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Prosocial I-O: Quo Vadis: Project Organizational Gini Coefficient

Stuart Carr
Massey University

 Statistician, demographer and sociologist, Corrado Gini is probably best known for the “Gini coefficient,” which in turn is widely used by economists as an index of economic fairness in a society—a topical issue for us all. Professor Gini studied law at the University of Bologna, before taking up chairs in statistics at universities in Cagliari, Padua, and Rome. He was given an honorary degree in sciences from Harvard University. A contemporary of Kendall and Fisher, Professor Gini founded the statistical journal Metron, which emphasizes the applied. His political leanings were certainly not without controversy. Those aside however, his famous metric continues to be more and more influential since his death (in 1965). The Gini coefficient has found increasing applications across a variety of disciplines—excepting, perhaps, our own. Here we speculate what relevance the Gini coefficient might hold for industrial and organizational psychology. Where possible, I have tried to use Gini’s own words as an answer to the questions being asked.

Please tell us a little more about the index.
The Gini coefficient is a statistical index of concentration in a distribution, typically of income, often in a country. The statistic can range from 0 (total equality, all members of the society or group have the same income) to 1 (maximal inequality, where 1 member of the society or group receives the entire group’s income). Macro-economists often use this index to capture income diversity in countries like the U.S. (.45), and New Zealand (.36), or across regions like the EU (.31) and even for the world as a whole (the estimates vary but appear to hover around .60. Income of course is not necessarily the same as opportunity: Lower Gini countries may have more barriers to upward mobility just as higher Gini countries may have fewer of them (through genuine meritocracy, or rewarding seniority). A country that accepts many refugees may raise its Gini, even though it is less exclusionist than its neighbors, whose Gini by comparison will drop.

What these and other caveats mean perhaps is that the index has to be supplemented by other indicators of equality and inequality, or concentration and dispersion, apart from income per se. Expressed somewhat differently, from an earlier publication, “it helps to build theoretical schemes that must not be confused with reality, but may be compared with reality, so as to judge if, in what way and to what extent, they differ from reality, and thus provide an opportunity for a deeper analysis of the structure of the phenomena” (Gini, 1965, p. 106).

Where does the psychology of work and organization come in?
Interestingly, country-level Ginis have recently been linked, empirically, to individual well-being, health, and happiness (Wilkinson & Pickett, 2009). For many TIP readers, that linkage might start to raise questions about the space in between—at the level of organizations. After all, organizations pay salaries, which “are” the incomes in question, and logically, their own workplace is where income differences might be—comparatively speaking at least—quite proximal and salient. To give one example of how this relevance can literally play out, some research with sporting teams have found a link between the Gini coefficients for major league baseball teams and their sporting human performance: Greater compression of incomes (a lower Gini) was linked empirically to higher performance, at both individual and organizational levels (Bloom, 1999). A similar pattern may exist in business organizations, for instance in performance by high-technology firms (Siegel & Hambrick, 2005). Further studies, in sports and using differing income dispersion indices, have been somewhat less consistent (for a review, Mondello & Maxcy, 2009). Overall, it seems, there might be an optimal balance, a trade off to be achieved between on the one hand (a) rewarding good performance and on the other hand (b) maintaining harmony.

How prominent is work and organizational psychology in this field?
Stu: Perhaps I can answer this question from my own perspective as an organizational psychologist. Along with valued colleagues and collaborators in the field of equality at work, we have been drawn to this issue of incomes at work because of debates in wider society about CEO salaries, banking-sector bonuses, the 99% protests on Wall Street, and so-called dual salary systems for expatriate/host workers in international aid and business ventures. Our own particular training did not really prepare us well for organizational variation. In fact most organizational psychology is arguably individual level or focuses on groups within organizations rather than organizations per se. Somewhat ironically perhaps, we leave out much of the “organization” in organizational psychology—even though it is a richly informative, and important, mezzanine-level variable. Arguably in fact, other social sciences have overlooked the organizational level too, leaving us room to make some fresh, unique contributions. How? Could it be time to incorporate some of the existing and widely respected measures of equality, like the Gini coefficient, into our theories, research, and practice?

How can we become more involved in this topical issue?
Although Gini coefficients of 0 may be overly idealistic and possibly even harmful (say when people make unequal contributions to the work), we could make more use of the index, and its various cousins, as an indicator of performance. How does an organizational Gini coefficient relate to organizational performance, individual well-being, and societal issues such as decent work and quality of life? Do organizations with lower or higher organizational Gini coefficients perform better? How does their OGC moderate conventional linkages, at the individual and/or group level? And perhaps most impactful of all, is it conceivable that one good organizational Gini—whatever “good” turns out to be—may bring another, for example at the country or community level. Letting an organizational Gini out of the organizational bottle—warts, justice, and all—could be an interesting journey…

Heartfelt thanks to Professors Malcolm MacLachlan and Matthew Bloom, respectively from the Centre for Global Health in Trinity College Dublin, and Mendoza College of Business, University of Notre Dame Indiana. Without your generous feedback and insightful ideas for the project this “interview” would never have been possible. Thanks to Alex Gloss for locating the vital archives for this interview.

Anyone who is interested in discussing Project Organizational Gini Coefficient some more can contact us via s.c.carr@massey.ac.nz.

Bloom, M. (1999). The performance effects of pay dispersion on individuals and organizations. Academy of Management Review, 42, 25–40.

Gini, C. (1965). On the characteristics of Italian statistics. Journal of the Royal Statistical Society, 128, 89–109.

Mondello, M., & Maxcy, J. (2009). The impact of salary dispersion and performance bonuses in NFL organizations. Management Decision, 47, 110–23.

Siegel, P. A., & Hambrick, D. C. (2005). Pay disparities within top management groups: Evidence of harmful effects on performance of high-technology firms. Organization Science, 16, 259–274.

Wilkinson, R., & Pickett, K. (2009). The spirit level: Why more equal societies almost always do better. London, UK: Allen Lane.