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Do Comparison Wages Play a Major Role in Determining Overall Job Satisfaction? Evidence from Australia

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Abstract

A vast research literature indicates that comparison wages play a key role in determining job satisfaction. To examine this in the case of Australia, comparison wages are first constructed using two different measures, namely (1) cell average wages by age, gender and education level; and (2) ranked position of an individual’s wages in each cell. Then, using the first six waves of the HILDA Survey dataset, a random effects ordered probit model is utilized to predict overall job satisfaction. The findings of the study show that both own wages and comparison wages have an impact on overall job satisfaction. Comparison wages computed using the ranked position of an individual’s wages within a cell have an equal effect as that of own wages. The study further confirms that the ranked position of an individual’s wages in each cell matters more than cell average wages.

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Notes

  1. For more information on how to do this in Stata refer to Jones et al. (2007).

  2. An attempt to predict wage from a Mincer-type equation is made but due to a lack of suitable exclusion restrictions the regression output paints a muddier picture in terms of change of sign and magnitude of non wage variables inserted into a model.

  3. An individual’s utility (satisfaction) from working is nested in the total utility function, \({\text{v}} = {\text{v}}({\text{u}}, \, \mu ),\) where v is overall utility, u is utility from work and μ is utility from other aspects of life (e.g., leisure time, family time).

  4. For more information on the mathematical expression refer to Boyce et al. (2010).

  5. This is known as the incidental parameters problem.

  6. Such a strong assumption that the individual-specific error term is uncorrelated with the explanatory variable may not hold and thus a random effects regression is run with the addition of Mundlak correction (more information on this is written in the following section of the paper).

  7. The number of observations in columns 1 of Table 3 is slightly higher than in the other columns. When computing the cell average income, 11 observations were dropped because they couldn’t be grouped by age, gender and education level.

  8. Such a relationship might be because more qualified workers are more susceptible to have higher expectations that do not always come true. It might also be due to the fact that more qualified workers are more prone to be overqualified, hence less satisfied with their jobs.

  9. A formal test is carried out by computing a Wald statistic for the null hypothesis that the coefficients included as a result of Mundlak correction equal zero and the test result indicates that the null hypothesis cannot be rejected.

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Acknowledgments

I would like to thank the Melbourne Institute and the Department of Family and Community Services for providing me with the HILDA dataset. The views expressed in this article do not necessarily reflect those of the Melbourne Institute nor the Department of Family and Community Services. All errors and omissions remain my own.

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Correspondence to Temesgen Kifle.

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Kifle, T. Do Comparison Wages Play a Major Role in Determining Overall Job Satisfaction? Evidence from Australia. J Happiness Stud 15, 613–638 (2014). https://doi.org/10.1007/s10902-013-9439-6

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