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3. Monetary and Macroprudential Policies in Saudi Arabia

Author(s):
Ahmed Al-Darwish, Naif Alghaith, Alberto Behar, Tim Callen, Pragyan Deb, Amgad Hegazy, Padamja Khandelwal, Malika Pant, and Haonan Qu
Published Date:
March 2015
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Author(s)
Naif Alghaith, Ahmed Al-Darwish, Pragyan Deb and Padamja Khandelwal 

Monetary policy in Saudi Arabia is anchored by the Saudi riyal’s peg to the U.S. dollar. Fiscal policy is therefore the primary macroeconomic management tool. However, there is a complementary role for liquidity management operations and macroprudential policy in macroeconomic and financial sector management. The Saudi Arabian Monetary Agency (SAMA) is currently developing its toolkit to manage liquidity. There is scope to reduce the volatility of the monetary base by implementing a formal liquidity forecasting framework and by taking steps to help strengthen the monetary policy transmission mechanism. Use of the macroprudential policy toolkit to manage systemic risk in Saudi Arabia would benefit if a formal macroprudential framework were set up, with SAMA as the designated authority and with publication of early warning indicators and risk assessments.

Monetary Policy in Saudi Arabia

Commodity price volatility in resource-rich countries poses significant challenges to policymakers. There is considerable volatility associated with conditions in global commodity markets, and swings in a commodity exporter’s terms of trade often spill over to the rest of the economy. When commodity prices rise, higher revenues often lead to a strengthening of the external balance and an increase in government spending, boosting activity in the noncommodity sector of the economy. With the influx of liquidity, credit and asset prices are likely to move closely with the commodity price cycle, and consumer and business confidence are likely to increase. When commodity prices drop, this cycle quickly reverses, putting particular stress on borrowers and financial institutions that have become overexposed during the upswing. While the cycles may be driven largely by exogenous factors, domestic policies play an important role in managing their impact.

Saudi Arabia is among the world’s largest oil exporters and is highly dependent on oil exports. In this context, it is useful to note key elements of the policy framework at the outset:

  • Monetary policy in Saudi Arabia is anchored by the Saudi riyal’s peg to the U.S. dollar. The peg—which has been in place for nearly three decades—provides credibility to monetary policy and stability to trade, income flows, and financial assets. However, the peg also means that Saudi Arabia has limited flexibility in monetary policy, as short-term policy interest rates closely follow U.S. Federal Reserve interest rates.

  • In the absence of an independent interest rate policy, the authorities use a mix of fiscal policy, liquidity management operations, and macroprudential regulations to influence economic activity and manage financial sector risks. While the credibility of the exchange rate peg helps anchor price expectations over the long term, fiscal policy has the primary responsibility for managing aggregate demand and minimizing volatility. Indeed, fiscal policy played a countercyclical role in the global financial crisis. However, fiscal policy is not always flexible enough to prevent credit booms and the buildup of systemic risk in the financial sector. There is, therefore, a complementary role for liquidity management operations and macroprudential policy.

Strong policy frameworks will help Saudi Arabia prepare for any potential challenges stemming from developments in the domestic and global economy. For example, Saudi Arabia will need to manage the effects of tapering of unconventional monetary policy in the United States. Meanwhile, financial deepening is increasing, and trade has contributed to more business-cycle synchronization with developing Asia rather than the United States. Coupled with the authorities’ plans to diversify the economy, these recent trends suggest an increasing relevance of monetary and macroprudential policies.

International Comparison of Monetary Policy Frameworks in Commodity Exporters

There is considerable heterogeneity in monetary policy frameworks across commodity exporters. Table 3.1 presents the monetary and exchange rate policy framework in Saudi Arabia, other Gulf Cooperation Council (GCC) countries, and 13 other commodity-exporting, high-income, and emerging market economies. All GCC countries, including Saudi Arabia, have conventional exchange rate pegs (all to the U.S. dollar, except Kuwait) and lack an independent interest rate policy. In contrast to the GCC, only six of the comparator countries (Algeria, Azerbaijan, Brunei, Indonesia, Kazakhstan, and Trinidad and Tobago) employ the exchange rate as the nominal anchor. Three of these (Azerbaijan, Brunei, and Trinidad and Tobago) have limited exchange rate flexibility in the form of a currency board or stabilized exchange rate.

Table 3.1.Monetary and Exchange Rate Policy Framework of Selected Commodity Exporters, end-April 2013
Monetary Policy FrameworkDe Facto Classification of Exchange Rate Arrangement
Hydrocarbon exports

(in percent of total, 2013)
Exchange rate

anchor
Inflation

targeting
Other1Currency

board
Conventional pegStabilized

arrangement
Crawl-like

arrangement
Other managed

arrangement
FloatingFree floating
Bahrain58.7USD
Kuwait58.2Basket
Oman45.2USD
Qatar54.5USD
Saudi Arabia44.4USD
United Arab Emirates30.0USD
Algeria31.7Basket
Azerbaijan236.6
Brunei Darussalam71.1Singapore dollar
Canada5.9
Chile
Indonesia22.0
Kazakhstan25.7USD
Malaysia8.8
Mexico3.7
Norway9.7
Russia313.3
South Africa
Trinidad and Tobago15.7USD
Sources: IMF, World Economic Outlook and Annual Report on Exchange Arrangements and Exchange Restrictions, 2013.

Includes countries that have no explicitly stated nominal anchor but rather monitor various indicators in conducting monetary policy.

The country maintains a de facto exchange rate anchor to the U.S. dollar.

The central bank has taken preliminary steps towards inflation targeting.

Sources: IMF, World Economic Outlook and Annual Report on Exchange Arrangements and Exchange Restrictions, 2013.

Includes countries that have no explicitly stated nominal anchor but rather monitor various indicators in conducting monetary policy.

The country maintains a de facto exchange rate anchor to the U.S. dollar.

The central bank has taken preliminary steps towards inflation targeting.

Other countries allow greater exchange rate flexibility. Algeria, Indonesia, and Kazakhstan have crawl-like or managed exchange rate arrangements, while five countries have floating exchange rates and target inflation. On average, countries with more diversified exports have a more flexible exchange rate regime.

No single policy framework is associated with better macroeconomic outcomes among commodity exporters over the past decade. Table 3.2 presents some key variables to assess macroeconomic performance and stability across commodity exporters. GCC countries, including Saudi Arabia, have mostly achieved high growth rates accompanied by low inflation. Kuwait, Qatar, and the United Arab Emirates have experienced higher growth volatility and inflation than other GCC countries. Among the non-GCC commodity-exporting countries with greater exchange rate flexibility, several performed worse than Saudi Arabia in terms of growth, volatility, and inflation. Only Malaysia and Chile performed at a comparable level to Saudi Arabia. Of course, it is important to acknowledge that growth potential may be lower in several countries, especially advanced economies (e.g., Canada and Norway). Additionally, growth in Saudi Arabia may be strong owing to rapid growth in fiscal expenditure. Saudi Arabia’s success in this regard is in part attributable to flexible labor markets and energy subsidies that are likely to have played a role in mitigating macroeconomic volatility and the risk of Dutch disease.

Table 3.2.Macroeconomic Performance in Selected Commodity Exporters
Volatility ofReal Gov’tCurrent
GDPGDPExpenditureAccount
GrowthGrowth1InflationGrowth2Balance
Bahrain5.51.71.610.47.9
Kuwait4.76.03.210.032.9
Oman4.92.92.810.39.4
Qatar11.96.64.414.921.6
Saudi Arabia5.22.82.210.116.9
United Arab Emirates4.74.34.37.29.7
GCC average6.14.13.110.516.4
Algeria3.71.63.910.712.5
Azerbaijan11.310.16.521.38.6
Brunei Darussalam1.62.00.74.044.6
Canada2.21.72.02.5−0.1
Chile4.42.03.26.3−0.1
Indonesia5.30.97.69.61.4
Kazakhstan7.93.38.513.2−0.2
Malaysia5.02.62.27.511.4
Mexico2.32.74.84.0−1.3
Norway1.71.41.94.013.7
Russia4.94.311.98.27.7
South Africa3.41.85.96.4−3.5
Trinidad and Tobago4.65.56.75.515.0
Non-GCC average4.53.15.17.98.4
Source: IMF, World Economic Outlook.

Computed as the standard deviation of growth.

Growth rate of general government expenditure deflated by Consumer Price Index; Data for Mexico and Trinidad and Tobago does not include net acquisition of non-financial assets.

Note: GCC = Gulf Cooperation Council.
Source: IMF, World Economic Outlook.

Computed as the standard deviation of growth.

Growth rate of general government expenditure deflated by Consumer Price Index; Data for Mexico and Trinidad and Tobago does not include net acquisition of non-financial assets.

Note: GCC = Gulf Cooperation Council.

The Monetary Policy Toolkit in Saudi Arabia

SAMA’s policy interest rates closely track U.S. short-term interest rates. The central bank sets an interest rate corridor using a repo rate (ceiling) and reverse repo rate (floor). Short-term interest rates in Saudi Arabia, including the Saudi Inter-Bank Offered Rate (SIBOR) and the SAMA bill rates (for maturities ranging from one week to one year), fluctuate within this corridor.6 The interest rate corridor is set to closely track short-term interest rates in the U.S. (Figure 3.1; see also Espinoza and Prasad, 2012).7

Figure 3.1.Interest Rates in Saudi Arabia, 1999–2014

(Period average, in percent)

Sources: Country authorities.

Large external surpluses and fiscal spending fuel a liquidity surplus in the banking system.8 An examination of the factors driving growth in the monetary base shows that government spending and repayment of government debt (proxied by net international reserves less government deposits) have been the main contributors (Figure 3.2). Banks hold large excess deposits at SAMA in the form of reverse repos, which creates room for credit expansion.9

Figure 3.2.Contributions to Monetary Base Growth

(In percent)

Sources: IMF and SAMA staff calculations.

Lacking the ability to set policy interest rates independently, SAMA has been developing other tools to manage liquidity and influence credit conditions:

  • Reserve requirements are SAMA’s most powerful tool to control liquidity. Banks are required to maintain cash reserves of 7 percent of demand deposits and 4 percent of time and saving deposits. Additionally, banks hold 20 percent of their deposits in the form of short-term assets to meet statutory liquidity requirements. The cash reserve requirements have been changed infrequently and were last adjusted during the global financial crisis.10

  • Repo transactions help manage domestic liquidity by injecting or absorbing overnight liquidity from the banking system. Eligible collateral includes government and SAMA securities. Repo operations increased significantly during the global financial crisis but have dropped to normal levels since 2010. Currently, the repo rate is 2 percent. This rate has remained unchanged since early 2009.

SAMA bills are issued to banks and nonbanks to absorb excess liquidity (Figure 3.3). There is a ceiling on the weekly issuance of SAMA bills to banks that is revised infrequently (the last revision was in February 2010). The current ceiling on weekly issuance is SAR 9 billion and maturities range between 1 and 52 weeks. SAMA sets the interest rate on SAMA bills administratively at 80 percent of the Saudi Inter-Bank Bid (SIBID) rate for the corresponding maturity in order to encourage transactions in the inter-bank market and reflect the lower risk of SAMA securities. Banks decide the amount of SAMA bills they purchase, with bids being prorated by maturity, and across banks in the event of oversubscription. SAMA bill issuance to nonbanks is on an ad hoc basis and is not included in the ceiling on weekly issuance. Despite the ceiling on weekly issuances, SAMA bill issuances are not consistently oversubscribed at present.

Figure 3.3.Liquidity Management by SAMA

(Billions of SAR not seasonally adjusted)

Sources: IMF and SAMA staff calculations.

  • Foreign exchange swaps are used to provide liquidity and absorb shocks stemming from the foreign exchange market. Swaps are similar to repo transactions in securities and have been used to provide the banking system with foreign exchange liquidity when the currency has come under speculative pressures. For instance, in the 1990s the riyal came under selling pressure in 1993 and 1998 due to falling oil prices. At these times, intervention in the forward market helped alleviate market pressures.

  • Placement of public funds is a complementary instrument to the day-to-day liquidity management through repos, issuance of SAMA bills, and foreign exchange swaps. If there is a shortage of liquidity in the system, SAMA may place deposits on behalf of autonomous government institutions with banks. Conversely, if there is an abundance of liquidity in the system, SAMA may withdraw the deposits placed with banks on behalf of the autonomous government institutions.

Stepped up issuance of SAMA bills has helped sterilize a significant part of the growth in surplus liquidity since 2009. The outstanding stock of SAMA bills has seen a significant increase in recent years as the weekly issuance has been increased to withdraw liquidity. However, the monetary base is volatile, suggesting scope to improve liquidity management. Forecasting the liquidity needs of the banking system can help guide the size and timing of liquidity operations, reduce excess liquidity, smooth the availability of credit, and strengthen the monetary transmission mechanism.

Empirical Analysis of Monetary Policy Transmission

Empirical analysis can help identify the channels of monetary transmission. Four channels through which monetary policy affects aggregate demand are often considered in the literature: the interest rate channel, the credit channel, the exchange rate channel, and the asset price channel. Monetary policy is considered to have an impact on the cost of credit through the interest rate channel, whereas the credit channel affects the availability of credit through the supply of bank reserves. Monetary policy also influences the exchange rate and asset prices—changes in the former can affect external demand, while the latter affects demand through wealth effects. The exchange rate channel is inactive in Saudi Arabia owing to the fixed exchange rate regime, while analysis of the asset price channel data is hampered by a lack of data on real estate prices. Thus, this analysis takes an approach similar to that of Espinoza and Prasad (2012) and models the interest rate and credit channels of monetary transmission. A key innovation in our analysis is that the transmission of shocks from the monetary base to economic activity through the credit channel is examined. In the empirical analysis, two model specifications are considered as a robustness check to support the validity of the results. The details of the empirical specification can be found in Appendix 3.1.

The main results of the analysis are summarized as follows:

  • Interest rates are not found to have a significant impact on economic activity. Results suggest that an increase in the U.S. federal funds rate has a significant negative impact on prices in Saudi Arabia, but the impact on non-oil output is found to be small and statistically insignificant.11 One explanation for the lack of impact from interest rates to output may be that often the rising U.S. interest rate is accompanied by strong growth and rising oil prices, which may offset a negative impact. An alternative explanation may be the presence of excess liquidity in the banking system, which may weaken the monetary transmission of shocks to policy interest rates.

  • There is strong evidence that the credit channel is active in Saudi Arabia. Impulse response functions across two different specifications indicate that a one standard deviation shock to credit has a positive and statistically significant impact on non-oil output after seven quarters (Figure 3.4). The point estimates of the output response suggest an elasticity ranging between 0.6 and 0.7 after seven quarters.

Figure 3.4.Saudi Arabia: Impulse Responses from a Cholesky 1 Standard Deviation Shock

Sources: IMF and SAMA staff estimates.

  • There is weak evidence in support of an economic impact from shocks to the monetary base. Impulse responses of non-oil output and prices to a monetary base shock are statistically significant in only one of the two specifications. However, the two different empirical specifications yield directionally similar and consistent results.

  • An increase in global oil prices increases government spending in Saudi Arabia. The impact of an increase in oil prices on government spending is positive and significant after three quarters.

  • An increase in the Consumer Price Index of partner countries increases prices in Saudi Arabia. Estimates imply an elasticity of Saudi prices to partner countries’ prices of nearly 0.6 after six months. This is due to the large weight of imported goods in the consumption basket.

  • An increase in U.S. GDP is found to have a positive and statistically significant impact on Saudi non-oil output. This likely reflects the impact of U.S. GDP on global oil demand, and consequently, oil prices and government spending.

These results suggest that a normalization of U.S. monetary policy is unlikely to have an adverse growth impact on Saudi Arabia, especially if driven by an improving U.S. economy. This is derived from the lack of an adverse impact of an increase in the U.S. federal funds rate on Saudi non-oil output and a positive impact from U.S. GDP. However, these results do not rule out an adverse impact on oil prices from surges in global financial market volatility related to premature normalization of U.S. monetary policy. In this scenario, fiscal policy has the space to respond to slowing growth given substantial buffers, while SAMA could provide liquidity to the financial system as needed.

In line with international experience, the surplus liquidity in the banking system may hamper monetary transmission. The lack of strong empirical evidence in support of the transmission of monetary shocks (interest rates and the monetary base) to economic activity and prices is not surprising, because bank liquidity has not been a constraining factor in the supply of credit (Saxegaard, 2006). With weak monetary transmission and interest rates that track U.S. rates, SAMA has limited ability to influence aggregate demand through the provision of additional reserves. Going forward, if oil prices moderate and result in reduced surplus liquidity, the monetary policy transmission may improve such that SAMA may be able to influence economic outcomes more actively through its liquidity management operations.

Macroprudential Policy in Saudi Arabia

In addition to implementing the Basel III capital and liquidity requirements, SAMA has used a wide variety of macroprudential instruments, including:

  • Capital tools: leverage ratio and provision requirements.

  • Liquidity tools: loan-to-deposit ratio, liquid-asset-to-deposit ratio.

  • Sectoral tools: loan-to-value (LTV) ratio, debt-to-income ratio (DTI), and concentration limits.

  • Exposure limits: large exposures.

During the last decade, SAMA has used a number of macroprudential tools to smooth credit growth. Banks have been encouraged to provision in a countercyclical way and provisioning levels increased to over 150 percent of gross nonperforming loans by end-2013. However SAMA’s countercyclical provisions are part of the supervisory process and are done on a bilateral basis with individual banks, based on microprudential concerns such as operating performance, composition of assets, and riskiness of the loan portfolio. Other instruments have been introduced to limit the build-up of risks, but they have been adjusted infrequently. For example, the DTI ratio was introduced at the end of 2005 to limit consumer credit and contain the buildup of household debt. However, since its introduction, it has not been adjusted. Similarly, it can be argued that the implementation of Basel III capital requirements in 2012 played a part in moderating credit growth in 2013, although implementation was not a direct response to developments in the credit market. Despite these measures, credit developments have been closely linked to developments in oil prices (Figure 3.5).

Figure 3.5.Growth in Bank Credit and Oil Prices

(Percent)

Sources: Country authorities; and IMF staff calculations.

Comparison of Saudi Macroprudential Policy with Other Commodity Exporters

The macroprudential toolkit in Saudi Arabia is comparable to other commodity exporters in terms of the macroprudential tools that have been used. Table 3.3 shows that SAMA has used most of the capital, liquidity, and sectoral tools that are popular with other commodity exporters. However, Saudi Arabia does not have caps on currency lending or foreign exchange positions, which are common among GCC countries as well as other commodity-exporting countries.12 Furthermore, Saudi Arabia does not explicitly limit real estate and other sectoral exposures, although SAMA does monitor such exposure of each bank as part of its routine surveillance process and imposes a loan-to-value ratio of 70 percent for real estate finance companies.

Table 3.3.Macroprudential Toolkit of Selected Commodity Exporters, 2013
Capital ToolsLiquidity ToolsSectoral ToolsExposure Limits
Leverage

Ratio
Dynamic

Provisions
Loan-to-

Deposit

Ratio
Liquidity

Requirements
Asset

Maintainance

Ratio
Concentration

Limit
Loan-to-

Value

Ratio
Debt to

Income

Ratio
Sectoral

Capital

Buffers
Limits on

Domestic

Currency

Loans
Foreign

Exchange

&

Currency
Real

Estate
Interbank
Saudi Arabia
Bahrain
Kuwait
Oman
Qatar
United Arab Emirates
Algeria
Azerbaijan
Brunei Darussalam
Canada
Chile
Indonesia
Kazakhstan
Malaysia
Mexico
Norway
Russia
South Africa
Trinidad and Tobago
Sources: IMF staff; and country authorities.Note: √ Not used countercyclically • Used countercyclically ○ Tightened over time, but not intended as a countercyclical tool
Sources: IMF staff; and country authorities.Note: √ Not used countercyclically • Used countercyclically ○ Tightened over time, but not intended as a countercyclical tool

Resource-rich countries are increasingly adopting countercyclical macroprudential policies to influence macroeconomic outcomes. The stance of macroprudential policy is explicitly linked to macroeconomic developments such as credit growth, real estate prices, levels of household and corporate indebtedness, etc. Table 3.3 shows that sectoral tools such as concentration limits and LTV and DTI ratios are the most popular, followed by liquidity and capital measures. Sectoral tools can be used to target risks emanating from specific sectors of the economy without affecting the wider economy. For example, if risks are limited to the real estate sector, sectoral tools such as LTV and DTI ratios may be more appropriate than capital and liquidity tools, since the sectoral tools can more effectively slow down lending to the real estate sector without affecting credit to the wider economy. Algeria, Azerbaijan, Canada, Chile, Malaysia, and Norway have used LTV and DTI ratios in a countercyclical way to contain credit. Mexico is planning to do the same in the near future. Algeria, Azerbaijan, and Canada have used liquidity requirements countercyclically, while Indonesia has a countercyclical loan-to-deposit ratio. Kazakhstan has introduced dynamic provisioning. Within the GCC, Kuwait used sectoral capital buffers and DTI ratios to curtail retail lending in 2008.

Effectiveness of Countercyclical Macroprudential Policy

A growing body of academic literature suggests that macroprudential policy can be effectively used in a countercyclical manner to influence economic activity and manage financial sector risk. Table 3.4 provides an overview of the empirical literature on the effectiveness of countercyclical macroprudential policy. For example, drawing on a sample of 49 countries that have actively applied macroprudential instruments, Lim and others (2011) assess the effectiveness of macroprudential instruments by examining the performance of the target (risk) variables before and after the use of the macroprudential policy instrument. They find that caps on LTV and DTI ratios, dynamic provisioning, and reserve requirements are effective in curtailing credit growth (Figure 3.6) and, to a lesser extent, asset price inflation.

Table 3.4.Summary of Literature Findings on Effectiveness of Macroprudential Tools
ReferenceInstrumentsMethodologyConclusion
Cross-country analysis
Arregui and others (2013)LTV, DTI, risk weights, reserve requirement, provisioning requirementDynamic panel regression on 38 countries based on Krznar and others (2013) data (2000-11) (see Table X)LTV, DTI, risk weights, reserve requirement effective in contaning credit (to GDP) and house price growth; reserve requirement asociated with leakages
Ahuja and Nabar (2011)LTV, DTIDynamic panel regression on the 2010 IMF Survey data (2000-10)LTV caps tend to have a decelerating effect on property price growth. LTVs and DTIs slow property lending growth
Almeida, Campello, Liu (2005)LTVPanel regression of house price growth and mortgage credit growth on a sample of 26 countries over the 1970–99 period.New mortgage borrowings are more sensitive to aggregate income shocks in countries with higher LTVs; house price more sensitive to income shocks in countries with higher LTVs
Dell’Ariccia and others (2012)Differential treatment of deposit accounts, reserve requirements, liquidity requirements, interest rate controls, credit controls, open foreign exchange position limitsPanel regression with a composite measure of the six instrumentsReduce the incidence of credit booms and decrease the probability that booms end up badly
IMF (2012), Board paper on interaction between monetary and macroprudential policyLTV, DTI, risk weights, reserve requirement, provisioning requirementDynamic panel regression on 38 countries based on Krznar and others (2013) data (2000-11) (see Table X)LTV, DTI, risk weights, reserve requirement effective in contaning credit and house price growth
Kuttner and Shim (2012)LTVs, DTIs, risk weights on mortgage loans, provisioning rules, exposure limits to the property sector, reserve requirement, capital gains tax at the time of sale of properties and stamp dutiesPanel regressions of housing price growth and housing credit growth on a sample of 57 countries (1980-10)LTV and DTI effective in curbing mortgage credit and house price growth
Lim and others (2011)LTVs, DTIs, ceiling on credit growth, reserve requirement, capital requirement, provisioning requirementDynamic panel regression on the 2010 IMF Survey data (2000-10)Reduce procyclicality of credit growth
Tovar and others (2012)Reserve requirement, dynamic provisioning, capital requirement etc.Dynamic panel data vector autoregression on 5 Latin American countries (Brazil, Chile, Colombia, Mexico and Peru) during 2003-11; Macroprudential measures are captured through a cumulative dummyAverage reserve requirements and a composite of other types of macroprudential policies had a moderate and transitory effect on credit growth
Vandenbussche and others (2012)Major prudential measures grouped into 29 categoriesError correction model on 16 Central, Eastern and Southeastern Europe from the late 1990s or early 2000s to end-2010Changes in the minimum capital requirement and non-standard liquidity measures (marginal reserve requirements on foreign funding, marginal reserve requirements linked to credit growth) have impact on housing price inflation.
Wong and others (2011)LTVPanel regression data from 13 economiesReduce the sensitivity of mortgage default risk to property price shocks; Tightening LTV caps in general would reduce household leverage
Individual-country analysis
Ahuja and Nabar (2011), Hong KongLTVVAR modelLTV has small effect on credit. LTV tightening could affect property activity through the expectations channel rather than through the credit channel
Craig and Hua (2011), Hong KongLTVs and stamp duties on property transactionsError-correction model of house price growthHelped slow down property price inflation.
Galac (2010), CroatiaCredit growth ceiling, marginal reserve requirement, foreign currency liquidity reserveRegression of total private creditCredit growth ceiling reduced domestic private but not total private sector credit growth (as domestic corporate debt was substituted with foreign). Marginal reserve requirement useful for building capital buffers.
Igan and Kang (2011), South KoreaLTV, DTIRegression of mortgage credit growth and house price growth on their determinants and dummy variable representing macroprudential policyReduce house price appreaciation and transaction activity
Jiménez and others (2012), SpainDynamic provisioningPanel regression on comprehensive bank-, firm-, loan- and loan application-level data from 1999 to 2010Mitigate credit supply cycles and have positive aggregate firm-level credit availability and real effects
Krznar and Medas (2012), CanadaLTV, DTI, amortization periodRegression of mortgage credit growth and house price growth on their determinants and dummy variable representing macroprudential policyReduce mortgage credit and house price growth
Wang and Sun (2013), ChinaReserve requirement ratio, house-related policies, capital ratio, liquidity ratio, reserves for impaired loans to total loans ratioPanel fixed-effects regression of loan growth, house price growth on 171 banks and 31 provinces between 2000 and 2011The change in the reserve requirement is negatively associated with loan growth, house-related policies, capital requirement and liquidity ratios are ineffective; reserve requirement and house related policies effective with respect to the house price growth
Note: DTI = loan-to-income; LTV = loan-to-value; VAR = vector autoregression.
Note: DTI = loan-to-income; LTV = loan-to-value; VAR = vector autoregression.

Figure 3.6.Change in Credit Growth After the Introduction of Instruments

(Percent)

Sources: Lim and others (2011); and IMF, International Financial Statistics.

Note: Lines denote average of sample countries’ y/y (year-over-year) growth in credit (detrended). “t” denotes the time of the introduction of instruments; LTV = loan-to-value ratio; DTI = debt-to-income ratio.

The experience from Canada also suggests that macroprudential policy measures taken to address a housing boom can be effective. Since 2008, in response to surging house prices and mortgage credit, the Canadian authorities undertook four rounds of measures to tighten mortgage rules. These measures included tightening LTV ratios on refinancing loans and on loans to purchase properties not occupied by the owner; reducing the maximum amortization periods to 25 years; and introducing a maximum total debt service ratio of 44 percent. Figures 3.7 and 3.8 suggest that mortgage credit growth slowed sharply after the first measures were taken in 2008, while house price growth, although more volatile, has also been lower since the measures were introduced. Krznar and Morsink (2014) formally test the effectiveness of macroprudential policy in Canada and conclude that the moderation in house prices and mortgage credit since 2010 has been due in part to policy measures.

Figure 3.7.Canada: Residential Mortgage Credit

(Year-over-year percent change)

Sources: Krznar and Morsink (2014); Bank of Canada.

Figure 3.8.Canada: House Prices

(Year-over-year percent change)

Sources: Krznar and Morsink (2014); Canada Real Estate Association.

Framework for Countercyclical Macroprudential Policy

A prerequisite for countercyclical macroprudential policy is a system of early warning indicators to signal vulnerabilities and guide the use of macroprudential tools. Indicators to identify systemic risks (such as macroeconomic imbalances and strong credit growth), inter-linkages between financial and real sectors, and fragility in the structure of the financial system can be used to determine timing for activation or deactivation of macroprudential instruments and to bring clarity and credibility to macroprudential policy. Indicators can be used in a “rules-based” fashion to time the use of macroprudential instruments (e.g., the Swiss guided discretion approach for the countercyclical capital buffer), or they can be used in a more “discretionary” way as a guide to macroprudential policymaking (e.g., UK core indicators monitored by the Financial Policy Committee). A recent paper by the Committee on the Global Financial System (CGFS, 2012) and the IMF Staff Guidance Note on Macroprudential Policy (IMF, 2014b, 2014c and 2014d) discuss the best practices in this area.

In order to strengthen macroprudential analysis, GCC countries generally conduct regular systemic assessments and publish financial stability reports. Table 3.5 shows that all other GCC countries now publish financial stability reports, although some have only recently started doing so. In Saudi Arabia, a dedicated Financial Stability Division, established in 2013, has recently developed an internal macroprudential dashboard (Table 3.6) and is improving the stress-testing framework, which should help establish an early warning system. It is also in the process of finalizing the first financial stability report. Outside the GCC, financial stability reports have a longer history, with Norway starting reporting in 1997 and Canada in 2002. Such reports help improve the transparency of risk recognition in the financial system and facilitate broad communication.

Table 3.5.Macroprudential Framework of Selected Commodity Exporters, 2013
Financial Stability ReportDesignated
(First Published)Macroprudential Authority
Saudi Arabia
Bahrain2007
Kuwait2013
Oman2013
Qatar2010
United Arab Emirates2013
Algeria
Azerbaijan2010
Brunei Darussalam
Canada2002
Chile2004
Indonesia2003
Kazakhstan2006
Malaysia2006
Mexico2006
Norway1997
Russia2012

(New Format)
South Africa2004
Trinidad and Tobago2008
Source: IMF; and national authorities.
Source: IMF; and national authorities.
Table 3.6.Internal SAMA Macroprudential Dashboard
IndicatorExamples
Overall economyOil GDP
Inflation
Oil Prices
Credit OverviewCredit growth (aggregate and by sector)
Credit to GDP
Credit Maturity
Banking Sector

(Credit risk, funding and liquidity risk, capital

adequacy, market risk, global risk, and

interconnectedness)
Total assets
Credit
Revenues
Profitability
Expenses
Nonperformng loans
Loan to deposit
Liquidity
Capital adequacy ratio
Investment breakdown
Insurance Sector

(Funding, liquidity risk, solvency, market risk)
Gross written premium
Net loss ratio
Profitability
Expenses
Liquidity
Solvency
Investment breakdown
Capital MarketMarket capitalization
Turnover
Profitability
Source: Saudi Arabian Monetary Authority.
Source: Saudi Arabian Monetary Authority.

More broadly, a formal framework for macroprudential policy is important to ensure effectiveness. A framework helps establish responsibility for macroprudential policy and ensures that the designated authority has the willingness to act and coordinate with other authorities when necessary. Regulatory “underlap” in advanced economies was considered a big factor behind the global financial crisis. A framework also ensures access to information for effective early warning and ensures that the macroprudential authority has the requisite powers to act in the face of evolving risk. Such powers can be “hard” (direct), “semi-hard” (comply or explain), or “soft” (recommendation), depending on tools and country-specific factors. Finally, as with the early warning system and dashboard, a formal framework helps in communication to create public awareness of risk and allows markets to form expectations about future action.

Commodity-exporting countries, particularly those that use macroprudential tools in a countercyclical way, are moving toward formal frameworks. This is done by designating a macroprudential authority to ensure coordination and assign responsibility for macroprudential regulation. Brunei, Canada, Mexico, Russia, and South Africa have established Financial Stability Boards to coordinate and implement macroprudential policy, while other countries such as Kazakhstan and Malaysia have given the central bank explicit powers over macroprudential policy (Table 3.6). Internationally, three broad frameworks have evolved:

  • Central Bank with explicit mandate and powers (e.g., Czech Republic)

  • Committee within central bank (e.g., UK Financial Policy Committee)

  • Committee outside central bank (e.g., Australia, France, United States)

Currently, macroprudential tools in Saudi Arabia are used outside of a formal macroprudential framework and coordination among regulators is largely informal. However, the authorities are considering a formal macroprudential framework, and SAMA has carried out a detailed study, identifying the key requirements, international developments in peer and other countries, and the tools and instruments for its implementation. The structure is yet to be decided upon, but it is likely that the overall responsibility will reside with SAMA, with inputs from other institutions.

Conclusions and Policy Recommendations

The normalization of U.S. monetary policy is expected to have a limited economic impact on Saudi Arabia, especially if it is accompanied by stronger U.S. economic prospects. Empirical results indicate an increase in U.S. interest rates may not impact Saudi non-oil output. However, if a premature normalization of U.S. monetary policy results in a surge in global financial market volatility and has an adverse impact on oil prices, economic activity in Saudi Arabia could slow. In such a scenario, fiscal policy would have the space to smooth spending, while SAMA could provide liquidity to the financial system.

SAMA has been developing its toolkit to influence credit and liquidity conditions. In recent years, large external surpluses and fiscal spending have fueled a liquidity surplus in the banking system. To absorb this liquidity, SAMA has used a number of instruments ranging from reserve requirements to more market-based instruments such as repo operations and issuance of SAMA bills. Reserve requirements were used actively to manage liquidity during the global financial crisis in 2008, but SAMA bills are used to absorb excess banking system liquidity on a more regular basis. SAMA has increased the volume of SAMA bills being issued over time. However, the monetary base is volatile, suggesting that it may be useful to develop a formal liquidity forecasting framework and further refine liquidity management tools.

There is scope to strengthen monetary policy transmission. Fiscal policy is the primary macroeconomic management tool. However, as a result of excess liquidity in the banking system, SAMA has a limited ability to contribute toward the management of aggregate demand through the provision of additional reserves. Going forward, SAMA may find it useful to deploy more active liquidity management operations to reduce excess liquidity and strengthen monetary policy transmission to help manage the impact of future shocks. In this direction, steps to strengthen monetary policy transmission may include developing the markets for short- and long-term securities to aid in the transmission of policy signals.

The macroprudential toolkit in Saudi Arabia is comparable to that of other commodity exporters although it has not generally been used in a countercyclical way. Macroprudential policies are increasingly being used in a countercyclical manner in many commodity-exporting countries to influence economic activity and financial sector risk. The experience of other countries suggests that these policies have been effective in limiting systemic risk.

A formal framework for countercyclical macroprudential policy would help to ensure effectiveness. Although early warning indicators and financial risk assessments are being developed, macroprudential tools in Saudi Arabia are currently used outside of a formal macroprudential framework, and coordination among regulators is largely informal. Establishing a formal framework with SAMA as the designated macroprudential authority would bring clarity and credibility to macroprudential policy and ensure the willingness to act and coordinate with other authorities when necessary. It would also be useful to develop early warning indicators to determine the timing for activation of macroprudential instruments and to signal systemic risks.

Appendix 3.1. Empirical Methodology

Empirical Model and Data

  • Following Espinoza and Prasad (2012), four exogenous variables are considered in the model—oil prices, U.S. real GDP, a trade-weighted price index from partner countries, and the U.S. federal funds rate. Movements in oil prices, U.S. real GDP, and the trade weighted prices in partner countries are likely to influence economic activity and consumer prices in Saudi Arabia. Additionally, the U.S. federal funds rate is the de facto policy interest rate, owing to the lack of an independent interest rate policy. It is set in response to economic developments in the United States, but is exogenous to developments in Saudi Arabia.

  • Five macroeconomic variables for Saudi Arabia are considered to be endogenous and relevant for modeling monetary policy transmission: government expenditure (G), non-oil real GDP (Y), private sector credit (Credit), consumer prices, and reserve money (RM) (Table A3.1). RM is considered to be a policy variable, as SAMA controls this through its liquidity management operations. Quarterly data from 1993:Q1 to 2013:Q4 are used. Annual series for G and Y are interpolated using a quadratic trend.

  • All endogenous and exogenous variables except the federal funds rate are expressed in logarithm and found to be stationary in first differences (I(1)) according to the Augmented Dickey-Fuller unit root tests.

  • Correlations between innovations in the endogenous variables are reported below. Correlation between G and Y, and Y and Credit are statistically significant. There is limited evidence of collinearity between the variables.

  • The Johansen cointegration test reveals the presence of one cointegrating vector among the endogenous variables. Therefore, to model the long-run relationship between the endogenous variables, we estimate a vector error correction model.

  • The Cholesky ordering of the endogenous variables (to calculate the impulse responses) is akin to that of Espinoza and Prasad (2012) and Cevik and Teksoz (2012). Government expenditure (G) is ordered first under the assumption that it does not contemporaneously respond to developments in the other variables owing to lags in implementation. Y is ordered second, followed by Credit, CPI, and RM.

  • Lag exclusion tests are used to determine the appropriate lags for inclusion in the vector error correction model. As a result, we include lags 1, 4, 5, and 8 for endogenous variables, while lags 1 through 4 are included for the exogenous variables. The model is stable.

Table A3.1.Correlation Matrix of Innovations
GYCreditCPIRM
G10.38−0.05−0.060.08
Y0.3810.270.200.08
Credit−0.050.271−0.130.17
CPI−0.060.20−0.131−0.01
RM0.080.080.17−0.011
Sources: Saudi Arabia Monetary Authority; and IMF staff calculations.
Sources: Saudi Arabia Monetary Authority; and IMF staff calculations.

The Cointegrating Vector and the Error-Correction Term

  • The cointegrating equation (with t-statistics in parentheses) is estimated as:

  • The cointegrating equation suggests that an increase in G or Y is associated with an increase in credit and reserve money over the long term. Similarly, an increase in Credit or RM may be associated with an increase in G, Y, and the CPI.

  • The second step of the vector-error correction model includes the error correction term and the first-differenced lags of the endogenous and exogenous variables. Estimated coefficients for the error-correction term imply that deviations from long-run equilibrium are corrected primarily through adjustments in Y and CPI.

Robustness Checks

  • We estimate an additional specification of the model, replacing the trade-weighted price index for partner countries with the U.S. consumer price index and the nonfuel commodity price index. These specifications of the model result in two cointegrating vectors. Impulse response functions derived from these models are directionally consistent with those derived above.

References

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    EspinozaRaphael and AnanthakrishnanPrasad. 2012. “Monetary Policy Transmission in the GCC Countries.IMF Working Paper 12/132.” IMF Working Paper 12/191International Monetary FundWashington, DC.

    International Monetary Fund (IMF). 2013a. “Key Aspects of Macroprudential Policy,SM13/145 (Washington)

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