The monetary policy pass-through mechanism: Is the search-for-yield incentive at work?

The study asks whether banks’ incentives to “search for yield” constitute an underlying supply-side mechanism driving the pass-through of monetary policy to bank outcomes. In the wake of the 2008 global financial crisis, attention has focused on how monetary policy affects banks through the lending and risk-taking channels. The paper argues that lower interest rates can erode bank profitability and prompt banks to expand lending and accept higher risks to meet return targets, potentially shaping how monetary policy transmits to the real economy. Vietnam provides a pertinent context: a bank-dominant financial system, multiple monetary policy tools (notably refinancing and rediscounting rates), and extensive banking reforms since WTO accession in 2007. The study’s purpose is to test whether search-for-yield incentives moderate the effects of monetary policy on (i) bank lending, (ii) bank risk-taking, and (iii) bank liquidity creation, thereby clarifying the supply-side mechanism in monetary pass-through and informing policymakers about how bank incentives shape policy effectiveness and financial stability.

The paper situates itself within the bank lending and bank risk-taking channels of monetary policy. The lending channel posits that policy tightening can reduce loanable funds or raise external finance premia, contracting lending (Bernanke and Blinder, 1988; Kashyap and Stein, 1995; Disyatat, 2011), while lower rates can relax lending standards (Maddaloni and Peydró, 2011). Evidence shows heterogeneous pass-through depending on bank size, capital, liquidity, and risk (e.g., Kashyap and Stein, 2000; Kishan and Opiela, 2006; Altunbas et al., 2010), and on reforms and market conditions (e.g., Hussain and Bashir, 2019; Zhan et al., 2021; Fabiani et al., 2022). The risk-taking channel suggests low rates increase risk tolerance and leverage, and influence risk via expectations/communication (Borio and Zhu, 2012; Dell’Ariccia et al., 2014; Angeloni et al., 2015). Empirical work confirms that lower rates increase banks’ risk-taking, conditional on bank characteristics (Altunbas et al., 2014; Jiménez et al., 2014; Drakos et al., 2016). Despite these strands, little work directly tests whether banks’ search-for-yield incentives—stemming from profit pressures under low-rate environments—constitute the mechanism behind pass-through. Prior related studies (Orzechowski, 2017; Dang and Dang, 2020) examine heterogeneity by profitability/performance but do not directly test search-for-yield as a mechanism or across multiple banking channels. The paper also links to the nascent literature on the bank liquidity creation channel (Berger and Bouwman, 2017; Dang and Dang, 2021; Dang and Huynh, 2022a), extending it by testing the role of search-for-yield.

Data: Unbalanced panel of 31 Vietnamese commercial banks from 2007–2019 (accounting for >90% of sector assets). Bank-level data are from annual financial reports; monetary policy indicators (refinancing and rediscounting rates) from the State Bank of Vietnam; macro variables (inflation, GDP growth) from World Bank WDI; stock market returns (VNIndex) from Vietstock. Bank-level variables are winsorized at the 2.5th and 97.5th percentiles. Dependent variables (bank outputs): - Bank lending channel: annual loan growth rate. - Bank risk-taking channel: natural logarithm of (1 + Z-score), where Z-score = (ROA + Capital) / σ(ROA); σ(ROA) computed using a three-year rolling window (also an alternative computation over full sample in robustness checks). Lower Z-score implies higher risk. - Bank liquidity creation channel: growth rate of liquidity creation using Berger and Bouwman (2009) methodology, with “cat fat” (includes off-balance-sheet items) and “cat nonfat” (excludes OBS). Key independent variables: - Monetary policy indicators: short-term policy rates—refinancing rate and rediscounting rate. In robustness checks, average short-term lending rates are used. - Search-for-yield (SFY) proxies: SFYroa = ROA minus its past three-year average; SFYroe = ROE minus its past three-year average. Lower values indicate stronger incentives to search for yield when current profitability falls below recent history. Controls: - Bank-specific: size (ln assets), capital (equity/asset), liquidity (liquid assets/total assets). In Z-score regressions, capital is replaced by business model proxy (non-interest income/total operating income) to avoid mechanical correlation with Z-score construction. - Macro: stock market return (VNIndex growth), GDP growth (economic cycle). Inflation is excluded in main regressions due to high correlation with policy rates. Econometric design: - Dynamic panel model estimated via two-step system GMM (Blundell and Bond, 1998) with lagged dependent variable, and all independent variables lagged one period to mitigate endogeneity. Instrument collapse (Roodman, 2009) is applied to avoid instrument proliferation. Validity assessed via Hansen test of over-identifying restrictions and AR(1)/AR(2) serial correlation tests (expect AR(1) present, AR(2) absent). - Baseline model: Y_{it} = a0 + a1·Y_{i,t-1} + a2·MPI_{t-1} + a3·SFY_{i,t-1} + a4·(MPI_{t-1}×SFY_{i,t-1}) + a5·Z_{i,t-1} + a6·X_{t-1} + ε_{it}, where Y is loan growth or ln(1+Z-score); analogous specification for liquidity creation growth. - Robustness: substitute MPI with lending rates; alternative Z-score construction; fixed-effects static models with Driscoll-Kraay standard errors; multiple SFY proxies; both liquidity creation measures.

- Bank lending channel: Policy rates have significant negative effects on loan growth. A 1 percentage point decrease in the refinancing rate raises bank loan growth by about 2.188% (Table 3, col. 1). The interaction between policy rates and SFY is positive and significant, showing that banks with stronger search-for-yield incentives amplify the pass-through. Example: a one-standard-deviation decrease in SFYroa (stronger SFY) increases the effect of a 1 pp refinancing rate change on loan growth by about 0.290% (~0.460 × 0.630). - Bank risk-taking channel: Policy rates enter positively and significantly in ln(Z-score) regressions, implying that lower rates reduce Z-score (higher overall risk), consistent with a risk-taking channel. For instance, a 1 pp decrease in the rediscounting rate changes bank overall riskiness by about 0.039% (Table 4, example). Interactions of policy rates with SFY are generally negative and significant, indicating that stronger SFY incentives magnify the risk-taking response to monetary easing. - Bank liquidity creation channel: Policy rates significantly and negatively affect liquidity creation growth (both cat fat and cat nonfat), establishing a liquidity creation channel. Interactions with SFY are positive and significant in most specifications, indicating that demotivated (profit-pressured) banks amplify the liquidity creation response to policy easing. Quantitatively, with the cat fat measure, a 1 pp drop in the refinancing rate increases liquidity creation growth by about 4.006%, amplified by approximately 2.809% when SFYroe rises by one standard deviation (~0.621 × 4.523) (Table 5, col. 2). Similar magnitudes and signs hold for cat nonfat (Table 6). - Robustness: Results hold when using average short-term lending rates, alternative Z-score construction, fixed-effects with Driscoll-Kraay errors, and across both SFY measures. Diagnostic tests (Hansen, AR(1)/AR(2)) support instrument validity and model specification.

The findings confirm that monetary policy transmits to bank outcomes via lending, risk-taking, and liquidity creation channels in Vietnam, and that a key supply-side mechanism underpinning this transmission is banks’ search-for-yield incentive. When policy easing compresses net interest margins and profitability, banks intensify lending, assume greater risk, and expand liquidity creation to meet return targets. This mechanism clarifies heterogeneity in pass-through across banks: those with stronger SFY incentives are more responsive to policy shocks. The results are relevant for monetary authorities and regulators, suggesting that the effectiveness and side effects of policy depend on bank incentives, not just traditional balance-sheet characteristics. Recognizing this mechanism helps anticipate procyclical lending and risk accumulation under low-rate environments and informs macroprudential calibration alongside monetary easing.

The paper contributes by (i) jointly examining three key banking channels—lending, risk-taking, and liquidity creation—within a single framework; (ii) directly testing and confirming the search-for-yield incentive as an underlying supply-side mechanism of monetary pass-through; and (iii) employing multiple policy rate indicators, alternative bank output measures, and robust econometric approaches. Evidence from Vietnamese banks (2007–2019) shows that monetary easing increases lending and liquidity creation while elevating risk-taking, with these effects amplified at banks exhibiting stronger search-for-yield incentives. Policymakers should account for bank incentive structures when designing and communicating monetary policy, potentially coordinating with macroprudential tools to mitigate risk-taking externalities. Future research should test generalizability across other countries and banking systems, and more rigorously investigate demand-side mechanisms interacting with bank incentives.

The study focuses on one country’s banking system, which may limit external validity. While the paper provides evidence for a supply-side mechanism (search-for-yield), it does not comprehensively model or test demand-side channels. Data constraints (e.g., unbalanced panel, winsorization) and the reliance on policy rates as monetary stance proxies are additional considerations. Extending to cross-country or multi-market settings and explicitly modeling demand-side effects are suggested for future work.