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Pareto distribution

The Pareto distribution, named after the Italian civil engineer, economist, and sociologist Vilfredo Pareto,[2] is a power-law probability distribution that is used in description of social, quality control, scientific, geophysical, actuarial, and many other types of observable phenomena; the principle originally applied to describing the distribution of wealth in a society, fitting the trend that a large portion of wealth is held by a small fraction of the population.[3][4] The Pareto principle or "80-20 rule" stating that 80% of outcomes are due to 20% of causes was named in honour of Pareto, but the concepts are distinct, and only Pareto distributions with shape value (α) of log45 ≈ 1.16 precisely reflect it. Empirical observation has shown that this 80-20 distribution fits a wide range of cases, including natural phenomena[5] and human activities.[6][7]

Parameters

scale (real)
shape (real)

does not exist

[1]

The of a random variable following a Pareto distribution is

expected value

Parameters

location (real)
location (real)

shape (real)


(this is the second raw moment, not the variance)

(this is the kth raw moment, not the skewness)

Statistical inference[edit]

Estimation of parameters[edit]

The likelihood function for the Pareto distribution parameters α and xm, given an independent sample x = (x1x2, ..., xn), is

Therefore, the logarithmic likelihood function is


It can be seen that is monotonically increasing with xm, that is, the greater the value of xm, the greater the value of the likelihood function. Hence, since xxm, we conclude that


To find the estimator for α, we compute the corresponding partial derivative and determine where it is zero:


Thus the maximum likelihood estimator for α is:


The expected statistical error is:[22]


Malik (1970)[23] gives the exact joint distribution of . In particular, and are independent and is Pareto with scale parameter xm and shape parameter , whereas has an inverse-gamma distribution with shape and scale parameters n − 1 and , respectively.

Occurrence and applications[edit]

General[edit]

Vilfredo Pareto originally used this distribution to describe the allocation of wealth among individuals since it seemed to show rather well the way that a larger portion of the wealth of any society is owned by a smaller percentage of the people in that society. He also used it to describe distribution of income.[4] This idea is sometimes expressed more simply as the Pareto principle or the "80-20 rule" which says that 20% of the population controls 80% of the wealth.[24] As Michael Hudson points out (The Collapse of Antiquity [2023] p. 85 & n.7) "a mathematical corollary [is] that 10% would have 65% of the wealth, and 5% would have half the national wealth.” However, the 80-20 rule corresponds to a particular value of α, and in fact, Pareto's data on British income taxes in his Cours d'économie politique indicates that about 30% of the population had about 70% of the income. The probability density function (PDF) graph at the beginning of this article shows that the "probability" or fraction of the population that owns a small amount of wealth per person is rather high, and then decreases steadily as wealth increases. (The Pareto distribution is not realistic for wealth for the lower end, however. In fact, net worth may even be negative.) This distribution is not limited to describing wealth or income, but to many situations in which an equilibrium is found in the distribution of the "small" to the "large". The following examples are sometimes seen as approximately Pareto-distributed:

 – Pattern of references in science journals

Bradford's law

 – Law in seismology describing earthquake frequency and magnitude

Gutenberg–Richter law

 – The rich get richer and the poor get poorer

Matthew effect

 – Statistical principle about ratio of effects to causes

Pareto analysis

 – Weakly optimal allocation of resources

Pareto efficiency

 – Method of estimating the median of a population

Pareto interpolation

 – Functional relationship between two quantities

Power law probability distributions

 – "Ninety percent of everything is crap"

Sturgeon's law

 – simulated flow of data in a communications network

Traffic generation model

 – Probability distribution

Zipf's law

 – Probability distribution

Heavy-tailed distribution

M. O. Lorenz (1905). "Methods of measuring the concentration of wealth". . 9 (70): 209–19. Bibcode:1905PAmSA...9..209L. doi:10.2307/2276207. JSTOR 2276207. S2CID 154048722.

Publications of the American Statistical Association

Pareto, Vilfredo (1965). Librairie Droz (ed.). Ecrits sur la courbe de la répartition de la richesse. Œuvres complètes : T. III. p. 48.  9782600040211.

ISBN

, Encyclopedia of Mathematics, EMS Press, 2001 [1994]

"Pareto distribution"

"Pareto distribution". MathWorld.

Weisstein, Eric W.

Aabergé, Rolf (May 2005). "Gini's Nuclear Family". (PDF).

International Conference to Honor Two Eminent Social Scientists