Monetary policy and the asset risk-taking channel

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Monetary policy and the asset risk-taking channel Angela Abbate 1 Dominik Thaler 2 1 Deutsche Bundesbank and European University Institute 2 European University Institute Trinity Workshop, 7 November 215 This paper represents the authors personal opinions and does not necessarily reflect the views of the Deutsche Bundesbank or its staff.

Motivation The Global Financial Crisis has reignited the debate on: The determinants of financial sector risk The influence of low interest rates on risk-taking behaviour Risk-taking channel of monetary policy - Borio and Zhu (28) In the lead up to the crisis: low US interest rate and increasing measures of bank risk taking Many empirical contributions on the topic using: Loan level panel data: Jimenez et al. (ECMTA, 214), Ioannidou et al. (Rev Financ, 214) Aggregate time series data: Buch et al. (JEDC, 214) How important is the channel?

Ex-ante bank risk and the nominal interest rate Average loan risk (from 1997Q2) Banks assign an internal risk rating to newly issued loans Construct a weighted average loan risk series, [, 5], 5 = max risk An increase in average risk could result from an active choice of the banks to extend credit to riskier borrowers 2.6 Weighted average loan risk (inverse) Nominal interest rate 8 2.8 6 3 4 3.2 2 3.4 1996 1998 2 22 24 26 28 21 212 214

An expansionary monetary policy shock on US bank risk taking.14 Output growth.4 Inflation % p oints.12.1.8.6.4.2 % p oints.3.2.1 2 4 6 8 1 12 2 4 6 8 1 12 Loan safety.1 Nominal interest rate % p oints.5 1 1.5 % p oints.1.2.3.4 2 4 6 8 1 12 2 4 6 8 1 12 Sample period: 1997q2-29q4; IRFs over a 3-year, identified through sign restrictions. Error bands shown correspond to a 9% confidence interval.

Contributions: 1. Develop a dynamic New Keynesian model with a risk-taking channel, by extending Dell Ariccia et al. (JET, 214) Lower risk-free rate banks grant loans to riskier borrowers This level of risk is not optimal 1 st and 2 nd order effects on consumer welfare Main differences from other models of financial frictions: Asset risk vs funding risk Pro-cyclical leverage dynamics 2. How important is the risk-taking channel? Estimate the model on US data How does the channel affect the trade-off faced by the monetary policy authority? Literature review

Overview of the model

The supply of deposits and equity: Households Choose consumption and labour, and save through government bonds (s t ), bank deposits (d t ), and bank equity (e t ) 1. If a bank defaults, e t pay and d t pay the (limited) deposit insurance 2. Real cost of holding equity ξ (premium over the risk free rate) Equity is more costly for banks than deposits Each bank defaults with probability 1 q, but HH perfectly diversify among a continuum of banks In equilibrium, the no-arbitrage conditions must hold: [ E u ( ψ ) ] c(c t+1) q tr d,t + (1 q t) = E [u c(c t+1)r t] (1 k t) [ E u ( c(c t+1) r e,t+1q t ξ )] = E [u c(c t+1)r t]

Banks: Introduction Continuum of identical banks facing a 2-stage problem: Stage 1: Raise deposits and equity from households Stage 2: Invest in projects with a specific risk-return trade off Assumptions: 1. Equity (residual claimant) is more costly for banks than deposits 2. Bank managers/equity are protected by limited liability 3. Depositors cannot observe the risk choice made in Stage 2 Implications: Equity is more costly, but deposits entail an agency problem: The less equity the bank has, the higher the incentives for risk taking In equilibrium excessive risk choice is chosen The lower the real risk free rate, the higher is the risk chosen

Banks: Asset side and Objective function In the 2 nd stage banks choose asset riskiness, given the capital structure and the cost of deposits, to maximise equity s profits buys capital projects of type q t with a specific risk-return trade off the riskier the project, the higher the net return in case of success with probability q t, the project is successful: capital is produced in t + 1 and rented to firms; banks get paid the rental rate with probability 1 q t the project defaults: the bank/equity get while depositors get the deposit insurance Bank s objective function is: { [ ]} E t Λ t+1q t (ω 1 ω 2/2q t)r k,t+1 r d,t (1 k t) r e,t+1k t }{{}}{{} per-unit real revenue funding costs Note that, because of limited liability, banks are protected by the downside risk of their investment

The risk-taking channel Bank problem is solved backwards: 2. Choose q t, taking the deposit rate and capital structure as given by assumptions, depositors cannot contract on the choice of q t 1. Choose the optimal capital structure k t et (d t+e t), anticipating the risk choice made in Stage 2 In equilibrium, a lower risk-free rate makes banks increase leverage: Equity premium becomes relatively more important Substitute equity for deposits Internalise less the consequences of risk (limited liability) Choose a portfolio with higher risk (but a higher net return in case of repayment)

Steady state and dynamic implications of excessive risk taking Bank risk choice vs choice made under no banking frictions: Bank risk choice is excessive in the steady state inefficient capital production technology in the steady state bank economy is under-capitalized inefficiently low levels of output, consumption and welfare Risk taking gets more excessive as the real interest rate falls To compare dynamics, we define a benchmark model: risk choice and equity ratio are parameters set to the steady state values of the bank model corresponds to a standard New Keynesian model with a small markup in capital markets

The full macro model We embed the risk-taking channel in a medium-scale model similar to Smets and Wouters (AER 7): internal habits, investment adjustment costs and imperfect competition and wage stickiness in the labor market This serves two purposes: 1. perform a sound monetary policy evaluation through a quantitative model that can replicate key empirical moments of the data 2. assess whether our channel is quantitatively important compared to other monetary and real frictions

Estimation details The model is estimated with Bayesian techniques using 8 US series from 1984q1 to 27q3: federal funds rate, hours, inflation, and growth rates in real wage, per-capita real GDP, consumption and investment bank equity ratio (FDIC data) Three block of parameters: 1. a set of calibrated parameters 2. a set of standard parameters: priors as in Smets and Wouters (7) 3. a set of banking parameters: rewrite deposit insurance and investment efficiency as a function of the steady state equity ratio and default rate mean equity ratio of 11% and mean annual default rate of 4% recovery rate takes values [.3,.7] with 95% probability

Model responses to an expansionary monetary policy shock in the bank and benchmark models.3 Output.8 Inflation 1.15 Nominal interest rate.5 Real interest rate % deviation from SS.2.1 % points.75.7.65 % points 1.1 1.5 1.95 % points.4.3.1 5 1 15 2 5 1 15 2.9 5 1 15 2.2 5 1 15 2 99.2 Loan Safety 12.35 Equity ratio 1.5 return on investment 1 total assets % points 99 98.8 98.6 98.4 % points 12.3 12.25 12.2 12.15 % points 1 99.95 99.9 99.85 % deviation from SS.5 98.2 5 1 15 2 5 1 15 2 5 1 15 2.5 5 1 15 2 1 Investment.3 Consumption.2 Capital.3 Labor % deviation from SS.5 % deviation from SS.2.1 % deviation from SS.2.4 % deviation from SS.2.1.5 5 1 15 2.1 5 1 15 2.6 5 1 15 2.1 Benchmark model 5 1 15 2

Model responses to an expansionary monetary policy shock in the bank and benchmark models - 9% credible sets.3 Output.74 Inflation 1.15 Nominal interest rate.5 Real interest rate % deviation from SS.2.1 % points.72.7.68.66.64 % points 1.1 1.5 1.95 % points.45.4.35.3.25.1 5 1 15 2.62 5 1 15 2.9 5 1 15 2.2 5 1 15 2 99.2 Loan Safety 12.35 Equity ratio 1.5 return on investment 1 total assets % points 99 98.8 98.6 98.4 % points 12.3 12.25 12.2 12.15 % points 1 99.95 99.9 99.85 % deviation from SS.5 98.2 5 1 15 2 5 1 15 2 5 1 15 2.5 5 1 15 2 % deviation from SS 1.2 1.8.6.4.2 Investment % deviation from SS.25.2.15.1.5.5 Consumption % deviation from SS.2.2.4 Capital % deviation from SS.3.25.2.15.1.5 Labor Benchmark model.2 5 1 15 2.1 5 1 15 2.6 5 1 15 2.5 5 1 15 2

The effects of a monetary policy expansion An unexpected cut in the risk-free rate causes: standard effects: c, y, π risk-taking effects: Banks substitute equity for deposits, and choose a riskier investment less efficient capital production expected return on aggregate investment drops investment and consumption rise less then in the benchmark case and capital stock declines considerably A cut in the risk-free rate is less expansionary if the risk-taking channel is present, because it creates financial sector distortions

The risk-taking channel model - estimation Data favours the model with the risk-taking channel (seven-variable comparison) The inclusion of banking sector leverage identifies the key friction parameters We are matching the dynamics of loan risk taking 1.2.5 1.98 q model (left scale) loan safety data (right scale).5 1996 1998 2 22 24 26 28

Implications for monetary policy (1/2) Is the risk-taking channel quantitatively significant for monetary policy? Determine the optimal simple monetary policy rules in the bank and in the benchmark models: R t R = φ π ˆπ t + φ y ŷ t + ρ ( R t 1 R ) the hat denotes % deviations from the steady state Compute the welfare costs of implementing the optimal benchmark policy in the bank model expressed in % of the consumption stream, based on the 2 nd order approx. of household s welfare

Implications for monetary policy (2/2) benchmark model bank model rule ρ φ πt φ yt ρ φ πt φ yt Ω ρ = 7.2.11 3.11.12.5 ρ 7.21.12 1.1.1.89 Bank model: φ y and φ π are smaller and full smoothing is optimal optimal rule is close to a stable real interest rate rule reduce the volatility of the real interest rate reduce the volatility in banking sector risk and increase mean efficiency of the banking sector tradeoff between inflation and financial market volatility ( moments ) The costs Ω of applying in the bank model the rule that is optimal for the benchmark model are always significant The additional welfare gains of reacting to leverage are small

Differences in moments (in %) associated to different rules For example, under rule-type 1, risk is on average.12% lower and 44.55% less volatile if the optimal bank policy rule is applied Standard deviation rule q R r π y c φ k, ρ = -44.546-48.511 52.957 -.87-4.19 φ k = -69.41-78.915 66.99-7.44-9.775 ρ = -42.464-47.82 53.641 -.739-3.897 Mean rule q R r π y c φ k, ρ =.154.2 -.57.321.517 φ k =.219.7 -.81.44.79 ρ =.25.1 -.83.437.695

Conclusions Low risk-free rates lead banks to make riskier investments Excessive risk taking and inefficient capital production in SS Monetary policy expansion dampened by financial frictions Optimal monetary stabilizes the the real interest rate path accept more inflation volatility to reduce welfare detrimental fluctuations in risk taking Open questions (Trinity-related) Can macropudential policy do a better job? We analyse one aspect of risk different financial frictions imply different transmission mechanisms, and (possibly) different policy prescriptions which financial friction is most relevant for the data?

Literature review Theoretical contributions on banking sector risk Funding risk: Gertler, Kiyotaki and Queralto (JME, 212), Angeloni, Faia (JME, 213) Asset risk: Dell Ariccia, Laeven and Marquez (JET, 214) Empirical contributions on the asset risk-taking channel Loan level panel data: Jimenez et al. (ECMTA, 214), Ioannidou et al. (Rev Financ, 214) Aggregate time series data: Buch et al. (JEDC, 214) Back to main

Data symbol series mnemonic unit source Y greal gross domestic product gdpc96 bn. usd fred / bea P gdp deflator gdpdef index fred / bea R effective federal funds rate fedfunds % fred C personal consumption expenditure pcec bn. usd fred / bea I fixed private investment fpi bn. usd fred / bea H 1 civilian employment ce16ov thousands fred / bls H 2 nonfarm business (..) hours index prs85623 dpt of labor W 1 nonfarm business (..) hourly compensation index prs85613 dpt of labor N civilian population ce16ov lns1 bls q average weighted loan risk % board of gov. E equity capital over liabilities % fdic Equity capital is defined as equity plus reserves plus subordinated debt, while total liabilities are equity plus deposits. Back

Loan demand: Capital producers Continuum of capital producers (competitive): Use loans to purchase capital projects o t o t is used to produced capital in the next period, leased to firms Each produce has access to a continuum of technologies q t [, 1]: {( ) ω1 ω 2 2 K t+1 = qt ot with probablity q t θo t else The safer the technology, the lower the output in case of success. The bank orders the capital projects with a given technology q t. Since we are working with a continuum of representative agents, we can derive the law of motion of capital as: ( K t+1 = q t ω 1 ω ) 2 2 q t o t + (1 q t )s t θ t. Back to main