## wp1731

## Source details

**Canonical URL:** [wp1731](https://www.imf.org/-/media/files/publications/wp/wp1731.pdf)

## Other formats

- [Markdown version](/-/media/files/publications/wp/wp1731.pdf.md)
- [Structured JSON version](/-/media/files/publications/wp/wp1731.pdf.json)

---

### I. Introduction — context and motivation
- Oil prices have fallen since mid-2014, reducing inflows of oil receipts, prompting fiscal spending cuts, and weakening economic activity.
- Funding conditions tightened: the 3-month Interbank Offered Rate (SIBOR) rose to the highest level in many years.
- Deposit growth fell and remained mostly in negative territory on a year-on-year basis during 2016; credit to the private sector remained robust, particularly to the construction sector.
- Banks reduced holdings of excess reserves at the Saudi Arabian Monetary Agency (SAMA) and SAMA bills to fund private sector credit and purchases of government bonds re-started in 2015.
- SAMA measures to ease funding:
  - Placed more than SAR 20 billion ($5.3 billion) of government entity deposits with domestic commercial banks in September.
  - Introduced 7, 28, and 90-day repos (previously only overnight repos).
  - Relaxed the loan-to-deposit ratio, allowing it to exceed the 85 percent limit.
- Other easing factor:
  - Issuance of $17.5 billion international bonds by the government in October (largest by an emerging market and heavily oversubscribed).
- Outcomes:
  - 3-month SIBOR declined to the lowest level in six months in mid-December; the 3-month SIBOR ended 2016 at 2.035 percent.
  - Deposit growth rebounded to marginally above zero percent and bank holdings of excess liquidity rose in November.

### II. Methodology and data
- Empirical specification:
  - Baseline panel fixed-effects model: rcg_{i,t} = Σ_{j} α_{1,j} Bank_{j,i,t−1} + Σ_{k} α_{2,k} Macro_{k,t} + Σ_{l} α_{3,l} time_{l} + θ_{i} + ε_{i,t}
  - rcg_{i,t}: real growth of bank credit to the private sector.
  - Bank_{j,i,t−1}: bank-level variables lagged one period.
  - Macro_{k,t}: contemporaneous macro-level variables (assumed exogenous to individual banks).
  - Time dummies for 2008 and 2009 capture effects of defaults of two large family-owned domestic conglomerates.
  - θ_{i}: bank fixed effects; ε_{i,t}: random errors.
- Estimation choice:
  - Panel fixed-effects model used.
  - Lagged dependent variable excluded because its coefficient was generally statistically insignificant; GMM approaches not used.
- Data coverage and treatment:
  - Annual data spanning 2000–15.
  - Sample: 10 of 12 domestic Saudi banks (representing 93.6 percent of total banking system assets in 2015).
  - All variables expressed in real terms except ratios.
  - Key bank-level explanatory variables (lagged): Capital ratio; Growth of NPL provisions; Deposit growth; Net income growth.
  - Macro-level contemporaneous variables: Oil price growth; US Fed funds rate (detrended); Nonoil private sector GDP growth; Domestic 3-month money market interest rate (3-month SIBOR), detrended; Bank holdings of excess liquidity (ppt change of bank assets).
- Notes on rates and treatment:
  - US Fed funds rate and 3-month SIBOR are detrended using a linear time trend.
  - Given the Saudi riyal’s peg to the US dollar, the US Fed funds rate and domestic 3-month SIBOR are not included together in regressions.
  - Some deposit base in Saudi Arabia is interest free.

### III. Data diagnostics and summary statistics (2000–15)
- Key bank-level summary statistics (Obs, Mean, Std. Dev., Min, Max):
  - Credit growth: 244, 10.4, 12.2, -10.8, 35.3
  - Capital ratio: 163, 16.2, 3.2, 11.8, 23.6
  - NPL provision growth: 225, 3.7, 17.3, -26.6, 43.3
  - Deposit growth: 245, 8.2, 8.8, -5.7, 27.8
  - Net income growth: 237, 7.3, 10.2, -10.4, 28.3
- Key macro-level summary statistics (Obs, Mean, Std. Dev., Min, Max):
  - Oil price growth: 297, 7.5, 42.2, -61.8, 130.3
  - Nonoil private sector GDP growth: 295, 5.2, 4.2, -0.4, 19.6
  - US Fed funds rate, detrended: 290, 0.0, 1.4, -2.3, 2.3
  - Saudi 3M interest rate, detrended: 230, 0.0, 2.4, -4.4, 4.6
  - Excess liquidity, ppt chg.: 220, 0.9, 2.9, -7.7, 7.6
- Descriptive patterns:
  - Real growth of bank credit rose in early-2000 but declined to negative territory in the late-2000s primarily due to domestic conglomerate defaults.
  - Tier 1 ratio remained around 15 percent.
  - NPLs well provisioned: about 1.6 times in Q4 2015.
  - Deposit growth broadly in line with credit growth; balance sheet size grew with deposits.
  - Net income growth moderated under low oil prices and tighter funding.
  - Oil price growth experienced its worst performance in at least three decades, dampening non-oil private sector GDP growth (fell to the lowest since early 2000s).
  - Domestic 3-month money market rate surged as Fed began policy normalization and domestic liquidity tightened.
  - Bank holdings of excess liquidity (ppt change of assets) declined notably.
- Correlations (significant at the 5 percent level):
  - Credit growth positively correlated with deposit growth, net income growth, and nonoil private sector GDP growth.
  - Deposit growth positively correlated with economic activity, bank profitability, and excess liquidity.
  - Domestic money market rates rise with the US Fed funds rate and as liquidity conditions tighten (lower excess liquidity and lower oil prices).

### IV. Results — determinants of bank credit (bivariate and multivariate)
- Estimation approach:
  - Bivariate panel fixed-effects regressions estimated on each independent variable (bank-level lagged; macro contemporary). All models control for 2008 and 2009 time effects.
  - Multivariate panel fixed-effects models combine variables; bank-level lagged variables used.
- Key empirical magnitudes (summarized):
  - Capital ratio:
    - An increase in Tier 1 capital by 1 percentage point of risk-weighted assets leads to 0.5–1.0 percent increase in credit growth.
  - Deposit growth:
    - Around 0.2–0.4 of a rise in deposit growth in real terms is transmitted to credit growth.
  - NPL provisions:
    - Every one percent growth in NPL provisions in real terms reduces credit growth by 0.1–0.2 percent.
  - Oil prices and non-oil activity:
    - A ten percent increase in oil price growth leads to 0.9–1.4 percent increase in credit growth.
    - A one percent rise in non-oil private sector economic growth leads to 0.5–0.8 percent increase in credit growth.
  - Excess liquidity:
    - Lower bank holdings of excess liquidity support credit extension; in some specifications, a one percentage point reduction in the variable accelerates credit growth by 0.4 percent.
  - Interest rates and net income:
    - Interest rates (domestic and foreign), net income growth, and bank holdings of excess liquidity do not systematically affect lending growth in many specifications.
- Model interpretation and performance:
  - Sharp decline in credit growth around the global financial crisis attributed to lower capital ratios, weaker deposit growth, lower oil-price growth, and lower non-oil private sector GDP; time dummies for 2008–09 required to capture additional effects (e.g., defaults of two large domestic conglomerates).
  - Model predictions (using Model 16) show credit growth held up in 2015 despite a large fall in oil prices, supported by resilient bank balance-sheet conditions and a reduction in bank holdings of excess liquidity.
  - Looking ahead, credit growth could slow further if deposit growth weakens, the capital ratio declines, provisioning for NPLs accelerates, and economic activity slows.

### V. Country-specific extensions and findings
- Bank holdings of government bonds:
  - Historical context: government bond issuance active during 1997–2007, averaging 17–18 bonds per year; outstanding amount peaked at close to SAR 700 billion in the early 2000s.
  - Domestic banks historically held 10–20 percent of total outstanding; bank holdings of government bonds as a share of total bank assets peaked at close to 30 percent.
  - Econometric result: A one percentage point of bank balance-sheet increase in holdings of government bonds reduces credit growth by 1–1.5 percent (coefficient loses statistical significance when combined with non-oil private sector GDP growth).
- Specialized Credit Institutions (SCIs):
  - SCI lending accelerated during the 2000s and remained relatively high; the stock of SCI lending represents some ¼ of that of banks.
  - Regressions: SCI lending does not appear to systematically complement commercial bank lending; coefficients mostly not statistically significant; one specification shows a negative coefficient suggesting competition in overlapping market segments.
- Banking system concentration:
  - Saudi Arabia’s banking system is the least concentrated among GCC countries; concentration has been declining.
  - Empirical result: Higher banking system concentration leads to lower bank lending growth (coefficient becomes insignificant when included with bank holdings of excess liquidity — possible link: higher concentration -> more excess liquidity accumulation).
- State ownership:
  - Definitions:
    - “Wide” state ownership: Saudi government, Public Investment Fund (PIF), and two domestic pension funds (GOSI and PPA); high when 50 percent or above.
    - “Narrow” state ownership: Saudi government and PIF; high when 30 percent or above.
  - Tentative findings:
    - State ownership does not systematically affect overall bank lending growth.
    - At the 10 percent significance level, evidence suggests banks with high state ownership lend more pro-cyclically with respect to oil price performance.
    - For banks with high state ownership, credit growth is less affected by the capital ratio (interaction term broadly cancels the capital-ratio coefficient); in 2015, banks with high state ownership had a higher average capital ratio compared to other banks by 1–1.5 percentage points.
    - Interpretation: When oil prices are low and fiscal balance is strained, high-state-ownership banks may purchase government bonds and reduce lending more than other banks.

### VI. Policy-relevant implications and recommendations
- Main conclusions:
  - Bank lending in Saudi Arabia is influenced importantly by both bank balance-sheet conditions (supply) and macroeconomic developments (demand).
  - A rise in the capital ratio, stronger deposit growth, and a reduction in bank holdings of excess liquidity all lead to higher credit growth.
  - Greater NPL provisioning reduces credit growth.
  - Bank lending growth rises with stronger oil prices and domestic economic activity.
  - Interest rates (domestic or foreign) do not systematically affect bank lending.
- Policy recommendations to support bank credit provision:
  - Bank balance sheets need to remain strong, particularly as the National Transformation Program and Vision 2030 expand private-sector opportunities.
  - Banks need to maintain sufficient capital even as low oil prices put balance sheets under pressure.
  - Adequate provisioning for NPLs is essential for financial stability despite its dampening effect on credit extension.
  - Strengthening public confidence in the banking system helps attract deposits and support credit supply.
  - Reducing reliance on the banking system to finance the budget deficit would support credit provision to the private sector.

### VII. Appendix — selected variable definitions (Table A1, units)
- Credit growth — Year on year growth of gross loans deflated by Saudi CPI index. Unit: Percent. (bank-level)
- Capital ratio, Tier1 — Tier 1 capital to risk weighted assets. Unit: Percent. (bank-level)
- NPL provisions growth — Year on year growth of NPL provisions deflated by Saudi CPI index. Unit: Percent. (bank-level)
- Deposit growth — Year on year growth of total customer deposits deflated by Saudi CPI index. Unit: Percent. (bank-level)
- Net income growth — Year on year growth of net interest income deflated by Saudi CPI index. Unit: Percent. (bank-level)
- Nonoil private sector GDP growth — Year on year growth of non oil private sector real GDP. Unit: Percent. (macro-level)
- Oil price growth — Year on year growth of Brent oil prices deflated by US CPI index. Unit: Percent. (macro-level)
- US Fed funds rate — US Fed funds interest rate effective minus US CPI inflation detrended by linear trend. Unit: Percent. (macro-level)
- Domestic 3 month interest rate — Saudi 3 month SIBOR minus Saudi CPI inflation detrended by linear trend. Unit: Percent. (macro-level)
- Excess liquidity — Sum of bank holdings of (i) current and other deposits at SAMA and (ii) SAMA bills. Year on year differences divided by bank assets in the base year. Unit: Percent. (bank-level)
- Bank holdings of government bonds, change — Year on year difference in bank holdings of government bonds scaled by bank total assets. Unit: Percent. (bank-level)
- SCI lending growth — Year on year growth of lending by Specialized Credit Institutions deflated by Saudi CPI index. Unit: Percent. (macro-level)
- Bank concentration index, change — Assets of five largest banks as a share of total commercial banking assets, year on year percentage point change. Unit: Percent. (macro-level)

*Content based on the source document provided.*

### References _______________________________________________________________________________________ 25

### wp1731 - References _______________________________________________________________________________________ 25

### I. INTRODUCTION — context and motivation
- Oil prices have fallen since mid-2014, reducing inflows of oil receipts, prompting fiscal spending cuts, and weakening economic activity.
- Funding conditions tightened: the 3-month Interbank Offered Rate (SIBOR) rose to the highest level in many years (Figure 1, upper right panel).
- Deposit growth fell and remained mostly in negative territory on a year-on-year basis during 2016; credit to the private sector remained robust, particularly to the construction sector.
- Banks reduced holdings of excess reserves at the Saudi Arabian Monetary Agency (SAMA) and SAMA bills to fund private sector credit and purchases of government bonds re-started in 2015.
- SAMA measures to ease funding:
  - Placed more than SAR 20 billion ($5.3 billion) of government entity deposits with domestic commercial banks in September.
  - Introduced 7, 28, and 90-day repos (previously only overnight repos).
  - Relaxed the loan-to-deposit ratio, allowing it to exceed the 85 percent limit.
- Other easing factors:
  - Issuance of $17.5 billion international bonds by the government in October (largest by an emerging market and heavily oversubscribed).
- Outcomes by mid-December and November:
  - 3-month SIBOR declined to the lowest level in six months in mid-December; the 3-month SIBOR ended 2016 at 2.035 percent.
  - Deposit growth rebounded to marginally above zero percent and bank holdings of excess liquidity rose in November.

### Financial development, oil exporters, and bank credit
- Bank credit is a key channel from oil prices to the real economy in Saudi Arabia.
- Cross-country evidence: Saudi credit deepening (bank credit to the nonfinancial private sector relative to GDP) broadly consistent with GDP per capita stage (2010–15) but cross-country panels may miss country-specific features.
- Literature findings:
  - Financial development generally spurs growth (Levine (1997, 2005); Demirguc-Kunt and Levine (2008)).
  - Sahay et al (2015): benefits of financial development are bell-shaped and weaken at higher levels of financial development.
  - Studies suggest weaker effects of financial development on growth in oil exporters (Naceur and Ghazouani (2007); Barajas et al (2013); Hakura (2004)).
  - Single-country estimations can complement cross-country results; Miyajima (2016) finds higher bank lending strengthens real GDP growth in Saudi Arabia.

### Determinants of bank credit — literature overview
- Bank-specific characteristics affecting credit: size, liquidity, capitalization, lenders’ default probabilities (Altunbas et al, 2010; Gambacorta and Marques-Ibanez, 2011; Gambacorta and Shin, 2016).
- Global factors gained importance for emerging markets as capital flows grew more volatile (Kohlscheen and Miyajima (2015)).
- Determinants emphasized in emerging markets and GCC analyses: balance sheet conditions, banking regulation, domestic activity, domestic and external monetary conditions, foreign funding, bank capitalization, concentration, financial deepening, institutional quality (Chen and Wu (2014); Guo and Stepanyan (2011); Amidu (2014); Barajas et al (2010); Ghosh (2013); Ganil and AlMuharramil (2016)).

### Study objective and scope
- Paper analyzes determinants of bank credit in Saudi Arabia using bank-level balance sheet and macro-level data for 2000–15.
- Focused sample: 10 of 12 domestic Saudi banks (representing 93.6 percent of total banking system assets in 2015).
- Does not distinguish Islamic vs conventional finance due to lack of breakdown by Shariah-compliant and conventional exposures; Bankscope-based separation did not yield meaningful results for the Saudi sample.

### Organization
- Section II: methodology and data.
- Section III: results.
- Section IV: extensions addressing Saudi-specific questions.
- Section V: conclusion.

### II. METHODOLOGY AND DATA — empirical approach
- Baseline panel specification for bank i in year t:
  - rcg_{i,t} = Σ_{j} α_{1,j} Bank_{j,i,t−1} + Σ_{k} α_{2,k} Macro_{k,t} + Σ_{l} α_{3,l} time_{l} + θ_{i} + ε_{i,t}
  - rcg_{i,t} is real growth of bank credit to the private sector.
  - Bank_{j,i,t−1} are bank-level variables lagged one period.
  - Macro_{k,t} are contemporaneous macro-level variables (assumed exogenous to individual banks).
  - time dummies for 2008 and 2009 capture effects of defaults of two large family-owned domestic conglomerates.
  - θ_{i} are bank fixed effects; ε_{i,t} are random errors.
- Estimation choice:
  - Panel fixed-effects model is used.
  - Lagged dependent variable was not included because its coefficient was generally statistically insignificant; GMM approaches were not used.

### Data: coverage, variables, and treatment
- Frequency and sample: annual data spanning 2000–15.
- Bank-level data source: Bankscope; analysis includes 10 domestic banks representing 93.6 percent of system assets (2015).
- All variables expressed in real terms except ratios.
- Key bank-level explanatory variables (lagged):
  - Capital ratio
  - Growth of NPL provisions
  - Deposit growth
  - Net income growth
- Rationale: growth of NPL provisions is preferred over NPL ratios because Saudi banks provisioned counter-cyclically; NPL provisions better capture capacity to extend credit.
- Macro-level variables (contemporaneous):
  - Oil price growth (important external shock)
  - US Fed funds rate (controls global monetary conditions; not included together with 3-month SIBOR in regressions due to peg)
  - Nonoil private sector GDP growth
  - Domestic 3-month money market interest rate (3-month SIBOR), detrended
  - Bank holdings of excess liquidity (sum of excess reserves at central bank and central bank bills), measured in percentage point change of bank assets
- Notes on rates:
  - US Fed funds rate and 3-month SIBOR are detrended using linear time trend.
  - Given the Saudi riyal’s peg to the US dollar, the US Fed funds rate and domestic 3-month SIBOR are not included together in regressions.
  - Some deposit base in Saudi Arabia is interest free.

### Data visual summary and diagnostics
- Figure 2 summarizes macro and bank-level variable behavior for 2000–15:
  - Real growth of bank credit rose in early-2000 but declined to negative territory in the late-2000s due primarily to domestic conglomerate defaults.
  - Tier 1 ratio remained around 15 percent.
  - NPLs well provisioned: about 1.6 times in Q4 2015.
  - Deposit growth broadly in line with credit growth; balance sheet size grew with deposits.
  - Net income growth moderated under low oil prices and tighter funding.
  - Oil price growth experienced worst performance in at least three decades, dampening non-oil private sector GDP growth (fell to the lowest since early 2000s).
  - Domestic 3-month money market rate surged as Fed began policy normalization and domestic liquidity tightened.
  - Bank holdings of excess liquidity (ppt change of assets) declined notably.

### Data summary statistics (2000–15)
- Bank level data (Obs, Mean, Std. Dev., Min, Max):
  - Credit growth: 244, 10.4, 12.2, -10.8, 35.3
  - Capital ratio: 163, 16.2, 3.2, 11.8, 23.6
  - NPL provision growth: 225, 3.7, 17.3, -26.6, 43.3
  - Deposit growth: 245, 8.2, 8.8, -5.7, 27.8
  - Net income growth: 237, 7.3, 10.2, -10.4, 28.3
- Macro level data (Obs, Mean, Std. Dev., Min, Max):
  - Oil price growth: 297, 7.5, 42.2, -61.8, 130.3
  - Nonoil private sector GDP growth: 295, 5.2, 4.2, -0.4, 19.6
  - US Fed funds rate, detrended: 290, 0.0, 1.4, -2.3, 2.3
  - Saudi 3M interest rate, detrended: 230, 0.0, 2.4, -4.4, 4.6
  - Excess liquidity, ppt chg.: 220, 0.9, 2.9, -7.7, 7.6

### Correlations and preliminary relationships
- Correlation analysis (Table 3) — significant at the 5 percent level:
  - Credit growth positively correlated with deposit growth, net income growth (profitability), and nonoil private sector GDP growth.
  - Deposit growth positively correlated with economic activity, bank profitability, and excess liquidity.
  - Domestic money market rates rise with the US Fed funds rate and as liquidity conditions tighten (lower excess liquidity and lower oil prices).

_Italic: Content based on the source document provided._

### Appendix Table 1 for data description.

### Appendix Table 1 for data description.

### III. RESULTS — Bivariate and Multivariate Findings
- Methodology
  - Bivariate panel fixed-effects regressions of bank credit growth estimated on each independent variable; bank-level data lagged by one period; macro-level data introduced contemporaneously. All models control for time effects for 2008 and 2009.
  - Multivariate panel fixed-effects models combine variables; bank-level lagged variables used.

- Key bank-balance-sheet and macro results (summary of empirical magnitudes reported)
  - Capital ratio:
    - An increase in Tier 1 capital by 1 percentage point of risk-weighted assets leads to 0.5–1.0 percent increase in credit growth.
  - Deposit growth:
    - Around 0.2–0.4 of a rise in deposit growth in real terms is transmitted to credit growth.
  - NPL provisions:
    - Every one percent growth in NPL provisions in real terms reduces credit growth by 0.1–0.2 percent.
  - Oil prices and non-oil activity:
    - A ten percent increase in oil price growth leads to 0.9–1.4 percent increase in credit growth.
    - A one percent rise in non-oil private sector economic growth leads to 0.5–0.8 percent increase in credit growth.
  - Excess liquidity:
    - Lower bank holdings of excess liquidity support credit extension; in some specifications, a one percentage point reduction in the variable accelerates credit growth by 0.4 percent.
  - Interest rates and net income:
    - Interest rates (domestic and foreign), net income growth, and bank holdings of excess liquidity do not systematically affect lending growth in many specifications.

- Model performance and interpretation
  - Sharp decline in credit growth around the global financial crisis attributed to lower capital ratios, weaker deposit growth, lower oil-price growth, and lower non-oil private sector GDP; time dummies for 2008–09 required to capture additional effects (e.g., defaults of two large domestic conglomerates).
  - Model predictions (using Model 16) show credit growth held up in 2015 despite a large fall in oil prices, supported by resilient bank balance-sheet conditions and a reduction in bank holdings of excess liquidity.
  - Looking ahead, credit growth could slow further if deposit growth weakens, the capital ratio declines, provisioning for NPLs accelerates, and economic activity slows.

### IV. CONSIDERING ADDITIONAL FACTORS (country-specific)
- Bank holdings of government bonds
  - Historical context: Saudi government bond issuance active during 1997–2007, averaging 17–18 bonds per year; outstanding amount peaked at close to SAR 700 billion in the early 2000s.
  - Domestic banks historically held 10–20 percent of total outstanding; bank holdings of government bonds as a share of total bank assets peaked at close to 30 percent.
  - Econometric result: A one percentage point of bank balance-sheet increase in holdings of government bonds reduces credit growth by 1–1.5 percent (coefficient loses statistical significance when combined with non-oil private sector GDP growth).

- Specialized Credit Institutions (SCIs)
  - SCI lending accelerated during the 2000s and remained relatively high; the stock of SCI lending represents some ¼ of that of banks.
  - Regressions: SCI lending does not appear to systematically complement commercial bank lending; coefficients mostly not statistically significant; one specification shows a negative coefficient suggesting competition in overlapping market segments.

- Banking system concentration
  - Saudi Arabia’s banking system is the least concentrated among GCC countries; concentration has been declining.
  - Empirical result: Higher banking system concentration leads to lower bank lending growth (coefficient becomes insignificant when included with bank holdings of excess liquidity — possible link: higher concentration -> more excess liquidity accumulation).

- State ownership
  - Definitions and thresholds:
    - “Wide” state ownership: accounts for Saudi government, Public Investment Fund (PIF), and two domestic pension funds (GOSI and PPA); high when 50 percent or above.
    - “Narrow” state ownership: accounts only for Saudi government and PIF; high when 30 percent or above.
  - Tentative findings:
    - State ownership does not systematically affect overall bank lending growth.
    - At the 10 percent significance level, evidence suggests banks with high state ownership lend more pro-cyclically with respect to oil price performance (as oil prices increase, lending by high-state-ownership banks tends to rise more).
    - For banks with high state ownership, credit growth is less affected by the capital ratio (interaction term broadly cancels the capital-ratio coefficient); in 2015, banks with high state ownership had a higher average capital ratio compared to other banks by 1–1.5 percentage points.
    - Interpretation: When oil prices are low and fiscal balance is strained, high-state-ownership banks may purchase government bonds and reduce lending more than other banks.

### V. CONCLUDING DISCUSSION — Policy-relevant implications
- Main conclusions
  - Bank lending in Saudi Arabia is influenced importantly by both bank balance-sheet conditions (supply) and macroeconomic developments (demand).
  - A rise in the capital ratio, stronger deposit growth, and a reduction in bank holdings of excess liquidity all lead to higher credit growth.
  - Greater NPL provisioning reduces credit growth.
  - Bank lending growth rises with stronger oil prices and domestic economic activity.
  - Interest rates (domestic or foreign) do not systematically affect bank lending.

- Policy recommendations and implications
  - To support bank credit provision:
    - Bank balance sheets need to remain strong, particularly as the National Transformation Program and Vision 2030 expand private-sector opportunities.
    - Banks need to maintain sufficient capital even as low oil prices put balance sheets under pressure.
    - Adequate provisioning for NPLs is essential for financial stability despite its dampening effect on credit extension.
    - Strengthening public confidence in the banking system helps attract deposits and support credit supply.
    - Reducing reliance on the banking system to finance the budget deficit would support credit provision to the private sector.

### VI. APPENDIX: Data description (selected variables and units from Table A1)
- Credit growth — Year on year growth of gross loans deflated by Saudi CPI index. Unit: Percent. (bank-level)
- Capital ratio, Tier1 — Tier 1 capital to risk weighted assets. Unit: Percent. (bank-level)
- NPL provisions growth — Year on year growth of NPL provisions deflated by Saudi CPI index. Unit: Percent. (bank-level)
- Deposit growth — Year on year growth of total customer deposits deflated by Saudi CPI index. Unit: Percent. (bank-level)
- Net income growth — Year on year growth of net interest income deflated by Saudi CPI index. Unit: Percent. (bank-level)
- Nonoil private sector GDP growth — Year on year growth of non oil private sector real GDP. Unit: Percent. (macro-level)
- Oil price growth — Year on year growth of Brent oil prices deflated by US CPI index. Unit: Percent. (macro-level)
- US Fed funds rate — US Fed funds interest rate effective minus US CPI inflation detrended by linear trend. Unit: Percent. (macro-level)
- Domestic 3 month interest rate — Saudi 3 month SIBOR minus Saudi CPI inflation detrended by linear trend. Unit: Percent. (macro-level)
- Excess liquidity — Sum of bank holdings of (i) current and other deposits at SAMA and (ii) SAMA bills. Year on year differences divided by bank assets in the base year. Unit: Percent. (bank-level)
- Bank holdings of government bonds, change — Year on year difference in bank holdings of government bonds scaled by bank total assets. Unit: Percent. (bank-level)
- SCI lending growth — Year on year growth of lending by Specialized Credit Institutions deflated by Saudi CPI index. Unit: Percent. (macro-level)
- Bank concentration index, change — Assets of five largest banks as a share of total commercial banking assets, year on year percentage point change. Unit: Percent. (macro-level)

*Source: IMF staff calculations and author’s calculation in the referenced Appendix Table 1 for data description.*

### REFERENCES

### wp1731 - REFERENCES

### Finance, growth, and financial development
- Barajas, A., R. Chami, and S. R. Yousefi (2013). “The Finance and Growth Nexus Re-Examined: Do All Countries Benefit Equally?” IMF Working Paper 13/130.
- Demirguc-Kunt, A. and R. Levine (2008). “Finance, Financial Sector Policies, and Long-Run Growth,” Commission on Growth and Development Working Paper 11.
- Levine, R. (1997). “Financial development and economic growth: Views and agenda,” Journal of Economic Literature, 35, 688–726.
- Levine, R. (2005). “Finance and growth: Theory and evidence,” in P. Aghion and S. Durlaff (eds.), Handbook of Economic Growth. The Netherlands: Elsevier Science.
- Sahay, R. M. Cihak, P. N’Diaye, A. Barajas, D. Pena, R. Bi, Y. Gao, A. Kyobe, L. Nguyen, C. Saborowski, K. Svirydzenka, R. Yousefi (2015). “Rethinking Financial Deepening: Stability and Growth in Emerging Markets,” IMF Staff Discussion Note 15/08.
- Ben Naceur, S., and S. Ghazouani (2007). “Stock markets, banks, and economic growth: Empirical evidence from the MENA region,” Research in International Business and Finance, 21, 297–315.

### Bank lending, monetary policy, and bank risk
- Altunbasa Y., L. Gambacorta, D. Marques-Ibanez (2010). “Bank risk and monetary policy,” Journal of Financial Stability, 6, 121–29.
- Gambacorta L. and D. Marques-Ibanez (2011) “The bank lending channel: lessons from the crisis,” Economic Policy, April, 135–82.
- Gambacorta L. H. S. Shin (2016). “Why bank capital matters for monetary policy,” BIS Working Papers 558.
- Kohlscheen E. and K. Miyajima (2015). “The transmission of monetary policy in EMEs in a changing financial environment: a longitudinal analysis,” BIS Working Papers 495.
- Ghosh S. (2013). “Funding structure, procyclicality and lending: Evidence from GCC banks,” MPRA Paper 51225.
- Amidu, M. (2014). “What Influences Bank Lending in Sub-Saharan Africa?” Journal of Emerging Market Finance, 13 (1), pp 1–42.
- Gani A. and S. Al-Muharrami (2016). “The Effect of Institutional Quality on Bank Lending in the Gulf Cooperation Council Countries,” Review of Middle East Economics and Finance, 12, 1, 55–63.

### Regional studies: MENA, GCC, Saudi Arabia, oil-linked analyses
- Alhumaidah F., R. Alkhareif, K. AlSaeed, N. B. Ltaifa, K. Miyajima, and G. Pedras (2016) “Financing the fiscal deficits–possible options and their potential implications.” IMF Country Report No. 16/327.
- Al-sadig, A. (2013). “Government Specialized Credit Institutions and Private Domestic Investment: The Case of Saudi Arabia,” Review of Middle East Economics and Finance, 9, 1, 51–64.
- Miyajima, K. (2016). “An Empirical Investigation of Oil-Macro-Financial Linkages in Saudi Arabia,” IMF Working Paper 16/22.
- Hakura, D. (2004). “Growth in the Middle East and North Africa,” IMF Working Paper 04/56.
- Husain, A. M., R. Arezki, P. Breuer, V. Haksar, T. Helbling, P. Medas, M. Sommer, and an IMF Staff Team (2015). “Global Implications of Lower Oil Prices,” IMF Staff Discussion Note 15/15.

### Econometric and methodological references
- Arellano, M., and O. Bover (1995). “Another look at the instrumental variable estimation of error-components models,” Journal of Econometrics, 68 (1), pp 29–51.
- Blundell, R. and S. Bond (1998). “Initial conditions and moment restrictions in dynamic panel data models,” Journal of Econometrics, 87, pp 115–43.

---


_Source: https://www.imf.org/-/media/files/publications/wp/wp1731.pdf_