Retrospectives: Pareto's Law

Persky, Joseph

doi:10.1257/jep.6.2.181

Cited by 110 publications

(37 citation statements)

References 13 publications

(5 reference statements)

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“…However, this is not consistent with the measured values of Pareto exponent, if one associates lower values of the exponent with increased inequality. To resolve this issue, we note that if the distribution follows a power-law nature throughout, then a clear correspondence exists between the two measures, e.g., a Pareto exponent of 1.5 implies a Gini coefficient of 0.5 [29]. However, observed distributions show a power-law only over a very limited range, and hence the correspondence breaks down.…”

Section: Discussionmentioning

confidence: 99%

Evidence for power-law tail of the wealth distribution in India

Sinha

2006

Physica A: Statistical Mechanics and its Applications

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The higher-end tail of the wealth distribution in India is studied using recently published lists of the wealth of richest Indians between the years 2002-4. The resulting rank distribution seems to imply a power-law tail for the wealth distribution, with a Pareto exponent between 0.81 and 0.92 (depending on the year under analysis). This provides a comparison with previous studies of wealth distribution, which have all been confined to Western advanced capitalist economies. We conclude with a discussion on the appropriateness of multiplicative stochastic process as a model for asset accumulation, the relation between the wealth and income distributions (we estimate the Pareto exponent for the latter to be around 1.5 for India), as well as possible sources of error in measuring the Pareto exponent for wealth.

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Section: Discussionmentioning

confidence: 99%

Evidence for power-law tail of the wealth distribution in India

Sinha

2006

Physica A: Statistical Mechanics and its Applications

150

100

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“…The majority of Internet users in general, and participants of social network communities in particular, are consumers, while only a small fraction of the participants function as content contributors (Forkosh-Baruch & Hershkovitz, 2012). Applying the Pareto Law to users' online behavior (Persky, 1992), this distribution ranges near the 20:80 rule, according to which 20% of the participants produce 80% of the value. This "long tail" distribution of online participation is neither restricted to the medium nor to the participant's age (Blau, 2011).…”

Section: Literature Reviewmentioning

confidence: 99%

Twitter as a Platform for an Israeli Community of Information Science Professionals

Blau

Neuthal²

2012

IISIT

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This paper examines an Israeli professional community on Twitter, which connects people working or studying the field of Information Science. The participants were 31 individual and organizational users and 175 structural connections established among them during March 2007-November 2011. The data was extracted using NodeXL application and analyzed in terms of user's investments (i.e., participation by tweeting and following others) and gratification mechanisms (i.e., influence on the audience: the degree of centrality into the community network, the number of followers and tweets marked as favorites). The results show that (1) The evolution of the community over time was in a bell curve, in concordance with the Diffusion of Innovations Theory (Rogers, 2003). (2) Concerning the rate of active participation, five of the most active individual community members (16.1%) shared 54% of the community tweets. Thus, the head of this "long tail" distribution is relatively small, indicating a moderate level of participation inequality in the community. (3) Regarding user investment and gratification mechanisms, participation by tweeting and following others is highly related to the visible form of influencing community audiencethe number of followers, moderately related to the hidden influence -location of the participant in the community network measured by PageRank, and unrelated to the content quality -the percentage of user's tweets marked as favorites by others.Keywords: professional communities of practice on Twitter, structural connections on Twitter, influence on the audience, active participation, network analysis by NodeXL.

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“…From the time of Pareto's discovery of this relationship (1896) there has been interest in whether it somehow characterises a "law" of income distributionwhether the straight-line approximation described above is generally a good one (it is) and whether it is reasonable to assume that across countries there is a natural tendency for to approach one particular value (it isn't) (Persky 1992). …”

Section: Representations Of Income Distributionmentioning

confidence: 99%