## wpiea2019129

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### I. Introduction — context and motivation
- The 2014−16 collapse in oil prices was one of the three largest declines since World War II and the longest lasting since the 1986 slump.
- Sub-Saharan African oil exporting countries in the sample: Angola, Cameroon, Chad, Congo Republic, Equatorial Guinea, Gabon, Nigeria, and South Sudan (South Sudan excluded from some analyses for data issues).
- Negative GDP growth in 2016 for these oil exporters: -2.2 percent.
- Observed macro→finance transmission emphasized:
  - Oil price downturns → lower oil revenues → weaker fiscal and external positions → reduced government spending → negative effects on asset prices, credit volumes, banking sector liquidity, and bank balance sheets.
  - Financial sector deterioration can feed back to the real economy via reduced credit and investment and weaker government spending.
- Novel contribution:
  - Focus on role of bank ownership (foreign-owned, Pan-African Banks (PABs), domestic) and bank characteristics (size, asset quality, liquidity, business model) in transmission of oil price downturns to bank-level outcomes.
  - First paper to study relative behavior of PABs in response to an oil price shock (authors’ claim).

### II. Stylized facts — observed bank-level outcomes during the oil down cycle
- Timing and cycles:
  - Up cycle: 2009-2012.
  - Down cycle: 2013-2016 (exceptions: Chad uses 2013-2014 for some indicators; sample ends in 2016).
- Aggregate banking system changes (2013-2016 relative to 2009-2012):
  - Credit growth fell in all countries, particularly in Angola, Cameroon and Chad.
  - Asset quality deteriorated (higher NPL ratios).
  - Liquidity positions deteriorated (deposits growth and loans-to-customer deposits fell; loans-to-deposits fell to a lesser extent in Angola).
  - Profitability (return on average equity) and capital adequacy (leverage ratio, equity-to-assets) fell.
- Differential effects by bank type:
  - Foreign-owned banks:
    - More conservative as oil prices fell: reduced credit and improved asset quality and liquidity positions.
    - Resilient: increased profitability, asset and deposit growth, and decreased NPL ratios.
  - Pan-African Banks (PABs):
    - Helped stabilize overall credit following the oil shock.
    - Heterogeneous by size: small PABs improved asset quality; largest PABs experienced deterioration in asset quality after a negative oil shock.
    - Asset growth declined, but financial soundness indicators did not fall significantly in aggregate.
  - Domestic banks:
    - Bore the brunt of oil price declines: asset quality and deposits declined.
  - Banks with high asset quality (low NPL ratios):
    - Most resilient: increases in total assets, total deposits, credit growth, liquidity, and capital buffers; minimal change in NPL ratio (authors caution due to correlation between NPL dummy and NPL ratio).
  - Banks with low asset quality (high NPLs):
    - Experienced deterioration in asset quality and falls in deposit growth.
- Inferred resilience factors:
  - Strong pre-shock buffers (low NPL ratios).
  - Ability to diversify risk during shock (PABs and large banks).
  - Access to external liquidity from parent banks (foreign-owned banks).

### III. Methodology and data
- Main model: dynamic panel with lagged dependent variable to capture persistence and shocks.
- Bank-level dependent variables (y_it):
  - Logarithmic change in gross loans (credit growth).
  - Logit transformation of ratio of total impaired loans to gross loans (NPL ratio).
  - Logarithmic change in total deposits (deposit growth).
- Oil price shock measure:
  - Oil Price Growth_{c,t} = θ_c ∆log(Oil Price_t).
  - Oil Price_t = international price of Brent Crude oil in year t; θ_c = time-invariant average value of oil exports in total exports for country c.
  - Coefficients multiplied by −1 so that each coefficient is interpreted as a 1 percent decrease (after multiplying by −1) in the change in oil prices and its impact on the banking sector.
- Estimation equation:
  - y_it = α0 + α1 y_{i,t−1} + α2 (D_{i,t−1} * Oil Price Growth_{c,t−1}) + Σ_j α3j Macro_{j,t−1} + Σ_k α4k Bank_{i,k,t−1} + τ_t + ϑ_i + μ_it
    - D_{i,t−1} = dummy for bank characteristics at t−1 capturing size, NPL ratio, liquidity, leverage, profitability, ownership/business model (domestic, foreign-owned, PAB).
    - τ_t = year dummies; ϑ_i = bank fixed effects.
- Macro controls:
  - Oil Price Growth_{c,t}, log change non-oil GDP, exchange rate, inflation rate, ratio of private credit-to-GDP.
- Bank controls:
  - Lagged credit growth or deposit growth (as appropriate), other interest income, ratio of net loans-to-total assets, log total assets, holdings of government securities.
- Data sources and coverage:
  - Bank-level data from Fitch Connect.
  - Macro data from IMF World Economic Outlook, IMF Primary Commodity Prices, and IMF International Financial Statistics.
  - Country sample: Angola, Cameroon, Chad, Congo Republic, Equatorial Guinea, Gabon, Nigeria (South Sudan excluded in some analyses).
- Transformations and estimation notes:
  - Logit transform applied to NPL ratio to improve normality.
  - Robustness: system GMM (incorporates current and past information on credit, NPL, and deposit growth).

### IV. Main empirical findings (summary)
- Ownership and characteristics shape transmission of oil price shocks:
  - Foreign-owned banks:
    - Reduce credit and strengthen asset quality (improve NPLs) while increasing deposit growth during oil price declines — characterized as conservative and resilient.
  - Pan-African Banks (PABs):
    - Stabilize credit overall; small PABs improve asset quality, while large PABs experience asset quality deterioration.
    - Tend to increase lending and decrease government securities holdings during oil price declines; asset-quality implications are mixed.
  - Domestic banks:
    - Most adversely affected: higher NPLs, lower deposit growth, increased role in government financing as oil prices fall.
  - Large banks:
    - Increase lending following decreases in oil price growth but at the cost of increased NPLs.
  - Banks with low capital buffers (high leverage):
    - Decrease credit, increase funding, and increase holdings of government securities in response to falling oil prices.
  - Banks with high liquidity:
    - Increase deposits during oil price downturns.
- Mechanisms suggested:
  - Foreign banks obtain funding from parents and benefit from reputational effects.
  - Domestic/public banks may be used to place government securities as financing needs rise when oil prices fall.

### V. Key numerical results (selected coefficients and statistics; exact preservation)
- Determinants of Credit Growth (Tables 1A, 1B, Table 4 system GMM):
  - Table 1A Oil Price growth (t -1) coefficients: -0.519 (0.309); -0.962*** (0.194); -0.776*** (0.282); -0.571** (0.278); -0.949*** (0.244); -0.670** (0.305); -0.778** (0.296); -0.656** (0.310).
  - Selected interaction coefficients:
    - Large Bank * Oil price growth (t -1): -0.225** (0.0995).
    - Low Leverage * Oil price growth (t -1): 0.342** (0.132).
    - Foreign bank * Oil price growth (t -1): 0.280** (0.114).
  - Table 1B notable interactions:
    - Large PAB bank * Oil price growth (t -1): -0.243** (0.0992).
    - Small Foreign bank * Oil price growth (t -1): 1.306*** (0.157).
    - Private Domestic Bank * Oil price growth (t -1): -0.832*** (0.234).
  - Table 4 (system GMM) selected:
    - Credit Growth (t-1): coefficients range 0.176** to 0.224*** (e.g., 0.182** (0.072), 0.224*** (0.0801)).
    - Small Bank * Oil price growth (t-1): 0.430* (0.223).
    - Large Bank * Oil price growth (t-1): -0.256** (0.103).
    - Foreign * Oil price growth (t-1): 0.290* (0.146).
    - Observations: 210, 178, 210, 210, 207, 210, 210, 210.
    - Number of Banks: 55, 48, 55, 55, 54, 55, 55, 55.
    - F-stat range: 4.013 to 6.924; Prob > F = 0.000 in all columns.
    - Hansen statistics reported (e.g., 29.79, 27.56, 25.56, 35.55, 30.81, 32.83, 32.37, 32.50) with Hansen p-values (e.g., 0.0279, 0.0356, 0.00241, 0.00526, 0.0211, 0.0175, 0.0199, 0.0192).
- Determinants of NPL Growth (Tables 2A, 2B, Table 5 system GMM):
  - Table 2A Oil Price growth (t -1) coefficients: -3.088 (3.027); -4.486 (2.893); -5.130* (2.857); -2.671 (3.254); -4.526 (2.808); -4.195 (2.953); -5.718** (2.775); -4.864* (2.852).
  - Interaction examples:
    - Large Bank * Oil price growth (t -1): -1.471** (0.696).
    - Foreign bank * Oil price growth (t -1): 2.384* (1.250).
    - Small PAB bank * Oil price growth (t -1): 2.983* (1.633).
    - Large PAB bank * Oil price growth (t -1): -1.023* (0.560).
    - High NPL Foreign bank * Oil price growth (t -1): 5.162* (2.711).
    - Low NPL Domestic bank * Oil price growth (t -1): -1.042* (0.607).
  - Table 5 (system GMM) selected:
    - NPL Growth (t-1): coefficients range from -0.185 to -0.254* (e.g., -0.225 (0.137), -0.224* (0.126)).
    - Small Bank * Oil price growth (t-1): -3.589*** (1.112).
    - Large Bank * Oil price growth (t-1): -1.741*** (0.522).
    - PAB * Oil price growth (t-1): -1.383*** (0.438).
    - Foreign * Oil price growth (t-1): 2.251** (0.882).
    - Observations: 151 in all columns; Number of Banks: 46.
    - Hansen statistics examples: 30.86 (p-value 0.0761), 30.37 (p-value 0.0848), 11.76 (p-value 0.465).
- Determinants of Deposit Growth (Tables 3A, 3B, Table 6 system GMM):
  - Table 3A Oil Price growth (t -1) coefficients: 0.385 (0.322); 0.326 (0.339); 0.698** (0.299); 0.472 (0.304); 0.559* (0.311); 0.501* (0.298); 0.559* (0.285); 0.471 (0.287).
  - Interaction examples:
    - High Liquidity * Oil price growth (t -1): -0.389*** (0.109).
    - Low Leverage * Oil price growth (t -1): -0.341* (0.194).
    - Foreign bank * Oil price growth (t -1): -0.263** (0.120).
    - Small Foreign bank * Oil price growth (t-1): -0.447** (0.211).
    - Large Domestic bank * Oil price growth (t-1): 0.162*** (0.0586).
    - Low NPL Foreign bank * Oil price growth (t-1): -0.543** (0.266).
    - High NPL Foreign bank * Oil price growth (t-1): -1.482*** (0.279).
  - Table 6 (system GMM) selected:
    - Deposit Growth (t-1): e.g., 0.212*** (0.0622), 0.166*** (0.0478), 0.210*** (0.0642).
    - High Liquidity * Oil price growth (t-1): -0.328** (0.160).
    - Foreign * Oil price growth (t-1): -0.316* (0.180).
    - Observations: 210, 178, 210, 210, 207, 210, 210, 210; Number of Banks: 55, 48, 55, 55, 54, 55, 55, 55.
- Determinants of Government Securities (Table 7) selected:
  - Oil Price growth (t-1) coefficients across columns: -1.156 (2.624); -1.914 (2.631); -0.310 (2.812); -1.200 (2.619); -2.938 (2.761); -0.751 (2.532); -2.088 (2.720); -1.124 (2.657); -1.152 (2.653).
  - Deposit growth coefficient (highly significant across columns): 1.483*** (0.333); 1.618*** (0.343); 1.530*** (0.392); 1.452*** (0.315); 1.484*** (0.383); 1.507*** (0.342); 1.544*** (0.336); 1.513*** (0.345); 1.659*** (0.356).
  - Low Leverage * Oil price growth (t-1): -6.358*** (1.799).
  - PAB * Oil price growth (t-1): 0.858** (0.338).
  - Domestic bank * Oil price growth (t-1): -1.121** (0.507).
  - Observations typically 156; Number of Banks typically 42; R-squared range 0.262 to 0.368.
- Notes applicable to tables:
  - Standard errors in parentheses. Robust standard errors used.
  - Significance: * p < 0:10, ** p < 0:05, *** p < 0:01.
  - System GMM tables report AR(p) (Arellano-Bond) and Hansen J statistics for instrument validity.

### VI. Appendix highlights — variables, sample sizes, summary statistics, and bank list
- Appendix 3 summary statistics (selected exact values):
  - Oil Price Growth: N = 353; mean = -0.0544; s.d. = 0.252; min = -0.604; max = 0.315.
  - Credit Growth: N = 294; mean = 0.189; s.d. = 0.335; min = -2.155; max = 2.960.
  - Deposit Growth: N = 289; mean = 0.204; s.d. = 0.475; min = -0.638; max = 4.996.
  - Log Total Assets: N = 353; mean = 12.78; s.d. = 1.538; min = 2.432; max = 15.37.
  - logit of NPL ratio: N = 261; mean = -3.080; s.d. = 1.225; min = -8.517; max = -0.063.
  - NPL growth: N = 206; mean = 0.294; s.d. = 0.841; min = -1.39; max = 4.48.
  - Net Loans / Total Assets: N = 350; mean = 0.415; s.d. = 0.154; min = 0.0168; max = 0.784.
  - PAB dummy: N = 353; mean = 0.439; s.d. = 0.497; min = 0; max = 1.
  - Foreign-owned Bank dummy: N = 353; mean = 0.176; s.d. = 0.381; min = 0; max = 1.
  - Domestic dummy: N = 353; mean = 0.385; s.d. = 0.487; min = 0; max = 1.
  - Small Bank and Large Bank dummies: N = 353; mean = 0.255; s.d. = 0.436; min = 0; max = 1 (each).
  - Low NPL and High NPL: N = 263; mean = 0.262; s.d. = 0.441; min = 0; max = 1 (each).
  - Low Leverage and High Leverage: N = 353; mean = 0.255; s.d. = 0.436; min = 0; max = 1 (each).
  - Low Profitability and High Profitability: N = 311; mean = 0.260; s.d. = 0.440; min = 0; max = 1 (each).
- Appendix 4: List of banks (selected entries by country and ownership) and totals:
  - Total banks listed: 62.
  - Composition reported: 25 (Pan-African) 13 (Foreign-owned) 25 (Domestic).

### VII. Robustness, interpretation, and caveats
- Robustness:
  - System GMM robustness checks generally confirm core results: foreign-owned banks reduce credit and NPL growth while increasing deposit growth during oil price declines; PABs reduce asset quality in some specifications; larger size helps sustain credit but associates with higher NPL growth.
- Interpretation notes:
  - Coefficients on interactions are interpreted after multiplying by −1 to reflect a 1 percent decrease in the change in oil prices.
  - Ownership type may coincide with other characteristics (e.g., a PAB may also be small or have high NPLs); mutually exclusive group analyses used in some tables.
  - Sample of domestic banks is dominated by publicly owned domestic banks; results involving domestic banks may reflect this dominance.
- Limitations highlighted in source:
  - Some coefficients are sensitive to specification; authors caution interpretation where sample composition or correlation across dummies may influence results.

### VIII. Policy implications (as stated)
- Heterogeneity in bank responses implies tradeoffs between maintaining credit growth and safeguarding financial stability during an oil slump.
- Policy recommendations:
  - Use both microprudential and macroprudential policies to mitigate oil price shock impacts on banking systems in oil-exporting countries.
  - Policies should account for heterogeneity across bank types (foreign-owned, PABs, domestic) and bank characteristics (size, asset quality, liquidity, capital).
  - Strengthen pre-shock buffers (capital, asset quality).
  - Enhance mechanisms for liquidity support (including cross-border parent support where appropriate).
  - Further study of the business model of Pan-African Banks (PABs) warranted given their distinct behavior relative to foreign-owned banks.

*Source: Extracted content from wpiea2019129 - References (PDF).*

### References _________________________________________________________________________ 13

### wpiea2019129 - References _________________________________________________________________________ 13

### I. Introduction — context and motivation
- The 2014−16 collapse in oil prices was one of the three largest declines since World War II and the longest lasting since the 1986 slump.
- Sub-Saharan African oil exporting countries (Angola, Cameroon, Chad, Congo Republic, Equatorial Guinea, Gabon, Nigeria, and South Sudan) experienced a negative GDP growth in 2016 of -2.2 percent.
- A 70 percent oil price decline placed a particularly heavy burden on the banking sector of these African oil exporters: bank credit and deposit growth as well as bank profitability and liquidity fell, and financial soundness indicators deteriorated markedly.
- Mechanisms emphasized:
  - Oil price downturns → lower oil revenues → weaker fiscal and external positions → reduced government spending → negative effects on asset prices, credit volumes, banking sector liquidity, and bank balance sheets.
  - Financial sector deterioration can feed back to the real economy via reduced credit and investment and weaker government spending.

### Empirical background and literature
- Studies cited and key findings:
  - Khandelwal, Miyajima, and Santos (2016): feedback loops between oil price movements, bank balance sheets, and asset prices in GCC; bank capital and provisioning behave countercyclically.
  - Miyajima (2016; 2017): in Saudi Arabia, lower oil price growth and non-oil private sector output → slower credit and deposit growth and higher NPLs, with feedbacks within bank balance sheets.
  - Kinda, Mlachila and Ouedraogo (2016): in a sample of 71 commodity exporters, negative commodity price shocks → higher NPLs, bank costs, and banking crises; reduce bank profits, liquidity, and provisions to NPLs; effects stronger with low governance, weak fiscal space, no macroprudential policies, and non-diversified export base.
  - Beck and Poelhekke (2017): financial system plays a limited role in absorbing windfalls; government consumption increases but not private credit.
  - Agarwal, Duttagupta, and Presbitero (2018): credit supply channel important; banks with lower deposits and poor asset quality transmit commodity price changes to lending more aggressively; no significant difference between foreign-owned and domestic banks in that study.
  - Cull, Martinez Peria, and Verrier (2017): foreign-owned banks can stabilize credit in idiosyncratic shocks but may transmit external shocks and not always expand access to credit.

### Contribution of the paper
- Novel focus: role of bank ownership (foreign-owned, Pan-African Banks (PABs), domestic) and other bank characteristics (size, asset quality, liquidity, business model) in transmission of oil price downturns to bank-level outcomes in sub-Saharan African oil exporters.
- First paper to study relative behavior of PABs in response to an oil price shock (according to the authors).
- Policy implication preview: differentiated bank responses imply roles for both micro- and macroprudential policies to mitigate oil price shock impacts.

### Key statistics and datasets referenced
- Oil down cycle studied: the oil down cycle ending in 2016 (with Chad using 2013-2014 due to data availability).
- Comparison up cycle: 2009-2012; down cycle: 2013-2016 (with exceptions noted for Chad and Gabon in specific indicators).
- Bank categorizations and thresholds:
  - Large Banks = top 25 percent of banks by total assets for each year; Small Banks = bottom 25 percent.
  - High NPLs = top 25 percent of banks by NPL ratio for each year; Low NPLs = bottom 25 percent.
  - PAB list from Pan-African Banks Opportunities and Challenges for Cross-Border Oversight (Enoch et al., 2015); subsidiaries where PABs have majority shareholding counted as PABs.
  - Foreign vs domestic classification based on location of majority shareholder and/or ultimate parent as per Fitch Connect.

### II. Stylized facts — observed bank-level outcomes during the oil down cycle
- Aggregate banking system effects (2013-2016 relative to 2009-2012):
  - Credit growth fell in all countries, particularly in Angola, Cameroon and Chad.
  - Asset quality deteriorated (higher NPL ratios).
  - Liquidity positions deteriorated (deposits growth and loans-to-customer deposits fell, though loans-to-deposits fell to a lesser extent in Angola).
  - Profitability (return on average equity) and capital adequacy (leverage ratio, equity-to-assets) also fell.
- Differential effects by bank type:
  - Foreign-owned banks:
    - Behaved more conservatively as oil prices fell: they reduced credit and improved asset quality and liquidity positions.
    - Were resilient during the oil price decline: increased profitability, asset and deposit growth, and decreased NPL ratios.
  - Pan-African Banks (PABs):
    - Helped stabilize overall credit following the oil shock.
    - Heterogeneity by size: small PABs improved asset quality, while largest PABs experienced deterioration in asset quality after a negative oil shock.
    - To a lesser extent showed resilience: asset growth declined but did not experience significant falls in financial soundness indicators.
  - Domestic banks:
    - Appeared to bear the brunt of oil price declines: both asset quality and deposits declined.
    - Experienced deterioration of asset quality and declines in deposit growth.
  - Banks with high asset quality (low NPL ratios):
    - Most resilient to an oil price shock: saw increases in total assets, total deposits, credit growth, liquidity, and capital buffers; minimal change in NPL ratio (though authors caution this result due to correlation between the NPL dummy and the NPL ratio).
  - Banks with low asset quality (high NPLs):
    - Experienced deterioration in asset quality and falls in deposit growth.
- General inference: resilience associated with (a) strong pre-shock buffers (low NPL ratios), (b) ability to diversify risk during shock (PABs and large banks), and (c) access to external liquidity from parent banks (foreign-owned banks).

### III. Methodology and data — modeling approach
- Model framework:
  - Dynamic panel model using a lagged dependent variable to capture persistence and potential innovation/shocks.
  - Dependent variables modeled at bank level (i):
    - Logarithmic change in gross loans (credit growth).
    - Logit transformation of ratio of total impaired loans to gross loans (NPL ratio).
    - Logarithmic change in total deposits (deposit growth).
  - Oil price shock measure (following Arezki and Bruckner (2010) and Bruckner and Ciccone (2010)):
    - Oil Price Growth_{c,t} = θ_c ∆log(Oil Price_t)
    - Oil Price_t = international price of Brent Crude oil in year t; θ_c = time-invariant average value of oil exports in total exports for country c.
    - Authors use first differences to ensure stationarity and note θ_c barely changes over time for sub-Saharan African oil exporters.
- Estimation equation (dynamic panel):
  - y_it = α0 + α1 y_{i,t−1} + α2 (D_{i,t−1} * Oil Price Growth_{c,t−1}) + Σ_j α3j Macro_{j,t−1} + Σ_k α4k Bank_{i,k,t−1} + τ_t + ϑ_i + μ_it
    - y_it as defined above.
    - D_{i,t−1} = dummy for bank characteristics at t−1 capturing high vs. low size, NPL ratio (asset quality), liquidity, leverage (capital buffer), profitability, and ownership/business model (domestic, foreign-owned, PAB).
    - τ_t = year dummies; ϑ_i = bank fixed effects; μ_it = error term.
- Macro and bank control variables:
  - Macro_j,t−1 includes Oil Price Growth_{c,t}, log change non-oil GDP, exchange rate, inflation rate, and ratio of private credit-to-GDP.
  - Bank_{i,k,t−1} includes lagged credit growth or deposit growth, other interest income, ratio of net loans-to-total assets, logarithm of total assets, and holdings of government securities.
- Data notes:
  - Panel covers oil down cycle ending in 2016 for major oil exporters in sub-Saharan Africa (except South Sudan due to data issues); Chad uses 2013-2014 for some indicators.
  - Logit transformation applied to NPL ratio to approximate normality.

### IV. Main empirical findings and policy implications
- Main empirical findings (summarized):
  - Bank ownership significantly influences transmission of oil price shocks.
  - Foreign banks reduce credit and strengthen asset quality and liquidity during oil price declines (conservative response).
  - PABs stabilize credit overall; small PABs improve asset quality, while largest PABs see asset quality deterioration after a negative oil shock.
  - Domestic banks experience declines in asset quality and deposits, indicating they bear the brunt of oil price declines.
  - Banks with strong pre-shock buffers (low NPLs) are more resilient across multiple financial soundness indicators.
- Policy recommendations (implications drawn by the authors):
  - Both microprudential and macroprudential policies can play a significant role in mitigating the impact of oil price shocks on banking systems in oil-exporting countries.
  - Policies should account for heterogeneity across bank types (foreign-owned, PABs, domestic) and bank characteristics (size, asset quality, liquidity, capital).
  - Strengthening pre-shock buffers (capital, asset quality) and enhancing mechanisms for liquidity support (including cross-border parent support where appropriate) can increase resilience.
  - Consideration of macro-financial linkages is crucial given feedback loops between oil prices, fiscal positions, asset prices, and bank balance sheets.

*Source: Extracted content from wpiea2019129 - References _________________________________________________________________________ 13*

### Appendix 3 explains

### Appendix 3 explains

### Variables, measurement, and data
- Variables of interest: 퐷푖,푡−1 ∗ 푂푖푙 푃푟푖𝑐𝑒 퐺푟표𝑤𝑡ℎ 푐,푡−1 and 푂푖𝑙 푃푟𝑖𝑐𝑒 퐺푟표𝑤𝑡ℎ 푐,푡; coefficients are multiplied by −1 so that each coefficient is interpreted as a 1 percent decrease (after multiplying it by −1) in the change in oil prices and its impact on the banking sector.
- Time period and cycles: data over the oil down cycle ending in 2016; a 4-year up cycle 2009-2012 and a 4-year down cycle 2013-2016 are identified.
- Country sample (major oil exporters in sub-Saharan Africa, except South Sudan): Angola, Cameroon, Chad, Congo Republic, Equatorial Guinea, Gabon, and Nigeria.
- Bank-level controls: credit growth used as a bank level control when assessing deposit growth; deposit growth used as a bank level control when assessing credit growth and the logit of banks NPL ratio; change in the natural logarithm of the holding of government securities is taken.
- Data sources: bank level data from Fitch Connect; macro data from IMF World Economic Outlook, IMF Primary Commodity Prices, and IMF International Financial Statistics.

### Empirical approach and interpretation
- Main empirical focus is on coefficients for interactions with oil price growth; coefficients multiplied by −1 to interpret impacts of declining oil prices.
- Robustness check uses system GMM that incorporates both current and past information on banking systems (credit, NPL, and deposit growth).

### Credit growth: differentiated effects by bank characteristics
- Foreign-owned banks and banks with low capital buffers (leverage ratio) reduce credit growth during periods of declining oil prices (appear more conservative).
- Large banks increase credit growth following a decrease in oil price growth.
- Some bank characteristics show no statistical impact on credit growth when oil price growth decreases; ownership type may coincide with characteristics (e.g., a PAB may coincide with a small bank or a bank with high NPLs).
- Mutually exclusive group analysis (Table 1B) findings:
  - Small foreign-owned banks, and foreign-owned banks with both low and high NPLs, decrease credit growth during oil price decline.
  - Large PABs and PABs with low NPLs increase credit growth following a decrease in oil price growth.
  - Private domestic banks increase credit growth relative to publicly owned domestic banks as oil price growth declines (interpret with caution because public domestic banks dominate the sample).

### Asset quality (NPLs)
- Foreign-owned banks improve asset quality (NPL ratios improve) in periods of falling oil prices.
- Large banks experience deterioration in asset quality (increased NPL growth) as oil prices fall.
- PABs show mixed evidence:
  - Small PABs improve asset quality (decreased NPL growth).
  - Large PABs experience deterioration in asset quality (increased NPL growth).
- Domestic banks, even those with high asset quality, experience higher NPLs as oil prices fall.

### Deposit growth
- Foreign-owned banks increase deposit growth following a negative oil price shock; result holds irrespective of foreign-owned banks’ size or asset quality (possible explanations: funding from parent banks, positive reputational effects).
- Deposit growth falls for domestic banks, whether small or large, following an oil price decline.

### Summary of differentiated bank responses
- Foreign-owned banks: decrease lending, improve asset quality, and increase deposit funding when oil prices fall — characterized as more conservative.
- PABs: increase lending and decrease holdings of government securities during oil price declines; asset-quality response is mixed (small PABs improve; large PABs deteriorate).
- Domestic banks: most adversely impacted — NPLs increase and deposit funding falls; sample dominance by publicly owned domestic banks may influence results.
- Large banks: increase lending but at the cost of increased NPLs.
- Banks with low capital buffers: decrease credit, increase funding, and increase holdings of government securities in response to falling oil prices.

### Robustness tests (system GMM results)
- System GMM estimates (Tables 4-6) use current and past information on credit, NPL, and deposit growth.
- Robust findings:
  - Foreign-owned banks reduce both credit and NPL growth while increasing deposit growth in periods of oil price declines.
  - PABs reduce asset quality (Table 5); impact on credit growth for PABs can be positive or negative depending on type.
  - Larger size helps banks sustain credit growth after the oil shock but is associated with lower asset quality (higher NPL growth).
  - Small banks reduce credit growth and increase NPL growth.
  - Banks with high liquidity increase deposits during an oil price downfall.

### Government securities holdings
- Mixed evidence that reduced oil price growth leads to larger government securities holdings by banks (Table 7).
- Specific findings:
  - Domestic banks and banks with low capital buffers increase their holdings of government securities.
  - PABs reduce their portfolios of government securities.
  - Foreign-owned banks decrease their holdings of government securities (statistically insignificant).
- Interpretation: since the sample of domestic banks is dominated by publicly owned banks, increased government securities held by domestic banks could reflect governments’ increased reliance on such banks for placement of government securities as financing needs rise when oil prices fall.

### Conclusions and policy implications
- Banks adjust differently to falling oil prices depending on ownership and characteristics; PABs behave differently from foreign-owned and domestic banks.
- Key conclusions:
  - Foreign-owned banks exhibit a conservative business model during oil price declines: decrease lending, improve asset quality, increase deposit funding.
  - PABs increase lending and decrease government securities holdings; asset-quality implications are mixed and large PABs may deteriorate asset quality.
  - Domestic banks are most adversely affected: higher NPLs, lower deposit funding, and increased burden relating to government financing needs.
  - Large banks show resilience in lending but at the cost of higher NPLs.
  - Banks with low capital buffers respond by decreasing credit, increasing funding, and increasing government securities holdings.
- Policy implications:
  - The heterogeneity in banks’ responses suggests a tradeoff between maintaining credit growth and safeguarding financial stability during an oil slump.
  - Both micro- and macroprudential policies may help mitigate the impact of falling oil prices on banking systems in oil-exporting countries in sub-Saharan Africa.
  - Further study of the business model of Pan-African Banks (PABs) is warranted given their distinct behavior relative to foreign-owned banks.

*Source: Appendix 3 explains (wpiea2019129 - Appendix 3 explains).*

### References

### wpiea2019129 - References (Tables and Notes)

### Key findings: Determinants of Credit Growth (Tables 1A, 1B, and Table 4 system GMM)
- Table 1A (columns (1)-(8)): Oil Price growth (t -1) coefficients and standard errors:
  - -0.519 (0.309)
  - -0.962*** (0.194)
  - -0.776*** (0.282)
  - -0.571** (0.278)
  - -0.949*** (0.244)
  - -0.670** (0.305)
  - -0.778** (0.296)
  - -0.656** (0.310)
- Table 1A: Interaction coefficients (selected):
  - Large Bank * Oil price growth (t -1): -0.225** (0.0995)
  - Low Leverage * Oil price growth (t -1): 0.342** (0.132)
  - Foreign bank * Oil price growth (t -1): 0.280** (0.114)
- Table 1B (columns (1)-(7)): Oil Price growth (t -1) coefficients:
  - -0.497 (0.297)
  - -0.737** (0.300)
  - -0.684** (0.304)
  - -0.976*** (0.177)
  - -1.080*** (0.192)
  - -0.969*** (0.193)
  - -0.803 (0.751)
- Table 1B: Notable interactions:
  - Large PAB bank * Oil price growth (t -1): -0.243** (0.0992)
  - Small Foreign bank * Oil price growth (t -1): 1.306*** (0.157)
  - Private Domestic Bank * Oil price growth (t -1): -0.832*** (0.234)
- Table 4 (system GMM, columns (1)-(8)):
  - Credit Growth (t-1): coefficients range from 0.176** to 0.224*** with standard errors shown (e.g., 0.182** (0.072), 0.224*** (0.0801)).
  - Oil Price growth (t-1): coefficients reported include 0.462 (0.712), -0.0614 (0.727), 0.603 (0.865), 0.352 (0.792), 0.397 (0.822), 0.533 (0.824), 0.382 (0.809), 0.574 (0.827).
  - Small Bank * Oil price growth (t-1): 0.430* (0.223)
  - Large Bank * Oil price growth (t-1): -0.256** (0.103)
  - Foreign * Oil price growth (t-1): 0.290* (0.146)
  - AR(1) and AR(2) and Hansen statistics (selected):
    - AR(1) values include -3.817, -2.855, -3.726, -3.733, -3.484, -3.711, -3.749, -3.700 (AR(1) p-value 0.000 to 0.004).
    - AR(2) values include -0.388 to -0.925 (AR(2) p-value range 0.355 to 0.726).
    - Hansen statistics: 29.79, 27.56, 25.56, 35.55, 30.81, 32.83, 32.37, 32.50 with Hansen p-values 0.0279, 0.0356, 0.00241, 0.00526, 0.0211, 0.0175, 0.0199, 0.0192.
  - Observations and panel size:
    - Observations 210, 178, 210, 210, 207, 210, 210, 210
    - Number of Banks 55, 48, 55, 55, 54, 55, 55, 55
  - F-stat and Prob > F:
    - F-stat range 4.013 to 6.924; Prob > F = 0.000 in all columns.

### Key findings: Determinants of NPL Growth (Tables 2A, 2B, and Table 5 system GMM)
- Table 2A (columns (1)-(8)): Oil Price growth (t -1) coefficients and standard errors:
  - -3.088 (3.027)
  - -4.486 (2.893)
  - -5.130* (2.857)
  - -2.671 (3.254)
  - -4.526 (2.808)
  - -4.195 (2.953)
  - -5.718** (2.775)
  - -4.864* (2.852)
- Table 2A: Interaction coefficients (selected):
  - Large Bank * Oil price growth (t -1): -1.471** (0.696)
  - Foreign bank * Oil price growth (t -1): 2.384* (1.250)
- Table 2B (columns (1)-(6)): Oil Price growth (t -1) coefficients:
  - -3.156 (2.770)
  - -4.801 (2.877)
  - -5.010 (2.877)
  - -4.666 (2.927)
  - -3.242 (2.789)
  - -4.977** (2.881)
- Table 2B: Notable interactions:
  - Small PAB bank * Oil price growth (t -1): 2.983* (1.633)
  - Large PAB bank * Oil price growth (t -1): -1.023* (0.560)
  - High NPL Foreign bank * Oil price growth (t -1): 5.162* (2.711)
  - Low NPL Domestic bank * Oil price growth (t -1): -1.042* (0.607)
- Table 5 (system GMM, columns (1)-(8)):
  - NPL Growth (t-1): coefficients range from -0.185 to -0.254* with standard errors shown (e.g., -0.225 (0.137), -0.224* (0.126)).
  - Oil Price growth (t-1): coefficients include -2.709 (2.916), -3.726 (2.556), -4.146 (3.065), -3.862 (2.949), -3.570 (2.516), -4.370 (2.825), -4.852* (2.591), -3.780 (2.605).
  - Small Bank * Oil price growth (t-1): -3.589*** (1.112)
  - Large Bank * Oil price growth (t-1): -1.741*** (0.522)
  - PAB * Oil price growth (t-1): -1.383*** (0.438)
  - Foreign * Oil price growth (t-1): 2.251** (0.882)
  - AR(1) and AR(2) and Hansen statistics (selected):
    - AR(1) values -2.304 to -2.572 (AR(1) p-value 0.010 to 0.023).
    - AR(2) values -0.699 to 0.913 (AR(2) p-value 0.361 to 0.952).
    - Hansen statistics: 30.86, 30.37, 11.76, 23.22, 20.67, 27.95, 27.09, 24.07 with Hansen p-values 0.0761, 0.0848, 0.465, 0.332, 0.479, 0.177, 0.208, 0.343.
  - Observations 151 in all columns; Number of Banks 46.

### Key findings: Determinants of Deposit Growth (Tables 3A, 3B, and Table 6 system GMM)
- Table 3A (columns (1)-(8)): Oil Price growth (t -1) coefficients and standard errors:
  - 0.385 (0.322)
  - 0.326 (0.339)
  - 0.698** (0.299)
  - 0.472 (0.304)
  - 0.559* (0.311)
  - 0.501* (0.298)
  - 0.559* (0.285)
  - 0.471 (0.287)
- Table 3A: Interaction coefficients (selected):
  - High Liquidity * Oil price growth (t -1): -0.389*** (0.109)
  - Low Leverage * Oil price growth (t -1): -0.341* (0.194)
  - Foreign bank * Oil price growth (t -1): -0.263** (0.120)
- Table 3B (columns (1)-(7)): Oil Price growth (t-1) coefficients:
  - 0.508* (0.289)
  - 0.534* (0.298)
  - 0.489 (0.293)
  - 0.340 (0.351)
  - 0.323 (0.386)
  - 0.324 (0.362)
  - 1.737*** (0.538)
- Table 3B: Notable interactions:
  - Small Foreign bank * Oil price growth (t-1): -0.447** (0.211)
  - Large Domestic bank * Oil price growth (t-1): 0.162*** (0.0586)
  - Low NPL Foreign bank * Oil price growth (t-1): -0.543** (0.266)
  - High NPL Foreign bank * Oil price growth (t-1): -1.482*** (0.279)
  - Private Domestic Bank * Oil price growth (t-1): 0.335** (0.136)
- Table 6 (system GMM, columns (1)-(8)):
  - Deposit Growth (t-1): coefficients include 0.212*** (0.0622), 0.166*** (0.0478), 0.210*** (0.0642), 0.198*** (0.0572), 0.208*** (0.0651), 0.217*** (0.0654), 0.533* (0.313), 0.216*** (0.0668).
  - Oil Price growth (t-1): coefficients include 0.152 (0.953), 0.475 (1.130), 0.516 (1.127), 0.286 (0.971), 0.235 (1.006), 0.181 (0.916), -0.0276 (0.973), 0.246 (1.017).
  - High Liquidity * Oil price growth (t-1): -0.328** (0.160)
  - Foreign * Oil price growth (t-1): -0.316* (0.180)
  - AR(1) and AR(2) and Hansen statistics (selected):
    - AR(1) values -3.740 to -2.869 (AR(1) p-value 0.000 to 0.004).
    - AR(2) values include 0.208 to 1.395 (AR(2) p-value 0.163 to 0.835).
    - Hansen statistics: 22.00, 24.10, 19.59, 23.88, 28.01, 27.04, 26.02, 26.82 with Hansen p-values 0.185, 0.0872, 0.0206, 0.123, 0.0449, 0.0782, 0.0741, 0.0824.
  - Observations 210, 178, 210, 210, 207, 210, 210, 210; Number of Banks 55, 48, 55, 55, 54, 55, 55, 55.

### Key findings: Determinants of Government Securities (Table 7)
- Oil Price growth (t-1) coefficients (columns (1)-(9)):
  - -1.156 (2.624)
  - -1.914 (2.631)
  - -0.310 (2.812)
  - -1.200 (2.619)
  - -2.938 (2.761)
  - -0.751 (2.532)
  - -2.088 (2.720)
  - -1.124 (2.657)
  - -1.152 (2.653)
- Deposit growth: consistently positive and highly significant across columns:
  - 1.483*** (0.333), 1.618*** (0.343), 1.530*** (0.392), 1.452*** (0.315), 1.484*** (0.383), 1.507*** (0.342), 1.544*** (0.336), 1.513*** (0.345), 1.659*** (0.356)
- Deposit growth (t-1): negative and significant in many columns:
  - -0.323*** (0.143), -0.133 (0.213), -0.330*** (0.152), -0.333*** (0.159), -0.324** (0.129), -0.309* (0.161), -0.327** (0.134), -0.317** (0.148), -0.310** (0.136)
- Other selected explanatory variables (t-1) with coefficients and standard errors:
  - Net Loans/ Total Assets (t-1): 1.743* (0.926), 1.601* (0.887), 1.856* (1.058), 1.762* (0.949), 1.836* (0.720), 1.937* (0.975), 1.771* (0.926), 1.705* (0.907), 1.659* (0.875)
  - PAB * Oil price growth (t-1): 0.858** (0.338)
  - Low Leverage * Oil price growth (t-1): -6.358*** (1.799)
  - Domestic bank * Oil price growth (t-1): -1.121** (0.507)
- Panel and fit statistics:
  - Observations 156 (most columns), Number of Banks 42 (most columns), R-squared range 0.262 to 0.368.

Notes applicable to all tables (as stated in source):
- Standard errors in parentheses. Robust standard errors are used.
- Significance notation: * p < 0:10, ** p < 0:05, *** p < 0:01.
- Dependent variables:
  - Table 1A/1B/Table 4: credit growth.
  - Table 2A/2B/Table 5: NPL growth.
  - Table 3A/3B/Table 6: deposit growth.
  - Table 7: government securities.
- The list of macro and bank controls is as explained in the methodology; exchange rate growth is excluded (as it is always statistically insignificant) as well as the private credit to GDP ratio and government securities growth (where applicable).
- System GMM tables report AR(p) (Arellano-Bond) and Hansen J statistics for instrument validity.

*Source: wpiea2019129 - References (PDF).*

### Appendix 1: Financial Soundness Indicators for Selected Regions

### Appendix 1: Financial Soundness Indicators for Selected Regions

### Data sources and coverage
- Sources: Fitch Connect and author's calculation.
- All Fitch Connect Data is bank level data while all IMF data is macro level data.
- Note: IMF WEO = IMF World Economic Outlook; IMF IFS = IMF International Financial Statistics.
- Data used for authors’ calculation is taken from Fitch Connect.

### Appendix 3 — Variable definitions, sample sizes, and summary statistics
- Oil Price Growth: N = 353; mean = -0.0544; s.d. = 0.252; min = -0.604; max = 0.315; Description = log difference in the international price of Brent Crude oil weighted by a country specific share of oil exports in the total export basket; Source = IMF Primary Commodity Prices
- Credit Growth: N = 294; mean = 0.189; s.d. = 0.335; min = -2.155; max = 2.960; Description = log difference of gross loans; Source = Fitch Connect
- Deposit Growth: N = 289; mean = 0.204; s.d. = 0.475; min = -0.638; max = 4.996; Description = log difference of total deposits; Source = Fitch Connect
- Log Total Assets: N = 353; mean = 12.78; s.d. = 1.538; min = 2.432; max = 15.37; Description = log of total assets; Source = Fitch Connect
- logit of NPL ratio: N = 261; mean = -3.080; s.d. = 1.225; min = -8.517; max = -0.063; Description = logit of the ratio of total impaired loans to gross loans; Source = Fitch Connect
- NPL growth: N = 206; mean = 0.294; s.d. = 0.841; min = -1.39; max = 4.48; Description = log difference of non-performing loans; Source = Fitch Connect
- Net Interest Income Growth: N = 270; mean = 0.206; s.d. = 0.441; min = -3.204; max = 2.267; Description = log difference of net interest income; Source = Fitch Connect
- Government Securities Growth: N = 198; mean = 0.206; s.d. = 0.754; min = -2.673; max = 4.626; Description = log difference of government securities; Source = Fitch Connect
- Other Interest Income Growth: N = 270; mean = 0.132; s.d. = 0.622; min = -3.621; max = 2.833; Description = log difference of other interest income; Source = Fitch Connect
- Net Loans / Total Assets: N = 350; mean = 0.415; s.d. = 0.154; min = 0.0168; max = 0.784; Description = Ratio of net loans to total assets; Source = Fitch Connect
- Nonoil GDP Growth: N = 295; mean = 0.122; s.d. = 0.0496; min = -0.0467; max = 0.278; Description = log difference of non-oil GDP; Source = IMF WEO
- Inflation: N = 295; mean = 0.0788; s.d. = 0.0504; min = -0.0213; max = 0.280; Description = log difference of national consumer price index; Source = IMF WEO
- Exchange Rate Growth: N = 295; mean = 0.0802; s.d. = 0.127; min = -0.425; max = 0.501; Description = log difference of national currency units per U.S. dollar (end-of-period); Source = IMF IFS
- PAB: N = 353; mean = 0.439; s.d. = 0.497; min = 0; max = 1; Description = Dummy variable equating 1 if bank is a Pan-African Bank; Source = Authors Calc
- Private Credit to GDP: N = 347; mean = 0.152; s.d. = 0.054; min = 0.039; max = 0.272; Description = Ratio of private credit to GDP; Source = IMF IFS
- Foreign-owned Bank: N = 353; mean = 0.176; s.d. = 0.381; min = 0; max = 1; Description = Dummy variable equating 1 if bank is a Foreign-owned Bank; Source = Authors Calc
- Domestic: N = 353; mean = 0.385; s.d. = 0.487; min = 0; max = 1; Description = Dummy variable equating 1 if bank is a Pan-African Bank; Source = Authors Calc
- Small Bank: N = 353; mean = 0.255; s.d. = 0.436; min = 0; max = 1; Description = = 1 for bottom 25 percent of banks with the lowest total bank assets for each year; Source = Authors Calc
- Large Bank: N = 353; mean = 0.255; s.d. = 0.436; min = 0; max = 1; Description = =1 for top 25 percent of banks with the highest total bank assets for each year; Source = Authors Calc
- Low NPL: N = 263; mean = 0.262; s.d. = 0.441; min = 0; max = 1; Description = = 1 for bottom 25 percent of banks with the lowest NPL ratios for each year; Source = Authors Calc
- High NPL: N = 263; mean = 0.262; s.d. = 0.441; min = 0; max = 1; Description = = 1 for top 25 percent of banks with the highest NPL ratios for each year; Source = Authors Calc
- Low Liquidity: N = 346; mean = 0.254; s.d. = 0.436; min = 0; max = 1; Description = =1 for top 25 percent of banks with highest loans to customer deposit ratios for each year; Source = Authors Calc
- High Liquidity: N = 346; mean = 0.257; s.d. = 0.438; min = 0; max = 1; Description = =1 for bottom 25 percent of banks with lowest loans to customer deposit ratios for each year; Source = Authors Calc
- Low Leverage: N = 353; mean = 0.255; s.d. = 0.436; min = 0; max = 1; Description = =1 for bottom 25 percent of banks with lowest total equity to total assets ratios for each year; Source = Authors Calc
- High Leverage: N = 353; mean = 0.255; s.d. = 0.436; min = 0; max = 1; Description = =1 for top 25 percent of banks with highest total equity to total assets ratios for each year; Source = Authors Calc
- Low Profitability: N = 311; mean = 0.260; s.d. = 0.440; min = 0; max = 1; Description = =1 for bottom 25 percent of banks with lowest return on average equity ratios for each year; Source = Authors Calc
- High Profitability: N = 311; mean = 0.260; s.d. = 0.440; min = 0; max = 1; Description = =1 for top 25 percent of banks with highest return on average equity ratios for each year; Source = Authors Calc

### Appendix 4 — List of banks (selected entries by country and ownership)
- Angola (Pan-African / Foreign-owned / Domestic entries listed in source):
  - Banco Angolano de Investimentos, S.A. — Yes (Pan-African)
  - Banco Angolano de Negocios e Comercios S.A. — Yes (Domestic)
  - Banco BIC, S.A. — Yes (Domestic)
  - Banco Caixa Geral Angola — Yes (Domestic)
  - Banco Comercial do Huambo — Yes (Domestic)
  - Banco de Comercio e Industria — Yes (Domestic)
  - Banco de Desenvolvimento de Angola — Yes (Domestic)
  - Banco de Negocios Internacional SA — Yes (Domestic)
  - Banco Economico S.A. — Yes (Pan-African and Domestic)
  - Banco Fomento Angola — Yes (Domestic)
  - Banco Millennium Angola SA — Yes (Domestic)
  - Banco Millennium Atlantico — Yes (Domestic)
  - Banco Regional do Keve SARL — Yes (Domestic)
  - Banco Sol — Yes (Domestic)
  - Standard Bank Angola, S.A. — Yes (Foreign-owned)
- Cameroon:
  - Afriland First Bank — Yes (Pan-African)
  - Alios Finance Cameroun — Yes (Domestic)
  - Banque Int du Cameroun pour l'Epargne et le Credit — Yes (Domestic)
  - BGFIBank Cameroun S.A — Yes (Pan-African)
  - CA SCB Cameroun — Yes (Domestic)
  - Citibank Cameroun Plc — Yes (Foreign-owned)
  - Commercial Bank - Cameroun,S.A. — Yes (Pan-African)
  - Ecobank Cameroon — Yes (Pan-African)
  - Societe Generale Cameroon — Yes (Foreign-owned)
  - Standard Chartered Bank Cameroon S.A. — Yes (Foreign-owned)
- Chad:
  - Commercial Bank Tchad — Yes (Domestic)
  - Ecobank Tchad SA — Yes (Pan-African)
  - Orabank Tchad — Yes (Pan-African)
- Congo, Republic:
  - Banque Commerciale Internationale S.A. — Yes (Domestic)
  - Banque Congolaise de L' Habitat — Yes (Domestic)
  - BGFIBANK Congo — Yes (Pan-African)
  - Ecobank Congo — Yes (Pan-African)
- Equatorial Guinea:
  - Ecobank Guinee Equatoriale — Yes (Pan-African)
  - Societe Generale de Banques de Guinee Equatoriale (SGB-GE) — Yes (Domestic)
- Gabon:
  - Banque Internationale pour le Commerce et l'Industrie du Gabon SA — Yes (Pan-African)
  - BGFIBank Gabon, S.A. — Yes (Pan-African)
  - Ecobank Gabon — Yes (Pan-African)
  - Orabank Gabon — Yes (Pan-African)
  - Union Gabonaise de Banque — Yes (Domestic)
- Nigeria (selected entries):
  - Access Bank Plc — Yes (Pan-African)
  - Citibank Nigeria Limited — Yes (Foreign-owned)
  - Diamond Bank Plc — Yes (Pan-African)
  - Ecobank Nigeria Ltd — Yes (Pan-African)
  - FBN Holdings Plc — Yes (Domestic)
  - Fidelity Bank PLC — Yes (Domestic)
  - First Bank of Nigeria Ltd — Yes (Pan-African)
  - First City Monument Bank Limited — Yes (Domestic)
  - FSDH Merchant Bank Limited — Yes (Domestic)
  - Guaranty Trust Bank PLC — Yes (Pan-African)
  - Keystone Bank Limited — Yes (Pan-African)
  - Mainstreet Bank Limited — Yes (Domestic)
  - Skye Bank Plc — Yes (Pan-African)
  - Stanbic IBTC Bank PLC — Yes (Pan-African)
  - Stanbic IBTC Holdings PLC — Yes (Pan-African)
  - Standard Chartered Bank Nigeria Limited — Yes (Foreign-owned)
  - Union Bank of Nigeria PLC — Yes (Pan-African)
  - United Bank For Africa Plc — Yes (Pan-African)
  - Unity Bank Plc — Yes (Domestic)
  - Wema Bank PLC — Yes (Domestic)
  - Zenith Bank Plc — Yes (Pan-African)
  - Sterling Bank Plc — Yes (Pan-African)
  - SunTrust Bank Nigeria Limited — Yes (Domestic)
- Totals reported in source:
  - Total = 62
  - 25 (Pan-African) 13 (Foreign-owned) 25 (Domestic)

*Sources: Fitch Connect and author's calculation.*

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_Source: https://www.imf.org/-/media/files/publications/wp/2019/wpiea2019129.pdf_