AEA Continuing Education Program. DSGE Models and the Role of Finance. Thomas Philippon, New York University

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1 AEA Continuing Education Program DSGE Models and the Role of Finance Thomas Philippon, New York University January 7-9, 2018

2 Finance in Macro Models Thomas Philippon NYU, NBER, CEPR January 2018, AEA Continuing Education, Philadelphia

3 Does finance matter? Not much? Where enterprise leads finance follows." Joan Robinson (1952) Alot?..that financial markets contribute to economic growth is a proposition too obvious for serious discussion. Merton Miller (1988)

4 Some (Contradictory) Views about Finance Financial Regulation - Deregulation was responsible for the crisis; regulations should be tightened - Finance is over-regulated and credit supply is impaired Finance and Growth - Financial development is important for growth - The last useful financial innovation was the ATM Finance and Inequality - Lack of access to finance creates poverty traps - Finance increases income inequality Fin-tech and Bitcoins

5 Financial Contracts Fundamentals of Financial Contracting

6 Three Financial Frictions Debt overhang, Myers (1977) Monitoring & Moral hazard Screening & Adverse Selection

7 Basic Setup Risk neutral investors, two periods t = 0, 1, limited liability Legacy assets & liabilities - liquidity m, assetsa with p Pr ( a = A H),(longterm)debtD New Investment - Invest k to generate additional v = V with prob. q, otherwise v = 0 Total income at t = 1 y = a + v Borrowing b to close funding gap b = k m

8 Debt Overhang Total Senior Debt Equity p 1-p A H D A H -D A L A L 0 Key Friction: Difficult to Renegotiate Senior Debt Free riding among dispersed creditors Risk of runs

9 How New Projects Are Evaluated Total Senior Debt Junior Debt Equity -k p 1-p A H + v H D Rk A H -D+ v H -Rk A L + v L A L + v L 0 0 New lenders break even R=1/p Shareholder Value: v H -Rk 1. Risk shifting: v L irrelevant 2. Underinvestment: R>1

10 Underinvestment in Safe Projects Total Senior Debt Junior Debt Equity -k p 1-p A H + v D k/p A H -D+ v-k/p A L + v A L + v 0 0 Myers (1977) Philippon-Schnabl (2009): (p,v) unknown to government Philippon (2010): bailouts in open economy

11 v Philippon-Schnabl (2009) V Debt Overhang Invest x 0 1 p

12 Risk Shifting -k p 1-p Total Senior Debt Junior Debt Equity A H +v D k/p A H -D+ v-k/p A L -v A L -v 0 0 NPV = (2p-1)v-k can be negative, e.g. when p<0.5 But if v>k/p, shareholders like the project

13 Reluctance to Sell Assets Total Senior Debt Equity -m p 1-p (1-z)A H +m D (1-z)A H -D+m (1-z)A L +m (1-z)A L +m 0 Buyers: m=ze[a] Equity: A H -D -z(1-p)(a H -A L ) Papers Philippon-Schnabl (2009) Landier-Ueda (2009) Diamond-Rajan (2010)

14 Moral Hazard: Endogenous q Ignore existing assets and liabilities (a = D = 0): q is q H,or q L with private benefit ψ. Incentiveconstraintwithy e payment to entrepreneur y e > y e min ψ q H q L Therefore pledgeable income is q H (V ymin e ( ) ) Financing constraint is q H V ψ > k m and q H q L investment condition is ( m > ˆm k q H V ψ ) q H q L - Existing assets can be used as collateral to increase pledgeable income

15 Adverse Selection Quality of existing assets privately known: bad types a = A b, good types a = A g - Good types safe, bad types risky A b < D < A g k q Issuance game & security design - Myers and Majluf (1984), Nachman and Noe (1994) Pooling rate given perceived quality z (fraction of good types) r (z)= Good types refuses to invest if 1 q + z (1 q) rk > qv

16 Time 1: Credit Market 1 q Rate r qv k Limit Rate For Strong Types Pooling Rate 1 0 z I 1 Perceived Quality z

17 Time 1: Credit Market Equilibrium 1 q Equilibrium Rate Rate r qv k Limit Rate For Strong Types 1 0 z I 1 Perceived Quality z

18 Taking Stock Debt overhang: legacy debt can limit/distort investment Moral Hazard & Adverse Selection: inside liquidity is important - Role for intermediation: monitoring (lower private benefit ψ) and screening (acquire information about types) Collateralized borrowing: pledging existing assets to fund new investment - financial sophistication determines what can be collateralized (e.g., patents in the US) - adverse selection can limit pledgeability of existing assets How much are agents willing to pay for intermediation?

19 Intermediation Measuring Financial Intermediation Philippon (2015)

20 Price and Quantity of Financial Intermediation Price u = r + ψ - User cost of borrowers, expected return of savers - Unit cost of intermediation: ψ Quantity - Household finance b c - Corporate finance b k, e k - Liquidity services m

21 Traditional Banking

22 Modern Finance

23 Income Share of Finance Industry year VA fire, Hist. WN fin, NIPA WN fire, Hist. VA fin, NIPA

24 Outstanding Credit / GDP year Farm, Hist Household, Hist Nonfarm Business, Hist Farm, FoF Household, FoF Nonfarm Business, FoF

25 Neoclassical Growth with Intermediation Households consumption and liquidity services: u (c t,m t ),life cycle borrowing/lending Costs of intermediation services - ψ m for liquid assets, ψ c for households credit, ψ k for firm credit Non financial businesses - user cost k α = Financial intermediation income 1 α r + δ + ψ k, y f t = ψ c b c,t + ψ m m t + ψ k k t,

26 Aggregation Assumption: Constant Relative Costs: ψ i,t = µ i ψ t, with the normalization µ c = 1. Quantity of assets q t b c,t + µ m m t + µ k k t, Estimate the µ s with micro data on rates, returns and issuance costs

27 Intermediated Assets & Services year Business Credit & Equity Liquidity Services Household Credit M&As

28 Financial Intermediation (in the U.S.) Share of GDP Intermediated Assets/GDP year... Share of GDP Intermediated Assets/GDP Source: Philippon (AER, 2015)

29 Unit Cost in the U.S. Raw Unit Costs time 2012 Data New Data Source: Philippon (AER, 2015)

30 Unit Costs, Global Comparison Source: Bazot (2013)

31 Constant Returns to Scale

32 Notes: Series normalized to one in 1950 Evidence of Constant Returns to Scale year Unit Cost Real Assets Real GDP PC

33 Quality Adjustments with Heterogenous Borrowers

34 Corporate Finance Heterogenous inside equity (retained earnings) x. Monitoring µ to prevent cash flow diversion. - IC constraint, etc. Aggregate monitoring where s k l k l +k h µ t = µ h +(1 + r)(x h x l )s t, Income from corporate finance intermediation y f k,t = ϕ tk t + ζ t µ t. where ϕ is an asset management fee

35 Household Finance Heterogenous labor endowment η F (.) Credit: marginal cost ϕ, fixedcostκw - Participation for η > ˆη - Household debt market b c w = 1 (( λ (1 ϕ) 1) ) η κ df (η) 2 + r η>ˆη - Income y f c,t = ϕ b c,t + κ t w (1 F (ˆη t )).

36 Calibration Rate Deprec. Growth Labor Sh. CRRA r = 0.05 δ = 0.1 γ = 0.02 α = 0.7 ρ = 1 High cash Low cash Asset Mgt Fee x h = 0.62 x l = 0.1 ϕ = 0.01

37 Calibration Moments B Cost share HH D Frac Top 20 Liquid b k /y ϕ + ζ µ k b k s b c /y 1 F (ˆη)... m/y y f /y data model Implied Parameters Monit Firms Slope Ineq. Fix Liq D Liq S ζ = r 3.3 k h k = λ = 2.07 H = κ = ν = ψ m = 0.019

38 Calibrated Model A. CORP. FINANCE INCOME SHARE B. CORPORATE DEBT / GDP C. CORPORATE ADJUSTMENT Share of Low Cash Firms D. PARTICIPATION E. HOUSEHOLD DEBT / GDP F. HH ADJUST. FACTOR Fixed Cost Index

39 Quality-Adjusted Quantity of Intermediation year Assets Firm Adj. Firm & HH. Adj.

40 Adjusted Unit Cost year Raw Firm Adj. Firm & HH Adj.

41 Dynamics Macro-Finance Dynamics

42 Asset Pricing, Cochrane (2017) Equity premium 6% - Just as likely to be 1% (in good times) or 11% (in bad times) Pricing kernel Λ t+1 = β ( Ct+1 C t ) γ Ξ t+1 - Aggregate consumption growth not volatile enough, γ = 25 is just silly. Ξ t+1 needed. Cochrane (2017) reviews 10 models, including: Habits, LR risk with EZ preferences, disasters, ambiguity aversion, behavioral biases

43 Epstein-Zin Recursive Utility An important class of recursive utility function uses a CES aggregator (ε) where risk aversion is γ ( [ U t = (1 β)c 1 ε + β (E t This leads to a pricing kernel Λ t+1 = β ( Ct+1 C t ) ε [ (E t U 1 γ t+1 U t+1 U 1 γ t+1 ]) 1 ε 1 γ ]) 1 1 γ ) 1 1 ε ε γ - Typical calibration of long run risk model à la Bansal and Yaron (2002) has ε close to 1 and γ > 1 - Household worried not only about bad news to consumption but also to future utility - See also Cochrane s discussion of disaster risk

44 Friction-less Benchmark: Q-Theory Firm value Capital accumulation V t = E t [ j=0 Dividends & Adjustment Costs Λ t,t+j Π t+j ] K t+1 =(1 δ t )K t + I t Π t = R k,t K t P k,t I t ϕ ( ) 2 k 2 P It k,tk t δ t K t

45 Recursive Define V t V t K t Friction-less Benchmark: Q-Theory V t (K t )=max I t Π t + E t [Λ t+1 V t+1 (K t+1 )] and net investment x t I t K t δ: V t = maxr k,t P k,t (x t + δ t ) ϕ k x 2 P k,tx 2 +(1 + x t )E t [Λ t+1 V t+1 ] FOC P k,t (1 + ϕ k x t )=E t [Λ t+1 V t+1 ] can be written as x t = 1 ϕ k ( Q k t 1 ) where Q k t E t [Λ t+1 V t+1 ] P k t = E t [Λ t+1 V t+1 ] P k t K t+1

46 Tobin s q and Investment I/K Q I/K Usual Q

47 Q-Theory: Bonds vs Stocks, Philippon (2009) Let e t = E t[λ t+1 Vt+1] e Pt k K t+1 and b t = E t[λ t+1 Vt+1] b Pt k K t+1 q t = e t + b t for equity and bonds Suppose you observe b t :canyoure-constructq t?leland (1994) and Leland (1998): debt with coupon c and average maturity 1/φ. Oneunitofprincipalatt repays t + 1 t τ... c + φ (1 φ)(c + φ)... (1 φ) τ t 1 (c + φ)... Risk neutral debt pricing, with book leverage l, in state ω: b (ω)= r (ω) E π [ min { (c + φ)l +(1 φ)b ( ω ) ;V ( ω )} ω ]

48 Bond q and Investment, Philippon (2009)

49 Bond q and Investment, Philippon (2009) I/K Bond Q I/K Bond Q

50 Models with Financial Frictions Financial Accelerator - Financial frictions can amplify and propagate macroeconomic shocks First generation: Backward loop, Bernanke and Gertler (1989); Bernanke et al. (1999) - Based on simple moral hazard model: dynamics of cash on hand - Bad shock: m t = K t+1 = m t+1 Second generation: Forward loop, Kiyotaki and Moore (1997) - Collateralized borrowing by specialists B t θ t Q t K t+1 - Second best use of capital and fire sales: if constraint binds, K needs to be operated by non-specialists, and Q goes down - Bad shock: Q t = K t+1 = Q t+1 - But Q is forward looking Q t = E t [Q t+1 ]

51 Intermediary-Driven Crisis The crisis centered around financial intermediaries

52 Intermediary-Driven Crisis

53 Intermediary-Driven Crisis New models focused on financial intermediaries, such as He and Krishnamurthy (2012) and Gertler and Kiyotaki (2013). - Banker with survival probability σ maximizes V t = E t [Λ t+1 ((1 σ)n t+1 + σv t+1 )] subject to budget constraint Q t k t = d t + n t and incentive/collateral constraint θq t k t V t Promised rate on deposits is R t so n t =(Z t + Q t )k t 1 R t d t 1

54 Discussion What we get from Gertler and Kiyotaki (2013) - value function is linear in net worth V t = ν t n t,soaggregation is straightforward - key choice for intermediary is leverage Q t k t n t - recessions driven by liquidity and intermediation risk Notes - What is missing from Fig 1 in GG? - What is the link between Ξ, timevaryingriskaversion,andthe Gilchrist-Zakrajsek EBP (excess bond premium)?

55 APrototypicalCrisisModel The basic elements of a modern financial crisis model are: - Output depends on asset price - Asset price is forward looking Y = Y (Q) Y Q = E[Z + Q ] R k - Risk spread increases with intermediary distress - Monetary policy is constrained s = R k r r 0

56 Intermediary-Driven Crisis

57 Household Finance Most macro finance of the 1990 s models had representative agent. Action was on firm side Household balance sheet were important in the crisis. Two classes of models - Two agents with different β Eggertsson and Krugman (2012) - Bewley-style models Kaplan and Violante (2011)

58 Greece Greece: A Macro-Financial Tragedy

59 Three Financial Frictions In 2007, Greek GDP per capita was around 22,600 euros and the unemployment rate was 8.4%. In 2014, Greek GDP per capita was around 17,000 euros and the unemployment rate was 26.6% What happened?

60 Benchmarking: the Comparison Group Sudden Stops - Combination of capital flow reversal & large drop in domestic output - Extend Calvo et al (2006), Korinek & Mendoza (2013) - 49 sudden stops Sovereign Defaults - from Gourinchas & Obstfeld (2012) based on literature - default on domestic or external debt - 65 default episodes Lending booms/busts - defined as in Gourinchas et al (2001) - deviation of credit/output from trend boom/busts

61 The Incidence of Crises Sudden Stop Defaults Credit Booms Trifecta # AE 13 Greece 18 Greece 22 EM Total

62 Benchmarking 1: GDP Relative to All Sudden Stops Collapse of 25%

63 Benchmarking 1: Aggregate Domestic Investment/Output Collapse of 50%

64 Benchmarking 2: Other Crises

65 Sovereign Default? Credit Bust?... Trifecta

66 Benchmarking 3: Compared to EM Floaters & Peggers

67 Benchmarking 4: Endogenous Peg?

68 Empirical Lessons 1. Greek crisis significantly more severe persistent and backloaded than typical sudden stop 2. Greek crisis significantly more severe persistent and backloaded than Trifecta episodes 3. Greek crisis more severe than for peggers (even Estonia or Latvia) 4. Collapse in aggregate investment unprecedented in its persistence and magnitude

69 Model Small Open Economy in a currency union (r,π F exogenous) Standard NK DSGE à la Galì (2011) with financial frictions - Government (B g,t,g,r g ) - Banks (V,r d ) - Households (B h,c,r h ) - Firms (I,K,r k ) Various shocks ζ # t = ρ # ζ # t 1 + σ # ε # t

70 Budget constraint Government Bt g Rt g + τ t Y t = G t + T t + B g t 1 Π H t Fiscal rule (spending and social transfers) Tax rate g t = F l g t 1 F n n t F r r g t F b b g t + ζ spend t Government funding cost τ t = τ + ζ tax t rt g = r t + dt g dt g = d B g g Y [ ] (bt g E t [y t+1 ] E t πt+1 h ) + ζt dg

71 Households ( ( ) U i C = E 0 βi t i 1 γ ( ) t N i 1+φ ) t t=0 1 γ 1 + ϕ ; C i t [ (1 ϖ) 1 ε h C i ε h 1 ε h H,t + ϖ 1 ε h C i ε h 1 ε h F,t ] ε h ε h 1 Borrowers, massχ, B h t B h t, P t C b t =(1 τ t)w t Nt b + P H,tBt h Rt h dt p = d y y t + d b bt h + ζt def b t h = ψ bh b t 1 h ξ bh rt d + ζ t bh ( 1 dt p ) PH,t 1 Bt 1 h + P H,tTt b Savers, β > β b (mass 1 χ), P t C s t =(1 τ t )W t N s t + R t P H,t 1 S t 1 P H,t S t + P H,t T s t

72 Non-Financial Firms Capital-producing firms: - Qtheory Goods-producing firms: - Convert capital and labor into goods. - Cobb-Douglas with constant TFP. - Financing friction: pay part of wage bill in advance. Intra-period loan with funding cost r k.

73 Price and Wage Rigidity Wage-calvo process yields a Phillips curve for wages π w t = βe t π w t+1 λ w (w t γc t ϕn t )+ζ w t Price-calvo process yields a Phillips curve for domestic prices ζ w t π h t = βe t π h t+1 + λ p mc t + ζ πh t, where mc t is log real marginal cost in terms of domestic goods. :wagemarkupshock,ζ πh t :domesticpricemarkupshock

74 Banks Domestic deposits and foreign loans Lend to households, firms and government Subject to capital requirement ( B k V t κ t Rt k where V t is franchise value. + B t h ) Rt h No capital requirement for sovereign exposure Bank funding costs r d t = r t + ζ rd t + ξ d [ LE t d p ] t+1

75 Key equations Summary of Funding Costs - Funding cost: banks > households & firms r k t = r d t - Banks: sudden stop and capital loss - Government r d t = r t + ζ rd t + ξ d [ LE t d p ] t+1 d p t = d y y t + d b b t 1 + ζ def t - Households rt g = r t + dt g dt g = B d g g Y [ ] (bt g E t [y t+1 ] E t π h t+1 rt h = r t d + E [ t d p ] t+1 ) + ζt dg

76 Doom Loops No direct doom loop, but indirect GE feedback loops: Sovereign risk shock ζ dg t : - Government funding costs increase Government raises taxes and reduces expenditure Output declines Expected costs of default on private-sector loans increase Funding costs for private sector increase and investment drops. Sudden stop ζ rd t : - Funding costs for private sector increase Output and investment drop Fiscal revenues drop Expected costs of default on sovereign loans increase Government funding costs increase.

77 Impulse Response: Sovereign Risk Shock Sov Risk 0.05 Output 0.1 Consumption Saver 0.1 Investment 0.05 Employment 0.05 Borrower Funding Cost rk 0.05 Sovereign Yield 0.2 NPL/Total Loans 0.01 Inflation 1 zrd Govt Finance 0.1 Govt Debt 0.01 Household Debt 0.01 Current Account/GDP Rev. Spend Years Years Years Years

78 Impulse Response: Sudden Stop Sudden Stop 0.1 Output 0.1 Consumption Saver 0.5 Investment 0.1 Employment Borrower Funding Cost 0.01 Sovereign Yield 0.5 NPL/Total Loans 0.01 Inflation rk 0.01 zrd Govt Finance 0.04 Govt Debt 0 Household Debt 0.02 Current Account/GDP Rev Spend Years Years Years Years

79 Bayesian Estimation of the Model Standard techniques (Herbst & Schorfheide (2015)) Period: 1999 to 2015 Calibrate steady state parameters Estimate dynamic parameters Observable Description Shock Shock Description G t + T t Government spending ζt spend τ t Y t Government revenues ζt tax Rt g Greek government spread over EZ average ζt dg Govt. spending shock Tax rate shock Sovereign risk shock Rt k SME spread over EZ average ζt r Funding cost shock exp ( dt p ) Non-performing loans/total loans, def = npl ζ def Private default shock Π t Greece CPI - EZ CPI ζ πh PPI cost push shock B h t Household debt ζ bh t Household credit shock Π w t Greek Wage Inflation - EZ Wage Inflation ζ w Wage inflation shock Table: Observables and Shocks

80 Calibrated Parameters-I Parameter Description Value β Discount Factor 0.97 α Capital Share 1/3 ε h Elasticity between H and F 1 ε f Elasticity between exports 1 ϕ Inverse labor supply elasticity 1 γ Risk Aversion 1 ϑ Price Stickiness 0.5 ε Elasticity of Substitution Goods 6 ϑ w Wage Stickiness 0.5 ε w Elasticity of Substitution Labor 6 ε r Elasticity of R to NFA ϕ k Adjustment Cost 1 δ Depreciation 0.07 FC Fixed cost of production, 10% of Y

81 Calibrated Parameters-II Parameter Description Value ϖ Openness (Martin and Philippon (2014)) 0.3 χ Fraction of Impatient (Martin and Philippon (2014)) 0.65 Annual lending spread of 2% 1.02 B h Y Household debt to GDP of 50% 0.5 B g Y G Y Government debt to GDP of 120% 1.2 Government consumption to GDP of 20% 0.2 T Y Public social expenditure to GDP of 20% 0.2 d h Steady state default rate for Households 5.4% d k Steady state default rate for Corporates 5.4% B k Y Corporate debt to GDP of 50% 0.5 ψ sk Working Capital Constraint 1 τ Tax rate, budget balance in SS L Leverage scaling 1

82 Calibrated Parameters-III Parameter Description Value F b Elasticity of govt. spending to public debt 0.05 F n Elasticity of govt. spending to employment F r Elasticity of govt. spending to the int. rate 0.5 F l Persistence of govt. spending 0.75

83 Data Inputs Govt. Revenue Govt. Spending Govt. Yield Private Funding Cost NPL/Total Loans (Obs.) 1 dlog GDP Deflator (Obs.) Household Debt Wage Inflation (Obs.)

84 Output Fit of the Model Investment PPI Inflation Data Model Wage Inflation Data Model Current Account/GDP

85 Decomposition of Output and Investment GDP Spending Tax Credit Demand Sudden Stop Priv. Def. Sov. Risk Markup Wage Markup Investment Years Years

86 Decomposition of Sovereign Debt Govt. Debt Spending Tax Credit Demand Sudden Stop Priv. Def. Sov. Risk Markup Wage Markup

87 Decomposition of Private Default Private Default Spending Tax Credit Demand Sudden Stop Priv. Def. Sov. Risk Markup Wage Markup

88 0.4 Decomposition of Government Spending Govt. Spending Spending Tax Credit Demand Sudden Stop Priv. Def. Sov. Risk Markup Wage Markup

89 Key Lessons Fiscal trajectory prior to 2009 unsustainable. Stimulates output initially, but depresses it later on. First phase of the crisis ( ) - Sovereign risk - Sudden stop Second phase of the crisis ( ) - Non-performing loans - Price markups.

90 4CounterfactualExercises 1. Low leverage (EME leverage) 2. Banking union 3. Fiscal discipline 4. Price flexibility (Latvia)

91 Counterfactual I: EME Leverage Greece Typical EME Min Max Credit / GDP Sovereign Debt / GDP Current Account /GDP Table: Leverage and Imbalances Before Sudden Stop Notes: Average from t-6 to t-2 where t is sudden stop.

92 Counterfactual I: EME Leverage GDP Investment Data CFact Model Current Account/GDP 0.3 Govt. Spending

93 Counterfactual II: Banking Union GDP Investment Data CFact Model Current Account/GDP 0.3 Govt. Spending

94 Counterfactual III: No Discretionary Spending GDP Investment Data CFact Model Current Account/GDP 0.3 Govt. Spending

95 Counterfactual V: Low Price Stickiness GDP Investment Data CFact Model Current Account/GDP 0.3 Govt. Spending

96 Greece, Conclusion: What Would Have Helped? What we can say - Exposure Y+10%, I+15% - Banking union Y+10%, I+30% - Sound fiscal Y+15%, I+20% - More flexible prices Y+15%, I+20% Open issues - Uncertainty (political, EZ risk)? - Early sovereign default? - Devaluation?

97 Regulation Systemic Risk

98 Systemic Risk (with Acharya, Pedersen, and Richardson) Need to avoid two pitfalls - Too narrow: only leveraged, short-term wholesale-funded banks are systemic - Too broad: Everything is systemic Not much consensus beyond banking - Are insurance companies systemic? - Asset managers? Regulatory approach - Size + Interconnectedness + Substitutability Our initial approach (2010) - Systemic risk when aggregate capital shortfall - Tax/regulate contribution to shortfall > SES

99 Basic Model of Systemic Risk J financial firms, i = 1,..J, twodatest = 0,1, normalize r f = 0 Time 0 a i = w i,0 + b i Time 1, random gross return q Debt priced fairly w i = q i a i d i b i = E[min(q i a i,d i )].

100 Basic Model of Systemic Risk Firm i s problem U i = max d i, q i E[max(q i a i d i ;0) w i,0 τ i ] Regulator cares about aggregate externality: s.t. max {τ i } i J i=1 U i + E E ee[1 W κa (κa W )].

101 Reduced Form Externality

102 Optimal Pigouvian tax Proposition In the simple model with exogenous externality, the efficient outcome is obtained by a tax τ i = e Pr(W < κa) MES i + τ 0 where the systemic expected shortfall is defined by MES i E[κa i w i W < κa] Look for MES at

103 BAC MES

104 MES & SCAP

105 Measuring Leverage Not Easy

106 Liquidity & Maturity Source: Hanson, Shleifer, Stein, Vishny, 2014

107 Bank Capital Regulations? identify four constraints on bank equity $equityper$1ofasset - Risk based capital (RBC): k RBC w i,capitalrequirement* risk weight - Supplementary leverage ratio (SLR): k SLR - Post stress RBC: k RBC,STRESS w i + NLR i,rbc+netloss rate - Post stress SLR: k SLR,STRESS w i + NLR i - GS more likely to be bound by SLR, while WF bound by RBC

108 Required Capital Ratios

109 Distance from Requirements?

110 Estimated Capital Charges Compute capital charge for bank j under j s most binding constraint?

111 Banks vs Non-Banks Agreement that banks (and shadow banks) can create systemic risk Much more controversial for non-banks - MetLife sued FSOC January 2015 over their decision to designate MetLife as a SIFI Insurance Companies play important role in financial system - 30% 35% of bonds issued by European financial firms - Fire sales can happen (Dick-Nielsen-Feldhutter-Lando, Ellul-Jotikasthira-Lunblad, Manconi-Massa-Yasuda) - Market activities: McDonald and Paulson (2015)

112 FinTech Are Financial Innovations Useful?

113 What did NOT happen in Finance Retail Trade: Relative Price year

114 Relative Wage & Eduction in Finance Source: Philippon & Reshef (QJE, 2012)

115 Source: Philippon & Reshef (QJE, 2012) Relative Wage: Financiers vs Engineers

116 Employment Shares & Relative Wages Source: Philippon & Reshef (QJE, 2012)

117 Pay & Regulation Source: Philippon & Reshef (QJE, 2012)

118 Regulation: Where We Are & Where We Want To Be

119 Current Strategy Has Run Its Course Will not work: entrenched interests, coordination costs, intractable design problem

120 My Proposal: Strategy 2

121 My Proposal: Strategy 2

122 This Will Not Happen Automatically

123 This Will Not Happen Automatically

124 Finance and Climate Change New risks Insurance - impact on insurance liabilities from climate- and weather-related events, such as floods and storms that damage property or disrupt trade Asset management - Revaluation risks from adjustment towards a lower-carbon economy - Stranded assets : Fossil fuels companies: mainly valued on their reserves. But reserves exceed the budget of the planet: 2,795 GtCO2, but budget : 1,437 GtCO2

125 Low Carbon Indices How would you go about providing financial incentives for reducing carbon footprint Option 1: exclude poluters from portfolio and/or bet on replacements - very costly and complicated How do you buil an investment strategy when you think there is a risk in the long run but you have no idea when risk might materialize? Option 2: start from existing indexes and reduce footprint - start from MSCI index & match with carbon emission data - choose porfolio that achieves X% reduction of Emission Intensity and Z% reduction in exposure to stranded assets - optimize and re-balance regularly : low tracking error

126 Low Carbon Indices: Theory

127 Low Carbon Indices: Historical Performance

128 References I Bansal, R. and A. Yaron (2002). Risks for the long run: A potential resolution of asset pricing puzzles. forthcoming, Journal of Finance. Bernanke, B. and M. Gertler (1989). Agency costs, net worth and business fluctuations. American Economic Review 79, Bernanke, B., M. Gertler, and S. Gilchrist (1999). The financial accelerator in a quantitative business cycle framework. In J. B. Taylor and M. Woodford (Eds.), Handbook of Macroeconomics, Volume 1C. Elsevier Science, North Holland. Cochrane, J. H. (2017). Macro-finance. Eggertsson, G. and P. Krugman (2012). Debt, deleveraging, and the liquidity trap:a fisher-minsky-koo approach. Quarterly Journal of Economics (127(3)), Gertler, M. and N. Kiyotaki (2013). Banking, liquidity and bank runs in an infinite horizon economy. Working Paper, NYU.

129 References II He, Z. and A. Krishnamurthy (2012). A model of capital and crises. Review of Economic Studies. Kaplan, G. and G. L. Violante (2011, August). A Model of the Consumption Response to Fiscal Stimulus Payments. NBER Working Papers 17338, National Bureau of Economic Research, Inc. Kiyotaki, N. and J. Moore (1997, Apr). Credit cycles. Journal of Political Economy 105(2), Leland, H. E. (1994). Bond prices, yield spreads, and optimal capital structure with default risk. Working Paper 240, IBER, University of California, Berkeley. Leland, H. E. (1998). Agency costs, risk management, and capital structure. Journal of Finance 53,

130 References III Martin, P. and T. Philippon (2014). Inspecting the mechanism: Leverage and the great recession in the eurozone. Working Paper NYU. Myers, S. C. (1977). Determinants of corporate borrowing. Journal of Financial Economics 5, Myers, S. C. and N. S. Majluf (1984). Corporate financing and investment decisions when firms have information that investors do not have. Journal of Financial Economics 13, Nachman, D. and T. Noe (1994). Optimal design of securities under asymmetric information. Review of Financial Studies 7, Philippon, T. (2009). The bond market s q. The Quarterly Journal of Economics 124(3),

131 References IV Philippon, T. (2015). Has the us finance industry become less efficient? on the theory and measurement of financial intermediation. The American Economic Review 105(4),