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Macroprudential policy under uncertainty

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Abstract

In this paper, an index of domestic macroprudential policy tools is constructed and the effectiveness of these tools in controlling credit growth, managing GDP growth and steadying inflation is studied using a dynamic panel data model for the period between 2000 and 2017. The empirical analysis includes two panels namely an EU panel of 27 countries and a Latin American panel of 7 countries, the paper also looks at a case study of Japan, Portugal and the UK. Our main results show that a tighter overall macroprudential policy stance would result in lower credit growth as well as lower GDP growth while, a tighter overall macroprudential policy tool stance would lead to higher inflation in the majority of cases. Factors such as capital openness and the perception of global market risk play an important role in both the exigency of policy implementation as well as the success thereof.

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Fig. 1

Source: Author’s Index based on Alam et al. (2019), Cerutti et al. (2017) and IMF (2018)

Fig. 2

Source: Author’s Index based on Alam et al. (2019), Cerutti et al. (2017) and IMF (2018)

Fig. 3

Source: Author’s Index based on Alam et al. (2019), Cerutti et al. (2017) and IMF (2018)

Fig. 4

Source: Author’s Index based on Alam et al. (2019), Cerutti et al. (2017) and IMF (2018)

Fig. 5

Source: Author’s Index based on Alam et al. (2019), Cerutti et al. (2017) and IMF (2018)

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Notes

  1. Vice-President of the ECB between June 2010 and May 2018.

  2. See Borio (2003).

  3. Tovar et al. (2012) and Habermeier et al. (2011).

  4. See Vandenbussche et al. (2012), Ahuja and Nabar (2011), The Hong Kong Monetary Authority (2011), Kim (2014), Zhang and Zoli (2014), Crowe et al. (2011) and Cerutti et al. (2015).

  5. Baba and Kokenyne (2011) find that capital controls that do not cover the majority of inflows may not have the macroeconomic impact that is expected even if they are successful at reducing targeted flows.

  6. See Peydró (2016).

  7. Regression results of robustness checks available on request.

  8. Higher perceived volatility in the markets which hence, results in investors becoming more risk averse.

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Acknowledgements

I am grateful to a blind reviewer at the PEJ, Luis Costa, Ana Venâncio, Isabel Proença and André Teixeira for their useful comments. I am also grateful to António Afonso for his useful comments. Any omissions or exclusions are exclusively the author’s own.

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Authors and Affiliations

  1. ISEG - Lisbon School of Economics and Management, Universidade de Lisboa; UECE – Research Unit On Complexity and Economics, R. Miguel Lúpi, 20, P - 1249-078, Lisbon, Portugal

    Zoë Venter

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  1. Zoë Venter
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Correspondence to Zoë Venter.

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Appendices

Appendix A

1.1 Variable sources

Table 8 Sources of variables
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1.2 Variable definitions

Table 9 Definitions of variables
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1.3 Summary statistics

Table 10 Summary statistics for Japan, Portugal and the UK
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Table 11 Summary statistics for the European panel, the Latin American panel and the full sample
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Appendix B

2.1 Maddala and Wu Test (Maddala and Wu 1999) for the presence of panel unit roots

Table 12 Maddala and Wu unit root tests
Full size table

2.2 First generation fisher type tests (Phillips–Perron Test) for the presence of panel unit roots

Table 13 Results of fisher type unit root tests
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2.3 Second generation pesaran test (Pesaran 2007) for the presence of panel unit roots

Table 14 Pesaran unit root tests
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2.4 Wooldridge test for autocorrelation in panel data and durbin watson test for autocorrelation:

Table 15 Results of wooldridge test for autocorrelation in panel data and durbin watson test for autocorrelation
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2.5 Modified wald test for heteroskedasticity:

Table 16 Results for modified wald test for heteroskedasticity
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Appendix C

3.1 Additional regression results: sum of macroprudential policy choices with instrumental variables

Table C1 focuses on the sum of macroprudential policy choices and the value of the macroprudential policy choice index is therefore indicative thereof. An instrumental variable (Regulatory Quality) is included to account for any measurement error, omitted variable bias or simultaneity bias that may occur due to the endogeneity of the macroprudential policy tool index. The coefficient on lagged credit growth is positive and statistically significant for the first regression in the case of the Latin American panel and Japan, in the remaining cases the sign is positive with the exception of the negative sign in the case of Portugal. The coefficient on lagged GDP growth is positive and statistically significant for the second regression for the cases of the EU panel, the Latin American panel, Japan and Portugal while, in the case of the full sample, the sign is negative. Further, the coefficient on lagged inflation growth is positive and statistically significant in the all cases except that of the UK. In the remaining cases, the sign is positive with the exception of the first regression for the case of Portugal, the second regression for the full sample and the third regression for the case of the UK. When considering the full sample for the third regression, the coefficient on the macroprudential index is positive and statistically significant implying that a tighter macroprudential stance generally results in higher inflation when looking at the full sample.

Table 17 Regression results for sum of macroprudential policy changes with Instrumental variables
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Appendix D

4.1 Policy instruments

Table 18 - Summary of Various Macroprudential Policy Instruments
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4.2 iMaPP database and other existing databases

Table 19 Summary of Data Sources and Coverage of the iMaPP Database, constituting Databases as well as Other Macroprudential Databases
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Note (As Defined by Alam et al. 2019):

  1. 1)

    The classification of instruments differs across databases. The column "Instruments" shows the number of categories, including subcategories, available in each dataset, without standardizing classification.

  2. 2)

    "T/L indexes" is the dummy-type indexes for tightening and loosening actions of macroprudential policy measures.

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Venter, Z. Macroprudential policy under uncertainty. Port Econ J 21, 161–209 (2022). https://doi.org/10.1007/s10258-021-00194-8

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