Banks balance sheets, uncertainty and macroeconomy

Transcription

1 Banks balance sheets, uncertainty and macroeconomy Ekaterina Pirozhkova Birkbeck College, University of London Recent Developments in Money, Macroeconomics and Finance University of Portsmouth 3rd April 217 Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

2 Motivation Weak bank credit growth Year over year real quarterly growth. Source: BIS. Creditless recoveries are typically slower than those with robust credit growth: Claessens, Kose and Terrones (212), Abiad, Dell Ariccia and Li (211). Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

3 Uncertainty Heightened uncertainty as one of the key factors of the Great Recession: Stock and Watson (212): decline in output and employment in the Great Recession was mainly due to financial and uncertainty shocks. Christiano et al. (214): The full magnitude of the GDP drop in the recession can be accounted for by the risk shock. Caldara et al. (216):... uncertainty shocks have an especially negative economic impact in situations where they elicit a concomitant tightening of financial conditions. Evidence suggests that the Great Recession was likely an acute manifestation of the toxic interaction between uncertainty and financial shocks. Balke and Zeng (213):... the financial crisis appeas to be largely due to a decline in the financial intermediation. This decline in financial intermediation seems to have originated from output and uncertainty shocks, rather than shocks to financial intermediation itself. Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

4 This paper The question: I find: What is the impact of heightened uncertainty on allocation of assets in banks portfolios? Empirical evidence: commercial banks reduce loans issuance and increase the stock of safe assets in face of heightened uncertainty. DSGE model with portfolio-optimizing banking sector: expected profitability of banks helps to explain the endogenous movements of risk premium. Precautionary motive induces banks to reallocate portfolios of assets. Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

5 Outline Motivation Empirical evidence The model: Banking sector Optimal debt contract Uncertainty Results Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

6 Empirical evidence SVAR model estimated on US quarterly data 1985Q1-215Q3. Measures of uncertainty (Bachmann et al (213), Bloom (29), Baker et al. (216)): Forecasters disagreement about future inflation - a benchmark measure News-based economic policy uncertainty index Economic policy uncertainty index VIX/VXO index Bank assets components analyzed (volumes and shares of the portfolio of assets): business loans (C&I loans) safe assets: cash and Treasury and agency securities Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

7 Empirical evidence Identification: Cholesky ordering an uncertainty measure real GDP GDP deflator leverage of the corporate sector banks capital ratio a bank assets component: business loans or safe assets charge-off rate of issued loans Federal Funds rate 9% bias-corrected bootstrap confidence bands calculated an in Kilian (1998) AIC for lag order selection Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

8 Empirical evidence: IRFs C&I loans Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

9 Empirical evidence: IRFs Safe assets Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

10 Empirical evidence Robustness checks: alternative measures of uncertainty alternative ordering: uncertainty placed last period without the financial crisis: 1985Q1-27Q4 the share of business loans and safe assets in total assets portfolio Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

11 Uncertainty and credit market: existing models Christiano et al. (214): estimated DSGE model with financial accelerator a la Bernanke et al. (1999) and idiosyncratic uncertainty. Gilchrist et al. (214): DSGE model with capital adjustment frictions associated with irreversibility and frictions in debt and equity markets: fluctuations in uncertainty affect economy mainly through financial distortions. Arellano et al. (21): DSGE model with financial frictions manifested as labour wedges and the fixed cost for firms to enter: uncertainty shocks tighten credit constraints, so factor inputs and output fall. Benes and Kumhof (215): DSGE with financial accelerator as in Bernanke et al. (1999) and bank capital adequacy requirements. Bonciano and van Roye (215): stickiness of retail interest rates of banks amplify the effect of macro uncertainty on economy. Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

12 The model: banking sector Balance sheet constraint Expected profit D t = B t + L t E t (Π t+1 ) = E t [(1 F ( ω t+1 ))R L t L t + R G t B t R D t D t + (1 µ)v d t+1] (1 F ( ω t+1 )) - the share of non-defaulted firms RtL l t - loans repayment Rt g B t - return on govertment bonds Rt d D t - bank s payment for households deposits (1 µ)vt+1 d - the value of assets of defaulted firms took over by the bank after paying monitoring costs µ E t (Π t+1 ) = E t [L t ((1 F ( ω t+1 ))R L t R G t ) + (1 µ)v d t+1] Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

13 The model: banking sector Assume bank preferences are concave Parkin (197), Pyle (1971), Hart and Jaffee (1974), Koehn and Santomero (198), Ross (1973) Aksoy and Basso (214): the role of Value-at-Risk constraint Empirical evidence on bank managers risk-aversion: Panousi and Papanikolaou (212), Hughes and Mester (1998), Flannery (1989). Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

14 The model: banking sector Decision problem: max E t α t S t,t+s+1 u(π t+s+1 ) s= α t = Lt D t - the share of portfolio invested in entrepreneurial loans S t,t+1 - households stochastic discount factor Utility function featurs risk-prudence as defined by Kimball (199): u ( ) >, u ( ) < and u ( ) >. CRRA utility: u(π t ) = (Π t) 1 κ 1 κ Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

15 The model: banking sector First order conditions Risk-averse banks: Risk-neutral banks: Rt L,RA E t [Π κ t+1 (1 F ( ω t+1))] = Rt G E t [Π κ t+1 ] Rt L,RN E t [(1 F ( ω t+1 ))] = Rt G Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

16 The model: banking sector Risk-averse banks: R L,RA t Risk-neutral banks: [ Cov(Π κ t+1, (1 F( ω t+1))) Cov(Π κ t+1, (1 F( ω t+1))) <, so Under the same F ( ω t+1 ) and r G t E t [Π κ t+1 ] + E t [(1 F ( ω t+1 ))]] = R G t. Rt L,RN E t [(1 F ( ω t+1 ))] = Rt G R L,RA t > R L,RN t Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

17 The model: banking sector Risk premium charged by risk-averse banks: RP RA t = 1 Cov(Π κ t+1,(1 F( ω t+1))) E t[π κ E t+1 ] t [(1 F ( ω t+1 ))] Cov(Π κ t+1,(1 F( ω t+1))) + E E t[π κ t+1 ] t [(1 F ( ω t+1 ))] Risk premium charged by risk-neutral banks: RP RN t = 1 E t[(1 F ( ω t+1 ))] E t [(1 F ( ω t+1 ))] R G t R G t RPt RA RPt RA and RPt RN are increasing in E t [F ( ω t+1 )] is decreasing in E t [Π t+1 ] - the effect of precautionary mechanism Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

18 The model: optimal debt contract Q t K t+1 = L t + NW t Ex-post gross return on capital for firm j: ω j t+1 Rk t+1 ω j t+1 - idiosyncratic disturbance to firm s j return. ωj is i.i.d. across entrepreneurs and time, F (ω) is a continuous cdf over non-negative support E(ω j ) = 1 with P[ω x] = F (x). R k t+1 - the ex-post aggregate return on capital ω is as a cutoff value of idiosyncratic shock such that entrepreneurs: ω t+1 R k t+1q t K t+1 = R L t L t. Firms with ω j ω pay back their loans, receive ω j R k t+1 Q tk j t+1 RL t L t. Firms with draws ω j < ω default and receive nothing, bank gets (1 µ)ω j R k t+1 Q tk j t+1. Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

19 The model: optimal debt contract Constant returns to scale: ω specifies, how R k t+1 Q tk t+1 is divided: Share going to bank: Γ( ω) µξ( ω) = ω Share going to entrepreneurs: ωf (ω)dω + ω ω 1 Γ( ω) = 1 ( ωf (ω)dω + ω ω ω f (ω)dω µ ωf (ω)dω ω f (ω)dω) Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

20 The model: optimal debt contract Original Bernanke et al. (1999) formulation: max E t [(1 Γ( ω t+1 ))Rt+1Q k t K t+1 ] K t+1, ω t+1 subject to zero profit condition of banks: ωt+1 [(1 F ( ω t+1 ))]Rt+1L L t+1 + (1 µ) ωdf (ω)rt+1q k t K t+1 = R t+1 L t+1 Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

21 The model: optimal debt contract Modification: debt contracts are non-contingent on future aggregate outcomes (also in Benes and Kumhof (215) and in Lewis and Roth (215)): max K t+1, ω t+1 E t [(1 Γ( ω t+1 ))R k t+1q t K t+1 ] subject to incentive compatibility constraint of banks: ωt+1 E t [[(1 F ( ω t+1 ))]Rt L L t + (1 µ) ωdf (ω)rt+1q k t K t+1 ] = Rt e L t, where R e t is the net return for each dollar of loans originated Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

22 The model: Idiosyncratic uncertainty log(ω) N(M, (σ F ) 2 ), and drawing from Christiano et al. (214) and Dorofeenko et al. (28): log( σf t σ F ) = ρ σ log( σf t 1 σ F ) + σσ ɛ σf t. A positive shock to σt F higher ω higher rate of entrepreneurial defaults E t (F ( ω t+1 )) lower E t [Π t+1 ] higher E t [Π κ t+1 ] higher RPRN, even higher RP RA. Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

23 The model: calibration Based on Christensen and Dib (28), Christiano et al. (214), Poterba (1998). Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

24 The model: Solution method Third-order approximation Perturbation method Pruning procedure to deal with the problem of explosive behaviour of simulated data with high-order perturbations (Kim et al. (28)) IRFs are computed as percent deviations from ergodic mean of the distributions: Fernandez-Villaverde et al. (211), Born and Pfeifer (211) Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

25 Results: IRFs - idiosyncratic uncertainty shock Total Output, % Price of capital, % Investment, % Net worth, % Consumption, % 1 2 Loans to firms, % Risk free rate, annual % LendRate, annual % Defaults, % LoanShare, % RisklessShare, % Leverage, % Risk averse banks Risk neutral banks Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

26 The impact of uncertainty Banks precautionary motive: higher dispersion of productivity of firms extreme values of expected profitability are more probable motive to self-insure against profitability reduction risk premium today increases the share of safe assets in portfolio goes up, the share of risky loans goes down Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

27 Conclusion Empirical result: heightened uncertainty induces banks to reallocate their portfolios of assets. In a DSGE setting with the financial accelerator mechanism, where lenders are risk-averse and choose their balance sheets volumes before observing shock values, heightened idiosyncratic uncertainty leads to: widening of credit spread lowering of the volume of bank credit Precautionary motive of banks following uncertainty shock helps to explain the additional share of the risky lending reduction and business cycle movements. Financial accelerator mechanism amplifies the reallocation effect of uncertainty shock. Our result of banks portfolio reallocation is in line with a key postulate of the modern portfolio theory, which is obtained under different assumptions. Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3

28 Thank you Banks balance sheets, uncertainty and macroeconomy MMF PhD 3rd April, / 3