From Lars Syll The unpopularity of the principle of organic unities shows very clearly how great is the danger of the assumption of unproved additive formulas. The fallacy, of which ignorance of organic unity is a particular instance, may perhaps be mathematically represented thus: suppose f(x) is the goodness of x and f(y) is the goodness of y. It is then assumed that the goodness of x and y together is f(x) + f(y) when it is clearly f(x + y) and only in special cases will it be true that f(x + y) = f(x) + f(y). It is plain that it is never legitimate to assume this property in the case of any given function without proof. J. M. Keynes “Ethics in Relation to Conduct” (1903) Since econometrics doesn’t content itself with only making optimal predictions, but also aspires
Topics:
Lars Pålsson Syll considers the following as important: Uncategorized
This could be interesting, too:
Dean Baker writes Health insurance killing: Economics does have something to say
Lars Pålsson Syll writes Debunking mathematical economics
John Quiggin writes RBA policy is putting all our futures at risk
Merijn T. Knibbe writes ´Extra Unordinarily Persistent Large Otput Gaps´ (EU-PLOGs)
from Lars Syll
The unpopularity of the principle of organic unities shows very clearly how great is the danger of the assumption of unproved additive formulas. The fallacy, of which ignorance of organic unity is a particular instance, may perhaps be mathematically represented thus: suppose f(x) is the goodness of x and f(y) is the goodness of y. It is then assumed that the goodness of x and y together is f(x) + f(y) when it is clearly f(x + y) and only in special cases will it be true that f(x + y) = f(x) + f(y). It is plain that it is never legitimate to assume this property in the case of any given function without proof.
J. M. Keynes “Ethics in Relation to Conduct” (1903)
Since econometrics doesn’t content itself with only making optimal predictions, but also aspires to explain things in terms of causes and effects, econometricians need loads of assumptions — the most important of these are additivity and linearity. Important, simply because if they are not true, your model is invalid and descriptively incorrect. It’s like calling your house a bicycle. No matter how you try, it won’t move you an inch. When the model is wrong — well, then it’s wrong.