Borrower-based macroprudential measures and credit growth: How
biased is the existing literature?

J 2024

Borrower-based macroprudential measures and credit growth: How biased is the existing literature?

MALOVANÁ, Simona, Martin HODULA, Zuzana GRIC a Jozef BAJZÍK

Základní údaje

Originální název

Borrower-based macroprudential measures and credit growth: How biased is the existing literature?

Autoři

MALOVANÁ, Simona, Martin HODULA, Zuzana GRIC a Jozef BAJZÍK

Vydání

Journal of Economic Surveys, ENGLAND, John Wiley & Sons Ltd, 2024, 0950-0804

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

50206 Finance

Stát vydavatele

Velká Británie a Severní Irsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 5.300 v roce 2022

Organizační jednotka

Ekonomicko-správní fakulta

DOI

http://dx.doi.org/10.1111/joes.12608

UT WoS

001137177000001

Klíčová slova anglicky

Bayesian model averaging; borrower-based measures; macroprudential policy; meta-analysis; publication bias

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 24. 2. 2024 09:36, Mgr. Zuzana Gric, Ph.D.

Anotace

V originále

This paper analyzes over 700 estimates from 34 studies on the impact of borrower-based measures (such as loan-to-value, debt-to-income, and debt-service-to-income ratios) on bank loan provision. Our dataset reveals notable fragmentation in the literature concerning variable transformations, methods, and estimated coefficients. We run a meta-analysis on a subsample of 422 semi-elasticities from 23 studies employing a consistent estimation framework to draw an economic interpretation. We confirm strong publication bias, particularly against positive and statistically insignificant estimates. After correcting for this bias, the effect indicates a credit growth reduction of −0.6 to −1.1 percentage points following the occurrence of borrower-based measures, significantly lower than the unadjusted simple mean effect of the collected estimates. Additionally, our study examines the contexts of these estimates, finding that beyond publication bias, model specification and estimation method are vital in explaining the variation in reported coefficients.

Citovat

MALOVANÁ, Simona, Martin HODULA, Zuzana GRIC a Jozef BAJZÍK. Borrower-based macroprudential measures and credit growth: How biased is the existing literature? Journal of Economic Surveys. ENGLAND: John Wiley & Sons Ltd, 2024, s. 1-37. ISSN 0950-0804. Dostupné z: https://dx.doi.org/10.1111/joes.12608.

@article{2359657,
   author = {Malovaná, Simona and Hodula, Martin and Gric, Zuzana and Bajzík, Jozef},
   article_location = {ENGLAND},
   doi = {http://dx.doi.org/10.1111/joes.12608},
   keywords = {Bayesian model averaging; borrower-based measures; macroprudential policy; meta-analysis; publication bias},
   language = {eng},
   issn = {0950-0804},
   journal = {Journal of Economic Surveys},
   title = {Borrower-based macroprudential measures and credit growth: How biased is the existing literature?},
   url = {https://onlinelibrary.wiley.com/doi/10.1111/joes.12608},
   year = {2024}
}

TY  - JOUR
ID  - 2359657
AU  - Malovaná, Simona - Hodula, Martin - Gric, Zuzana - Bajzík, Jozef
PY  - 2024
TI  - Borrower-based macroprudential measures and credit growth: How biased is the existing literature?
JF  - Journal of Economic Surveys
SP  - 1-37
EP  - 1-37
PB  - John Wiley & Sons Ltd
SN  - 09500804
KW  - Bayesian model averaging
KW  - borrower-based measures
KW  - macroprudential policy
KW  - meta-analysis
KW  - publication bias
UR  - https://onlinelibrary.wiley.com/doi/10.1111/joes.12608
N2  - This paper analyzes over 700 estimates from 34 studies on the impact of borrower-based measures (such as loan-to-value, debt-to-income, and debt-service-to-income ratios) on bank loan provision. Our dataset reveals notable fragmentation in the literature concerning variable transformations, methods, and estimated coefficients. We run a meta-analysis on a subsample of 422 semi-elasticities from 23 studies employing a consistent estimation framework to draw an economic interpretation. We confirm strong publication bias, particularly against positive and statistically insignificant estimates. After correcting for this bias, the effect indicates a credit growth reduction of −0.6 to −1.1 percentage points following the occurrence of borrower-based measures, significantly lower than the unadjusted simple mean effect of the collected estimates. Additionally, our study examines the contexts of these estimates, finding that beyond publication bias, model specification and estimation method are vital in explaining the variation in reported coefficients.
ER  -

MALOVANÁ, Simona, Martin HODULA, Zuzana GRIC a Jozef BAJZÍK. Borrower-based macroprudential measures and credit growth: How biased is the existing literature? \textit{Journal of Economic Surveys}. ENGLAND: John Wiley \&{} Sons Ltd, 2024, s.~1-37. ISSN~0950-0804. Dostupné z: https://dx.doi.org/10.1111/joes.12608.

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