## _spn1009

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---

### I. INTRODUCTION
- Central question: How does monetary policy affect bank risk taking (defined as choices that increase the volatility of bank profits)?
- Competing narratives:
  - Monetary easing can induce greater risk taking via search for yield, leverage, and asset-price channels.
  - A countervailing short-run risk-shifting effect arises from limited liability: low policy rates can reduce risk taking for poorly capitalized banks while increasing it for well-capitalized banks.
- Key caveats:
  - Monetary policy is approximated by changes in the real yield on safe assets.
  - The paper does not assess the ex ante optimality of bank risk choices.
- Structure of the paper:
  - Mechanisms linking policy to risk taking.
  - Empirical evidence (including new U.S. stylized facts).
  - Tentative policy implications.

### II. CONCEPTUAL FRAMEWORK
- Modeling stance:
  - Monetary policy modeled as exogenous changes in the policy rate; bank risk taking equals actions that increase volatility of returns on bank assets.
- Mechanisms implying easing promotes risk taking:
  - Asset substitution: lower real yield on safe assets reduces their portfolio weight; risk-neutral banks increase demand for risky assets.
  - Search for yield: institutions with long-term commitments shift into riskier assets when safe yields are low.
  - Procyclical leverage (Adrian and Shin, 2009): target leverage ratios imply asset-price increases from easing raise equity and asset demand, reinforcing asset-price rises and increasing fragility.
- Mechanisms implying easing can reduce risk taking:
  - Limited liability and risk shifting: leveraged banks act like risk-loving agents because downside is borne by depositors; prudential capital requirements and franchise value create “skin-in-the-game” that reduces excessive risk taking.
  - Intermediation spreads channel: a cut in the policy rate can increase bank spreads (when loan demand is negatively sloped), raising bank profits and franchise value, which reduces moral hazard and risk taking.
  - Expectation of policy backstops (the “Greenspan put” / “Bernanke put”): anticipation of aggressive rate cuts in crises increases collective moral hazard; where there is greater room for stimulus (when rates are high), higher rates may correspond to greater risk taking.
- Balancing opposite forces:
  - Short run: effect depends on banks’ degree of limited liability (capitalization). High-charter-value (well-capitalized) banks increase risk taking when policy rates are low; low-charter-value (poorly capitalized) banks may reduce risk taking.
  - Medium/long run: endogenous adjustments (capital raising, exit of weak banks) tend to produce a negative relationship between policy rate and bank risk taking.
  - Dynamic extension: disappearance of low-charter-value banks over time leads to a prevalent negative relationship between policy rate and bank risk taking.

### III. EMPIRICAL EVIDENCE
- Empirical strategy:
  - Ex ante measures of bank risk taking from U.S. sources (Federal Reserve lending surveys and Call Reports).
  - Results allowed to vary by degree of bank capitalization (e.g., low if below the 25th percentile).
  - Controls: one-year lag of real GDP growth and median forecast of probability that GDP will decline the following year.

- A. Evidence from U.S. Lending Surveys
  - Data: Federal Reserve quarterly survey of terms of business lending from a stratified sample of about 400 banks; loans issued during the first full business week of the middle month each quarter.
  - Two survey-based ex ante risk measures:
    - Average internal risk rating assigned by banks to loans.
    - Average relative spread between loan rates and the effective federal funds rate.
  - Real effective federal funds rate = effective federal funds rate minus CPI inflation.
  - Simple correlations:
    - Correlation of average internal risk rating with the real federal funds rate is –0.72 (significant at the 1 percent level).
    - Correlation of average spread with the real federal funds rate is –0.65 (significant at the 1 percent level).
  - Regression evidence (OLS, quarterly, 1997–2008):
    - Real interest rates are negatively associated with the two ex ante measures of bank risk taking.
    - The negative effect of the policy rate on risk taking is less pronounced when bank capital is low (below 25th percentile).
    - For bank spreads, the association with real funds rate can turn positive when bank capital is low.
  - Economic magnitude from spreads:
    - A one standard deviation decrease in real funds rates (equivalent to about 1.8 percent) implies:
      - An increase in bank spreads of 0.28 percentage point when bank capital is high.
      - A reduction in bank spreads of 0.61 percentage point when bank capital is low.
    - Standard deviation of the spread variable: 0.34.
  - Selected regression coefficients (standard errors in parentheses):
    - Real federal funds rate: –0.072** (0.012) for Risk rating; –0.155*** (0.018) for Spread.
    - Low capital: –0.147 (0.245) for Risk rating; –0.575*** (0.150) for Spread.
    - Real federal funds rate * low capital: 0.030 (0.077) for Risk rating; 0.174*** (0.043) for Spread.
    - Probability of recession coefficient for Spread: 0.019*** (0.004).
    - Observations: 46; R-squared: 0.55 for Risk rating, 0.42 for Spread.

- B. Evidence from U.S. Call Reports
  - Data: Quarterly bank-level Call Reports for U.S. commercial banks and bank holding companies.
  - Risk measure: ratio of risk-weighted assets to total assets (risk weights reflect regulatory guidance).
  - Regressions: OLS with bank fixed effects; independent variables include real federal funds rate and bank leverage (1 minus equity/total assets); alternative interaction with low-capital indicator (<25th percentile); controls for one-year lag real GDP growth and median forecast of probability GDP will decline.
  - Findings:
    - Strong negative relationship between real interest rates and riskiness of banks’ assets (risk-weighted assets / total assets).
    - Relationship is less pronounced when bank capital is low, consistent with theoretical predictions.
    - Negative association between ex ante risk measures and real GDP growth (loans turn riskier when economy weakens).
    - System average risk-weighted-assets-to-total-assets plotted against real effective federal funds rate confirms negative association, with a much flatter scatter for 2006–08 implying the risk-shifting effect is more important in distress periods.
  - Economic magnitude from risk-weighted assets:
    - A one standard deviation decrease in real funds rates (equivalent to about 1.8 percent) would imply an increase in the share of risk-weighted assets in total assets of [text truncated in source].
  - Selected Call Report regression coefficients and statistics (standard errors in parentheses):
    - Real federal funds rate: –0.769*** (0.182) in (1); –0.770*** (0.182) in (2); –1.967*** (0.577) in (3); –0.792*** (0.180) in (4).
    - Leverage ratio: –0.144*** (0.038) in (2); –0.157*** (0.042) in (3).
    - Real federal funds rate * leverage ratio: 1.317* (0.713) in (3).
    - Low capital: –0.011*** (0.001).
    - Real federal funds rate * low capital: 0.139*** (0.041).
    - Lagged real GDP growth: –0.271 (0.172).
    - Probability of recession: coefficients ~ –0.039 to –0.037 (0.076).
    - Observations: 82,708.
    - R-squared: 0.774.
    - Number of BHCs: 3,260.

- C. Selective Review of Existing Empirical Literature
  - Loan-officer survey studies:
    - Lown and Morgan (2006): credit standards tend to tighten after monetary contraction, but results not statistically significant.
    - Maddaloni, Peydró-Alcalde, and Scop (2009): statistically significant loosening of credit standards when overnight rates are lowered; prolonged low rates further soften lending standards.
  - Credit-registry studies:
    - Low interest rates at loan origination associated with higher probability of lending to borrowers with bad or no credit history.
    - Low rates can decrease riskiness of banks’ overall loan portfolios in some contexts.
  - Overall empirical picture:
    - Broad support for a negative association between the policy rate and ex ante bank risk taking, with dependence on banking-system health and bank capitalization.
    - Risk-shifting effects are more important in times of financial distress; medium-term dynamics tend to favor a negative relationship.

### Main findings on monetary policy and bank risk taking
- Monetary easing increases bank risk taking, but the effect depends on bank capitalization: an increase of 1.4 percentage points when bank capital is high compared with a modest increase of 0.6 percentage point when bank capital is low.
- These effects are significant relative to the standard deviation of the risk-weighted assets variable of 13.0 percent.
- Monetary easing tends to decrease the risk of outstanding loan portfolios in the short run via improved bank profitability (charter value hypothesis), since interest rate pass-through is typically larger for bank liabilities than assets.
- Two opposing short-term forces shape the relationship between real interest rates and bank risk taking:
  - Portfolio reallocation and search-for-yield effects imply a negative relationship between the policy rate and risk taking (easing → more risk taking).
  - Risk shifting by banks protected by limited liability can work in the opposite direction.
- Preliminary empirical evidence: monetary policy easing will increase risk taking, but less so for poorly capitalized banks.

### Interpretation and channels
- Charter value hypothesis: decreases in real interest rates raise bank profitability (similar effect to a bank capital shock), making banks safer in the short term.
- Balance sheet channel: differential responses across firms and borrowers to monetary shocks, where credit flows away from borrowers most affected by credit market imperfections during tightening or recessions.
- Micro and macro evidence supports that lax monetary policy associates with higher risk taking for new loans, but:
  - The precise transmission channels remain inconclusive.
  - The quantitative importance and economic efficiency of induced risk taking remain open questions.
- Heterogeneity in impacts: effect likely differs across countries and time, depending on local banking market conditions (bank leverage, charter values, contestability) and business cycle dynamics.

### Policy implications and recommendations
- Trade-offs between price stability and financial stability depend on shocks and dominant forces:
  - Near cycle peaks: monetary tightening can reduce both risk taking and price pressures (no trade-off).
  - Low inflation with excessive risk taking (e.g., asset or housing bubbles): tightening may reduce risk taking but cause undesired aggregate contraction or deflation (trade-off).
  - Currency crises with rising inflation and depleted bank capital: combating inflation may increase bank risk taking.
- Macroprudential measures can complement monetary policy and target specific sectors (e.g., capital requirements, tightening lending criteria such as limits on loan-to-value ratios to curb house price booms).
- Centralization of macroprudential responsibilities within the monetary authority is argued for, given interactions among banking conditions, monetary decisions, and bank risk taking.
- Monetary policy as a blunt tool: the policy rate is likely a weak and costly instrument to curb excessive risk taking; regulatory tools (taxing/restricting activities, raising capital requirements, tightening lending standards) may be more effective and less costly in output terms.
- Measurement and modeling recommendations:
  - Need for models that explicitly incorporate monetary policy effects on bank risk taking and joint modeling of monetary and macroprudential policy interactions.
  - Future empirical work should account for bank heterogeneity and endogeneity of capitalization and market shares.

*Italic source: _spn1009 - References .............................................................................................................*

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

### _spn1009 - References .............................................................................................................

### I. INTRODUCTION
- Central question: How does monetary policy affect bank risk taking (defined as choices that increase the volatility of bank profits)?  
- Competing narratives:
  - Monetary easing can induce greater risk taking via search for yield, leverage, and asset-price channels.
  - A countervailing short-run risk-shifting effect arises from limited liability: low policy rates can reduce risk taking for poorly capitalized banks while increasing it for well-capitalized banks.
- Key caveats noted:
  - Monetary policy is approximated by changes in the real yield on safe assets.
  - The paper does not assess the ex ante optimality of bank risk choices.
- Paper structure:
  - Mechanisms linking policy to risk taking.
  - Empirical evidence (including new U.S. stylized facts).
  - Tentative policy implications.

### II. CONCEPTUAL FRAMEWORK
- Definition and modeling stance:
  - Monetary policy modeled as exogenous changes in the policy rate; bank risk taking equals actions that increase volatility of returns on bank assets.
- Mechanisms that suggest monetary easing promotes risk taking:
  - Asset substitution: lower real yield on safe assets reduces their weight in portfolios; risk-neutral banks increase demand for risky assets.
  - Search for yield: institutions with long-term commitments (pension funds, insurance companies) shift into riskier assets when safe yields are low to match liabilities.
  - Procyclical leverage (Adrian and Shin, 2009): target leverage ratios imply asset-price increases from easing raise equity and asset demand, reinforcing asset-price rises and increasing fragility.
- Mechanisms that suggest monetary easing can reduce risk taking:
  - Limited liability and risk shifting: leveraged banks act like risk-loving agents because downside is borne by depositors; prudential capital requirements and franchise value create “skin-in-the-game” that reduces excessive risk taking.
  - Channel via intermediation spreads: a cut in the policy rate can increase bank spreads (when loan demand is negatively sloped), raising bank profits and franchise value, which reduces moral hazard and risk taking.
  - Expectation of policy backstops (the “Greenspan put” / “Bernanke put”): anticipation of aggressive rate cuts in crises increases collective moral hazard; however, the paper notes that where there is greater room for stimulus (when rates are high), higher rates may correspond to greater risk taking.
- Balancing opposite forces:
  - Short run: effect of policy on risk depends on banks’ degree of limited liability (capitalization). High-charter-value (well-capitalized) banks respond to low policy rates by increasing risk taking; low-charter-value (poorly capitalized) banks may reduce risk taking.
  - Medium/long run: endogenous adjustments (capital raising, exit of weak banks) tend to produce a negative relationship between the policy rate and bank risk taking.
  - Dynamic extensions imply low-charter-value banks disappear over time, leading to prevalent negative relationship between policy rate and bank risk taking.

### III. EMPIRICAL EVIDENCE
- Empirical strategy:
  - Examine ex ante measures of bank risk taking from U.S. sources (Federal Reserve lending surveys and Call Reports).
  - Allow results to vary by degree of bank capitalization (e.g., low if below the 25th percentile).
  - Control for macro performance: one-year lag of real GDP growth and median forecast of probability that GDP will decline the following year.
- A. Evidence from U.S. Lending Surveys
  - Data: Federal Reserve quarterly survey of terms of business lending from a stratified sample of about 400 banks; measures cover loans issued during the first full business week of the middle month each quarter.
  - Two survey-based ex ante risk measures used:
    - Average internal risk rating assigned by banks to loans.
    - Average relative spread between loan rates and the effective federal funds rate.
  - Real effective federal funds rate computed as effective federal funds rate minus CPI inflation.
  - Simple correlations:
    - Correlation of average internal risk rating with the real federal funds rate is –0.72 (significant at the 1 percent level).
    - Correlation of average spread with the real federal funds rate is –0.65 (significant at the 1 percent level).
  - Regression evidence (OLS, quarterly, 1997–2008):
    - Real interest rates are negatively associated with the two ex ante measures of bank risk taking.
    - The negative effect of the policy rate on risk taking is less pronounced when bank capital is low (below 25th percentile).
    - For bank spreads, the association with real funds rate can turn positive when bank capital is low.
  - Economic magnitude from spreads:
    - A one standard deviation decrease in real funds rates (equivalent to about 1.8 percent) implies:
      - An increase in bank spreads of 0.28 percentage point when bank capital is high.
      - A reduction in bank spreads of 0.61 percentage point when bank capital is low.
    - Standard deviation of the spread variable: 0.34.
- B. Evidence from U.S. Call Reports
  - Data: Quarterly bank-level Call Reports for U.S. commercial banks and bank holding companies.
  - Risk measure: ratio of risk-weighted assets to total assets (risk weights reflect regulatory guidance).
  - Regressions: OLS with bank fixed effects; independent variables include real federal funds rate and bank leverage (1 minus equity/total assets); alternative interaction with low-capital indicator (<25th percentile); controls for one-year lag real GDP growth and median forecast of probability GDP will decline.
  - Findings:
    - Strong negative relationship between real interest rates and riskiness of banks’ assets (risk-weighted assets / total assets).
    - Relationship is less pronounced when bank capital is low, consistent with theoretical predictions.
    - Negative association between ex ante risk measures and real GDP growth (loans turn riskier when economy weakens).
    - System average risk-weighted-assets-to-total-assets plotted against real effective federal funds rate confirms negative association (Figure 2), with a much flatter scatter for 2006–08 implying the risk-shifting effect is more important in distress periods.
  - Economic magnitude from risk-weighted assets:
    - A one standard deviation decrease in real funds rates (equivalent to about 1.8 percent) would imply an increase in the share of risk-weighted assets in total assets of [text truncated in source].
- C. Selective Review of Existing Empirical Literature
  - Loan-officer survey studies:
    - Lown and Morgan (2006): credit standards tend to tighten after monetary contraction, but results not statistically significant.
    - Maddaloni, Peydró-Alcalde, and Scop (2009): statistically significant loosening of credit standards when overnight rates are lowered; prolonged low rates further soften lending standards.
  - Credit-registry studies (Jimenez et al., Ioannidou et al.):
    - Low interest rates at loan origination associated with higher probability of lending to borrowers with bad or no credit history.
    - Low rates can decrease riskiness of banks’ overall loan portfolios in some contexts.
  - Overall empirical picture:
    - Broad support for a negative association between the policy rate and ex ante bank risk taking, but with dependence on banking-system health and bank capitalization.
    - Risk-shifting effects are more important in times of financial distress; medium-term dynamics tend to favor a negative relationship.

### Policy Implications (tentative from source text)
- Interaction of macroprudential and monetary policy:
  - The macroprudential authorities’ response to changes in the monetary policy stance should consider variables determining financial health of the banking system (capitalization, franchise values).
- Time-horizon considerations:
  - Short-run effects can vary across banks and over time depending on capitalization; medium/long-run dynamics (capital adjustments, market exit) likely produce a negative relationship between policy easing and aggregate bank risk taking.
- Measurement and modeling recommendations:
  - Need for models that explicitly incorporate monetary policy effects on bank risk taking and joint modeling of monetary and macroprudential policy interactions.
  - Future empirical work should account for bank heterogeneity and endogeneity of capitalization and market shares.

*Italic source: _spn1009 - References .............................................................................................................*

### 1.4 percentage points when bank capital is high compared with a modest increase of 0.6 percentage point when

### _spn1009 - 1.4 percentage points when bank capital is high compared with a modest increase of 0.6 percentage point when

### Main findings on monetary policy and bank risk taking
- Monetary easing increases bank risk taking, but the effect depends on bank capitalization: an increase of 1.4 percentage points when bank capital is high compared with a modest increase of 0.6 percentage point when bank capital is low.  
- These effects are significant relative to the standard deviation of the risk-weighted assets variable of 13.0 percent.  
- Monetary easing tends to decrease the risk of outstanding loan portfolios in the short run via improved bank profitability (charter value hypothesis), since interest rate pass-through is typically larger for bank liabilities than assets.  
- Two opposing short-term forces shape the relationship between real interest rates and bank risk taking:
  - Portfolio reallocation and search-for-yield effects imply a negative relationship between the policy rate and risk taking (easing → more risk taking).
  - Risk shifting by banks protected by limited liability can work in the opposite direction.
- Preliminary empirical evidence: monetary policy easing will increase risk taking, but less so for poorly capitalized banks.

### Empirical evidence and quantitative results (selected)
- Terms of Business Lending Survey (U.S.; quarterly data 1997:Q2–2008:Q4; ~400 sampled banks):
  - Dependent variables: weighted average risk rating and weighted average relative spread over the effective federal funds rate (both increasing in risk).
  - Low capital: dummy if capital-to-asset ratio is below its 25th percentile.
  - Key regression coefficients (standard errors in parentheses):
    - Real federal funds rate: –0.072** (0.012) for Risk rating; –0.155*** (0.018) for Spread.
    - Low capital: –0.147 (0.245) for Risk rating; –0.575*** (0.150) for Spread.
    - Real federal funds rate * low capital: 0.030 (0.077) for Risk rating; 0.174*** (0.043) for Spread.
    - Probability of recession coefficient for Spread: 0.019*** (0.004).
  - Observations: 46; R-squared: 0.55 for Risk rating, 0.42 for Spread.

- U.S. Call Reports (bank holding companies; quarterly data 1986–2008):
  - Dependent variable: risk-weighted assets-to-total-assets ratio.
  - Real effective federal funds rate = three-month average effective federal funds rate – three-month average change in CPI (in percent).
  - Low capital: dummy = 1 if equity-capital-to-total assets ratio below 25th percentile.
  - Leverage = 1 minus equity-to-total-assets ratio.
  - Regressions include bank fixed effects; standard errors clustered at FOMC date level.
  - Selected coefficients and statistics (standard errors in parentheses):
    - Real federal funds rate: –0.769*** (0.182) in (1); –0.770*** (0.182) in (2); –1.967*** (0.577) in (3); –0.792*** (0.180) in (4).
    - Leverage ratio: –0.144*** (0.038) in (2); –0.157*** (0.042) in (3).
    - Real federal funds rate * leverage ratio: 1.317* (0.713) in (3).
    - Low capital (column 3 or 4 context): –0.011*** (0.001).
    - Real federal funds rate * low capital: 0.139*** (0.041).
    - Lagged real GDP growth: –0.271 (0.172) (reported across columns).
    - Probability of recession: coefficients ~ –0.039 to –0.037 (0.076).
  - Sample and fit:
    - Observations: 82,708.
    - R-squared: 0.774.
    - Number of BHCs: 3,260.

### Interpretation and channels
- Charter value hypothesis: decreases in real interest rates raise bank profitability (similar effect to a bank capital shock in the bank capital channel), making banks safer in the short term.
- Balance sheet channel interpretation: differential responses across firms (and borrowers) to monetary shocks, where credit flows away from borrowers most affected by credit market imperfections during tightening or recessions.
- Existing micro and macro evidence supports that lax monetary policy associates with higher risk taking for new loans, but:
  - The precise transmission channels remain inconclusive.
  - The quantitative importance and economic efficiency of induced risk taking remain open questions.
- Heterogeneity in impacts: the effect of monetary policy on bank risk taking likely differs across countries and time, depending on local banking market conditions (bank leverage, charter values, contestability) and business cycle dynamics.

### Policy implications and recommendations
- Potential trade-offs between price stability and financial stability depend on shocks and dominant forces (portfolio effects vs. risk shifting).
  - Near cycle peaks: monetary tightening can reduce both risk taking and price pressures (no trade-off).
  - Low inflation with excessive risk taking (e.g., asset or housing bubbles): tightening may reduce risk taking but cause undesired aggregate contraction or deflation (trade-off).
  - Currency crises with rising inflation and depleted bank capital: combating inflation may increase bank risk taking.
- Macroprudential measures can complement monetary policy and target specific sectors (e.g., capital requirements, tightening lending criteria such as limits on loan-to-value ratios to curb house price booms).
- Centralization of macroprudential responsibilities within the monetary authority is argued for, given interactions among banking conditions, monetary decisions, and bank risk taking; the complexity of interactions supports centralization.
- Monetary policy as a blunt tool: the policy rate is likely a weak and costly instrument to curb excessive risk taking; regulatory tools (taxing/restricting activities, raising capital requirements, tightening lending standards) may be more effective and less costly in output terms.

### Figures and illustrative evidence
- Figure descriptions:
  - Figure 1: OLS regressions of ex ante bank risk measures (weighted average relative lending spread and weighted average risk rating) on the real federal funds rate using Terms of Business Lending Survey data (1997:Q2–2008:Q4).
  - Figure 2: OLS regression of quarterly average ratio of risk-weighted assets to total assets across U.S. BHCs on the real federal funds rate (1986–2008). Quarterly observations during 2006–08 are encircled by an ellipse.

*Italic: IMF staff paper content provided in the supplied source.*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/spn/2010/_spn1009.pdf_