## EXECUTIVE SUMMARY

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---

### Introduction
- Profitability remains a concern for Spanish and European banks despite a recovery since the crisis:
  - Return on equity for most banks is below the cost of equity.
  - Market valuations are below balance sheet values (GFSR, October 2016).
- Low profitability can affect financial stability by:
  - Limiting banks' ability to clean up balance sheets through write-downs.
  - Reducing banks' capacity to generate earnings and retain/attract private capital, risking undercapitalization after shocks.
  - Forcing banks to shrink assets and reduce credit intermediation.
  - Altering business models and risk-taking behavior.
- FSAP analysis scope:
  - Comparisons of profitability and income components (NIMs, non-interest income) across: (i) internationally-oriented Spanish banks vs. domestic counterparts, (ii) Spanish banks vs. European peers, (iii) two largest Spanish banks vs. GSIB counterparts.
  - Regression analysis samples and scope:
    - Spain sample: 14 Significant Institutions (SIs).
    - European sample: 64 European banks (including 2016 EBA stress test participants).
    - GSIB sample: 32 international global banks classified by the FSB.
    - Sample period: 2000 to 2015.
    - Data sources: publicly available data from FitchConnect, SNL, the IMF, and the ECB.

### Evolution of Bank Profitability and Potential Drivers — Spanish Banks
- System-wide profitability:
  - Consolidated ROE rose to 7.5 percent in 2016Q3.
  - ROE for domestic operations was 5.6 percent.
  - Pre-crisis average ROE between 2005 and 2010 was 14.3 percent.
  - Bank of Spain May 2016 FSR estimated the cost of capital at 6.8 percent for Spanish banks at end-2015.
- Income composition and asset quality:
  - Net interest income around 1 percent of total assets for the banking system in 2016.
  - NPL ratio: 5.7 percent on a consolidated basis and 9.2 percent for domestic operations.
  - Provisions declined from 3.3 percent of total assets in 2014 to 1.8 percent in 2016.
  - Operating costs to total assets ratio about 0.4 percent in 2016.
  - Cost-to-income ratio around 50 percent for the banking system.
  - Unproductive assets (NPLs and foreclosed assets) reached 190 billion euros as of December 2016.
  - Foreborne credit amounted to 144 billion euros in June 2016.
- Internationally oriented Spanish banks vs. domestic banks:
  - The two most internationally-oriented Spanish banks (Santander and BBVA) are more profitable than domestic counterparts.
  - Both NIMs and non-interest income to assets ratios were about twice as large for the two international banks compared with domestically oriented banks in recent years.
  - NPL ratio increases during the crisis were about half for the two international banks relative to domestic banks.
  - Flow of provisions to total assets was much lower for the two global banks during the crisis (reaching similar levels by end-2015).
  - Operating costs to assets ratio higher for the two large international banks, but they remain more efficient by cost-to-income ratio.

### International operations and profitability
- Overseas operations generate the majority of profits for the two international banks.
- Key geographic contributors:
  - Latin American countries including Mexico, Chile, and Brazil are among the most important sources of income for these two firms, as measured by the return on assets and the net interest income to total assets ratio.
  - Spanish banking assets account for 38 percent and 25 percent of total banking sector assets in Mexico and Chile, respectively, in 2016Q2.
- Footnote finding:
  - If the international business were not considered, the ROA of international banks’ Spain business would be broadly similarly to the more domestically-oriented banks.

### Digitalization and FinTech in the Spanish banking sector (Box 1)
- Recent developments:
  - The share of on-line and mobile banking customers has increased significantly for Spanish banks in the past year.
  - FinTech activities in Spain have grown four-fold from 2013 to 2016, with 241 FinTech companies as of April 2017.
  - Several banks have incorporated FinTech solutions and invested in IT infrastructure including cloud computing.
- Potential impacts:
  - Digitalization and FinTech could have important implications on cost savings and bank business models, for example through more cost-efficient payment systems and back-office operations.
- Regulatory and supervisory actions:
  - ECB and SSM announced three main priorities for 2017: (i) business models, (ii) profitability risks for banks in the Euro Area (EA), and (iii) a specific focus on FinTech and nonbank competition.
  - European-level actions include the creation of a Fintech Task Force at the European Commission and the launch of a public consultation on FinTech.
  - In Spain, the CNMV has opened a FinTech Portal; the Treasury, the Bank of Spain, DGSyFP and the CNMV established an interagency working group on financial innovations in 2016.
  - Spain has specific regulation for alternative finance (plataformas de financiación participative—crowdfunding platforms).
- Supervisory recommendation:
  - Supervisors should collect relevant data on digitalization and FinTech developments and analyze potential impacts on bank profitability, business models and the wider financial industry.

### Cross-country comparison with European banks
- Profitability and income components:
  - Spanish banks’ profitability has been supported by high net interest margins, although NIMs have experienced a downward trend amid the low interest rate environment.
  - Non-interest income to assets ratio has trended downward; Spanish banks’ non-interest income to assets ratio was below French or Italian banks, but above German and Irish banks more recently.
  - Non-interest income is less volatile for Spanish banks compared with European peers, partly due to the retail-based business model.
- Costs and efficiency:
  - Spanish banks have managed to keep the cost-to-income ratio at a favorable level despite costly retail banking business especially in terms of staff expenses.
  - The internationally-oriented Spanish banks are more cost efficient compared with their domestic counterparts.
- Asset quality and structure:
  - Non-accrual assets (NPLs and foreclosed assets) and provisions in some banks remain high.
  - Branch density remains high in European comparison, suggesting potential excess capacity despite some decline since 2008.
  - Bank employees per capita appear to be on the lower end compared with European peers; employees per branch in Spain is relatively low.
  - The CR5 index rose following consolidation of savings banks; concentration of the Spanish banking system remains below that of Belgium, Denmark, Finland, the Netherlands and Portugal.
  - Recent measures include branch reductions and ongoing merger discussions; scope for further consolidation and branch rationalization should be analyzed carefully, distinguishing rural branches from urban centers given digitalization effects.

### Comparison with GSIBs (Global Systemically Important Banks)
- Profitability and income structure:
  - Compared with foreign GSIBs, Spanish global banks tend to have higher net interest margins, more efficiency but also higher NPL ratios.
  - Measured by return on average assets, Spanish global banks’ profitability has recovered to a level comparable with other GSIBs.
  - The non-interest income to revenue ratio remains lower for Spanish GSIBs due to their retail-focused business model.
- Costs, provisions and asset quality:
  - Provisions in these two banks are relatively low, despite a slight pickup in 2014.
  - Operating costs are relatively high given the multi-banking subsidiary model, but cost-to-income ratios (efficiency) are more favorable compared with other GSIBs.
  - The NPL ratio for the Spanish global banks is still higher, about twice as large compared with their international peers.
- Individual bank performance:
  - The two Spanish global banks perform comparably in terms of profitability and asset quality.
  - Net interest margins for both firms are above the median for GSIBs; operating costs measured by non-interest expenses to assets are also above median.

### Scope, data and empirical methodology
- Samples:
  - Spain Sample: Significant institutions under SSM supervision (14 SIs; three Portuguese banks included).
  - European Sample: Spanish SIs and other banks in the 2016 EBA stress testing sample.
  - GSIB Sample: All banks classified as GSIBs by the FSB from 2014 to 2016.
- Data and period:
  - Bank balance sheet database constructed from 2000 to 2015 using FitchConnect and SNL.
  - Macroeconomic variables from the IMF International Financial Statistics, the IMF World Economic Outlook database and Haver Analytics.
  - Structural indicators from the ECB Banking Structural Statistics Indicators database.
- Empirical approach:
  - Panel data techniques (Arellano-Bover/Blundell-Bond linear dynamic panel-data estimator with robust standard errors).
  - Dependent variables: ROAE, ROAA, NIMs, non-interest income to assets ratio.
  - Controls: bank characteristics (size, Tier 1 capital ratio, NPL ratio, cost-to-income), business model variables (income diversification, deposit-to-assets ratio, geographic diversification), industry structure (competition, concentration, excess capacity), macro/cyclical variables (GDP growth, short-term interest rate).

### Structural indicators and key regression findings (selected coefficients preserved)
- Spain sample (selected coefficients, significance markers as in source):
  - Tier 1 capital ratio: positive with ROAE/ROAA (e.g., ROAE coefficient 0.271***; ROA E column 11.83*).
  - NPL ratio: negative impact (examples: -3.380**; -0.116***).
  - Cost-to-income ratio: negative impact (examples: -1.944**; -0.0543***).
  - Deposit to asset ratio: positive impact in several specifications (examples: 0.336; 0.0196*).
  - Non-interest income to revenue: positive for Spanish banks (examples: 0.924*; 0.0264**).
  - GDP growth: positive relation (examples: 2.214*; 0.0541**).
  - Short term interest rate (EURIBOR): positive relation with NIMs and profitability (examples: 6.858**; 0.238***).
  - Geographic diversification: positive impact on NIMs, non-interest income to assets ratio, and ROAA (data available for 7 of 14 banks).
- European sample (selected coefficients):
  - NPL ratio: negative association (examples: -1.018*; -0.0628***).
  - Tier 1 capital ratio: positive impact on ROAA in some specs (example: 0.0739*).
  - Cost-to-income ratio: negative relation (examples: -0.251; -0.00914*).
  - Non-interest income to revenue: negative in European sample (examples: -0.240; -0.00843*).
  - Deposit to asset ratio: positive for retail-oriented banks (examples: 0.669*; 0.0217*).
  - GDP growth: positive driver (examples: 1.575***; 0.0560***).
  - Short term interest rate: positive driver (examples: 3.109**; 0.0997***).
  - Excess capacity: branches per capita and bank employees per capita negatively associated with profitability (examples: Branch per capita -0.318; -0.00424**; Bank Employee per capita -0.0437; -0.00250***).
  - Concentration (CR5): inconclusive for headline profitability (examples: ShareFive -0.449; -0.0131).
- GSIB sample (selected coefficients):
  - NPL ratio: negative association (examples: -0.754***; -0.0346***).
  - Cost-to-income ratio: negative association (examples: -0.366***; -0.0178***).
  - Tier 1 capital ratio: positive in some specs (example: 0.0329**).
  - Non-interest income to revenue: positive evidence for GSIBs (example: 0.110***).
  - Bank size (ln total assets): negative effect on headline profitability (examples: -3.483***; -0.126**).
  - GDP growth: positive driver (examples: 0.775***; 0.0361***).
  - Short term interest rate: mixed results (examples: 0.462; 0.0648**).

### Descriptive statistics (selected exact figures)
- Spain sample (bank-year observations):
  - ROAE: Observations 148, Mean 1.15, Standard Deviation 3.9, Minimum -460.2, Maximum 36.4
  - ROAA: Observations 148, Mean 0.41, Standard Deviation 1.4, Minimum -11.8, Maximum 2.2
  - NIM: Observations 148, Mean 1.8, Standard Deviation 0.70, Minimum 0.8, Maximum 4.1
  - Non-interest income/Assets: Observations 152, Mean 0.9, Standard Deviation 0.40, Minimum 0.3, Maximum 1.9
  - NPL ratio: Observations 152, Mean 6.1, Standard Deviation 5.60, Minimum 0.3, Maximum 21.5
  - Tier 1 capital ratio: Observations 139, Mean 9.8, Standard Deviation 2.15, Minimum 5.0, Maximum 14.9
  - Deposit to asset ratio: Observations 152, Mean 49.0, Standard Deviation 10.5, Minimum 25.2, Maximum 78.6
  - Non interest income to revenue: Observations 152, Mean 34.7, Standard Deviation 9.1, Minimum 15.6, Maximum 54.5
  - Cost to income (efficiency): Observations 152, Mean 54.7, Standard Deviation 10.4, Minimum 34.2, Maximum 104.9
  - GDP growth: Observations 224, Mean 1.7, Standard Deviation 2.6, Minimum -3.6, Maximum 5.3
  - Short term interest rate (EURIBOR): Observations 224, Mean 2.2, Standard Deviation 1.6, Minimum 0.0, Maximum 4.6
  - Geographic Diversification: Observations 54, Mean 0.7, Standard Deviation 1.00, Minimum 0.03, Maximum 3.9
- European sample (selected):
  - ROAE: Observations 884, Mean 7.02, Standard Deviation 5.3, Minimum -460.2, Maximum 39.1
  - ROAA: Observations 884, Mean 0.40, Standard Deviation 0.8, Minimum -11.8, Maximum 3.5
  - NIM: Observations 883, Mean 1.5, Standard Deviation 0.9, Minimum -0.1, Maximum 6.9
  - Tier 1 capital ratio: Observations 862, Mean 10.9, Standard Deviation 4.43, Minimum 3.8, Maximum 44.0
  - Cost to income (efficiency): Observations 896, Mean 61.1, Standard Deviation 81.2, Minimum -1753.9, Maximum 1516.1
  - Branch per capita: Observations 972, Mean 2.2, Standard Deviation 25.6, Minimum 10.4, Maximum 101.6
  - Bank employees per capita: Observations 969, Mean 674.4, Standard Deviation 152.3, Minimum 268.1, Maximum 1015.9
  - Share Five Concentration ratio: Observations 976, Mean 48.5, Standard Deviation 17.2, Minimum 19.9, Maximum 87.0
- GSIB sample (selected):
  - ROAE: Observations 475, Mean 10.9, Standard Deviation 10.6, Minimum -59.0, Maximum 83.5
  - ROAA: Observations 480, Mean 0.6, Standard Deviation 0.5, Minimum -1.7, Maximum 3.1
  - Tier 1 capital ratio: Observations 443, Mean 10.6, Standard Deviation 3.24, Minimum 4.8, Maximum 21.3
  - Total assets (ln): Observations 486, Mean 13.7, Standard Deviation 0.81, Minimum 11.1, Maximum 15.2
  - Cost to income (efficiency): Observations 486, Mean 65.9, Standard Deviation 69.0, Minimum 26.8, Maximum 1516.1
  - GDP growth: Observations 512, Mean 2.6, Standard Deviation 3.4, Minimum -8.3, Maximum 14.2
  - Short term interest rate (EURIBOR): Observations 512, Mean 1.8, Standard Deviation 1.8, Minimum -0.8, Maximum 6.5

### Cross-sample synthesis
- Consistent findings:
  - Stronger solvency (higher Tier 1 capital ratio) and lower NPLs are associated with higher bank profitability.
  - Greater cost efficiency (lower cost-to-income ratio) is associated with higher profitability.
  - GDP growth and short term interest rates are consistently positive drivers of bank profitability.
- Divergent findings:
  - Income diversification (non-interest income) shows mixed effects: positive for Spanish banks and GSIBs, negative or unstable for the European sample.
  - Excess capacity (branches per capita, employees per capita) is negatively associated with profitability at the European level.
  - The relationship between concentration (CR5) and profitability is inconclusive.

### Conclusions and policy recommendations
- Current position of Spanish banks:
  - Profitability has recovered gradually since the crisis but return on equity remains below the cost of capital.
  - Net interest margins remain competitive but have trended downward amid low interest rates.
  - Cost-to-income ratio remains favorable compared with peers, though NPL ratio is still relatively high.
  - Branch density remains high in European comparison despite a relatively low bank employee per capita ratio.
- Recommended actions (timing and responsible authorities as specified in source):
  - Short term / Medium term:
    - Banks and supervisors should take further steps to reduce problem assets on bank balance sheets, and to lessen the burden of unproductive assets on banks’ profitability (BdE and ECB). [ST/MT]
  - Short term:
    - Examine the scope for further consolidation in the banking sector through mergers and a rationalization of the extensive branch network in Spain (BdE). [ST]
  - Medium term:
    - Analyze the benefits and potential risks associated with income diversification, particularly non-interest income driven activities for Spanish banks. Conduct analysis and in-depth discussions on business models (BdE). [MT]
    - Collect relevant data and analyze the benefits and potential risks associated with digitalization, FinTech and the impact on bank business models (BdE and ECB). [MT]
- Additional supervisory recommendations:
  - Supervisors should engage closely with banks on cost-cutting measures and thoroughly analyze the scope for consolidation and branch network rationalization.
  - Supervisors should analyze and discuss income diversification strategies and related risks with banks; thematic reviews on business models are underway at the SSM level.
  - Relevant data collection is needed to evaluate digitalization and FinTech impacts.

*Source: EXECUTIVE SUMMARY (cr17339)*

### EXECUTIVE SUMMARY __________________________________________________________________________ 5

### EXECUTIVE SUMMARY

### Introduction
- Despite a recovery since the crisis, profitability remains a concern for Spanish and European banks:
  - Return on equity for most banks is below the cost of equity.
  - Market valuations are below balance sheet values (GFSR, October 2016).
- Low profitability can affect financial stability via multiple channels:
  - Limits banks' ability to clean up balance sheets through write-downs.
  - Reduces banks' capacity to generate earnings and retain/attract private capital, risking undercapitalization after shocks.
  - May force banks to shrink assets and reduce credit intermediation.
  - Can alter business models and risk-taking behavior.
- Scope of the FSAP analysis:
  - Compares profitability and income components (NIMs, non-interest income) for (i) internationally-oriented Spanish banks vs. domestic counterparts, (ii) Spanish banks vs. European peers, and (iii) two largest Spanish banks vs. GSIB counterparts.
  - Regression analysis samples and scope:
    - Spain sample: 14 Significant Institutions (SIs).
    - European sample: 64 European banks (including 2016 EBA stress test participants).
    - GSIB sample: 32 international global banks classified by the FSB.
    - Sample period: 2000 to 2015.
    - Data sources: publicly available data from FitchConnect, SNL, the IMF, and the ECB.

### Evolution of Bank Profitability and Potential Drivers — Spanish Banks
- System-wide profitability has recovered since the crisis but remains below pre-crisis levels and below the cost of capital:
  - Consolidated ROE rose to 7.5 percent in 2016Q3.
  - ROE for domestic operations was 5.6 percent.
  - Pre-crisis average ROE between 2005 and 2010 was 14.3 percent.
  - Bank of Spain May 2016 FSR estimated the cost of capital at 6.8 percent for Spanish banks at end-2015.
- Income composition and asset quality:
  - Net interest income around 1 percent of total assets for the banking system in 2016.
  - NPL ratio: 5.7 percent on a consolidated basis and 9.2 percent for domestic operations.
  - Provisions declined from 3.3 percent of total assets in 2014 to 1.8 percent in 2016.
  - Operating costs to total assets ratio about 0.4 percent in 2016.
  - Cost-to-income ratio around 50 percent for the banking system.
  - Unproductive assets (NPLs and foreclosed assets) reached 190 billion euros as of December 2016.
  - Foreborne credit amounted to 144 billion euros in June 2016.
- Internationally oriented Spanish banks vs. domestic banks:
  - The two most internationally-oriented Spanish banks (Santander and BBVA) are more profitable than domestic counterparts.
  - Both NIMs and non-interest income to assets ratios were about twice as large for the two international banks compared with domestically oriented banks in recent years.
  - NPL ratio increases during the crisis were about half for the two international banks relative to domestic banks.
  - Flow of provisions to total assets was much lower for the two global banks during the crisis (reaching similar levels by end-2015).
  - Operating costs to assets ratio higher for the two large international banks, but they remain more efficient by cost-to-income ratio.

### Empirical Findings (Regression Analysis) — Key Drivers Across Samples
- Common influential factors for profitability across Spanish banks, European banks, and GSIBs:
  - NPL ratios influence profitability negatively (unproductive assets are costly and increase provisions).
  - Stronger solvency (Tier 1 capital ratio) is associated with better ROA and ROE performance.
  - Efficiency (lower cost-to-income ratio) is strongly associated with higher profitability.
  - Cyclical factors: GDP growth is positively related to bank profitability through higher credit demand.
  - Monetary policy: Short-term interest rate is a positive driver for profitability as NIMs rise with higher interest rates.
  - Industry structure (European level): Excess capacity measures — branches per capita and bank employees per capita — are negatively associated with profitability due to higher operating costs.

- Data and methodology notes:
  - Regression analysis used panel data techniques to account for macro-financial linkages, bank financial soundness measures, business model indicators (income diversification, deposit-to-assets ratio), industry structure (competition, concentration, excess capacity), and monetary policy effects.
  - Supervisory data were not available; analysis relied on publicly available datasets.

### Conclusions and Policy Recommendations
- Objectives: reduce NPLs and legacy assets, continue cost-cutting to enhance profitability, and strengthen supervisory communications on business models.

- Recommended actions (with timing and responsible authorities as specified):
  - Short term / Medium term:
    - Banks and supervisors should take further steps to reduce problem assets on bank balance sheets, and to lessen the burden of unproductive assets on banks’ profitability (BdE and ECB). [ST/MT]
  - Short term:
    - Examine the scope for further consolidation in the banking sector through mergers and a rationalization of the extensive branch network in Spain (BdE). [ST]
  - Medium term:
    - Analyze the benefits and potential risks associated with income diversification, particularly non-interest income driven activities for Spanish banks. Conduct analysis and in-depth discussions on business models (BdE). [MT]
    - Collect relevant data and analyze the benefits and potential risks associated with digitalization, FinTech and the impact on bank business models (BdE and ECB). [MT]

- Additional supervisory recommendations:
  - Supervisors should engage closely with banks on cost-cutting measures and thoroughly analyze the scope for consolidation and branch network rationalization.
  - Supervisors should analyze and discuss income diversification strategies and related risks with banks; thematic reviews on business models are underway at the SSM level.
  - Relevant data collection is needed to evaluate digitalization and FinTech impacts (see Box 1: Digitalization and FinTech in the Spanish Banking Sector).

*Source: EXECUTIVE SUMMARY (cr17339)*

### 7. The majority of the profits for the two international banks are generated through their

### 7. The majority of the profits for the two international banks are generated through their overseas operations

### International operations and profitability
- International operations of these banks are more profitable than their domestic business.
- Latin American countries including Mexico, Chile, and Brazil are among the most important sources of income for these two firms, as measured by the return on assets and the net interest income to total assets ratio.
- Spanish banking assets account for 38 percent and 25 percent of total banking sector assets in Mexico and Chile, respectively, in 2016Q2.
- Footnote finding: If the international business were not considered, the ROA of international banks’ Spain business would be broadly similarly to the more domestically-oriented banks.

### Digitalization and FinTech in the Spanish banking sector (Box 1)
- Recent developments
  - The share of on-line and mobile banking customers has increased significantly for Spanish banks in the past year.
  - FinTech activities have grown rapidly in Spain; FinTech activities in Spain have grown four-fold from 2013 to 2016, with 241 FinTech companies as of April 2017.
  - Several banks have incorporated FinTech solutions and invested in IT infrastructure including cloud computing.
- Potential impacts
  - Digitalization and FinTech could have important implications on cost savings and bank business models, for example through more cost-efficient payment systems and back-office operations.
- Regulatory and supervisory actions
  - ECB and SSM announced three main priorities for 2017, including (i) business models, (ii) profitability risks for banks in the Euro Area (EA), and (iii) a specific focus on FinTech and nonbank competition, exploring potential risks for banks’ business models emanating from the emergence of these potentially disruptive innovations.
  - European-level actions include the creation of a Fintech Task Force at the European Commission and the launch of a public consultation on FinTech.
  - In Spain, the CNMV has opened a FinTech Portal; the Treasury, the Bank of Spain, DGSyFP and the CNMV established an interagency working group on financial innovations in 2016.
  - Spain has specific regulation for alternative finance (plataformas de financiación participative—crowdfunding platforms).
- Supervisory recommendation
  - It would be essential for supervisors to collect the relevant data on digitalization and FinTech developments and analyze the potential impact on bank profitability, business models and the wider financial industry.

### Cross-country comparison with European banks
- Profitability and income components
  - Spanish banks’ profitability has been supported by high net interest margins, although NIMs have experienced a downward trend amid the low interest rate environment.
  - The non-interest income to assets ratio has trended downward, partly driven by a fall in net fee and commission income; Spanish banks’ non-interest income to assets ratio was below French or Italian banks, but above German and Irish banks more recently.
  - Non-interest income is less volatile for Spanish banks compared with European peers, in part due to the retail-based business model.
- Costs and efficiency
  - Spanish banks have managed to keep the cost-to-income ratio at a favorable level despite costly retail banking business especially in terms of staff expenses.
  - The internationally-oriented Spanish banks are more cost efficient compared with their domestic counterparts.
- Asset quality
  - Non-accrual assets (NPLs and foreclosed assets) and provisions in some banks remain high.
  - Spanish banks experienced a sharp increase in NPL ratio and provisions during the crisis; significant progress has been made in bringing down NPLs.
- Structural indicators and consolidation
  - Branch density remains high in European comparison, suggesting potential excess capacity despite some decline since 2008.
  - Bank employees per capita appear to be on the lower end compared with European peers; employees per branch in Spain is relatively low.
  - The CR5 index rose following consolidation of savings banks; the concentration of the Spanish banking system remains below that of Belgium, Denmark, Finland, the Netherlands and Portugal.
  - Recent measures include branch reductions and ongoing merger discussions; scope for further consolidation and branch rationalization should be analyzed carefully, distinguishing rural branches from urban centers given digitalization effects.

### Comparison with GSIBs (Global Systemically Important Banks)
- Profitability and income structure
  - Compared with foreign GSIBs, Spanish global banks tend to have higher net interest margins, more efficiency but also higher NPL ratios.
  - Measured by return on average assets, Spanish global banks’ profitability has recovered to a level comparable with other GSIBs.
  - The non-interest income to revenue ratio remains lower for Spanish GSIBs due to their retail-focused business model.
- Costs, provisions and asset quality
  - Provisions in these two banks are relatively low, despite a slight pickup in 2014.
  - Operating costs are relatively high given the multi-banking subsidiary model, but cost-to-income ratios (efficiency) are more favorable compared with other GSIBs.
  - The NPL ratio for the Spanish global banks is still higher, about twice as large compared with their international peers.
- Individual bank performance
  - The two Spanish global banks (Santander and BBVA as noted in the sample) perform comparably in terms of profitability and asset quality.
  - Net interest margins for both firms are above the median for GSIBs; operating costs measured by non-interest expenses to assets are also above median, reflecting the retail-based subsidiary model.
  - Asset quality remains relatively low compared with the majority of GSIBs, although more favorable compared with the Italian GSIB.

### Scope and methodology for the regression analysis
- Samples
  - Three samples of banks: Spanish (Significant institutions under SSM supervision), European (Spanish SIs and all other banks in the 2016 EBA stress testing sample), and GSIBs (all banks classified as GSIBs by the FSB from 2014 to 2016).
  - Note: Three Portuguese banks were included due to the close relationship between the Spanish and the Portuguese banking systems.
- Data sources and period
  - Bank balance sheet database constructed from 2000 to 2015 using FitchConnect and SNL.
  - Macroeconomic variables from the IMF International Financial Statistics, the IMF World Economic Outlook database and Haver Analytics.
  - Structural indicators for European banks from the ECB Banking Structural Statistics Indicators database.
- Empirical approach
  - Panel data techniques applied to examine determinants of profitability, controlling for bank characteristics, business models, industry structures, macroeconomics and cyclical factors and monetary policy of the home country.
  - Dependent variables include headline profitability measures such as ROAE and ROAA, and income components including NIMs and the non-interest income to assets ratio.
  - The panel regression is estimated with the Arellano-Bover/Blundell-Bond linear dynamic panel-data estimator with robust standard errors.
- Model specification and variables
  - Dynamic panel specification (equation provided in source) includes lagged dependent variable, bank-fixed effects, bank-specific indicators X_k,j,t, industry structural indicators I_j,t, and macro/cyclical variables M_j,t.
  - Bank characteristics:
    - Size: natural logarithm of total assets.
    - Solvency: Tier 1 capital ratio.
    - Credit risk: NPL ratio.
    - Cost efficiency: cost-to-income ratio.
  - Business model variables:
    - Income diversification: share of non-interest income over total revenue.
    - Retail banking intensity: deposit to total assets ratio.
    - Geographical diversification (for Spanish banks): ratio of non-domestic loans to domestic loans.
- Contribution
  - Comprehensive assessment accounting for macro-financial linkages, bank financial soundness, business models, industry concentration and excess capacity, and monetary policy.
  - Approach related to ECB (2015) and Borio, Gambacorta and Hofmann (2015) but differing in explicit consideration of monetary policy, low interest rate environment and excess capacity.

*International Monetary Fund — Chapter excerpt (cr17339).*

### 20. The banking industry structural indicators, 푰푰

### 20. The banking industry structural indicators, 푰푰

### Overview
- The top-five bank concentration (CR5) index is defined as the market share of the top five institutions in terms of assets (ECB, 2015).
- Excess capacity is captured by the number of bank branches per capita and bank employees per capita (ECB Structural Banking Statistics).
- The pairwise correlation between the CR5 index and the Herfindahl index is 95 percent.

### Empirical findings — Spanish banks
- Key drivers of Spanish banks’ profitability include credit risk, efficiency, business model variables, and solvency.
- Tier 1 capital ratio:
  - Positive relationship with ROAE and ROAA; coefficient in Table 1 for ROAE: 0.271*** (standard error 0.103); for ROA E column 11.83* (standard error 6.207) when listed in different specifications.
- NPL ratio:
  - Negative impact on profitability; Table 1 coefficients include -3.380** (standard error 1.493) and -0.116*** (standard error 0.0290) for different specifications.
- Cost to income ratio (efficiency):
  - Negative relationship with profitability; Table 1 reports -1.944** (standard error 0.756) and -0.0543*** (standard error 0.0170) across specifications.
- Deposit to asset ratio:
  - Positive impact on profitability in several specifications; Table 1 reports 0.336 (standard error 0.457) and 0.0196* (standard error 0.0106).
- Non-interest income to revenue:
  - Suggests some value in income diversification for Spanish banks; Table 1 reports 0.924* (standard error 0.502) and 0.0264** (standard error 0.0103).
- Macroeconomic drivers:
  - GDP growth: positive relation with ROAE and ROAA; Table 1 reports 2.214* (standard error 1.232) and 0.0541** (standard error 0.0217).
  - Short term interest rate (EURIBOR): positive relation with net interest margins and with ROAE/ROAA; Table 1 reports 6.858** (standard error 2.880) and 0.238*** (standard error 0.0711).
- Geographic diversification:
  - Positive impact on NIMs, non-interest income to assets ratio, and on ROAA; data on domestic vs. non-domestic loans available only for 7 out of 14 Spanish banks in the sample.

### Empirical findings — European banks
- Common drivers similar to Spanish banks: NPL ratio, Tier 1 capital, cost-to-income, macro factors.
- NPL ratio:
  - Negative association with profitability; Table 2 reports -1.018* (standard error 0.618) and -0.0628*** (standard error 0.0191).
- Tier 1 capital ratio:
  - Positive impact on ROAA in some specifications; Table 2 reports 0.0739* (standard error 0.0386).
- Cost to income (efficiency):
  - Negative relation with NIMs and ROAA; Table 2 reports -0.251 (standard error 0.201) and -0.00914* (standard error 0.00533).
- Non-interest income to revenue:
  - Affects profitability negatively in the European sample; Table 2 reports -0.240 (standard error 0.179) and -0.00843* (standard error 0.00479).
- Deposit to asset ratio:
  - Retail-oriented business model fares better; Table 2 reports 0.669* (standard error 0.350) and 0.0217* (standard error 0.0122).
- Macroeconomic drivers:
  - GDP growth: Table 2 reports 1.575*** (standard error 0.306) and 0.0560*** (standard error 0.0131).
  - Short term interest rate: Table 2 reports 3.109** (standard error 1.329) and 0.0997*** (standard error 0.0367).
- Excess capacity:
  - Branches per capita negatively associated with NIMs; Table 2 reports Branch per capita -0.318 (standard error 0.318) and -0.00424** (standard error 0.00216).
  - Bank employee per capita negatively associated with ROAA; Table 2 reports Bank Employee per capita -0.0437 (standard error 0.0285) and -0.00250*** (standard error 0.000631).
- Concentration (ShareFive/CR5):
  - Degree of concentration at the national level does not have a significant impact on headline profitability (ROAA and ROAE); Table 2 reports ShareFive -0.449 (standard error 0.417) and -0.0131 (standard error 0.0126).

### Empirical findings — GSIBs (Global Systemically Important Banks)
- Profitability drivers combine structural and cyclical factors similar to Spanish and European banks.
- NPL ratio:
  - Negative association with profitability; Table 3 reports -0.754*** (standard error 0.265) and -0.0346*** (standard error 0.0101).
- Cost to income ratio:
  - Negative association; Table 3 reports -0.366*** (standard error 0.0506) and -0.0178*** (standard error 0.00184).
- Tier 1 capital ratio:
  - Positive association in some specifications; Table 3 reports 0.0329** (standard error 0.0144).
- Non-interest income to revenue:
  - Positive evidence for GSIBs in Table 3: 0.110*** (standard error 0.0127).
- Bank size:
  - Negative effect on headline profitability; Table 3 reports Total asset (ln) -3.483*** (standard error 1.089) and -0.126** (standard error 0.0617).
- Macroeconomic drivers:
  - GDP growth: positive driver; Table 3 reports 0.775*** (standard error 0.229) and 0.0361*** (standard error 0.00839).
  - Short term interest rate: mixed results in Table 3, coefficient 0.462 (standard error 0.454) and 0.0648** (standard error 0.0305).

### Cross-sample synthesis
- Consistent findings across samples:
  - Stronger solvency position (Tier 1 capital ratio) and lower NPLs are often associated with higher bank profitability.
  - Greater cost efficiency (lower cost-to-income ratio) is associated with higher profitability.
  - GDP growth and short term interest rates are consistently positive drivers of bank profitability.
- Divergent findings:
  - The benefit of income diversification via non-interest income is mixed: positive for Spanish banks and GSIBs, but negative or more volatile for European banks.
  - Excess capacity (branches per capita, employees per capita) is negatively associated with profitability at the European level.
  - The relationship between bank concentration (CR5) and profitability is inconclusive.

### Conclusions and policy recommendations
- Current position of Spanish banks:
  - Profitability has recovered gradually since the crisis but return on equity remains below the cost of capital.
  - Net interest margins remain competitive but have trended downward amid low interest rates.
  - Cost-to-income ratio remains favorable compared with peers, though NPL ratio is still relatively high.
  - Branch density remains high in European comparison despite a relatively low bank employee per capita ratio.
- Policy recommendations:
  - Reduce problem assets:
    - Authorities and banks should take further steps to reduce problem assets in bank balance sheets given their negative impact on profitability.
  - Rationalize branch network and reduce costs:
    - Authorities should work with banks to analyze the scope for further cost reduction through mergers and a rationalization of the extensive branch network.
    - Analyze optimal size of branch network given digitalization and distinctions between rural and urban service needs.
  - Analyze income diversification:
    - Authorities should engage with banks to analyze benefits and potential risks of income diversification; supervisors should examine risks associated with non-interest income driven activities and potential negative impacts on client relations and banking volumes.
  - Collect data and analyze digitalization and FinTech:
    - Authorities should collect data on digitalization and FinTech activities, including the share of sales and transactions conducted through on-line and mobile banking.
    - Supervisors should analyze benefits and potential risks of digitalization and FinTech on bank profitability and business models.
    - Timely investment and upgrade in IT infrastructure may be warranted.

*International Monetary Fund — cr17339, "20. The banking industry structural indicators, 푰푰"*

### References

### References

### References Cited
- Albertazzi and Gambacorta (2009) “Bank Profitability and the Business Cycle”, Journal of Financial Stability.
- Bank of Spain (2015), Financial Stability Report, November 2015.
- Bank of Spain (2016), Financial Stability Report, May 2016.
- Bikker, J.A. and Hu, H., “Cyclical patterns in profits, provisioning and lending of banks and procyclicality of the new Basel capital requirements”, BNL Quarterly Review, 221, 2002.
- Borio, Gambacorta and Hofmann (2015), “The influence of monetary policy on bank profitability” BIS Working paper, No. 514, October 2015.
- ECB (2015), “Bank Profitability Challenges in Euro Area Banks: The Role of Cyclical and Structural Factors”, Financial Stability Review.
- ECB (2016), “Adapting bank business models: financial stability implications of greater reliance on fee and commission income”, Financial Stability Review.
- Gambacorta, L. and van Rixtel, A. (2013), “Structural bank regulation initiatives: approaches and implications”, BIS Working Papers, No 412, 2013.
- Gambacorta, L., Scatigna, M. and Yang, J., “Diversification and bank profitability: a nonlinear approach”, Applied Economics Letters, Vol. 21, 2014, pp. 438-441.
- GFSR (April 2016), Potent Policies for a Successful Normalization, Chapter 1, Global Financial Stability Report, IMF.
- GFSR (October 2016), Financial Stability Challenges in A Low-Growth, Low-Rate Era, Chapter 1, Global Financial Stability Report, IMF.
- GFSR (April 2017), Getting the Policy Mix Right, Chapter 1, Global Financial Stability Report, IMF.
- Molyneux, P. and Thornton, J., “Determinants of European bank profitability: a note”, Journal of Banking and Finance, 16, 1992, pp. 1173-1178.
- Tregenna, F., “The fat years: the structure and profitability of the US banking sector in the pre-crisis period”, Cambridge Journal of Economics, Vol. 33, 2009, pp. 609-632.

### Samples and Bank Lists
- Spain Sample (selected banks listed): Banco Santander, S.A.; Banco Bilbao Vizcaya Argentaria, S.A.; CaixaBank, S.A.; Bankia S.A.; Banco Popular Espanol S.A.; Banco de Sabadell; Banco Mare Nostrum S.A.; Banco Santander, SA; Bankinter; Ibercaja Banco, S.A.; Grupo Cooperativo Cajamar (GCC); Kutxabank, S.A.; Liberbank S.A.; Unicaja Banco S.A.; ABANCA Corporacion Bancaria, S.A.
- GSIB Sample (selected banks listed with country codes): Industrial and Commercial Bank of China CHN; China Construction Bank Corporation CHN; Bank of China Ltd. CHN; Agricultural Bank of China Limited CHN; BNP Paribas SA FRA; Crédit Agricole Group FRA; Groupe BPCE FRA; Société Générale SA FRA; Commerzbank AG DEU; Deutsche Bank AG DEU; UniCredit SpA ITA; Mitsubishi UFJ Financial Group, Inc. JPN; Mizuho Financial Group, Inc. JPN; Sumitomo Mitsui Financial Group, Inc. JPN; ING Bank NV NLD; Banco Bilbao Vizcaya Argentaria, SA ESP; Nordea Bank AB (publ) SWE; Credit Suisse Group AG CHE; UBS Group AG CHE; Barclays Plc GBR; HSBC Holdings Plc GBR; Royal Bank of Scotland Group Plc GBR; Standard Chartered Plc GBR; Bank of America Corporation USA; Citigroup Inc. USA; Goldman Sachs Group, Inc. USA; JPMorgan Chase & Co. USA; Morgan Stanley USA; State Street Corporation USA; Wells Fargo & Company USA.

- European Sample (selected banks listed with country codes): Erste Group Bank AG AUT; Raiffeisen Zentralbank Oesterreich AUT; Belfius Bank SA/NV BEL; KBC Groep NV BEL; Danske Bank A/S DNK; Jyske Bank A/S DNK; Nykredit Realkredit A/S DNK; OP Financial Group FIN; Societe Generale FRA; Crédit Mutuel Group FRA; BNP Paribas FRA; La Banque Postale FRA; Groupe BPCE FRA; Landesbank Baden-Wuerttemberg DEU; Deutsche Bank AG DEU; Commerzbank AG DEU; NRW.BANK DEU; Bayerische Landesbank DEU; DekaBank Deutsche Girozentrale DEU; Landesbank Hessen-Thueringen Girozentrale DEU; Norddeutsche Landesbank Girozentrale DEU; Volkswagen Bank GmbH DEU; Credit Suisse Group AG CHE; UBS AG CHE; Allied Irish Banks, plc IRL; Bank of Ireland IRL; UniCredit S.p.A. ITA; Banca Monte dei Paschi di Siena SpA ITA; Intesa Sanpaolo S.p.A. ITA; Unione di Banche Italiane S.p.A. ITA; Banco Popolare ITA; Bank Nederlandse Gemeenten (BNG) NLD; ABN AMRO Group N.V. NLD; Coöperatieve Rabobank U.A. NLD; DNB Group NOR; PKO Bank Polski POL; Caixa Geral de Depósitos, S.A. PRT; Banco Comercial Portugues, S.A. PRT; Banco BPI S.A. PRT; Banco Santander, S.A. ESP; Banco Bilbao Vizcaya Argentaria, S.A. ESP; CaixaBank, S.A. ESP; Bankia S.A. ESP; Banco Popular Espanol S.A. ESP; Banco de Sabadell ESP; Banco Mare Nostrum S.A. ESP; Bankinter ESP; Ibercaja Banco, S.A. ESP; Grupo Cooperativo Cajamar (GCC) ESP; Kutxabank, S.A. ESP; Liberbank S.A. ESP; Unicaja Banco S.A. ESP; ABANCA Corporacion Bancaria, S.A. ESP.

### Data Source and Variable Definitions
- Profitability:
  - Headline Profitability: ROAE = Net Income / Average Total Equity (Source: FitchConnect)
  - ROAA = Net Income / Average Total Assets (Source: FitchConnect)
- Income components:
  - Net Interest Margins (NIM) = Net Interest Income / Average Assets (Source: FitchConnect)
  - Net interest income = Gross Interest and Dividend Income - Total Interest Expense (Source: FitchConnect)
  - Non-interest income = Net Gains (Losses) on Trading and Derivatives + Net Gains (Losses) on Other Securities + Net Gains (Losses) on Assets at FV through Income Statement + Net Insurance Income + Net Fees and Commissions + Other Operating Income (Source: FitchConnect)
- Bank Characteristics:
  - Bank size: Total assets = Consolidated Total Assets (Source: FitchConnect)
  - Bank solvency: Tier 1 capital ratio = Regulatory Tier 1 Capital / Risk Weighted Assets (Sources: FitchConnect, SNL)
  - Credit risk: NPL ratio = Impaired Loans (NPLs) / Gross Loans (Source: FitchConnect)
  - Bank efficiency: Cost-to-income ratio = Total Non-Interest Expenses / Total Income (Source: FitchConnect)
- Bank business models:
  - Diversification: Income diversification (Non-interest income to total revenue) = Total Non-Interest Operating Income / (Total Non-Interest Operating Income + Net Interest Income) (Source: FitchConnect)
  - Geographical diversification = Non-domestic loans / Domestic loans (Sources: FitchConnect, SNL)
  - Retail business model: Deposits to assets ratio = Total deposits / total assets (Source: FitchConnect)
- Macro and monetary policy:
  - GDP Growth (Source: World Bank WDI)
  - Short Term Interest Rate = 3-month interest rates (Sources: Haver Analytics; WEO: FIDR (Short-term interest rate))
- Concentration:
  - Herfindahl = The sum of the squares of the market shares of all firms within the industry, where the market shares are expressed as fractions. (Source: ECB Banking Structural Indicators)
  - ShareFive = Shares of the 5 largest CIs in total assets (CR5) (Source: ECB Banking Structural Indicators)
- Excess capacity:
  - Branch per capita = Number of Branches in Country / Population of Country (Sources: ECB Banking Structural Indicators, Haver Analytics)
  - Bank employees per capita = Number of bank employees in Country / Population of Country (Sources: ECB Banking Structural Indicators, Haver Analytics)

### Descriptive Statistics (selected exact figures)
- Spain Sample (bank-year observations):
  - ROAE: Observations 148, Mean 1.15, Standard Deviation 3.9, Minimum -460.2, Maximum 36.4
  - ROAA: Observations 148, Mean 0.41, Standard Deviation 1.4, Minimum -11.8, Maximum 2.2
  - NIM: Observations 148, Mean 1.8, Standard Deviation 0.70, Minimum 0.8, Maximum 4.1
  - Non-interest income/Assets: Observations 152, Mean 0.9, Standard Deviation 0.40, Minimum 0.3, Maximum 1.9
  - NPL ratio: Observations 152, Mean 6.1, Standard Deviation 5.60, Minimum 0.3, Maximum 21.5
  - Total assets (ln): Observations 152, Mean 11.5, Standard Deviation 1.29, Minimum 9.4, Maximum 14.1
  - Tier 1 capital ratio: Observations 139, Mean 9.8, Standard Deviation 2.15, Minimum 5.0, Maximum 14.9
  - Deposit to asset ratio: Observations 152, Mean 49.0, Standard Deviation 10.5, Minimum 25.2, Maximum 78.6
  - Non interest income to revenue: Observations 152, Mean 34.7, Standard Deviation 9.1, Minimum 15.6, Maximum 54.5
  - Cost to income (efficiency): Observations 152, Mean 54.7, Standard Deviation 10.4, Minimum 34.2, Maximum 104.9
  - GDP growth: Observations 224, Mean 1.7, Standard Deviation 2.6, Minimum -3.6, Maximum 5.3
  - Short term interest rate (EURIBOR): Observations 224, Mean 2.2, Standard Deviation 1.6, Minimum 0.0, Maximum 4.6
  - Geographic Diversification: Observations 54, Mean 0.7, Standard Deviation 1.00, Minimum 0.03, Maximum 3.9

- European Sample (bank-year observations, selected):
  - ROAE: Observations 884, Mean 7.02, Standard Deviation 5.3, Minimum -460.2, Maximum 39.1
  - ROAA: Observations 884, Mean 0.40, Standard Deviation 0.8, Minimum -11.8, Maximum 3.5
  - NIM: Observations 883, Mean 1.5, Standard Deviation 0.9, Minimum -0.1, Maximum 6.9
  - Tier 1 capital ratio: Observations 862, Mean 10.9, Standard Deviation 4.43, Minimum 3.8, Maximum 44.0
  - Cost to income (efficiency): Observations 896, Mean 61.1, Standard Deviation 81.2, Minimum -1753.9, Maximum 1516.1
  - Branch per capita: Observations 972, Mean 2.2, Standard Deviation 25.6, Minimum 10.4, Maximum 101.6
  - Bank employees per capita: Observations 969, Mean 674.4, Standard Deviation 152.3, Minimum 268.1, Maximum 1015.9
  - Share Five Concentration ratio: Observations 976, Mean 48.5, Standard Deviation 17.2, Minimum 19.9, Maximum 87.0

- GSIB Sample (bank-year observations, selected):
  - ROAE: Observations 475, Mean 10.9, Standard Deviation 10.6, Minimum -59.0, Maximum 83.5
  - ROAA: Observations 480, Mean 0.6, Standard Deviation 0.5, Minimum -1.7, Maximum 3.1
  - Tier 1 capital ratio: Observations 443, Mean 10.6, Standard Deviation 3.24, Minimum 4.8, Maximum 21.3
  - Total assets (ln): Observations 486, Mean 13.7, Standard Deviation 0.81, Minimum 11.1, Maximum 15.2
  - Cost to income (efficiency): Observations 486, Mean 65.9, Standard Deviation 69.0, Minimum 26.8, Maximum 1516.1
  - GDP growth: Observations 512, Mean 2.6, Standard Deviation 3.4, Minimum -8.3, Maximum 14.2
  - Short term interest rate (EURIBOR): Observations 512, Mean 1.8, Standard Deviation 1.8, Minimum -0.8, Maximum 6.5

### Regression Results and Robustness Checks (selected coefficients and notes)
- Appendix III. Table 1: Spain Sample with Geographical Diversification (Arellano-Bover/Blundell-Bond linear dynamic panel-data estimation with robust standard errors)
  - Dependent variables across columns: ROAE (1), ROAA (2), NIM (3), Non-interest income/Assets (4)
  - Lagged dependent variables:
    - Column (1) coefficient -0.0565 (standard error 0.105)
    - Column (3) coefficient 0.314*** (standard error 0.0370)
    - Column (4) coefficient 0.264*** (standard error 0.0613)
  - NPL ratio:
    - Column (1) -1.982*** (0.654)
    - Column (2) -0.0664*** (0.0235)
    - Column (3) -0.0219*** (0.00622)
    - Column (4) -0.00981* (0.00572)
  - Non interest income to revenue:
    - Column (1) 2.078*** (0.798)
    - Column (2) 0.0697*** (0.0252)
    - Column (3) -0.0138** (0.00552)
    - Column (4) 0.0280*** (0.00320)
  - Geographic Diversification:
    - Column (1) 9.002 (7.001)
    - Column (2) 0.444** (0.184)
    - Column (3) 0.220** (0.0956)
    - Column (4) 0.133*** (0.0460)
  - Cost to income (efficiency):
    - Column (1) -3.624*** (1.310)
    - Column (2) -0.104*** (0.0325)
    - Column (3) -0.0152*** (0.00509)
    - Column (4) -0.00603** (0.00236)
  - GDP growth:
    - Column (4) -0.0196*** (0.00458)
  - Short term interest rate (EURIBOR):
    - Column (4) 0.0220*** (0.00748)
  - Observations 49 across columns, Number of Banks 7; Robust standard errors; significance: *** p<0.01, ** p<0.05, * p<0.1

- Appendix III. Table 2: Robustness Check: Spain Sample without Global Banks
  - Lagged dependent variables:
    - Column (1) -0.208*** (0.0637)
    - Column (3) 0.511*** (0.0466)
    - Column (4) 0.268*** (0.103)
  - NPL ratio:
    - Column (1) -2.617** (1.128)
    - Column (2) -0.0991*** (0.0373)
    - Column (3) -0.0121* (0.00659)
  - Deposit to asset ratio:
    - Column (2) 0.0233* (0.0135)
    - Column (3) 0.0153*** (0.00408)
    - Column (4) 0.0101*** (0.00298)
  - Cost to income (efficiency):
    - Column (1) -2.137** (0.851)
    - Column (2) -0.0569*** (0.0213)
    - Column (3) -0.0122*** (0.00286)
    - Column (4) -0.00761*** (0.00233)
  - GDP growth:
    - Column (1) 1.909 (1.357)
    - Column (2) 0.0547** (0.0269)
    - Column (4) -0.0152** (0.00617)
  - Short term interest rate (EURIBOR):
    - Column (1) 6.823** (2.650)
    - Column (2) 0.281*** (0.0802)
  - Observations 92 (columns vary), Number of Banks 12; Robust standard errors; significance: *** p<0.01, ** p<0.05, * p<0.1

- Appendix III. Table 3: Robustness Check: Spain Sample with Lagged Capital Ratio
  - Lagged dependent variables:
    - Column (1) -0.176*** (0.0482)
    - Column (3) 0.640*** (0.0379)
    - Column (4) 0.397*** (0.0982)
  - NPL ratio:
    - Column (1) -3.009** (1.335)
    - Column (2) -0.105*** (0.0320)
    - Column (3) -0.0133** (0.00628)
    - Column (4) -0.0126*** (0.00342)
  - Tier 1 capital ratio:
    - Column (1) 13.70* (8.097)
    - Column (2) 0.320*** (0.113)
    - Column (3) -0.0170 (0.0144)
  - Lagged Tier 1 capital ratio:
    - Column (3) 0.0282*** (0.00846)
  - Deposit to asset ratio:
    - Column (2) 0.0205** (0.00985)
    - Column (3) 0.0184*** (0.00452)
    - Column (4) 0.00922*** (0.00319)
  - Cost to income (efficiency):
    - Column (1) -1.848** (0.823)
    - Column (2) -0.0513** (0.0200)
    - Column (3) -0.0133*** (0.00228)
    - Column (4) -0.00642*** (0.00206)
  - GDP growth:
    - Column (1) 2.899 (1.775)
    - Column (2) 0.0727** (0.0308)
    - Column (4) -0.0118** (0.00493)
  - Short term interest rate (EURIBOR):
    - Column (1) 5.124** (2.329)
    - Column (2) 0.187*** (0.0693)
    - Column (3) 0.0578*** (0.0206)
  - Observations range 119–123 across columns, Number of Bank_id 14; Robust standard errors; significance: *** p<0.01, ** p<0.05, * p<0.1

*Source: cr17339 - References.*

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_Source: https://www.imf.org/-/media/files/publications/cr/2017/cr17339.pdf_