The bank lending channel of monetary policy: identification and estimation using Portuguese micro bank data



stronger during 1998 and 1999). This fact raises the question of whether the conclusions
above still apply once we allow for the possibility of a structural break in the last two
years of the sample.

To investigate this issue we “interacted” the variables in our basic specification with
a dummy variable, which is zero for the first six years of data (1990/1 to 1995/4) and
equals 1 for the two last years of the sample (1996/1 to 1997/4). This variable is denoted
by
d96 in Table 6 below and in our new equation whose basic formulation now reads as

ln(C / P)slt = βθi + βιln(D / P)it + ≠(D / P)itd96 + β2ln(D / P)it¾

+ β3 ln(K / P)u + α3ln(K / P)itd96 + β4ln(K / P)it zu +            (7.6)

+β5lt +α5ltd96+β6ltzit +β7st +α7std96+β8stzit +β9πt +β10zit

Notice that model (7.6) collapses into model (7.2) for the period 1990/1-1995/4. For
the period 1996/1-1997/4, the coefficient of
ln(D/ P) is given by (β1+α1) and
similarly for the coefficients of
ln(K/ P) , lt and st .

First, it is important to note that according to Table 6 there seems to be a strong
evidence of a structural break occurring in the two last years of the sample. In fact, with
the exception of the model in column (6), the coefficients of the variables of the model
interacted with the dummy variable
d96 are in general significantly different from zero. It
seems however that our liquidity variable basically accounts for the structural break
occurred in the last part of the sample. In fact, in the Portuguese case, the liquidity ratio
may be seen as a sort of “summary” variable that encompasses the main changes that the
Portuguese banking sector underwent over the nineties35.

35 The results of the two models displayed in columns (5) and (6) of Table 6 are somewhat puzzling.
According to the model with the capital variable in column (5) there seems to be a structural break, as the
coefficients of the variables interacted with the dummy variable are significantly different from zero.
However, a different conclusion emerges when we look at the model in column (6), as the coefficients of the
variables interacted with the dummy variable are all not different from zero. There are two alternative
econometric explanations for such an outcome: 1) if model in column (5) is the true model the results obtained
in column (6) stem from an omitted regressors misspecification bias and 2) if the model in column (6) is the
true model the results in column (5) are due to an over-parameterisation of the estimated model. Of course, in
this latter case it would mean that the introduction of the liquidity ratio in our basic specification is sufficient
to account for the structural break. Notice that the model in column (6) in table 6 reduces to the model in
column (6) of table 5 if we drop the (non significant) coefficients of the variables interacted with the dummy
variable.

33



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