Publication Details
Abstract
This study empirically investigates the impact of the Central Bank of the Republic of Uzbekistan's key monetary policy instruments on the liquidity of commercial banks over the period January 2017 – December 2025, using 108 monthly observations sourced from the Central Bank's statistical database. Five monetary policy variables — the policy rate, the required reserve ratio, the broad money supply (M3), the money market interest rate, and inflation — are examined in relation to four principal Basel III-aligned liquidity indicators: the ratio of High-Quality Liquid Assets to Total Assets (HQLA/TA), the Liquidity Coverage Ratio (LCR), the Net Stable Funding Ratio (NSFR), and the Instantaneous Liquidity Ratio (IML). A Structural Vector Autoregression (SVAR) model with a lag order of two is employed to identify the transmission channels, complemented by Augmented Dickey-Fuller and KPSS stationarity tests, Johansen cointegration analysis, Granger causality tests, Impulse-Response Functions (IRF), and Forecast Error Variance Decomposition (FEVD). The results reveal that all nine variables are integrated of order one, I(1), and that two long-run cointegrating relationships exist between monetary instruments and liquidity indicators. Granger causality tests confirm a highly significant channel from inflation to the NSFR (F = 11.35, p < 0.001), as well as statistically meaningful effects of the policy rate and the required reserve ratio on the HQLA ratio. The IRF analysis demonstrates that instantaneous liquidity is the most sensitive indicator to monetary shocks, with the policy rate producing a peak negative response of −1.18% and an M3 shock generating a peak positive response of +7.8% within one to three months. The FEVD results indicate that monetary policy instruments explain 24.38% of the variance in IML, 23.84% in HQLA, 18.39% in NSFR, and 11.30% in LCR over a twelve-month horizon. The study identifies the COVID-19 pandemic (2020) and geopolitical stress (2022) as structural break points during which monetary transmission channels are markedly amplified. On this empirical basis, the paper recommends daily real-time monitoring of the Instantaneous Liquidity Ratio for Domestically Systemically Important Banks (D-SIBs), the integration of inflation forecasts into bank liquidity stress-testing, the introduction of differentiated reserve requirements, the closer coordination of monetary aggregate targeting with inflation targeting, and the incorporation of the SVAR framework into the Central Bank's annual stress-testing methodology.