Should we care about pay ratios? Dealing with ISSP questions on actual and ideal wages from a comparative perspective

ABSTRACT

Questions on actual and ideal wages of various occupations are distinctive features of ISSP Social Inequality modules which can be used to quantify respondents’ perceived and ideal wage inequality, by computing pay ratios ex-post. However, recent research has raised harsh criticism of pay ratios, emphasizing that they suffer from anchoring bias, ratio bias, and, more generally, low validity. This article investigates what adjustments can be made to improve the validity of pay ratios for comparative analyses. It is found that country comparisons are very sensitive to adjustments and have major limitations. Nevertheless, as attitudes expressed by word-based items do not measure the extent of inequalities that respondents are willing to tolerate, further research is needed to find out ways to fix problems with pay ratios at the level of data collection rather than of data analysis. The article concludes with some suggestions regarding data collection.

KEYWORDS:

• Ideal pay ratios
• perceived actual pay ratios
• attitudes toward income inequality
• anchoring bias
• ISSP

Acknowledgments

This paper was presented at the ISSP User Conference on Social Inequality held online on 12^th December 2022 and at the European Survey Research Association conference in Milan on 17–21 July 2023. The author thanks conference participants, Camilla Borgna, Simona Guglielmi, and Gian Luca Pasin for their helpful comments on a previous version of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplemental data

Supplemental data for this article can be accessed online at https://doi.org/10.1080/13645579.2024.2349524.

Notes

1. Other occupations included in the questionnaire are doctor (general practitioner), shop assistant and cabinet minister.

2. I obtained substantively identical results with a dependent variable that has the average of the three high-earning occupations at the numerator and the average of two low-earning occupations at the denominator.

3. As a robustness check, I also re-run the analyses using only the first of these items which apparently has more face validity. The results are entirely consistent.

4. Given the mathematics of logarithms, the regression coefficient of ln(Ideal/Actual ratio) on x is equal to the difference between the coefficient from the regression of ln(Ideal ratio) on x minus the coefficient from the regression of ln(Actual ratio) on x. If the former is smaller than the latter the difference will be negative.

5. In practice, country dummies capture the variance that in a multilevel model is captured by random slopes.

6. For comparison, it should be noted that the two items forming the index are moderately correlated with r = 0.52 on average across countries, ranging 0.38–0.71.

7. This is also one of the conclusions put forward by Cansunar (2021) from a quite different perspective.

8. That might also help reduce the high percentage of missing values for the chairman estimates, which is 12% on average, but ranges 0–54% across countries. Similar figures are found for the other two high-status occupations (doctor, minister).

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.

Notes on contributors

Renzo Carriero

Renzo Carriero is associate professor of sociology at the University of Turin and affiliate of the Collegio Carlo Alberto in Turin. His research interests include welfare state and redistribution attitudes, gender and social inequalities, cultural transmission and change, comparative social research, social research methodology.