Credit Spreads and the Severity of Financial Crises Arvind Krishnamurthy, Stanford University and NBER Tyler Muir, Yale University October 2, 2015.

Credit Spreads and the Severity of Financial

CrisesArvind Krishnamurthy, Stanford University and NBER

Tyler Muir, Yale University

October 2, 2015

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Three results

1. Financial crises are followed by deep and protracted recessions• Estimates• Comparison to non-financial recessions

2. The severity of the GDP contraction following a crisis can be forecast based on the rise in spreads in the first year of the crisis and the extent of credit growth pre-crisis

3. Spreads pre-crisis are abnormally low• “Froth” precedes crises

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Data: Credit spreads, crisis dates, GDP• 1869-1929 across 14 countries from old newspapers• 1930-present from various central banks and other data sets

(Datastream, Global Financial Database) for more recent credit spreads• High grade minus low grade corporate spread• Corporate bond index to government bond

• We normalize each country’s spread as:

• Total of 900 country-year observations

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Credit spreads: 1869-1929• Individual bond prices on banks, sovereigns, railroad, etc.

• Over 4000 unique bonds, 200,000 bond / years• We convert to yield to maturity• Spread = high 10th percentile avg yield minus low 10th percentile avg yield

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Data: Credit spreads, crisis dates, GDP• We cross this data with crisis dates from Reinhart-Rogoff (RR) and

Schularick-Taylor (ST) and Bordo-Eichengreen-Klingebiel-Martinez (BE)

• Total of 900 country-year observations: • 44 ST crises• 48 RR crises• 27 BE crises

• GDP data from Barro-Ursua

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Empirical approach

• Define a set of dates identified with a major financial crisis

• Examine the behavior of output (and spreads) around these dates

• Choice of dates is important! • What defines an event as a “financial crisis”?

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Theory: What is a financial crisis?

• Shock : recessionary shock, lower expected cash-flows on assets held by intermediaries• Fragility : high leverage/low equity capital, short-term debt, correlated

intermediary positions, interconnected exposures

• “Trigger” + “Amplification”• Asset price feedback• Credit crunch• Bank runs/failures/disintermediation

• Credit spreads rise:• Expected default + risk/illiquidity premium

• Kiyotaki-Moore, He-Krishnamurthy, Brunnermeier-Sannikov

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Result 1: Aftermath of a crisis

• What should one have expected, standing in 2008?

• Reinhart and Rogoff (2009)• Across a set of defined events:

-9.3% Peak-to-trough

• Slow recovery

Crisis severity =

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Credit spreads are a continuous measure• Spreads rise more in more severe crises ( high):

• Underlying relation: if ThresholdDefault, Risk, Illiquidity

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Specification

• Panel data regressions (country , horizon ):• Interact spreads with crisis dummies

• Controls: lagged GDP growth, 3 year credit growth from Schularick-Taylor• Standard errors cluster by country• Why still use 0-1 crisis dummies?

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ST crisis recessions and no-crisis recessions• Schularick and Taylor (2012), Jorda, Schularick and Taylor (2013)

…we define financial crises as events during which a country's banking sector experiences bank runs, sharp increases in default rates accompanied by large losses of capital that result in public intervention, bankruptcy, or forced merger of financial institutions….

• Crisis date based on start of recession accompanying financial crisis (44 events in our sample)• Non-financial recession dates (100 events)

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RR and BE: dates based on failure event• Reinhart and Rogoff (2009): (48 crises)

We mark a banking crisis by two types of events: (1) bank runs that lead to the closure, merging, or takeover by the public sector of one or more financial institutions; and (2) if there are no runs, the closure, merging, takeover, or large-scale government assistance of an important financial institution (or group of institutions), that marks the start of a string of similar outcomes for other financial institutions.

• Bordo, et. al., (2001): (27 crises)We define financial crises as episodes of financial-market volatility marked by significant problems of illiquidity and insolvency among financial-market participants and/or by official intervention to contain those consequences. For an episode to qualify as a banking crisis, we must observe financial distress resulting in the erosion of most or all of aggregate banking system capital.

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Standard errors in parentheses

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Scatter plots: results not driven by outliers

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Comparing GDP outcomes across events

• We plot a Jorda projection impulse response:

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For crisis events, and recession events

• This attempts to mimic: underlying structural shock, , the same in two economies.

• Economy A: levered financial sector, financial crisis, financial recession• Economy B: no financial crises, and we have a non-financial recession

• However, it is likely that for same spread change is larger than , which means crisis impulse is an underestimate

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Impulse response to +1 shock (Jorda projection)

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-9% at 4yrs

-3% at 4yrs

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2008 Actual and Predicted (using ST dates)

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ST versus RR

-2.7% at 4 yrs

-9% at 4 yrs

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Summary and some doubts

• Recessions with financial crises are deeper and more protracted than recessions without financial crises• -9% versus -3%, 4 years out

• But results depends on dating used• Why date before bank failures (ST versus RR/BE)?

• Is dating subject to peek-ahead bias?

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Result 2: Losses X fragility

Theory: crisis severity =

• in most models is losses on bank assets

• is leverage

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Standard errors in parentheses

Losses change in spreads

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Standard errors in parentheses

Losses change in spreads

5 year GDP growth

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Define events based on and

• Shock

• Fragility : 3-year growth in Credit/GDP from Schularick and Taylor

HighCredit = 1 if 3-year growth in Credit/GDP>median

SpreadCrisis =

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Crises outcomes based on losses X fragility

HighCredit = 1 if 3-year growth in Credit/GDP>median

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Impulse responses based on alternative dates

• High Credit is free of peek ahead bias

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Result 3: Pre-crisis behavior

Lagged 3-year credit/GDP growth (ST crises)

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Spreads pre-crisis and credit growth

• Pre-crisis, growth in is observable

As rises

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Spread pre-crises compared to other periods

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0 means

Spreads over the cycle (ST Crises)

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Investor beliefs• Pre-crisis, growth in is observable

• A crisis is a surprise; large shift in investor expectations• Caballero-Krishnamurthy (2008): Knightian uncertainty• Gennaioli-Shleifer-Vishny (2012): Neglected risks

• Not a slow build up model, where crisis prob rises over time• Gorton-Ordonez (2014), Boissay-Collard-Smets (2014)

Pre-crisis as rises

Pre-crisis

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Conclusion

• Aftermath of financial crises is deep and protracted recession• Effect of crisis lasts many years• We use variation in severity indexed by spreads• Results consistent with Reinhart-Rogoff, Schularick-Taylor; we give more

precise answers

• Spikes in spreads + real fragility = Losses + Amplification• Lead to poor GDP outcomes (Kiyotaki-Moore, He-Krishnamurthy)

• Crises are preceded by unusually low spreads• Spreads pre-crisis do not price an increase in fragility• “Surprise” is a key dimension of crises (Caballero-Krishnamurthy, Gennaioli-

Shleifer-Vishny)

Extra pictures

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Spreads recover quickly, GDP drop persists

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Spreads recover quickly, GDP drop persists

Initial spread matters many years out

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2008 Actual and Predicted