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failure of (R.2) and (R.3), in particular, are arguments that 
the excluded effects are likely to be substantial in practice. 
While one may be willing to assume that they are not so in 
particular cases, depending on the structure of the model to 
be estimated, this seems a dangerous procedure in most eco- 
nomy-wide models given the high degree of approximation 
which such models inevitably involve. The Proximity Theorem 
in more general form will be of considerable help to us below 
and is of substantial value in other contexts; for structural 
estimation in economy-wide models, it seems a weak reed on 
which to rest estimation by ordinary least squares. 
2.5. Reduced Form Estimation 
Our discussion thus far has run in terms of the estimation 
of the parameters of structural equations. The simultaneous 
model context in which ordinary least squares is most often 
thought to be appropriate, however, is not this at all, but 
rather in the estimation of the equations of the reduced form. 
Here the difficulties in the use of ordinary least squares which 
arise from simultaneity apparently disappear as all variables 
on the right-hand side of reduced form equations are either 
exogenous or lagged. 
In this connection, the argument against the use of ordinary 
least squares has generally run in terms of lack of asymptotic 
efficiency when compared with estimates of the reduced form 
which are derived from structural estimates using overidentify- 
ing a priori information. Such lack of asymptotic efficiency 
may be particularly important in the event of a structural break 
or in the prediction of turning points (14). The argument in 
favor of ordinary least squares estimates of reduced form equa- 
tions has been the desirability of having forecasts of the endo- 
(%) LesNoy [18] 
‘61 Fisher - pag. 14