On the effectiveness of macroprudential measures

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On the effectiveness of macroprudential measuresLeonardo Gambacorta (BIS & CEPR)Panel on “Assessing the impact of macroprudential policy” – Banco de Portugal – 8 October, 2019The views expressed in this presentation are those of the author and not necessarily those of the Bank for International Settlements

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Outline

I. Some facts on Macroprudential Policies (MaPs)

II. The impact of MaPs on credit and their interaction with monetary policy: new evidence using credit registry data

III. MaPs and bank risk

IV. What are the effects of MaPs on macroeconomic performance?

V. Conclusions

Leonardo Gambacorta“On the effectiveness of macroprudential measures”

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I. Some facts on MaPs


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MaPs activism varies between countries

Number of policy actions

Advanced economies Emerging market economies

The sample covers 1,147 macroprudential policy actions adopted in 64 countries (29 AEs and 35 EMEs). The database is constructed using information in Lim et al (2011, 2013), Kuttner and Shim (2016), and Cerutti et al. (2017b). Data for the pre-crisis period cover the 1990–2007 period, while the post-crisis period refers to 2008–14.

Sources: IMF; BIS; authors’ calculations.


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MaPs are used in different ways

Use of macroprudential instruments1

In per cent Graph 2

Type of instrument Type of measure Advanced vs emerging market economies

1 The sample covers the period 1990–2014. Macroprudential tools for resilience include (a) capital-based instruments (countercyclical capital requirements, leverage restrictions, general or dynamic provisioning) and (b) liquidity requirements. Cyclical macroprudential tools include (c) asset-side instruments (credit growth limits, maximum debt service-to-income ratio, limits to banks’ exposures to the housing sector as a maximum loan-to-value ratio); (d) changes in reserve requirements; and (e) currency instruments (variations in limits on foreign currency exchange mismatches and net open positions).

Source: Authors’ calculations.


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II. The impact of macroprudential policies and their interaction with monetary policy: new evidence using credit registry data


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Main characteristics of the CCA research project

Joint project under the auspices of the Consultative Council for the Americas (CCA): Credit register data for five Latin America countries:

AR, BR, CO, MX, PE (good laboratory) Not possible to pool the data (data highly confidential) Research protocol (same modelling strategy and similar data

definition) Focus on domestic credit. Project wants to complement the

analysis of the IBRN (cross-border spillover of MaPs) Total of 15 episodes analysed:

- 12 tightening vs 3 easing- 6 enhancing resilience vs 9 dampening the cycle

Leonardo Gambacorta“On the effectiveness of macroprudential measures” 7

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Main results

Macroprudential tools are effective in stabilising credit cycles

A tightening in macroprudential policies is associated with a reduction in credit growth of 4.2% after three months and 7.2% after one year

Prudential policies aimed at raising additional buffers through capital requirements or provisioning take more time to manifest their effects

There is evidence from country team papers that lending supply reacts differently for banks with a different level of risk and capitalization

The effectiveness of macroprudential policies on credit growth is affected by monetary policy conditions

Macroprudential tools that acted as a complement to monetary policies (ie pushed in the same direction) were relatively more effective

8Leonardo Gambacorta“On the effectiveness of macroprudential measures”

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Effects of MaPs on credit growth after 3 months are different. MaPs with main aim to improve resilience are less effective

NOTE: Weights are from random effects analysis

Overall (I-squared = 99.7%, p = 0.000)

Argentina 4

Colombia 2 2

Mexico 1 1

Brazil 1

Colombia 1 2

Colombia 2 1

country

Argentina 2

Peru 1

Colombia 1 1

Colombia 3 2

Colombia 3 1

Argentina 1

Argentina 3

-0.02 (-0.05, 0.02)

-0.16 (-0.20, -0.13)

-0.30 (-0.89, 0.30)

0.00 (-0.01, 0.02)

-0.02 (-0.04, 0.00)

0.01 (0.01, 0.02)

-0.13 (-0.26, -0.01)

ES (95% CI)

-0.05 (-0.11, 0.00)

-0.02 (-0.04, -0.01)

0.01 (-0.00, 0.02)

-0.07 (-0.07, -0.07)

-0.05 (-0.07, -0.04)

-0.01 (-0.05, 0.03)

0.45 (0.32, 0.57)

100.00

8.72

0.33

9.34

9.17

9.56

4.34

Weight

7.79

9.39

9.49

9.56

9.43

%

8.49

4.38

-0.02 (-0.05, 0.02)

-0.16 (-0.20, -0.13)

-0.30 (-0.89, 0.30)

0.00 (-0.01, 0.02)

-0.02 (-0.04, 0.00)

0.01 (0.01, 0.02)

-0.13 (-0.26, -0.01)

ES (95% CI)

-0.05 (-0.11, 0.00)

-0.02 (-0.04, -0.01)

0.01 (-0.00, 0.02)

-0.07 (-0.07, -0.07)

-0.05 (-0.07, -0.04)

-0.01 (-0.05, 0.03)

0.45 (0.32, 0.57)

100.00

8.72

0.33

9.34

9.17

9.56

4.34

Weight

7.79

9.39

9.49

9.56

9.43

%

8.49

4.38

0-.892 0 .892


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Effects of MaPs on credit growth after one year are quite similar.Also MaPs with main aim to improve resilience are effective

NOTE: Weights are from random effects analysis

Overall (I-squared = 98.2%, p = 0.000)

Colombia 1 2

Argentina 2

Colombia 3 2

Colombia 3 1

country

Argentina 4

Colombia 2 1

Colombia 1 1

Mexico 1 1

Brazil 1

Argentina 3

Peru 1

Colombia 2 2

Argentina 1

-0.10 (-0.14, -0.06)

-0.07 (-0.08, -0.06)

-0.11 (-0.13, -0.09)

-0.14 (-0.15, -0.13)

-0.22 (-0.25, -0.19)

ES (95% CI)

-0.12 (-0.15, -0.10)

-1.10 (-1.46, -0.75)

-0.11 (-0.14, -0.08)

0.01 (-0.04, 0.06)

-0.02 (-0.03, -0.01)

-0.13 (-0.16, -0.10)

-0.01 (-0.02, -0.00)

-1.41 (-3.89, 1.06)

-0.03 (-0.05, -0.01)

100.00

9.29

9.04

9.31

8.89

Weight

8.90

1.00

8.83

8.14

9.25

8.92

9.29

0.02

9.10

%

-0.10 (-0.14, -0.06)

-0.07 (-0.08, -0.06)

-0.11 (-0.13, -0.09)

-0.14 (-0.15, -0.13)

-0.22 (-0.25, -0.19)

ES (95% CI)

-0.12 (-0.15, -0.10)

-1.10 (-1.46, -0.75)

-0.11 (-0.14, -0.08)

0.01 (-0.04, 0.06)

-0.02 (-0.03, -0.01)

-0.13 (-0.16, -0.10)

-0.01 (-0.02, -0.00)

-1.41 (-3.89, 1.06)

-0.03 (-0.05, -0.01)

100.00

9.29

9.04

9.31

8.89

Weight

8.90

1.00

8.83

8.14

9.25

8.92

9.29

0.02

9.10

%

0-3.89 0 3.89


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III. Macroprudential policy and bank risk


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Cross-sectional dispersion of bank risk measures


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MaPs have asymmetric effects (Altunbas et al, 2018)

Data for 3,177 banks operating in 61 countries

MaPs have a significant impact on bank risk, both those focused on dampening the cycle and those that are specifically designed to enhance banks’ resilience

MaPs are more effective in a tightening than an easing

The responses to changes in MaPs differ among banks: small, weakly capitalised and with a higher share of wholesale funding react more strongly to changes in MaPs


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Effect of a MaP tightening: well vs low capitalized banks

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Note: The graph reports the effect on bank risk of a tightening in macroprudential tool. The leftpart indicates the effects on banks’ expected default frequency (left-hand axis), the right partthe effects on the Z-score (right-hand axis).Source: Altunbas, Binici and Gambacorta (2018).

Z-scoreEDF


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IV. What are the effects of macroprudential policies on macroeconomic performance?


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Do MaPs affect output growth and volatility? (Boar et al, 2017)

1,140 MaPs in 64 countries (29 AEs vs 35 EMEs)

Panel data analysis on annual data (1990-2014)

Finance and growth model á la Beck and Levine (2004)

GMM to tackle endogeneity issues

On average, we find beneficial effects of MaPs on macroeconomic performance

The effects are reduced when the degree of financial development becomes particularly large (shadow banking)


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Effects of a macroprudential tightening on Growth-at-Risk


Response of 0.05th quantile of GDP growth to a policy action and mean response.

Source: Franta and Gambacorta (2019).

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V. Conclusions


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Main takeaways (1)

MaPs have been quite effective in stabilising credit cycles and containing bank risk. The propagation of the effects to credit growth is more rapid (they materialise after one quarter) for policies aimed at curbing the cycle (ie LTV) than for policies aimed at fostering resilience (ie capital based), which take effect within a year

The responses of bank risk and credit to changes in MaPs differ depending on bank-specific characteristics: banks that are small, weakly capitalised and with a higher share of wholesale funding react more strongly to changes in macroprudential tools


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Main takeaways (2)

MaPs have a greater effect on credit growth when reinforced by the use of monetary policy to push in the same direction

Countries that more frequently used MaPs, other things being equal, experienced stronger and less volatile GDP growth. These effects are influenced by each economy's openness and financial development

MaPs are more effective if embedded in a broader macro-financial stability framework and coordination with other policies


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References

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Altunbas, Y, M Binici and L Gambacorta (2018), “Macroprudential policies and bank risk”, Journal of International Money and Finance, 39: 153–185.

Altunbas, Y, M Binici and L Gambacorta and A Murcia (2017), “New evidence on the effectiveness of macroprudential measures ”, VOX article, https://voxeu.org/article/new-evidence-effectiveness-macroprudential-measures.

BIS (2018), “Moving forward with macroprudential frameworks”, Annual Economic Report, June, 63-90.

Boar, C, L Gambacorta, G Lombardo and L Pereira da Silva (2017), “What are the effects of macroprudential policies on macroeconomic performance?”, BIS Quarterly Review, September.

Claessens, S, S Ghosh and R Mihet (2013), “Macro-prudential policies to mitigate financial system vulnerabilities”, Journal of International Money and Finance, 39, 153–85.

Franta, M and L Gambacorta (2019), “On the effects of macroprudential policies on Growth-at-Risk”, mimeo.

Gambacorta, L and A Murcia (2019), “The impact of macroprudential policies and their interaction with monetary policy: an empirical analysis using credit registry data”, Journal of Financial Intermediation, forthcoming.


https://voxeu.org/article/new-evidence-effectiveness-macroprudential-measures

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On the effectiveness of macroprudential measures