Measuring the Concentration of Power in the International System

Ray, James Lee; Singer, J. David

doi:10.1177/004912417300100401

Cited by 112 publications

(50 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If these two teams are aggregated into a single team with six members-Team C ($2,000, $2,000, $3,000, $3,000, $5,000, $5,000), the pay disparity in Team C is the same as it had been in Team A or Team B (CV = 0.37, Gini = .20, SD = 1,247.22, Theil = 0.07, and RMD = .17). We agree with some researchers' propositions that there is no single Bbest^measure of disparity (Champernowne, 1974;Ray & Singer, 1973). Although CV, Gini, and Theil meet all of the properties of disparity, they all have some weaknesses.…”

Section: Literature Review Properties and Measures Of Organizationalsupporting

confidence: 86%

“…However, for a ten-person team, the maximum values of CV, Gini, and Theil are 3, 0.9, and ln(10), respectively. Researchers, depending on their different theoretical concerns, might want a disparity measure that increases with n, decreases with n, or is insensitive to changes in unit size (Ray & Singer, 1973). Thus, CV, Gini, and Theil might be not suitable for some research situations.…”

Section: Literature Review Properties and Measures Of Organizationalmentioning

confidence: 99%

“…We only focused on studies that used a particular measure (CV, Gini, SD, Theil, or RMD) to operationalize the corresponding disparity construct. We excluded studies that used the ratio (highest/lowest) measure, because this measure loses critical information about the resource distribution across the entire team (Cowell, 2011;Ray & Singer, 1973;Smith et al, 2006). We also excluded the gap measure, which refers to the difference in resources between the leader and the average resource of its other members, because it ignores resource variation across nonleader members.…”

Section: Overview Of Disparity Measures In Organizational Researchmentioning

confidence: 99%

See 2 more Smart Citations

Disparity in organizational research: How should we measure it?

2015

View full text Add to dashboard Cite

Researchers can use the coefficient of variation (CV), Gini coefficient, standard deviation (SD), Theil index, or relative mean deviation (RMD) to measure organizational disparity. Because these five measures have different properties, however, using them interchangeably may lead to inconsistent findings. Using simulated team pay data, we conducted two simulation studies to examine the similarities and potential differences among these measures. The results showed that CV, Gini, Theil, and RMD were strongly related in most circumstances and that interchanging them had little impact on their relations with outcome variables. Differences were observed, however, when interchanging any of these four measures (CV/Gini/Theil/RMD) with SD, especially when samples were characterized by a seriously skewed distribution, a wide pay gap, and a high sample disparity. Given that SD does not meet some of the properties of disparity, and that it may underestimate correlations between disparity and outcome variables, we suggest that researchers use CV, Gini, Theil, or RMD, rather than SD, to assess organizational disparity.

show abstract

Section: Literature Review Properties and Measures Of Organizationalsupporting

confidence: 86%

Section: Literature Review Properties and Measures Of Organizationalmentioning

confidence: 99%

Section: Overview Of Disparity Measures In Organizational Researchmentioning

confidence: 99%

See 1 more Smart Citation

Disparity in organizational research: How should we measure it?

2015

View full text Add to dashboard Cite

show abstract

“…One measure occasionally used as an indicator for uncertainty is the concentration index (Ray and Singer, 1973), which reflects how concentrated power is within the international system:…”

Section: Extant Proxies For Uncertaintymentioning

confidence: 99%

“…The variable reflects a dyad's relative capabilities defined by the ratio form contest success function that we use to construct both System Uncertainty and Regional Uncertainty, but excludes any third party actors. As a baseline for comparison, we also consider the effect of Dispersion, calculated as 1-CON (Ray and Singer, 1973). …”

Section: Empirical Analysismentioning

confidence: 99%

How Uncertainty about War Outcomes Affects War Onset

Bas

Schub

2016

Journal of Conflict Resolution

View full text Add to dashboard Cite

In canonical accounts of war, conflict outcomes are inherently uncertain. Contesting literatures posit that this uncertainty, arising from stochastic elements of the war-fighting process, may induce conflict due to greater risks of miscalculation or foster peace by breeding caution. We theorize that states, on average, exhibit prudence when confronting greater uncertainty. Despite its conceptual importance, extant proxies for uncertainty at various levels of analysissuch as polarity, balance-of-power, system concentration, and dyadic relative capabilitiesare imprecise and theoretically inappropriate indicators. To overcome this shortcoming, we theorize the conditions that elevate the magnitude of uncertainty over conflict outcomes and introduce a novel measure that captures this uncertainty within any k-state system. Through extensive empirical analysis, we confirm uncertainty's pacifying effect, and show how this effect operates at different levels of analysis.

show abstract

Rational normalization of concentration measures

Bonckaert

Egghe

1991

J. Am. Soc. Inf. Sci.

View full text Add to dashboard Cite

We study normalization features of good concentration measures. We extend the classical normalization to the case in which one requires a linear dependence between rational fractions of occupation and values of the concentration measure between 0 and 1. This is called "rational normalization." This principle is studied for general good concentration measures. In this context, a stability property of good concentration measures is proved. It is also shown that every good concentration measure can be rationally normalized. For the concentration measures of Theil and Atkinson, explicit calculations of the rational normalization are given. Furthermore, we show that, amongst the generalized Pratt measures, the original Pratt measure is the only one to be rationally normalized.

show abstract

Measuring the Concentration of Power in the International System

Cited by 112 publications

References 30 publications

Disparity in organizational research: How should we measure it?

Disparity in organizational research: How should we measure it?

How Uncertainty about War Outcomes Affects War Onset

Rational normalization of concentration measures

Contact Info

Product

Resources

About