Search results
1 – 2 of 2Moch. Doddy Ariefianto, Tasha Sutanto and Cecilia Jesslyn
This study aims to investigate the dynamic relationships between profitability, credit risk, liquidity risk and capital in Indonesian banking industry.
Abstract
Purpose
This study aims to investigate the dynamic relationships between profitability, credit risk, liquidity risk and capital in Indonesian banking industry.
Design/methodology/approach
The authors use a panel vector autoregression model that incorporates macroeconomic variables: growth, interest rate, foreign exchange. The analysis is based on a monthly panel data set of 88 banks spanning from January 2012 to September 2021, which comprises 10,296 bank-month observations.
Findings
Our key findings highlight (i) permanent credit cost and liquidity cost pass through practices, (ii) complementary function of liquidity and capital, (iii) earning management motivated asset write off and (iv) credit risk-liquidity risk neutrality. In addition, the authors observe that the banks demonstrated resilience to macroeconomic shocks.
Research limitations/implications
Our study have shown some interesting dynamic patterns of fundamentals; nevertheless, unified theoretical underpinning of the process is still unavailable. This should be an important future reasearch avenue.
Practical implications
The study brings significant implications for regulatory and supervisory practices aimed at enhancing the financial stability of banks.
Originality/value
We conduct estimation of Indonesian banks system in dynamic perspective and perform impulses responses.
Details
Keywords
Moch. Doddy Ariefianto, Irwan Trinugroho, Evan Lau and Bruno S. Sergi
This study aims to cover an important yet largely under-explored topic: the dynamic process of bank liquidity management in a vast developing economy by considering pool of funds…
Abstract
Purpose
This study aims to cover an important yet largely under-explored topic: the dynamic process of bank liquidity management in a vast developing economy by considering pool of funds hypothesis, signaling hypothesis and risk management hypothesis.
Design/methodology/approach
The authors apply the dynamic common correlated effect (DCCE) method with an error correction model format to a long panel datasets of 84 Indonesian banks from January 2003 to August 2019, resulting in 16,800 observations.
Findings
The authors obtain convincing evidence of dynamic liquidity management with an error correction mechanism. The time needed to adjust to a liquidity shock ranges from 2.5 to 3.5 months. The empirical results strongly support the pool of funds and signaling hypotheses, whereas risk management motive appears to have secondary importance.
Practical implications
The regulator should also encourage banks to diversify liquidity management to include interbank money market and off-balance-sheet instruments. The current condition shows that bank liquidity management is strongly correlated with intermediation dynamics and thus is contracyclical. Banks could end up with tight liquidity in a booming economy, which would pose a severe risk to their financial standing.
Originality/value
To authors’ knowledge, this study is the first to analyze bank liquidity management behavior empirically using a panel error correction mechanism. Here, the authors also try to combine a practitioner perspective with a scientific one.
Details