## 1. ECB Policy Rates and Tightening Cycles

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### Introduction
- From July 2022 to September 2023, the ECB increased its policy rates by 450 basis points, described as the ECB’s highest speed and largest magnitude of tightening from a historical perspective.
- Monetary policy transmits primarily via the banking and financial sector, affecting lending rates for consumers and corporates and interest received on deposits.
- Malta-specific observations:
  - Deposit rates with agreed maturity for households have increased broadly in line with the euro area, while rates for non-financial corporates (NFCs) have been subdued.
  - Mortgage rates have remained broadly stable.
  - Lending rates for NFCs increased about 100 basis points from June 2022 to September 2023, versus a 250 basis points increase in the euro area.
  - ECB’s composite cost of borrowing indicators suggest borrowing costs in Malta are the lowest for households and the third lowest for NFCs in the euro area.

### Measuring the Pass-Through — Methodology and Core Findings
- Methodology:
  - Deposit rate/Loan rate Beta = change in retail rate divided by change in monetary policy rate, using monthly changes from June 2022 to August 2023 for country-specific estimates.
  - Regression (Malta): Δrr_t = α + Σ_{k=0}^K β_k Δpr_{t−k}^{ECB} + Γ X_t + ε_t, with K = 3; X_t includes contemporaneous and lagged industrial production and core inflation; interaction dummy for recent tightening period included.
  - Cross-country panel expansion used for euro area comparison.
- Key empirical findings:
  - Pass-through to household deposits in Malta estimated at 0.6 (comparable to Austria, Finland, and the Slovak Republic).
  - For other retail products in Malta the pass-through is among the lowest in the euro area:
    - Mortgage loans: nearly zero.
    - NFC loans: 0.2.
    - NFC deposits: 0.3.
  - Malta table highlights:
    - Household total deposits: pass-through coefficients 0.37 for lag 1 and 0.24 for lag 3 (both statistically significant).
    - Interaction dummy coefficient for current tightening cycle is -0.137 (not significant), suggesting a weaker pass-through during the current cycle.
    - Longer-maturity deposits show larger lag coefficients (e.g., deposits over two years coefficient 0.722); overnight deposits coefficient about zero.
    - Pass-through coefficients for NFC deposits, household (mortgage) loans, and NFC loans were statistically insignificant in Malta.
  - Panel regressions for the euro area show generally positive and mostly statistically significant pass-through coefficients; pass-through in the recent cycle is weaker than in the previous tightening cycle.

### Response to Monetary Policy Shock: Cumulative IRF
- Method: Local-projection method (Jordà, 2005) to estimate impulse-response functions to a 1 percentage point shock to policy rates; monthly data January 2008 to August 2023.
- Results (Malta vs. euro area average):
  - Household deposits: positive response in Malta (not statistically significant); size of impulse response in Malta lower than euro area.
  - Other retail products (mortgage loans, NFC loans, NFC deposits): muted responses in Malta.
  - Euro area estimates suggest a statistically significant increase in retail rates over several months following a policy rate hike.
- Note: Confidence intervals presented for Malta only; euro area confidence intervals are outside zero for all estimations.

### Banking Sector Characteristics and Pass-Through
- Key banking metrics for Malta (2023:Q2 unless otherwise stated):
  - Core bank common equity Tier 1 capital ratios: about 20 percent.
  - Liquidity coverage ratios: nearly 400 percent.
  - Non-performing loan (NPL) ratio: 2.6 percent (historic low, 2023:Q2).
  - Core banks’ return on equity (ROE): 11 percent (2023:Q2).
  - Two largest banks (Bank of Valletta and HSBC Bank Malta) account for about 50 percent of total bank assets.
  - Loan-to-deposit ratios: generally low.
  - Claims on the Eurosystem remain high, reflecting excess liquidity.
- Correlations and panel regression (equation (2)) — cross-country panel (2022Q1–2023Q2, 19 euro area countries):
  - Higher loan-to-deposit ratio → stronger retail rate pass-through (i.e., ample liquidity associated with weaker pass-through).
  - Higher banking sector concentration → weaker retail rate pass-through.
  - Regression specification: Δrr_{c,t} = α + Σ_{k=0}^K β_k Δpr_{t−k}^{ECB} + Γ X_{c,t} + Φ Z_{c,t−1} + ϑ Δpr_t^{ECB} * Z_{c,t−1} + ε_t.
  - Z includes: total assets/GDP, CET1, liquid assets/total assets, NPL ratio, loan-to-deposit ratio, ROE, concentration (share of largest five banks or Herfindahl index).
  - Interaction coefficients: pass-through negatively correlated with capital, liquidity, NPL ratio, and concentration; positively correlated with loan-to-deposit ratio.
  - Interpretation: well-capitalized and liquid banks with better funding access react less to monetary policy shocks; poor credit quality can dampen responsiveness.

### Conclusions from Empirical Analysis
- The pace of monetary transmission in Malta has been much slower compared to other euro area countries during the recent tightening cycle.
- Considerable cross-country variation in pass-through exists across the euro area.
- Banking sector characteristics—including capital, liquidity, loan-to-deposit ratios, and concentration—significantly explain differential pass-through to retail rates.
- In Malta, abundant liquidity and relatively high banking system concentration are key factors behind the relatively limited pass-through from monetary policy rates.
- Other policies in Malta (borrower-based measures, interest rate caps, government mortgage support programs) have remained unchanged or have not been introduced since the beginning of the ECB monetary policy tightening cycle.

### Policy Implications of Weak Interest Rate Pass-Through
- Monetary policy transmission and macroeconomic stabilization:
  - Central Bank of Malta (2023) estimated that the direct impact from rising rates on economic activity and inflation would be quite limited.
  - Given the weak interest rate channel, fiscal policy should play an important role in macroeconomic stabilization.
  - Deposit rates have risen faster than lending rates, which could affect banks’ profitability and warrants close monitoring, especially for banks with a high loan-to-deposit ratio.
  - As Malta is a small open economy, indirect channels of monetary policy (notably lower economic activity in the euro area reducing demand for Malta’s exports, and lower import prices) could be more important.
- Empirical summary on pass-through (recent tightening cycle vs. full sample):
  - Evidence indicates weaker short-run and long-run pass-through from the policy rate to retail rates in the recent tightening cycle (2022–2023) compared with the full sample and pre-pandemic tightening cycles.
  - The subdued pass-through is consistent for both deposit and loan rates, and for both HH and NFC rates.
  - Possible contributing factors include ample liquidity and banking sector characteristics.

### Key Estimated Coefficients for Euro Area Pass-Through (Annex I. Table 1)
- HH Deposit Rates (Full sample):
  - ΔPolicyRate (t) = 0.201*** (0.042)
  - ΔPolicyRate (t-1) = 0.224*** (0.046)
  - ΔPolicyRate (t-2) = 0.113*** (0.032)
  - ΔPolicyRate (t-3) = 0.096** (0.042)
  - Observations = 4,134; Other controls = Yes; FE = Yes
- HH Deposit Rates (Recent Tightening Cycle):
  - ΔPolicyRate (t) = 0.112** (0.047)
  - ΔPolicyRate (t-1) = 0.082** (0.033)
  - ΔPolicyRate (t-2) = 0.052 (0.033)
  - ΔPolicyRate (t-3) = 0.037 (0.083)
  - Observations = 266; Other controls = Yes; FE = Yes
- NFC Deposit Rates (Full sample):
  - ΔPolicyRate (t) = 0.283*** (0.051)
  - ΔPolicyRate (t-1) = 0.235*** (0.049)
  - ΔPolicyRate (t-2) = 0.173*** (0.041)
  - Observations = 3,859; Other controls = Yes; FE = Yes
- NFC Deposit Rates (Recent Tightening Cycle):
  - ΔPolicyRate (t) = 0.189*** (0.039)
  - ΔPolicyRate (t-1) = 0.148** (0.066)
  - ΔPolicyRate (t-2) = 0.159*** (0.033)
  - Observations = 250; Other controls = Yes; FE = Yes
- HH Loan Rates (Full sample):
  - ΔPolicyRate (t) = 0.183*** (0.021)
  - ΔPolicyRate (t-1) = 0.195*** (0.022)
  - ΔPolicyRate (t-2) = 0.088*** (0.027)
  - ΔPolicyRate (t-3) = 0.067*** (0.023)
  - Observations = 4,048; Other controls = Yes; FE = Yes
- HH Loan Rates (Recent Tightening Cycle):
  - ΔPolicyRate (t) = 0.147*** (0.035)
  - ΔPolicyRate (t-1) = 0.152*** (0.015)
  - ΔPolicyRate (t-2) = 0.004 (0.029)
  - ΔPolicyRate (t-3) = 0.016 (0.028)
  - Observations = 266; Other controls = Yes; FE = Yes
- NFC Loan Rates (Full sample):
  - ΔPolicyRate (t) = 0.267*** (0.053)
  - ΔPolicyRate (t-1) = 0.166** (0.066)
  - ΔPolicyRate (t-2) = 0.202*** (0.076)
  - ΔPolicyRate (t-3) = 0.022 (0.056)
  - Observations = 4,334; Other controls = Yes; FE = Yes
- NFC Loan Rates (Recent Tightening Cycle):
  - ΔPolicyRate (t) = 0.223* (0.109)
  - ΔPolicyRate (t-1) = 0.137 (0.117)
  - ΔPolicyRate (t-2) = 0.451*** (0.095)
  - ΔPolicyRate (t-3) = 0.184 (0.136)
  - Observations = 275; Other controls = Yes; FE = Yes
- Notes: Standard errors in parentheses. Statistical significance markers: *** p<0.01, ** p<0.05, * p<0.1. Total deposits include deposit rates with agreed maturity only.

### Banking Sector Heterogeneity and Malta-Specific Coefficients
- Pass-through estimates conditional on bank characteristics show heterogeneous responses across Size, CET1, Liquidity, NPL, Loan-to-Deposit Ratio, ROE, Concentration, and Floating Loans Share.
- Selected Malta coefficients (preserve numeric values exactly):
  - HH Deposit: ΔPolicyRate (t-1) = 0.278*** (0.061) across bank-characteristic specifications; ΔPolicyRate (t) ranges from 0.097 to 0.506*** depending on specification.
  - NFC Deposit: ΔPolicyRate (t-1) = 0.381*** (0.037) across specifications; ΔPolicyRate (t) ranges from 0.117** to 0.659***.
  - HH Loan: ΔPolicyRate (t) = 0.232*** (0.054) in one specification; ΔPolicyRate (t-1) = 0.094* (0.040) in that same specification.
  - NFC Loan: ΔPolicyRate (t) = 0.200*** (0.036) in one specification; ΔPolicyRate (t-1) = 0.337*** (0.058).
  - Interaction terms (ΔPolicyRate * Z(t-1)) indicate that bank characteristics significantly modify pass-through in several specifications (examples include coefficients significant at ** and *** levels as reported).

### Policy Recommendations and Monitoring Priorities
- Prioritize fiscal policy for macroeconomic stabilization given weak direct interest rate transmission.
- Monitor bank profitability closely, as rising deposit rates relative to lending rates could compress net interest margins, particularly for banks with high loan-to-deposit ratios.
- Consider the role of indirect transmission channels for Malta (euro area demand and import prices) when designing policy responses.
- Supervisory attention on specific bank characteristics (CET1, liquidity, NPLs, loan-to-deposit ratios, concentration, and share of floating-rate loans) can help identify vulnerabilities and tailor macroprudential responses.

*Prepared by Mahir Binici; IMF staff calculations and ECB Data Portal used for figures and empirical analysis.*

### 1. ECB Policy Rates and Tightening Cycles __________________________________________________ 2

### 1. ECB Policy Rates and Tightening Cycles

### Introduction
- From July 2022 to September 2023, the ECB increased its policy rates by 450 basis points, described as the ECB’s highest speed and largest magnitude of tightening from a historical perspective.
- Transmission of monetary policy primarily occurs via the banking and financial sector, affecting lending rates for consumers and corporates and interest received on deposits.
- In Malta:
  - Deposit rates with agreed maturity for households have increased broadly in line with the euro area, while rates for non-financial corporates (NFCs) have been subdued.
  - Mortgage rates have remained broadly stable.
  - Lending rates for NFCs increased about 100 basis points from June 2022 to September 2023, versus a 250 basis points increase in the euro area.
  - ECB’s composite cost of borrowing indicators suggest borrowing costs in Malta are the lowest for households and the third lowest for NFCs in the euro area.

### Measuring the Pass-Through
- Methodology:
  - Deposit rate/Loan rate Beta = change in retail rate divided by change in monetary policy rate, using monthly changes from June 2022 to August 2023 for country-specific estimates.
  - Regression (Malta): Δrr_t = α + Σ_{k=0}^K β_k Δpr_{t−k}^{ECB} + Γ X_t + ε_t, with K = 3, including contemporaneous and lagged industrial production and core inflation in X_t; interaction dummy for recent tightening period included.
  - Cross-country panel expansion (Annex I) used for euro area comparison.
- Key empirical findings:
  - Pass-through to household deposits in Malta estimated at 0.6 (comparable to Austria, Finland, and the Slovak Republic).
  - For other retail products in Malta the pass-through is among the lowest in the euro area:
    - Mortgage loans: nearly zero.
    - NFC loans: 0.2.
    - NFC deposits: 0.3.
  - Table 1 (Malta) highlights:
    - Household total deposits: pass-through coefficients 0.37 for lag 1 and 0.24 for lag 3 (both statistically significant).
    - Interaction dummy coefficient for current tightening cycle is -0.137 (not significant), suggesting a weaker pass-through during the current cycle.
    - Longer-maturity deposits show larger lag coefficients (e.g., deposits over two years coefficient 0.722); overnight deposits coefficient about zero.
    - Pass-through coefficients for NFC deposits, household (mortgage) loans, and NFC loans were statistically insignificant in Malta.
  - Panel regressions for the euro area show generally positive and mostly statistically significant pass-through coefficients; pass-through in the recent cycle is weaker than in the previous tightening cycle.

### Response to Monetary Policy Shock: Cumulative IRF
- Method: Local-projection method (Jordà, 2005) to estimate impulse-response functions to a 1 percentage point shock to policy rates; monthly data January 2008 to August 2023.
- Results (Malta vs. euro area average):
  - Household deposits: positive response in Malta (not statistically significant); size of impulse response in Malta lower than euro area.
  - Other retail products (mortgage loans, NFC loans, NFC deposits): muted responses in Malta.
  - In contrast, euro area empirical estimates suggest a statistically significant increase in retail rates over several months following a policy rate hike.
- Note: Confidence intervals presented for Malta only; euro area confidence intervals are outside zero for all estimations.

### Banking Sector Characteristics and Pass-Through
- Key banking metrics for Malta (2023:Q2 unless otherwise stated):
  - Core bank common equity Tier 1 capital ratios: about 20 percent.
  - Liquidity coverage ratios: nearly 400 percent.
  - Non-performing loan (NPL) ratio: 2.6 percent (historic low, 2023:Q2).
  - Core banks’ return on equity (ROE): 11 percent (2023:Q2).
  - Two largest banks (Bank of Valletta and HSBC Bank Malta) account for about 50 percent of total bank assets.
  - Loan-to-deposit ratios: generally low.
  - Claims on the Eurosystem remain high, reflecting excess liquidity.
- Correlations and panel regression (equation (2)):
  - Higher loan-to-deposit ratio → stronger retail rate pass-through (i.e., ample liquidity associated with weaker pass-through).
  - Higher banking sector concentration → weaker retail rate pass-through.
  - Cross-country panel regression (sample 2022Q1–2023Q2, 19 euro area countries) specification:
    - Δrr_{c,t} = α + Σ_{k=0}^K β_k Δpr_{t−k}^{ECB} + Γ X_{c,t} + Φ Z_{c,t−1} + ϑ Δpr_t^{ECB} * Z_{c,t−1} + ε_t
    - Z includes banking sector characteristics: total assets/GDP, CET1, liquid assets/total assets, NPL ratio, loan-to-deposit ratio, ROE, concentration (share of largest five banks or Herfindahl index).
    - Interaction coefficients: pass-through negatively correlated with capital, liquidity, NPL ratio, and concentration; positively correlated with loan-to-deposit ratio.
  - Interpretation consistent with literature: well-capitalized and liquid banks with better funding access react less to monetary policy shocks; poor credit quality can dampen responsiveness.

### Conclusions
- The pace of monetary transmission in Malta has been much slower compared to other euro area countries during the recent tightening cycle.
- Considerable cross-country variation in pass-through exists across the euro area.
- Banking sector characteristics—including capital, liquidity, loan-to-deposit ratios, and concentration—significantly explain differential pass-through to retail rates.
- In Malta, abundant liquidity and relatively high banking system concentration are key factors behind the relatively limited pass-through from monetary policy rates.
- Other policies in Malta (borrower-based measures, interest rate caps, government mortgage support programs) have remained unchanged or have not been introduced since the beginning of the ECB monetary policy tightening cycle.

*Prepared by Mahir Binici; IMF staff calculations and ECB Data Portal used for figures and empirical analysis.*

### 15.      This has potentially important implications for policymaking. Taking into account the

### 15. Policy Implications of Weak Interest Rate Pass-Through

### Monetary policy transmission and macroeconomic stabilization
- Central Bank of Malta (2023) estimated that the direct impact from rising rates on economic activity and inflation would be quite limited.
- Given the weak interest rate channel, fiscal policy should play an important role in macroeconomic stabilization.
- Deposit rates have risen faster than lending rates, which could affect banks’ profitability and warrants close monitoring, especially for banks with a high loan-to-deposit ratio.
- As Malta is a small open economy, indirect channels of monetary policy (notably lower economic activity in the euro area reducing demand for Malta’s exports, and lower import prices) could be more important.

### Empirical findings: Malta and euro area pass-through
- Evidence indicates weaker short-run and long-run pass-through from the policy rate to retail rates in the recent tightening cycle (2022–2023) compared with the full sample and pre-pandemic tightening cycles.
- The subdued pass-through is consistent for both deposit and loan rates, and for both HH (household) and NFC (nonfinancial corporation) rates, suggesting reduced traditional efficacy of monetary policy in steering retail interest rates during the recent tightening cycle.
- Possible contributing factors include ample liquidity and banking sector characteristics.

Key estimated coefficients for euro area pass-through (Annex I. Table 1) — preserve numeric values exactly:
- HH Deposit Rates (Full sample):
  - ΔPolicyRate (t) = 0.201*** (0.042)
  - ΔPolicyRate (t-1) = 0.224*** (0.046)
  - ΔPolicyRate (t-2) = 0.113*** (0.032)
  - ΔPolicyRate (t-3) = 0.096** (0.042)
  - Observations = 4,134; Other controls = Yes; FE = Yes
- HH Deposit Rates (Recent Tightening Cycle):
  - ΔPolicyRate (t) = 0.112** (0.047)
  - ΔPolicyRate (t-1) = 0.082** (0.033)
  - ΔPolicyRate (t-2) = 0.052 (0.033)
  - ΔPolicyRate (t-3) = 0.037 (0.083)
  - Observations = 266; Other controls = Yes; FE = Yes
- NFC Deposit Rates (Full sample):
  - ΔPolicyRate (t) = 0.283*** (0.051)
  - ΔPolicyRate (t-1) = 0.235*** (0.049)
  - ΔPolicyRate (t-2) = 0.173*** (0.041)
  - Observations = 3,859; Other controls = Yes; FE = Yes
- NFC Deposit Rates (Recent Tightening Cycle):
  - ΔPolicyRate (t) = 0.189*** (0.039)
  - ΔPolicyRate (t-1) = 0.148** (0.066)
  - ΔPolicyRate (t-2) = 0.159*** (0.033)
  - Observations = 250; Other controls = Yes; FE = Yes
- HH Loan Rates (Full sample):
  - ΔPolicyRate (t) = 0.183*** (0.021)
  - ΔPolicyRate (t-1) = 0.195*** (0.022)
  - ΔPolicyRate (t-2) = 0.088*** (0.027)
  - ΔPolicyRate (t-3) = 0.067*** (0.023)
  - Observations = 4,048; Other controls = Yes; FE = Yes
- HH Loan Rates (Recent Tightening Cycle):
  - ΔPolicyRate (t) = 0.147*** (0.035)
  - ΔPolicyRate (t-1) = 0.152*** (0.015)
  - ΔPolicyRate (t-2) = 0.004 (0.029)
  - ΔPolicyRate (t-3) = 0.016 (0.028)
  - Observations = 266; Other controls = Yes; FE = Yes
- NFC Loan Rates (Full sample):
  - ΔPolicyRate (t) = 0.267*** (0.053)
  - ΔPolicyRate (t-1) = 0.166** (0.066)
  - ΔPolicyRate (t-2) = 0.202*** (0.076)
  - ΔPolicyRate (t-3) = 0.022 (0.056)
  - Observations = 4,334; Other controls = Yes; FE = Yes
- NFC Loan Rates (Recent Tightening Cycle):
  - ΔPolicyRate (t) = 0.223* (0.109)
  - ΔPolicyRate (t-1) = 0.137 (0.117)
  - ΔPolicyRate (t-2) = 0.451*** (0.095)
  - ΔPolicyRate (t-3) = 0.184 (0.136)
  - Observations = 275; Other controls = Yes; FE = Yes

Notes on statistical reporting:
- Standard errors shown in parentheses.
- Statistical significance markers: *** p<0.01, ** p<0.05, * p<0.1.
- Total deposits include deposit rates with agreed maturity only.

### Banking sector heterogeneity and pass-through (Malta-specific estimates)
- Pass-through estimates conditional on bank characteristics show heterogeneous responses across:
  - Size, CET1, Liquidity, NPL, Loan-to-Deposit Ratio, ROE, Concentration, and Floating Loans Share.
- Selected coefficients from Malta tables (preserve numeric values exactly):
  - HH Deposit: ΔPolicyRate (t-1) = 0.278*** (0.061) across bank-characteristic specifications; ΔPolicyRate (t) ranges from 0.097 to 0.506*** depending on specification.
  - NFC Deposit: ΔPolicyRate (t-1) = 0.381*** (0.037) across specifications; ΔPolicyRate (t) ranges from 0.117** to 0.659***.
  - HH Loan: ΔPolicyRate (t) = 0.232*** (0.054) in one specification; ΔPolicyRate (t-1) = 0.094* (0.040) in that same specification.
  - NFC Loan: ΔPolicyRate (t) = 0.200*** (0.036) in one specification; ΔPolicyRate (t-1) = 0.337*** (0.058).
- Interaction terms (ΔPolicyRate * Z(t-1)) indicate that bank characteristics significantly modify pass-through in several specifications (examples include coefficients significant at ** and *** levels as reported).

### Policy implications and monitoring priorities
- Fiscal policy should be prioritized for macroeconomic stabilization given weak direct interest rate transmission.
- Monitor bank profitability closely, as rising deposit rates relative to lending rates could compress net interest margins, particularly for banks with high loan-to-deposit ratios.
- Consider the role of indirect transmission channels for Malta (euro area demand and import prices) when designing policy responses.
- Given heterogeneity across banks, supervisory attention on specific bank characteristics (CET1, liquidity, NPLs, loan-to-deposit ratios, concentration, and share of floating-rate loans) can help identify vulnerabilities and tailor macroprudential responses.

*Source: IMF staff calculations; ECB Data Portal; Central Bank of Malta (2023).*

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_Source: https://www.imf.org/-/media/files/publications/cr/2024/english/1mltea2024002.pdf_