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16 Thus in our case the income is y » }C w a where we suppose that the distribution of income and wealth reflects in some way a growth nrocess which has taken dace in the cast. ■x^.ys In the ordinary formulation we should have V ■ c, a '» “ AC Y = C2« and after elimination of time h'Wvv '1^ *'*• ’ ' £, C 3- /W 7 - In c • ,/» I 5 C* I -tM6 ChX"*- ( w - In c, ) /V>V 0 ■u.6^’ )l * (7) which corresponds to our regression with <c » — xiy } ■ * yr, How in economics random elements or shocks play a large role and growth is influenced by them. We should therefore write, instead . the above: W SfC e + Y * c-» e +• 1 £(t) 'I (t) where £ (t) and ^(t) are random variables. As a result we obtain A r In ( Y - yj (t) ) - In c , = 0<s j ln( W . £(t) ) - In c^- . (3) The random variables or ’’errors" ( not mere errors of observation of course ) are in both variables. The common I tactics of regression is to ascribe all the "errors" to one variable only, which yields two regression lines according to . whether you choose the one or the other variable as the repository of the errors. The equation (3) will not correspond to either of the two regression lines. i t may be guessed that it will lie somewhere between them. Let us now start from a different angle and consider the two kinds of relations that exist between income and wealth. One is the influence of wealth on income via the rate of return. It mainly affects unearned income. The other is the influence of past incomes on wealth via the propensity to save. Since present and past incomes are fairly strongly correlated it will appear as if current income acts on wealth via the propensity to save. At first sight it seems that the linear regression of income on wealth represents simply the influence of wealth via the rate of return. There is however an alternative interpretation.