I
4
To find the tail of the steady state distribution P(y^) we
sum (/) from & to oo and obtain p . Thus
1 \ 1
3-n H7 K ) -^la p ) E 1» J B
«-I
and, putting -h In p = oC we have
In P(y^) = -cC In y*, (3)
Evidently the crucial feature of the model is the geometric
distribution of the recurrence time* This relates here to
the life-time of the persons as income receivers; since
promotion is automatic, the age of the system is measured
in income classes K. The age, or spent life-time, is
geometrically X a PP rcsiinai:e -7 exponentiallyf distributed.
I / I lit i \ l
Since the income is also an exponential function of K »
the Pareto law results from an elimination of time K from
5'
the two exponential functions.
This is exactly the same pattern of explanation as was used
m .. L* \ t ^ ^
/ 2. i, 1
in other fields
t)v
- _ —7 y - _
by Simon £ Jp and myself -43/ and
which is-directly■descended from Tule 1# J, who used it
(IQ2H> 2.
to explain the frequency of species in genera. According to
'Although Champernowne's^model is more complicated than the
above, v -the essential features remain the same (only, o in
the solution is replaced by b, the solution of a difference
equation).