additional regressor and the demand curve is identified because the supply curve includes
ln( D/ P) as an additional regressor.
Notice that for estimation purposes we do not need to specify the demand schedule.
All we need is to be aware of the existence of such a function with one regressor that does
not enter the supply function. In terms of the model defined by (3.3) and (3.4),
identification will be “lost” if we also include ln yt in equation (3.4). Some readers will
probably argue that this is likely to be the case, because the supply of credit by banks
could also depend on GDP as a measure of the “risk” or uncertainty in the economy. Of
course in the limiting case one could argue that any variable entering the demand curve
should also enter the supply curve. In this case the identification will be impossible and
there will not be a way out of this process. Thus, in the analysis that follows we implicitly
assume that for each estimated supply function there is a corresponding demand function,
which allows identifying the estimated supply function. This only requires that we assume
the existence of a demand equation, which includes a regressor not included in the supply
equation.
This alternative approach has the advantage of not requiring the imposition of any
sort of “spread condition” or any type of homogeneity condition to obtain the
identification of the lending channel. Also it allows one to get (direct) point estimates of
the relevant coefficients, which is not the case of the “reduced form” approach. Last but
not least, this alternative approach is immune to the specific type of monetary policy
instrument assumed to be used by the central bank. This again contrasts with the reduced
form approach in which the specific equation does depend on the type of instrument used
by the central bank, as we mentioned in the previous section. But, of course the now
proposed alternative approach also depends on two critical assumptions: deposits
exogeneity and econometric identification of the supply curve. In our opinion the
“econometric identification condition” is not a very restrictive assumption as it is
customarily assumed in the relevant literature whenever separate supply and demand
schedules are estimated. The assumption of deposits exogeneity is probably the major
limitation of our approach, but we argue below that this seems to be an issue deserving
further research also at the theoretical level.
Let us now address the estimation issue. So far in the literature the empirical models,
using panel data, have been estimated with variables in first differences to circumvent the
potential non-stationarity problem arising from the time-series dimension of the data.
However it is well known that in most cases this approach does not solve the
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