Financial Frictions in Macroeconomics. Lawrence J. Christiano Northwestern University

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Financial Frictions in Macroeconomics Lawrence J. Christiano Northwestern University

Balance Sheet, Financial System Assets Liabilities Bank loans Securities, etc. Bank Debt Bank Equity Frictions between financial institutions and their lenders. Source of financial crisis, bank runs, rollover crises, etc. Macro prudential policy

Balance Sheet, Financial System Assets Liabilities Financial frictions between bankers and borrowers. Bank loans Securities, etc. Bank Debt Bank Equity Perhaps the primary friction in normal times, when macro prudential is under control.

Outline Financial frictions for normal times Asset side of bank balance sheets. Provides a natural interpretation of business cycles when: We adopt a particular model of financial frictions (BGG) Incorporate a particular shock (Risk shock). Financial frictions for crisis times Liability side of bank balance sheets. The analysis of macroprudential policy questions: What leverage restrictions should be placed on banks? How should those restrictions be varied over the business cycle? Should you be easy in tough times and tough in easy times? Some tough practical issues.

3 2 Cyclical Behavior of Interest Rate Spread Interest rate spread strongly countercyclical! 1 0-1 -2-3 -4 detrended BAA minus 10-year Treasury HP filtered GDP 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

Counter-cyclicality of Interest Rate Spread Consistent with the idea that rise in riskiness has something to do with recessions. Let s see where this idea takes us Bernanke-Gertler-Gilchrist (1999) propose of way of thinking about an economy in which the interest rate spread reflects the riskiness of individual entrepreneurs (idiosyncratic risk). Of course, interest rate spreads reflect other factors too, like liquidity premia. Adopt a twist on the BGG Model: the riskiness of entrepreneurs can vary over time. Put this whole mechanism in a fully specified, medium sized DSGE model, as in Christiano-Motto-Rostagno (AER2014) Estimate everything using Bayesian methods.

density Economic Impact of Risk Shock lognormal distribution: 20 percent jump in standard deviation 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 *1.2 Lenders scared of lending because of large number of entrepreneurs expected in left tail. Entrepreneurs pay higher spread over risk free rate, and borrow less. Entrepreneurs invest less; GDP falls; consumption falls because of job losses; stock market falls; inflation falls: RECESSION! 0.5 1 1.5 2 2.5 3 3.5 4 idiosyncratic shock

Is there direct evidence of greater crosssectional risk in recessions? Yes Cross-sectional standard deviation of rate of return on equity. Non-financial firms in Center For Research in Securities Prices (CRSP) data base. Those data do show evidence of counter-cyclicality.

Cross-sectional standard deviation is countercyclical

How Much of US Business Cycles Can we Explain with the Risk Alone? A surprisingly large amount. Estimation delivers: Estimates of the risk shock. We ask: What would the data have looked like if ONLY the risk shock had been active?

Role of the Risk Shock in Macro and Financial Variables

Why Does the Econometrics like the Risk Shock So Much? In part: risk shock provides a straightforward interpretation of the countercyclical interest rate spread. Another reason: The impulse response function to a contractionary risk shock looks a lot like a recession.

Figure 3: Dynamic Responses to Unanticipated and Anticipated Components of Risk Shock 50 40 30 20 10 A: interest rate spread (Annual Basis Points) 0 0 5 10 15 B: credit -1-2 -3-4 0 5 10 15 C: investment -1-1.5-2 -2.5-3 -3.5 0 5 10 15 D: output -0.2-0.4-0.6-0.8-1 0 5 10 15 E: net worth 0-1 -2-3 -4-5 0 5 10 15 F: consumption 0-0.1-0.2-0.3-0.4-0.5 0 5 10 15 G: inflation (APR) 0-0.1-0.2-0.3-0.4 0 5 10 15 response to unanticipated risk shock, 0,0 response to anticipated risk shock, 8,0 0.1 0.08 0.06 0.04 0.02 I: risk, t 0 0 5 10 15 Looks like a business cycle

What s the model good for? Can think about how monetary policy should respond to an increase in interest rate spreads (should cut rates). Can be used to understand why including credit growth and the stock market in a Taylor rule might be a good idea (see, Christiano, et al, Jackson Hole paper, 2010). Open economy version can be used to think about financial dimension of exchange rate depreciation (see Mihai Copaciu and Cristian Bulete, Central Bank of Romania). Depreciation makes domestic goods cheaper and stimulates output. Depreciation imposes capital losses on unhedged borrowers in foreign currency, causing them to cut back spending and reducing output.

Financial frictions on liability side of bank balance sheets This is location of the financial problems in the US financial crisis. Macro prudential policy is about preventing those problems from happening again. But, must have a clear idea of what those problems were! A consensus appears to have emerged: rollover crisis hypothesis. By 2006-2007, a huge shadow banking system existed and it suffered a major run.

This is what a bank run looked like in the 19 th century: Diamond-Dybvig run. Bank runs in 2007 and 2008 were different and did not look like this at all (Gorton)! It was a rollover crisis in a shadow (invisible to normal people) banking system.

Rollover crisis Consider the following bank: Assets Liabilities 120 Deposits: 100 Banker net worth 20 This bank is solvent : at current market prices could pay off all liabilities. Suppose that the bank s assets are long term mortgage backed securities and the liabilities are short term (six month) commercial paper. The bank relies on being able to roll over its liabilities every period. Normally, this is not a problem.

Rollover crisis Now suppose the bank cannot roll over its liabilities. In this case, the bank would have to sell its assets. If only one bank had to do this: no problem, since the bank is solvent. But, suppose all banks face a roll over problem. Now there may be a big problem! In this case, assets must be sold to another part of the financial system, a part that may have no experience with the assets (mortgage backed securities).

The Drama of a Roll Over Crisis Brought to Life in Some Great Movies!

Rollover crisis A rollover crisis: when all banks in an industry (e.g., mortgage backed securities industry) are unable to roll over their liabilities. The only buyers of the securities have no experience with them, so they won t buy without a price cut (firesale). Interestingly, the buyers of the securities will all complain at how complex they are and how non-transparent they are. But, the real problem is that buyers in a fire sale are simply inexperienced. The rollover crisis hypothesis contrasts with the Big Short hypothesis: assets were fundamentally bad (Mian and Sufi).

Rollover crisis When the whole industry has to sell, then bank balance sheets could suddenly look like this: Fire sale value of assets: Assets Liabilities 90 Deposits: 100 Banker net worth -10 Multiple equilibrium: balance sheet could be the above, with run, or the following, with no run: A run could happen, or not. Assets Liabilities 120 Deposits: 100 Banker net worth 20 This is exactly the sort of financial fragility that regulators want to avoid! Under rollover crisis hypothesis, this was the situation in summer 2007.

Rollover Crisis: Role of Housing Market What matters is the actual value of assets and their firesale value. If bank is solvent under (firesale value), then probability of run is zero. Pre-housing market correction Assets Liabilities 120 (105) Deposits: 100 Banker net worth 20 (5) Post-housing market correction Assets Liabilities 110 (95) Deposits: 100 Banker net worth 20 (-5) Rollover Crisis Hypothesis: pre-2005, no crisis possible, post-2005, crisis possible.

How to think about regulation when the risk is of a rollover crisis. One possibility: model the rollover crisis directly. Best model of rollover crisis at this time: Gertler-Kiyotaki (AER2015). They adapt the rollover crisis model of sovereign debt created by Cole-Kehoe (JIE1996). Cole-Kehoe related to Diamond-Dybvig.

Possible states: s = 1, 2, 3,, T+2. Bank run, s = 1. No bank run in s > 1. In each no-run state there is a chance of a run in the next state, unless s = 2. Steady state s=t+2 s=4 s=3 s=2 Run, Run state s=1 s = 1.

One Hundred Year Stochastic Simulation Price of Capital, Q Probability of a bank run in t+1, p 0.98 0.04 0.97 0.96 0.03 0.95 0.94 0.02 0.93 0.01 0.92 0.91 0 100 200 300 400 100 200 300 400 0.04 0.03 0.02 0.01 0 Bank net worth, N 100 200 300 400 percent deviation from steady state 0-1 -2-3 -4-5 -6 GDP 100 200 300 400

Policy Use of Model Investigate the impact on financial stability of leverage restrictions. This analysis is hard! Not clear how you introduce lots of shocks, actual investment, open economy, currency mismatch, etc. At a deeper level, computing equilibrium requires knowing what happens in the crisis state. Seems unlikely other than for pedagogic purposes. Alternative: assume that governments will always act as lender of last resort. Construct models that do not allow rollover crisis, but do capture moral hazard implications of bailouts.

Conclusion I ve reviewed models of financial frictions that appeared interesting before and after crisis. Models of frictions on the asset side of financial firms seem likely to always be important and interesting. Discussed modeling the liability side of financial firm balance sheets. Difficult tradeoffs. Model things correctly, but that s perhaps intractable. Take full government bailout as exogenous (so no rollover risk), and do macro prudential policy to manage the resulting moral hazard problems.