Banks' Regulatory Buffers, Liquidity Networks and Monetary Policy Transmission

Merkl, Christian; Stolz, Stéphanie

doi:10.2139/ssrn.2793911

Cited by 8 publications

(2 citation statements)

References 12 publications

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“…Here, capital, liquidity and risk are used as dependent variables, bank specific factors and macroeconomic variables are used as controls. Thus, to estimate the capital, risk and liquidity adjustments of banks, we followed Louzis et al (2012), Merkl and Stolz (2009) and Salas and Saurina (2002) standard model used in empirical studies. The model specifications of these studies follow the generalized method of moments (GMM) estimators developed for the dynamic panel data model by Holtz-Eakin et al (1990), Arellano and Bond (1991) and Arellano and Bover (1995).…”

Section: Literature Reviewmentioning

confidence: 99%

Bank capital, liquidity and risk in Ghana

Carsamer

Abbam

Queku

2021

JFRC

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Purpose Capital, risk and liquidity are the vitality of the banking industry, which can improve the efficiency of banking and promote the efficiency of resource allocation. The purpose of this study is to examine how Basel III new liquidity ratios affect bank capital and risk adjustments and how banks respond to the new liquidity rules. Design/methodology/approach The authors adopted the system generalized method of moments (GMM) to examine how Basel III new liquidity ratios affect bank capital and risk adjustments and how banks respond to the new liquidity rules. Based on the call reports data from banks, GMM was used to test the hypotheses that new liquidity ratios affect bank capital and risk adjustments, as well as how banks respond to the regulation. Findings The results indicate banks targeted capital, risk and liquidity and simultaneously coordinate short-term adjustments in capital and risk. New liquidity measures enable banks to coordinate risk and liquidity decisions. Short-term adjustments in new liquidity rules inversely impact bank capital. Short-term adjustments in new liquidity rules inversely impact bank capital and capital adjustments adversely affect changes in the liquidity coverage ratio (LCR). Research limitations/implications The primary results revealed that Ghanaian banks simultaneously coordinate and target capital, risk exposure and liquidity level. Also, capital adjustments positively influence risk adjustments and vice versa while bidirectional negative coordination exists between bank capital and risk on one hand and liquidity on the other hand. Short-term adjustments in new liquidity rule inversely impact bank capital and capital adjustments adversely affect changes in the LCR. The findings partially confirm the theoretical predictions of Repullo (2005) regarding the negative links between capital, risk and liquidity but the authors have higher capital induces higher risk. Practical implications Banks should balance off their targeted risk and liquidity in order not to sacrifice capital accumulation for liquidity. Originality/value This research offers new contributions in the research of bank management of capital and liquidity toward banks during a financial crisis from a theoretical perspective and trust management from an applicative perspective.

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Section: Literature Reviewmentioning

confidence: 99%

Bank capital, liquidity and risk in Ghana

Carsamer

Abbam

Queku

2021

JFRC

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“…We are interested in the cumulative impact of macroeconomic and capital variables on current NPLs ratio. To achieve this objective, long‐run coefficients are calculated (following Merkl and Stolz (2009)) based on the estimated short run coefficients. To construct each long‐run coefficient βjLR in the previous two equations (8) and (9), short‐run coefficients are first estimated and then applying the following formula:

{β^{italicLR}}_{j} = \sum_{j = 1}^{j} β_{j} / ((), 1 - \sum_{j = 1}^{2} α_{j})

…”

Section: Methodsmentioning

confidence: 99%

Impact of bank capital on non‐performing loans: New evidence of concave capital from dynamic panel‐data and time series analysis in Malaysia

Hajja

2020

Int. J Fin Econ

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Amid the steep expansion in Malaysia household debt, we investigate the role of bank capital in disciplining non-performing loans (NPLs) after controlling for the macroeconomic environment. Utilizing generalized method of moments (GMM) on a dynamic panel-data of 19 commercial banks and stress testing of NPLs using vector autoregression (VAR) on aggregated-monthly time series of the banking system, we provide new evidence that the capital (in the past and in the future) is a concave function of NPLs implying that increasing the capital will initially increase the NPLs until NPLs reach a maximum threshold (under the moral hazard effect), after which more capital build ups will succeed in decreasing NPLs (under the disciplinary or regulatory effect). We also find that higher levels in GDP growth and lending interest rate and are associated with more NPLs, while higher inflation is associated with less NPLs. Monetary expansion, that is, higher money supply growth raises NPLs in banks, while competition between banks and higher liquidity of the stock market are NPLs reducing.

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