global financial cycles - julis-rabinowitz center for public policy … · julis-rabinowitz center...

Global Financial Cycles

Helene Rey

London Business School & NBER & CEPR

2018

Julis-Rabinowitz Center for Public Policy and Finance 7th Conference

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Global Financial Cycles

I Fluctuations in financial activity (risk taking, credit creation, assetprices, capital flows, spreads, leverage) on a global scale (Bruno andShin (2015), Miranda-Agrippino and Rey (2015), Baskaya et al.(2017)).

I Particularly interesting to link the Global Financial Cycle to issues offinancial stability (waves of crises) and to constraints it puts onmonetary policy.

I Dilemma versus trilemma: monetary conditions (including spreads,price of risk) are affected by the centre country(ies) even underfloating rates (Rey (2013, 2016)).

I Low real rates and zero lower bound: important constraint for mostadvanced economies (Global Real Rates: A Secular Approach(Gourinchas and Rey, 2016)).

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U.S. Real Rates

-6

-4

-2

0

2

4

6

8

10

12

1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016

percent

90-day 3-year 5-year 10-year

Ex-ante real yields on U.S. Treasury Securities constructed using median expected price changesfrom the University of Michigan’s Survey of Consumers. Source: FRED.

3 / 25

‘Historical’ U.S. Real Rates, 1871-2011

0

10,000

20,000

30,000

40,000

0

50,000

100,000

150,000

200,000

250,000

1875 1900 1925 1950 1975 2000

real consumption per capita real wealth per capita

.14

.16

.18

.20

.22

.24

.26

.28

1875 1900 1925 1950 1975 2000

consumption/wealth ratio

-.15

-.10

-.05

.00

.05

.10

.15

.20

1875 1900 1925 1950 1975 2000

short term real interest rate (percent)

The figure reports the annualized ex-post real 3-month interest rate for the U.S. since 1871.

Source: Jorda et al (2016).

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Global Real Rates: A Secular Approach

Empirical approach using the world budget constraint and historical data.

I Law of accumulation of wealth for the world (closed economy):

Wt+1 = Rt+1(Wt − Ct)

I Log-linearize around the steady-state consumption-wealth ratio andderive the world’s intertemporal budget constraint:

lnCt/Wt w Et

∑∞s=1 ρ

sw

(rwt+s − ∆ lnCt+s

)I Present value relation:

lnCt/Wt w Et

∑s ρ

sw r

ft+s +νEt

∑s ρ

sw rpt+s −Et

∑s ρ

sw∆ ln Ct+s +εt

≡ cw ft +cw rp

t +cwct +εt

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Global Consumption/Wealth Ratio: Hansen and Summers

-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

ln(c/w) Risk free comp.Risk premium comp. Consumption comp.Predicted

-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

LCWM

-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

ln(c/w) Risk free comp.

-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

ln(c/w) Risk free comp.Risk premium comp.

-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

ln(c/w) Risk free comp.Risk premium comp. Consumption comp.

-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

ln(c/w) Predicted

The figure decomposes the fluctuations in ln(C/W ) around its mean into a risk-free component

(cw f ), an excess return component (cw rp) and a consumption growth component (cwc).

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Decomposing the Global Consumption/Wealth Ratio

-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010


-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

LCWM

-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010


-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010


-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010


-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

ln(c/w) Predicted

The figure decomposes ln(C/W ) into a risk-free component (cw f ), an excess return component

(cw rp) and a consumption growth component (cwc).

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-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010


-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

LCWM

-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010


-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010


-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010


-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

ln(c/w) Predicted



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-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010


-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

LCWM

-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010


-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010


-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010


-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

ln(c/w) Predicted



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-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010


-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

LCWM

-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010


-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010


-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010


-.4

-.3

-.2

-.1

.0

.1

.2

.3

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

ln(c/w) Predicted



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Results

I Very good fit of the VAR

I Most of the movements in the consumption-wealth ratio reflectexpected movements in the future risk-free rate

I Consumption-wealth ratio today contains significant information onfuture real rates.

I This is not a causal decomposition: the risk free and risky returns aswell as consumption growth are endogenous and interdependent.

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Interpretation

I Most of the action is in the joint dynamics of the consumptionwealth ratio and the risk free rate.

I Plausible interpretation:I ‘Irrational exuberance’ in asset prices (‘Roaring 20s’ and the

‘Exuberant 1990-2000s’) leads to fast growing financial wealth andfast declining consumption-wealth ratios.

I Large financial crises (in 1929 and in 2008) lead to deleveraging(increased savings and lower consumption) for an extended time andto low real rates.

I Therefore low consumption wealth ratios tend to be associated withexpected low real rates.

I This is consistent with the important role of debt overhang effectsand credit dynamics, (Schularick and Taylor (2013), Reinhart andRogoff (2014), Mian, Sufi and Verner (2015) and a global financialboom/bust cycle (Miranda-Agrippino & Rey (2015)).

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An Aside: Predicting Global Real Risk-free Rates

-.12

-.08

-.04

.00

.04

.08

.12

.16

.20

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

1-year ahead

-.10

-.05

.00

.05

.10

.15

.20

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

2-years ahead

-.08

-.04

.00

.04

.08

.12

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

5-years ahead

-.12

-.08

-.04

.00

.04

.08

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

fittedactual

10-years ahead

The figure forecasts the 10-year average future short risk-free rate using ln(C/W ). Graph includes2 standard deviation bands.

2011-2021 forecast: −1.3%

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Global Financial Cycle and Risky Asset Prices

I Large panel of risky returns around the world.

I We test for the number of global factors.

I The data cannot reject the existence of one and only one globalfactor. That single factor explains about a quarter of the variance ofthe data.

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Global Factor in World Asset Prices.

1975 1980 1985 1990 1995 2000 2005 2010

−100

−50

0

50

100

Global Common Factor

1975 1980 1985 1990 1995 2000 2005 2010

−100

−50

0

50

100

1990:20121975:2010

15 / 25

Volatility Component and Aggregate Risk Aversion

Credit Crunch: 434.7*

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 20100

50

100

150

200

250

Global Realized Variance

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010

-2

-1

0

1

2

3 Aggregate Risk Aversion Proxy

Figure: Decomposition of the global factor in a volatility component and a riskaversion component; the measure of realized monthly global variance iscomputed using daily returns of the MSCI world index.

.

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Share of Banking Flows in Cross-Border Flows

1992 1994 1996 1998 2000 2002 2004 2006 2008 2010-10

0

10

20

30

40

50

60

70

PortfolioFDIDebtBank

.

17 / 25

US Monetary Policy and the Global Financial Cycle

I Dilemma versus trilemma: monetary conditions (including creditcreation, price of risk) are affected by the centre country(ies) evenunder floating rates.

I We estimate a Bayesian VAR (in levels) with 4 lags. Typical set ofmacroeconomic variables, including output, inflation, investment andlabor data PLUS global credit, cross border credit flows, financialleverage, global factor in asset prices, term spread (25 variables)

I The monetary policy shock is identified using the effective federalfunds rate as the instrument for monetary policy and (i)block-ordering the variables into slow-moving and fast-moving ones;(ii) using the Romer and Romer narrative approach as instrument(also experimented with high frequency instruments).

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Response of domestic Business Cycle

Real GDP

0 4 8 12 16 20

-8

-6

-4

-2

0

Real PersonalConsumption Expenditures

0 4 8 12 16 20

-8

-6

-4

-2

0

PersonalConsumption Deflator

0 4 8 12 16 20

-6

-4

-2

0

Consumer Sentiment

0 4 8 12 16 20-4

-3

-2

-1

0

1

CholeskyNarrative

Figure: Response of Business Cycle (% points) to a monetary policy shockinducing a 100bp increase in the Effective Fed Funds Rate.

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Response of Global Asset Prices

ExcessBond Premium

0 4 8 12 16 20−0.15

−0.1

−0.05

0

0.05

0.1

0.15

Term Spread

0 4 8 12 16 20−0.6

−0.4

−0.2

0

0.2

Global AssetPrices Factor

0 4 8 12 16 20

−8

−6

−4

−2

0

2

4

AggregateRisk Aversion

0 4 8 12 16 20

−4

−2

0

2

4

6

8

CholeskyNarrative

Figure: Response of Asset Prices (% points) to a monetary policy shockinducing a 100bp increase in the Effective Fed Funds Rate.

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Response of Global Credit, with and without US

US Domestic Credit

0 4 8 12 16 20

−16

−14

−12

−10

−8

−6

−4

−2

0

Global Domestic CreditExcluding US

0 4 8 12 16 20

−25

−20

−15

−10

−5

0

5

CholeskyNarrative

Figure: Response of Global Credit (% points) to a monetary policy shockinducing a 100bp increase in the Effective Fed Funds Rate.

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Response of Global Credit and of Cross Border Credit

GlobalDomestic Credit

0 4 8 12 16 20

−25

−20

−15

−10

−5

0

5

Cross BorderCredit to Banks

0 4 8 12 16 20

−35

−30

−25

−20

−15

−10

−5

0

5

Cross BorderCredit to Non−Banks

0 4 8 12 16 20−30

−25

−20

−15

−10

−5

0

5

CholeskyNarrative

Figure: Response of Global Credit (% points) to a monetary policy shockinducing a 100bp increase in the Effective Fed Funds Rate.

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Response of Banks Leverage in the US, Euro area, UK(GSIBs)

US Broker−DealersLeverage

0 4 8 12 16 20−3

−2.5

−2

−1.5

−1

−0.5

0

0.5

1

1.5

2

EA G−SIBsLeverage

0 4 8 12 16 20

−0.6

−0.5

−0.4

−0.3

−0.2

−0.1

0

0.1

0.2

0.3

0.4

UK G−SIBsLeverage

0 4 8 12 16 20−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

CholeskyNarrative

Figure: Response of Banking Sector Leverage (% points) to a monetary policyshock inducing a 100bp increase in the Effective Fed Funds Rate.

23 / 25

Conclusions

I We use historical data to understand determinants of long run realrates.

I Empirical evidence consistent with global financial boom/bust cycle.Euphoria pre-crisis leads to rapid increase in wealth (1920s,1990s-2000s). This is followed by deleveraging post crisis (1929,2008).

I We use a medium scale BVAR to understand the influence of USmonetary policy on the global financial cycle.

I US monetary policy is a determinant of global monetary andfinancial conditions. This puts in question one leg of the MundellianTrilemma.

I Research agenda for the Global Financial Cycle: source, propagation,amplification mechanisms, endogenous risk build ups.

I My view: Models with heterogenous intermediaries and moral hazard(risk-taking not properly priced) are what we need.

24 / 25

ReferencesI Baskaya,Yusuf Soner, di Giovanni, Julian, Kalemli-Ozcan,

Sebnem and Mehmet Fatih Ulu (2017) “International Spilloversand Local Credit Cycles ” NBER WP No. 23149

I Bruno Valentina and Hyun Song Shin (2015) “Capital Flows andthe Risk-taking Channel of Monetary Policy ” Journal of MonetaryEconomics, 71: 119–132

I Gourinchas Pierre-Olivier and Helene Rey (2016) “Global RealRates: A secular Approach ” LBS and Berkeley mimeo

I Mian, Atif, Sufi, Amir and Emil Verner (2015) “Household Debtand Business Cycles Worldwide ” NBER WP No. 21581

I Miranda-Agrippino, Silvia and Helene Rey (2015) “US MonetaryPolicy and the Global Financial Cycle, ” NBER WP 21722

I Reinhart, Carmen M. and Kenneth S. Rogoff (2009) “ThisTime Is Different: Eight Centuries of Financial Folly, ” PrincetonUniversity Press

I Rey, Helene(2013) “The Global Financial Cycle and MonetaryPolicy Independence , ” Jackson Hole Symposium

I Schularick, Moritz and Alan Taylor(2013) “Credit Booms GoneBust: Monetary Policy, Leverage Cycles and Financial Crises,1870-2008, ” American Economic Review, 102(2): 1029-1061

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global financial cycles - julis-rabinowitz center for public policy … · julis-rabinowitz center...

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