Page 263 - Special Topic Session (STS) - Volume 3

STS543 Veronica B. B. et al.
Following Bruno et al (2017), equation 3 estimates the effectiveness of
macroprudential tools when changes in monetary policy push in the same or
3 .
opposite direction. The test is on the overall significance of ∑ =1
Do responses to macroprudential policies vary over the financial cycles?
Additional interaction terms which combine macroprudential policy indicators
and real GDP growth (measured by the output gap or the difference between
the actual real GDP growth and the average output gap from four
approaches ). This is seen in equation 4 as,
4

∆ log , = + ∑ ∆ log ,− + ∑ =1 ∆ − +
=1

∑ =0 ∆ − + ∑ =1 ∆ − ∗ ∆ − + ,−1 + , +

,
(eq. 4)

The goal of this exercise is to determine possible presence of endogeneity
between output gap and macroprudential tools or their effects may be higher
when output gap has widened or vice versa. The test is on the overall
significance of ∑ =1 . In this study, a measure of financial cycle using credit-
to-GDP gap or the difference between the actual credit-to-GDP ratio and its
trend is used in the regression model. In the exercise, this study also
5
considered separate consumer loans-to-GDP ratios for U/KBs and TBs.
Impact on bank risk. In literature, the use of macroprudential tools is also
intended to limit excessive bank risk-taking activities in lending and
consequently, the probability of the occurrence of a financial crisis. This study
looks at how macroprudential tools have an impact on specific measures of
bank riskiness such as gross non-performing loans over total assets. This is
seen in equation 5 as,

, = + ∑ =1 ∆ log ,− + ∑ =1 ∆ − + ,−1 + , +

,
(eq. 5)

Where are bank fixed effects, ,−1 are bank characteristics,

, are macro-financial indicators. The main coefficient of interest
is ∑ =1 which represents the impact of changes in a domestic
macroprudential policy on bank risk-taking activities as seen in non-

3 In the estimation of ∑ =0 − , the contemporaneous impact is considered.
4 These approaches include (1) production function approach, (2) structural vector
autoregression (SVAR), (3) macroeconomic unobserved components model (MUCM), and (4)
Hodrick-Prescott (HP) filter.
5 Credit-to-GDP gaps are derived, in line with the Basel III guidelines for the countercyclical
capital buffer, as the deviations of the credit-to-GDP ratios from their (real-time) long-term
trend. Consumer loans-to-GDP was also used in the estimation.

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