Abstract
This paper explores the in-depth effect of bank competition on liquidity hoarding by using a comprehensive strategy for empirical measurement. More precisely, we include all asset-, liability-, and off-balance-sheet items when generating our measures of bank liquidity hoarding. For a multiple-aspect assessment of banking market structure, we simultaneously employ non-structural proxies (Lerner index, Boone indicator, and H-statistic index) and structural measures (top-bank market concentration ratio and Herfindahl–Hirschman index). Through bank-level financial data from 30 Vietnamese banks during 2007–2021, we find strong and consistent evidence that higher bank competition increases total liquidity hoarding. Disaggregate analysis reveals that the increased accumulation in total liquidity hoarding is driven by asset and liability items on the balance sheet, though our findings indicate that bank competition reduces liquidity hoarding off balance sheets. We further shed light on how the impact of competition on liquidity hoarding depends on bank-level heterogeneity. The results suggest that the link is less pronounced for banks that are larger in size, hold more equity capital, and yield better profitability. Our set of results consistently supports the view that financially healthier banks are more effective in handling competitive pressures in the banking market, and thus they may have a better position to mitigate the liquidity hoarding effect from bank competition. Multiple robustness checks are employed to lend further strength to our conclusions.
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Data availability
The data used in this study are available upon reasonable request.
Notes
Standard errors are adjusted using the Windmeijer correction for the two-step GMM estimator, which are robust to potential problems from heteroskedasticity and autocorrelation.
To ensure that our findings are not driven by how we winsorize bank-level data, we also winsorize all bank-level data at 1% and 99%. The main findings obtained are not significantly changed. We thank an anonymous reviewer for this point.
We generated instruments using the GMM style, employing LHt-2 for all liquidity hoarding measures in the transformed (first differences) equation and ΔLHt-1 for the levels equation. Additionally, we opted to instrument lag 1 for other independent variables in both levels and differences. We applied this constraint cautiously to prevent situations where the instruments outnumber the individual units in the panel, adhering to a practical rule of thumb. We ensured the validity of our chosen instruments through the overidentification test, confirming that our regression models yield reliable results.
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Huynh, J. Bank competition and liquidity hoarding. Eurasian Econ Rev 13, 429–467 (2023). https://doi.org/10.1007/s40822-023-00240-0
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DOI: https://doi.org/10.1007/s40822-023-00240-0