Banks’ liquidity management dynamics: evidence from Indonesia

Abstract

PurposeThis 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/approachThe 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.FindingsThe 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 implicationsThe 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/valueTo 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.

How Does Liquidity Risk Interact with Credit Risk? A Comparison Study of Indonesia and Malaysia Banking

“…This view is based on the fact that holding liquidity requires high costs (Gafrej & Boujelbéne, 2021;Sahyouni et al, 2021). Furthermore, banks with high liquidity tend to make mistakes in lending (Ariefianto et al, 2021). Second, banks with low liquidity tend to be apt to solvency problems.…”

“…As a lender of last resort, the central bank tried to help the banking conditions at that time, but the crisis persisted. Indonesia, like Malaysia, is a bank-based economy (Ariefianto et al, 2021), is on the identical geography, and has similar demographic conditions, but when the 1997 financial crisis occurred, banks in Malaysia allegedly recovered faster (Asutay & Othman, 2020); hence many vital lessons to be learned from this history. Thus this phenomenon became the basis of this study.…”

The dynamic relationships of credit risk, profitability, and capital: Evidence from Indonesia

“…The study also contributes to the field by utilizing a novel approach known as the dynamic common correlation effect (DCCE) approach. It takes into account cross-sectional unit dependence, a problem that the most recent panel techniques overlooked (Ariefianto, Trinugroho, Lau, & Sergi, 2022;Widjaja & Ariefianto, 2022).…”