## _wp12132

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---

### Introduction
- The dollar peg provides the nominal anchor for monetary policy for all GCC countries (other than Kuwait), constraining monetary policy independence and shifting macroeconomic management toward fiscal policy, prudential regulation, and various controls.
- GCC monetary authorities use open market operations, standing facilities, liquidity and reserve requirements, long-term government bonds, and macroprudential instruments to manage short-term and structural liquidity conditions.
- Although openness of GCC capital accounts suggests rapid convergence of domestic interest rates toward U.S. nominal interest rates, several instances of deviations from U.S. rates occurred, especially after the global crisis.

### Data and scope
- Monthly series used: three-month local interbank rates for each GCC country (January 2004 to January 2011); for Oman the overnight rate was the only available rate.
- U.S. benchmark: three-month U.S.-LIBOR rate.
- Rationale: three-month maturity reduces risk-premium differential relative to longer-term maturities.

### Behavior of GCC interbank rates relative to U.S. rates
- January 2004–January 2011 sample findings:
  - Bahrain and Saudi Arabia: GCC three-month interbank rates closely mirrored U.S. interbank rates.
  - Kuwait, Oman, Qatar, United Arab Emirates: varying degrees of deviation from U.S. rates, particularly after the onset of the global crisis in 2007.
  - Oman: persistent pattern of low domestic interest rates relative to comparable U.S. interest rates throughout the sample period.
- Historical/related findings cited:
  - Bova (2012), January 1993–May 2009: GCC rates are co-integrated with the U.S. rate; long-run coefficient very close to one.
  - Speed of adjustment to long-run relationship (Bova, 2012):
    - Bahraini rate: less than two months.
    - Qatar: less than four months.
    - Saudi Arabia: more than four months.
    - United Arab Emirates: about six months.
    - Kuwait and Oman: about a year.
  - During the financial crisis years, speed of adjustment slowed for all economies except the United Arab Emirates.
  - Deviations were larger since 2009 in Qatar and the United Arab Emirates.
  - Kuwait and Oman have followed U.S. monetary policy less closely; reasons include currency basket flexibility (Kuwait) and stricter capital movement restrictions (Oman).
- Espinoza, Prasad, and Williams (2011):
  - Found interest rate convergence within the GCC before 2008 and divergence during the crisis.
  - Estimated a half-life of two to five months for convergence measures.

### Interest rate pass-through (2004–11)
- Approach:
  - Interbank rate used as a proxy for the policy rate.
  - Weighted average deposit and lending rates used where available.
  - Panel estimates produced for four GCC countries (Bahrain, Kuwait, Oman, Qatar); Saudi Arabia lacked lending-rate data and the United Arab Emirates lacked deposit-rate data for some series.
- Panel estimate:
  - Interest rate pass-through for the four-country panel: 0.30.
- Comparative context:
  - Euro Area: overnight and three-month deposit rates have pass-through reaching at most 40 percent even in the long run.
  - UK (Mizen and Hofmann, 2002): pass-through from policy rates to deposit rates larger than for lending rates.
  - United States (Kwapil and Scharler, 2006): long-run pass-through complete for most deposit categories and on average 0.57 for lending rates.
  - Euro Area (Kwapil and Scharler, 2006): average long-run pass-through to deposit rates 0.32; pass-through for weighted average lending rates 0.48.
  - Cross-study observation: pass-through varies by country, over time, and by loan type; consumer lending rates often show weakest pass-through.

### Pass-through estimates (GCC-wide panel long-term relationship)
- Baseline fixed-effect regressions (estimation in levels):
  - Deposit Rate_{i,t} = α + 0.50 Interbank rate_{i,t} + μ_i + ε_{i,t}  R^2 = 0.28  (t-statistic: (4.72))
  - Lending Rate_{i,t} = α + 0.30 Interbank rate_{i,t} + μ_i + ε_{i,t}  R^2 = 0.21  (t-statistic: (1.91))
- Interpretation:
  - A reduction of 100 basis points (bps) in the policy rate led to a reduction of almost 50 bps in banks’ deposit rates and 30 bps in their lending rates.
  - Retail rates used include rates on existing and new loans and deposits; transmission to new rates might be somewhat higher.
- Limitations:
  - Small sample size; estimates are indicative with wide error bands.
  - Sample covers pre-crisis inflationary period (driven by rents) and post-crisis aggressive rate cuts—pass-through size and speed may differ when policy tightens versus eases.
  - Rolling regressions (36-month moving sample) suggest some improvement in pass-through to lending rates in the recent period.

### Country-level co-integration analysis and dynamics
- Model and estimation:
  - Co-integrated VAR for two variables (Interbank rate, IB, and bank rate R) estimated on monthly data January 2004–December 2010 with 12 lags (with some country-specific shorter lag structures where needed).
  - Impulse responses use Cholesky decomposition with interbank rate ordered first; shocks normalized to a permanent one percentage point shock.
- Long-term sensitivity (co-integrating vector — long-term sensitivity to interbank rate):
  - Bahrain: Deposit Rate 0.63; Lending Rate 0.29
  - Kuwait: Deposit Rate 0.80; Lending Rate 0.74
  - Oman: Deposit Rate -0.05; Lending Rate 0.03
  - Qatar: Deposit Rate 0.20; Lending Rate 0.01
- Dynamic adjustment:
  - Bahrain: lending rate adjusts fully after 20 months.
  - Kuwait: deposit and lending rates adjust slowly—only half adjustment in first six months.
  - Oman and Qatar: immediate small sensitivity (around 0.1 to 0.3) but most impact vanishes after 10 months.
- Institutional and regulatory frictions identified:
  - Ceilings on interest rates; limits on portfolio shares by product/geography; limits on real estate lending; ceilings on personal lending; mandated lending rate ceilings benchmarked to policy rates; limited competition; limited use of variable-rate products; lottery systems for deposits; prolonged negative real deposit rates.
  - Specific country regulatory notes:
    - Oman: ceiling on personal lending of 40 percent of credit portfolio, and an interest rate cap.
    - Qatar: limits to real estate lending, absolute and interest rate ceilings on personal loans assigned against salary.
    - Kuwait: lending rates operate within a mandated ceiling benchmarked to the policy discount rate.
    - Bahrain: limits on consumer credit.
- Forecast error variance contribution at a 12-month horizon (contribution of interbank rate shocks to variance of Deposit Rate / Lending Rate):
  - Bahrain: 0.52 / 0.30
  - Kuwait: 0.87 / 0.54
  - Oman: 0.10 / 0.16
  - Qatar: 0.38 / 0.28
- Interpretation:
  - Shocks to interbank rates contribute 30 to 57 percent of variance of deposit and lending rates in the region, except where no long-term relationship exists (Oman).

### Monetary transmission in the GCC — panel VAR approach
- Objective:
  - Investigate transmission of U.S. monetary policy and GCC monetary shocks to GCC macroeconomic outcomes using panel VARs.
- Data:
  - Eight-variable panel VAR on non-oil real GDP (GCC Y), government expenditure (GCC G), CPI inflation (GCC P), broad money (GCC M2) for GCC countries, plus Fed Funds Rate (FFR), U.S. GDP (US Y), U.S. Personal Consumption Deflator (US P), and IMF agriculture commodity price index (COM P).
  - Annual sample: 1980–2010 (data for Oman and UAE start in 1981; Qatar in 1983). All variables but FFR expressed in logs and found I(1) in levels but stationary in differences.
- Annual data panel VAR (3 lags; 162 observations):
  - Identification via Cholesky ordering: COM_P, US_Y, US_P, FFR, then GCC variables (GCC_G ordered first among GCC).
  - Findings:
    - Shocks to FFR of around 50 basis points reduce U.S. growth and prices in year 3 but show no effect on GCC activity, prices, or broad money in the annual VAR.
    - Permanent increases by 8 percent of M2 increased prices by 2 percent and non-oil GDP by slightly less than 1 percent.
  - Identification issues:
    - A “Price Puzzle” is present in the annual VAR despite including COM_P; indicates difficulty identifying U.S. monetary shocks with annual data.
    - Reduced-form OLS estimates indicate FFR is negatively related to GCC non-oil GDP, CPI and M2—relationship stronger with third lag of FFR.
- Quarterly data panel VAR (annual GCC data interpolated to quarterly via cubic spline; 4 lags):
  - Quarterly VAR avoids the Price Puzzle.
  - Impulse responses (annualized conversions):
    - A 100 basis points increase in U.S. policy rate reduces U.S. activity and U.S. prices by about 0.1 percent after 10 quarters (reduction in U.S. activity marginally insignificant at 90th percentile).
    - World commodity prices decline by 2 percent after the shock.
    - GCC prices reduced by 0.8 percent after 10 quarters (statistically significant at 90th percentile).
    - Non-oil GDP in the GCC reduced by around 0.1 percent and M2 by 0.6 percent (these IRFs not significantly different from 0).
    - Shocks to M2 increase GCC prices with an elasticity of around 0.3; effect on activity insignificant.
  - Additional results:
    - Shocks to world commodity prices boost government spending.
    - Shocks to government spending increase non-oil GDP with an elasticity of around 0.1 after 10 quarters.
    - Shocks to U.S. GDP have positive spillovers on GCC non-oil GDP with an elasticity of 0.9 after 10 quarters.
    - Forecast error variance decomposition: main drivers of GCC non-oil GDP are commodity prices, government spending, and U.S. growth; monetary policy shocks contribute relatively little to variance of economic activity.
- Robustness exercises:
  - Country exclusion: IRFs robust to excluding UAE, Qatar, Bahrain, or Oman. Excluding Saudi Arabia or Kuwait yields different IRFs for GCC prices—Saudi Arabia and Kuwait are large economies with better data, so specifications including them considered more representative.
  - Specification changes: Adding one lag leaves IRFs almost unchanged; using 8 lags reintroduces a Price Puzzle though after three years impacts on prices turn negative.
  - Subsample analysis:
    - 1980–1994: VAR estimates align with theoretical priors (declines in commodity prices, U.S. inflation, U.S. growth, GCC growth, GCC inflation, and broad money after U.S. monetary shock).
    - 1995–2010: identification weaker; minor Price Puzzle and counterintuitive short-run increases in U.S. growth, commodity prices, and GCC growth after U.S. monetary tightening.
  - Ordering of FFR has some influence but estimated impact of U.S. monetary policy shocks on GCC prices did not depend much on FFR position overall.

### Interpretation and institutional considerations
- Interbank rates better reflect monetary policy outcomes and intentions than posted policy rates in the GCC context because monetary policy is conducted using a range of direct instruments.
- Use of interbank rates complicates interpretation: changes may reflect market dynamics (capital flows, interbank conditions) or monetary policy interventions.
- Institutional and market structure factors affecting pass-through and deviations:
  - Capital controls, domestic inflationary pressures, corporate-sector problems (e.g., Dubai), and investment company issues (Kuwait) can increase local risk premia and alter pass-through dynamics.
  - Competition, contestability, and deposit administration influence the degree and speed of pass-through.

### Summary findings and policy implications
- Key empirical conclusions:
  - Three-month interbank rates in the GCC closely mirrored U.S. rates only in Bahrain and Saudi Arabia; deviations exist in Kuwait, Qatar, and the UAE, particularly after the global crisis.
  - Pass-through of local interbank rates to local deposit and lending rates in Bahrain, Kuwait, Oman and Qatar is less than complete.
  - Co-integration analysis: long-term relationship strongest in Bahrain and Kuwait.
  - Panel VAR (quarterly) indicates U.S. monetary policy has a strong and statistically significant impact on broad money, non-oil activity, and inflation in the GCC:
    - An increase of 100 basis points in the Fed Funds Rate decreases broad money growth by 0.6 percentage point and non-oil activity by 0.1 percent 10 quarters after the shock.
    - Global commodity prices are reduced by 2 percent, contributing to lower GCC inflation (-0.8 percent).
- Policy implications recommended:
  - Low pass-through is tied to shallowness of money markets and market frictions.
  - To increase interest-rate pass-through and strengthen monetary policy transmission, focus on:
    - Continued development of domestic financial markets (diversify institutions and instruments).
    - Remove arbitrary limits on lending and interest rate ceilings.
    - Foster greater competition among intermediaries and broader use of variable-rate products.
  - Regulatory distortions that operate over the long run (interest rate caps; portfolio share limits) are primary frictions limiting policy impact; liberalization efforts have shown increases in pass-through over time.

*Source: _wp12132 - References.*

### References .............................................................................................................

### _wp12132 - References .............................................................................................................

### Introduction
- The dollar peg provides the nominal anchor for monetary policy for all GCC countries (other than Kuwait), constraining monetary policy independence and shifting macroeconomic management toward fiscal policy, prudential regulation, and various controls.
- GCC monetary authorities use open market operations, standing facilities, liquidity and reserve requirements, long-term government bonds, and macroprudential instruments to manage short-term and structural liquidity conditions.
- Although openness of GCC capital accounts suggests rapid convergence of domestic interest rates toward U.S. nominal interest rates, several instances of deviations from U.S. rates occurred, especially after the global crisis.

### Data and scope
- Monthly series used: three-month local interbank rates for each GCC country (January 2004 to January 2011); for Oman the overnight rate was the only available rate.
- U.S. benchmark: three-month U.S.-LIBOR rate.
- Rationale: three-month maturity reduces risk-premium differential relative to longer-term maturities.

### Behavior of GCC interbank rates relative to U.S. rates
- Findings from the sample January 2004–January 2011:
  - Bahrain and Saudi Arabia: GCC three-month interbank rates closely mirrored U.S. interbank rates.
  - Kuwait, Oman, Qatar, United Arab Emirates: varying degrees of deviation from U.S. rates, particularly after the onset of the global crisis in 2007.
  - Oman: persistent pattern of low domestic interest rates relative to comparable U.S. interest rates throughout the sample period.
- Historical/related findings cited:
  - Bova (2012), January 1993–May 2009: GCC rates are co-integrated with the U.S. rate; long-run coefficient very close to one.
  - Speed of adjustment to long-run relationship (Bova, 2012):
    - Bahraini rate: less than two months.
    - Qatar: less than four months.
    - Saudi Arabia: more than four months.
    - United Arab Emirates: about six months.
    - Kuwait and Oman: about a year.
  - During the financial crisis years, speed of adjustment slowed for all economies except the United Arab Emirates.
  - Deviations were larger since 2009 in Qatar and the United Arab Emirates.
  - Kuwait and Oman have followed U.S. monetary policy less closely; reasons include currency basket flexibility (Kuwait) and stricter capital movement restrictions (Oman).
- Espinoza, Prasad, and Williams (2011):
  - Found interest rate convergence within the GCC before 2008 and divergence during the crisis.
  - Estimated a half-life of two to five months for convergence measures.

### Interest rate pass-through (2004–11)
- Approach:
  - Interbank rate used as a proxy for the policy rate.
  - Weighted average deposit and lending rates used where available.
  - Panel estimates were produced for four GCC countries (Bahrain, Kuwait, Oman, Qatar); Saudi Arabia lacked lending-rate data and the United Arab Emirates lacked deposit-rate data for some series.
- Key empirical findings:
  - Panel estimates for the four GCC countries suggest that the interest rate pass-through was 0.30.
- Comparative literature context:
  - Euro Area: overnight and three-month deposit rates have pass-through reaching at most 40 percent even in the long run.
  - UK (Mizen and Hofmann, 2002): pass-through from policy rates to deposit rates larger than for lending rates.
  - United States (Kwapil and Scharler, 2006): long-run pass-through complete for most deposit categories and on average 0.57 for lending rates.
  - Euro Area (Kwapil and Scharler, 2006): average long-run pass-through to deposit rates 0.32; pass-through for weighted average lending rates 0.48.
  - Cross-study observations: pass-through varies by country, over time, and by loan type; consumer lending rates often show weakest pass-through.

### Transmission and macroeconomic impacts (panel VAR)
- A monetary VAR model estimated using panel data for the GCC indicates:
  - Strong and statistically significant impact of U.S. monetary policy on broad money, non-oil activity, and inflation in the GCC region.
  - Identification of U.S. monetary policy shocks is more convincing when using data over the period 1980–1994.
  - Unanticipated changes to broad money (including those due to discretionary central bank policy) increase prices but have no significant effects on non-oil GDP.

### Interpretation and institutional considerations
- Interbank rates better reflect monetary policy outcomes and intentions than posted policy rates in the GCC context because monetary policy is conducted using a range of direct instruments.
- Use of interbank rates complicates interpretation: changes may reflect market dynamics (capital flows, interbank conditions) or monetary policy interventions.
- Institutional and market structure factors affecting pass-through and deviations:
  - Capital controls, domestic inflationary pressures, corporate-sector problems (e.g., Dubai), and investment company issues (Kuwait) can increase local risk premia and alter pass-through dynamics.
  - Competition, contestability, and deposit administration influence the degree and speed of pass-through.

*Source: _wp12132 - References .............................................................................................................*

### 0.50 for lending and deposit rates, respectively; i.e., a reduction of 100 basis points (bps) in

### _wp12132 - 0.50 for lending and deposit rates, respectively; i.e., a reduction of 100 basis points (bps) in

### Pass-through estimates (GCC-wide panel long-term relationship)
- Baseline fixed-effect regressions (estimation in levels) indicate:
  - Deposit Rate_{i,t} = α + 0.50 Interbank rate_{i,t} + μ_i + ε_{i,t}  R^2 = 0.28  (t-statistic: (4.72))
  - Lending Rate_{i,t} = α + 0.30 Interbank rate_{i,t} + μ_i + ε_{i,t}  R^2 = 0.21  (t-statistic: (1.91))
- Interpretation:
  - A reduction of 100 basis points (bps) in the policy rate led to a reduction of almost 50 bps in banks’ deposit rates and 30 bps in their lending rates.
  - Retail rates used include rates on existing and new loans and deposits; transmission to new rates might be somewhat higher.
- Limitations noted:
  - Small sample size; estimates are indicative with wide error bands.
  - Sample covers pre-crisis inflationary period (driven by rents) and post-crisis aggressive rate cuts—pass-through size and speed may differ when policy tightens versus eases.
  - Rolling regressions (36-month moving sample) suggest some improvement in pass-through to lending rates in the recent period.

### Country-level co-integration analysis and dynamics
- Model and estimation:
  - Co-integrated VAR for two variables (Interbank rate, IB, and bank rate R) estimated on monthly data January 2004–December 2010 with 12 lags (with some country-specific shorter lag structures where needed).
  - Impulse responses use Cholesky decomposition with interbank rate ordered first; shocks normalized to a permanent one percentage point shock.
- Long-term sensitivity (Table 1: Co-integrating Vector — long-term sensitivity to interbank rate):
  - Bahrain: Deposit Rate 0.63; Lending Rate 0.29
  - Kuwait: Deposit Rate 0.80; Lending Rate 0.74
  - Oman: Deposit Rate -0.05; Lending Rate 0.03
  - Qatar: Deposit Rate 0.20; Lending Rate 0.01
- Dynamic adjustment (Figure 4):
  - Bahrain: lending rate adjusts fully after 20 months.
  - Kuwait: deposit and lending rates adjust slowly—only half adjustment in first six months.
  - Oman and Qatar: immediate small sensitivity (around 0.1 to 0.3) but most impact vanishes after 10 months.
- Institutional and regulatory frictions identified as causes of incomplete pass-through:
  - Examples: ceilings on interest rates; limits on portfolio shares by product/geography; limits on real estate lending; ceilings on personal lending; mandated lending rate ceilings benchmarked to policy rates; limited competition; limited use of variable-rate products; lottery systems for deposits; prolonged negative real deposit rates.
  - Specific country regulatory notes:
    - Oman: ceiling on personal lending of 40 percent of credit portfolio, and an interest rate cap.
    - Qatar: limits to real estate lending, absolute and interest rate ceilings on personal loans assigned against salary.
    - Kuwait: lending rates operate within a mandated ceiling benchmarked to the policy discount rate.
    - Bahrain: limits on consumer credit.
- Forecast error variance contribution at a 12-month horizon (Table 2):
  - Contribution of interbank rate shocks to variance of Deposit Rate / Lending Rate (12 months ahead):
    - Bahrain: 0.52 / 0.30
    - Kuwait: 0.87 / 0.54
    - Oman: 0.10 / 0.16
    - Qatar: 0.38 / 0.28
  - Interpretation: shocks to interbank rates contribute 30 to 57 percent of variance of deposit and lending rates in the region, except where no long-term relationship exists (Oman).

### Monetary transmission in the GCC — panel VAR approach
- Objective:
  - Investigate transmission of U.S. monetary policy and GCC monetary shocks to GCC macroeconomic outcomes using panel VARs.
- Data:
  - Eight-variable panel VAR on non-oil real GDP (GCC Y), government expenditure (GCC G), CPI inflation (GCC P), broad money (GCC M2) for GCC countries, plus Fed Funds Rate (FFR), U.S. GDP (US Y), U.S. Personal Consumption Deflator (US P), and IMF agriculture commodity price index (COM P).
  - Annual sample: 1980–2010 (data for Oman and UAE start in 1981; Qatar in 1983). All variables but FFR expressed in logs and found I(1) in levels but stationary in differences.
- Annual data panel VAR (3 lags; 162 observations):
  - Identification via Cholesky ordering: COM_P, US_Y, US_P, FFR, then GCC variables (GCC_G ordered first among GCC).
  - Findings from OLS estimates (Table 4) and annual IRFs (Figure 5):
    - Shocks to FFR of around 50 basis points reduce U.S. growth and prices in year 3 but show no effect on GCC activity, prices, or broad money in the annual VAR.
    - Permanent increases by 8 percent of M2 increased prices by 2 percent and non-oil GDP by slightly less than 1 percent (last column in Table 4).
  - Identification issues:
    - A “Price Puzzle” (policy rate increases followed by higher inflation) is present in annual VAR despite including COM_P; indicates difficulty identifying U.S. monetary shocks with annual data.
    - Reduced-form OLS estimates indicate FFR is negatively related to GCC non-oil GDP, CPI and M2—relationship stronger with third lag of FFR.
- Quarterly data panel VAR (annual GCC data interpolated to quarterly via cubic spline; 4 lags):
  - Quarterly VAR avoids the Price Puzzle.
  - Impulse response magnitudes (converted to annual IRFs, Figure 6):
    - A 100 basis points increase in U.S. policy rate reduces U.S. activity and U.S. prices by about 0.1 percent after 10 quarters (reduction in U.S. activity marginally insignificant at 90th percentile).
    - World commodity prices decline by 2 percent after the shock.
    - GCC prices reduced by 0.8 percent after 10 quarters (statistically significant at 90th percentile).
    - Non-oil GDP in the GCC reduced by around 0.1 percent and M2 by 0.6 percent (these IRFs not significantly different from 0).
    - Shocks to M2 increase GCC prices with an elasticity of around 0.3; effect on activity insignificant.
  - Additional VAR results:
    - Shocks to world commodity prices boost government spending.
    - Shocks to government spending increase non-oil GDP with an elasticity of around 0.1 after 10 quarters.
    - Shocks to U.S. GDP have positive spillovers on GCC non-oil GDP with an elasticity of 0.9 after 10 quarters.
    - Forecast error variance decomposition: main drivers of GCC non-oil GDP are commodity prices, government spending, and U.S. growth; monetary policy shocks contribute relatively little to variance of economic activity.
- Robustness exercises:
  - Country exclusion (Figure 7): IRFs robust to excluding UAE, Qatar, Bahrain, or Oman. Excluding Saudi Arabia or Kuwait yields different, counterintuitive IRFs for GCC prices—Saudi Arabia and Kuwait are large economies with better data, so specifications including them (VAR1–VAR5) considered more representative.
  - Specification changes (Figure 8): Adding one lag leaves IRFs almost unchanged; using 8 lags reintroduces a Price Puzzle though after three years impacts on prices turn negative. Subsample analysis:
    - 1980–1994: VAR estimates align with theoretical priors (declines in commodity prices, U.S. inflation, U.S. growth, GCC growth, GCC inflation, and broad money after U.S. monetary shock).
    - 1995–2010: identification weaker; minor Price Puzzle and counterintuitive short-run increases in U.S. growth, commodity prices, and GCC growth after U.S. monetary tightening.
  - Ordering of FFR has some influence but estimated impact of U.S. monetary policy shocks on GCC prices did not depend much on FFR position overall.

### Summary findings and policy implications
- Key empirical conclusions:
  - Three-month interbank rates in the GCC closely mirrored U.S. rates only in Bahrain and Saudi Arabia; deviations exist in Kuwait, Qatar, and the UAE, particularly after the global crisis.
  - Pass-through of local interbank rates to local deposit and lending rates in Bahrain, Kuwait, Oman and Qatar is less than complete.
  - Co-integration analysis: long-term relationship strongest in Bahrain and Kuwait.
  - Panel VAR (quarterly) indicates U.S. monetary policy has a strong and statistically significant impact on broad money, non-oil activity, and inflation in the GCC:
    - An increase of 100 basis points in the Fed Funds Rate decreases broad money growth by 0.6 percentage point and non-oil activity by 0.1 percent 10 quarters after the shock.
    - Global commodity prices are reduced by 2 percent, contributing to lower GCC inflation (-0.8 percent).
- Policy implications recommended:
  - Low pass-through is tied to shallowness of money markets and market frictions.
  - To increase interest-rate pass-through and strengthen monetary policy transmission, focus on:
    - Continued development of domestic financial markets (diversify institutions and instruments).
    - Remove arbitrary limits on lending and interest rate ceilings.
    - Foster greater competition among intermediaries and broader use of variable-rate products.
  - Regulatory distortions that operate over the long run (interest rate caps; portfolio share limits) are primary frictions limiting policy impact; liberalization efforts have shown increases in pass-through over time.

*Source: Authors' calculations and analysis in the supplied IMF chapter content.*

### References

### _wp12132 - References

### References list
- Baele, L., A. Ferrando, P. Hördahl, E. Krylova, and C. Monnet, 2004, “Measuring Financial Integration in the Euro Area,” ECB Occasional Paper No. 14 (Frankfurt am Main: European Central Bank).
- Boivin, J., and M. Giannoni, 2010, “Global Forces and Monetary Policy Effectiveness,” in J. Galí and M. Gertler (eds.) International Dimensions of Monetary Policy, University of Chicago Press, pp. 429–488.
- Bondt, Gabe de, 2002, “Retail Bank Interest Rate Pass-Through: New Evidence at the Euro Level,” ECB Working Paper No. 136, April (Frankfurt am Main: European Central Bank).
- Bondt, Gabe de, B. Mojon and N. Valla, 2003, “Term Structure and the Sluggishness of Retail Bank Rates in Euro Area Countries,” ECB Working Paper, April (Frankfurt am Main: European Central Bank).
- Bova, E., forthcoming, “Interest Rate Spread in the GCC: the Role of Monetary Policy Intervention,” IMF working paper (Washington: International Monetary Fund).
- Chinn, M. and G. Meredith, 2004, “Monetary Policy and Long-Horizon Uncovered Interest Parity,” IMF Staff Papers 51(3): 409–430.
- Christiano, L.J, M. Eichenbaum and C. L. Evans, 1999, “Monetary Policy Shocks: What Have We Learned and to What End?” Handbook of Macroeconomics, Volume 1, Part A, pp. 65–148.
- Cottarelli, Carlo and Angeliki Kourelis, 1994, “Financial Structure, Bank Lending Rates, and the Transmission Mechanism of Monetary Policy,” IMF Staff Papers, Vol. 41(4).
- Efron, B. and R.J. Tibshirani, 1993, An Introduction to the Bootstrap (New York: Chapman & Hall).
- Espinoza, R., A. Prasad, and O. Williams, 2011, “Regional Financial Integration in the GCC,” Emerging Markets Review, Vol. 12, pp. 354–370.
- Espinoza, R., and A. Senhadji, 2011, “How Strong are Fiscal Multipliers in the GCC? An Empirical Investigation,” IMF Working Paper 11/61 (Washington DC: International Monetary Fund).
- Hanson, M.S., 2004, “The Price Puzzle Reconsidered,” Journal of Monetary Economics, pp. 1385–1413.
- Miniane, J., and J.H. Rogers, 2007, “Capital Controls and the International Transmission of U.S. Money Shocks,” Journal of Money, Credit and Banking, pp. 1004–1035.
- Mizen, P. and B. Hofmann, 2002, “Base Rate Pass-Through: Evidence from Banks’ and Building Societies’ Retail Rates,” Bank of England Working Paper No. 170 (London).
- Prasad, Ananthakrishnan and May Khamis, 2011, “Monetary Policy and the Transmission Mechanism in the GCC Countries,” in Gulf Cooperation Council Countries: Enhancing Economic Outcomes in an Uncertain Global Economy (Washington: International Monetary Fund).
- Runkle, D. E., 1987, “Vector Autoregressions and Reality,” Journal of Business and Economics Statistics, Vol. 5, pp.437–442.
- Sander, Harald and Stefanie Kleimeier, 2004, “Convergence in Euro-Zone Retail Banking? What Interest rate Pass-Through Tells Us about Monetary Policy Transmission, Competition and Integration,” Journal of International Money and Finance, Vol. 23.
- Sellon Jr., G., 2002, “The Changing U.S. Financial System: Some Implications for Monetary Transmission Mechanism,” Federal Reserve Bank of Kansas City Economic Review, First Quarter.
- Sims, C., 1992, Interpreting the Macroeconomic Time Series Facts: The effects of Monetary Policy," European Economic Review, Vol. 36, pp. 975–1000.
- Sims, C., 1998, “Comment on Glenn Rudebuschs’ ‘Do Measures of Monetary policy in a VAR Make Sense?’” International Economic Review, Vol.36, pp. 933–941.
- Scharler, Johann, and Claudia Kwapil, 2010, “Interest Rate Pass-Through, Monetary Policy Rules, and Macroeconomic Stability,” Journal of International Money and Finance, 2010, Vol. 29(2), pp. 236–251.
- Zha, T., 1997, “Identifying Monetary Policy: A Primer,” Federal Reserve Bank of Atlanta Economic Review, Vol. 82, pp. 26–43.

*Source: _wp12132 - References.*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2012/_wp12132.pdf_