performance pay and that alcohol and drug use is a coping mechanism for workers.

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Notes

  1. On productivity see, among others, Banker et al. (1996), Lazear (2000), Bandiera et al. (2005), Gielen et al. (2010), and Heywood et al. (2011), and on sorting for talent, see Lazear (2000), Cadsby et al. (2007), Dohmen and Falk (2011), and Shaw (2015).

  2. “Workmen…when they are liberally paid by the piece, are very apt to overwork themselves, and to ruin their health and constitution in a few years (Smith 1776, p. 83).”

  3. This reflects $249 billion per year in alcohol related costs (CDC 2016) and $193 billion per year in drug-related costs (NDIC 2011).

  4. Indeed, using UK data Green and Heywood (2008) show that as measured by subjective job satisfaction, performance pay workers, on balance, remain more satisfied.

  5. Which is not to say the two need be unrelated as Kaestner and Grossman (1998) present evidence on the influence of drug use on workplace accidents and injuries.

  6. Rohleder (2014) reviews the medical literature on the effects of stress arguing that constant chronic psychosocial stress that persists over time can be psychologically and physically damaging.

  7. The wave after 2011 (2013) does not include the marijuana and hard drugs use measures. Although the 2015 wave reintroduces these measures, we chose to omit the wave both because of the 4-year time span since 2011 and because the period since 2011 has seen growing legalization of marijuana among US states.

  8. There is unfortunately no 30-day equivalent for drugs in the survey. Similarly, while the drug measure indicates many types of drugs, different types of alcohol (beer, wine, spirits) are not identified.

  9. An example of such a concern would be that sales jobs are associated with commissions and with drinking with customers.

  10. As earnings are positively correlated with performance pay, their inclusion presumably robs some of performance pay’s influence on alcohol and drug use. We will explore this in depth when considering potential income effects.

  11. Although we note that probit estimates of the pooled estimates return very similar results in terms of the size and significance of the key variables.

  12. Dave and Saffer (2008) show evidence that both the probability of using alcohol and the amount consumed by users are 6–8% higher among risk-tolerant individuals.

  13. Dohmen et al. (2017) demonstrate that individuals become slowly less risk tolerant with age.

  14. We recognize a possible more complicated, and we think counter-intuitive, form of sorting. Firms could change their performance pay policy to reflect the risk preferences of their workers. While possible, this obviously implies that the workers initially sorted into their employer in direct opposition to their own risk preferences.

  15. The mean usage of marijuana among those not on performance pay is 0.160 and that for hard drugs is 0.042.

  16. We have used this alternative full earnings measure in all the estimates in this paper. They are available upon request but are remarkably unchanged throughout. We also tried to replace the indicator of performance pay with this measure of the wages associated with performance pay and overtime. It was also typically a positive and significant determinant of substance use but failed to be robust in some of the narrower fixed effect estimates perhaps because of the measurement error associated with the included overtime earnings.

  17. These are available upon request.

  18. As a check, we did perform Tobit estimates as a simple form of a double hurtle model. These continue to show a large and significant coefficient for performance pay and are presented in appendix Table 14.

  19. None of this denies that the amount of smoking among those already smoking might respond to stress and so to performance pay. Estimates in appendix Table 15 present mixed results with frequently of use positively associated with performance pay in the pooled and worker fixed-effect but not in the worker-employer match fixed effect.

  20. Again, the detailed estimates are available upon request.

  21. It is easier to identify performance for a sales person or drill press operator than for an assembly line operator. The aggregated measure then indicates greater scope for provision in the first occupations than in the latter.

  22. The exclusion requirement necessitates that the aggregated measure from the previous year does not directly influence the individual worker’s probability of substance use this year.

  23. Unfortunately, the relatively small number of workers who stay within this division and change performance pay does not allow meaningful fixed effect estimates within the food and beverage workers.

  24. Indeed, the pattern of significant results largely carries over to the individual fixed effect estimates but dissipates due to small sample size in the job match fixed effects.

  25. See Heywood and O'Halloran (2005) and Heywood and Parent (2012) for evidence on the extent to which performance pay reduces observed racial earnings gaps.

  26. These results are available upon request.

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Acknowledgement

The authors would like to thank the anonymous referees for helpful comments and suggestions. The authors express gratitude for a University of Wisconsin-Oshkosh Faculty Development Grant and for comments from seminar participants at Memorial University, Wittenberg University, 2019 Colloquium of Personnel Economics, the 2019 meetings of the Scottish Economic Society, and the 2020 LERA winter meetings.

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Correspondence to John S. Heywood.

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Appendices

Appendix A

Table 7 Descriptive statistics and variable definitions, NLSY97, 2002/2011
Table 8 Performance pay and the incidence of drug and alcohol use: controlling for ability, risk attitudes, and log total wages in pooled cross-section logit estimates
Table 9 Worker fixed effects Poisson estimations: frequency of use
Table 10 Poisson estimations: number of substances used (zero to three)
Table 11 Examining other Lifestyle Indicators
Table 12 FE OLS estimates of substance use

Appendix B

Table 13 Adding personality trait indicators to the pooled specifications
Table 14 Tobit estimations on the frequency of substance use
Table 15 Poisson estimations: Number of cigarettes smoked per day
Table 16 Summary of subsample estimates

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Artz, B., Green, C.P. & Heywood, J.S. Does performance pay increase alcohol and drug use?. J Popul Econ 34, 969–1002 (2021). https://doi.org/10.1007/s00148-020-00776-4

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Keywords

  • Performance pay
  • Alcohol
  • Drugs
  • Sorting

JEL Classification

  • I12
  • J33