The Personal Distribution of Income

Steindl, Josef

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Document type:: Works

Collection:: Josef Steindl Collection

Title:: The Personal Distribution of Income

Author:: Steindl, Josef

Scope:: Typoskript, 24 Seiten (23 Seiten auf Durchschlagpapier), mit zahlreichen handschriftlichen Anmerkungen und Anstreichungen

Year of publication:: 1972

Source material date:: August-September 1972

Language:: English

Note:: Unveröffentlichtes Typoskript.

Related work:: Steindl, Josef: The Personal Distribution of Income. In: Steindl, Josef: Economic Papers 1941-88. London: Macmillan, 1990, S. 356-371

Topic:: Stochastic processes and size distribution

Shelfmark:: S/M.52.8

Access:: Free access

11 Income and health* Ggpjrical Fatteras The foil wing renakrs refer to the cross-classifications of wealth and income published in Holland and Sweden. These data show certain characteristics which are found ajso in other cross-section data concerned with size distributions, especially data from official publications like censuses etc. The first feature is that the groat bulk of the observations is concentrated in the corner of the first ( the north-east ) quadrant. In other words these distributions are very skew. A great many of the units are small in either dimension. The second feature is that the wealth distribution is heavily truncated ( in Sweden for example at 150.0C crowns) while the inc me distribution is given down to rather lw levels. If the mean income in the vari>us wealth classes is calculated aalinear regressim of a very regular pattern is btained. ( This "regression of the first kind" as we may call it differs fr >m the usual least squares regressin in that it d ees not assume a or!rl a certain mothem tiwal functifor the re .ression; see Gerald CramAr, Mathematical etheds f Statistics,Pro neeton 1946jfo tjc> m if the regression of the means turns out to be inear as is the case here, then it sh lid be the same as the result of a linear least squares regress! n; this may be not quite true only in so far as we fail to use weights for the means corresponding to the various fre uencies in the different wealth classes ). The same regression of the first kind in the other dimension « wealth on income — gives a completely different picture* he mean wealth in the lower income classes does not indrease with income at all; for higher incomes it increases very strongly, so that a strongly ourved regression line results. At least one, and probably the most important reason for the curvi.linearity of this regression line lies in the truncation of the wealth data. If we try to fill in the missing wealth data in o r imagination, according to plausible and common ses.se prior knowledge, we find that the regression of wealth on incot e might well be quite linear and rather steep} at least it w >u d be very much nearer to linearity than it is n w The inclusion of cases with wealth below the tax li it, which is rrbably he lower and the more frequent the 1 wer the inc me, w uld reduce the mean wealih in all inc sae c asses but it w u d reduce it the more the 1 wer the

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