Financial Factors in EconomicFinancial Factors in Economic Fluctuations
Lawrence ChristianoLawrence ChristianoRoberto Motto
Massimo RostagnoMassimo Rostagno
What we doI t t fi i l f i ti i t t d d ilib i• Integrate financial frictions into a standard equilibrium model and estimate the model using Euro Area and US data.
– Asymmetric information and costly state verification (Townsend (1978), Bernanke-Gertler-Gilchrist (1999))
– Endogenous determination of financial liabilities, like M1 and M3 (Chari-Christiano-Eichenbaum (1995))
• Decompose 14 aggregate data series into shocks and propagation mechanisms:
– A new shock, a ‘risk’ shock
– A new source of propagation: non-state contingent nominal rates of interest.
Outline
• Sketch the basic ingredients of the model.
• Results
Standard Model
Firmsconsumption
Investment goods1 1 f,t Investment goodsYt 0
1Yjt
f,t djf,
, 1 ≤ f,t ,
Yjt tKjtztljt
1−
Supply labor Rent capitalother t
oilautK̄t Gt Ct It,t
≤ Yt.
HouseholdsK̄ 1 K̄ G I I Backyard capital accumulation:
E Rt1k
Kt1 1 − Kt Gi,t, It, It−1
u 1rk 1 P ′
Backyard capital accumulation:
uc,t Etc,tuc,t1t1
t1 Rt1k
ut1rt1 1 − Pk ′,t1Pk ′,t
Financial SectorA t• Assets:– Working capital loans– Loans to entrepreneurs for purchasing capital– Loans to entrepreneurs for purchasing capital
• Liabilities:– Provide utility to households– Neoclassical bank production function
• Results: – features on the liability side of banks do not addfeatures on the liability side of banks do not add
shocks or propagation to business cycle dynamics
– Features on the asset side do– Features on the asset side do matter…particularly ‘loans to entrepreneurs’
EntrepreneurEntrepreneur
• Buys capital from capital producers usingBuys capital from capital producers using own resources and loans from bank
• Rents capital to intermediate good dproducers.
Banks Households EntrepreneursBanks, Households, Entrepreneurs
entrepreneur~F,t, E 1
entrepreneur
entrepreneur
HouseholdsBank
entrepreneur
Bank
entrepreneurentrepreneur
Standard debt contract
Economic Impact of Risk ShockEconomic Impact of Risk Shock
l l di t ib ti
1
lognormal distribution: 20 percent jump in standard deviation
0.7
0.8
0.9
σσ *1.2
Larger number of entrepreneurs in lefttail problem for bank
0.4
0.5
0.6
dens
ity Banks must raise interest rate on entrepreneur
Entrepreneur borrows less
0 1
0.2
0.3
Entrepreneur borrows less
Entrepreneur buys less capital, investment drops, economy tanks
0.5 1 1.5 2 2.5 3 3.5 4
0.1
idiosyncratic shock
Risk Shocks and NewsRisk Shocks and News
• Finding:Finding:
Economic effects of risk shocks operate– Economic effects of risk shocks operate primarily via advance information, or news.
Risk Shock and NewsRisk Shock and News
• Assume iid Wold innovation in log tAssume
A t h d i f ti b t
logt logt−1 iid, Wold innovation in log t
ut
• Agents have advance information about pieces of ut
ut t0 t−1
1 . . . t−88
t−ii ~iid, E t−i
i 2 i2
t−ii ~piece of ut observed at time t − i
Monetary PolicyMonetary Policy
• Nominal rate of interest function of:Nominal rate of interest function of:
A ti i t d l l f i fl ti d h– Anticipated level of inflation and change.– Slowly moving inflation target.
f f– Deviation of output growth from ss path.– Growth of credit in case of EA. – Monetary policy shock.
Estimation• EA and US data covering 1985Q1-2008Q2
Δ log per capita stock market indextPt
GDP deflator inflationt
logper capita hourst
Δ log per capita credittPt
Δ logper capita GDPt
Δ log Hourly compensationtPt
Xt
Δ logper capita investmentt
Δ log per capita M1 t
Pt
Δ log per capita M3 tPtt
Δ logper capita consumptiont
Risk Spreadt
Rtlong − Rt
e
Rte
Δ logPIt)Δ logreal oil pricet
Δ log per capita Bank Reserves tP
• Standard Bayesian methodsΔ log Pt
Summary of results• Risk shocks:
– important source of fluctuationsimportant source of fluctuations.– news on the risk shock important.
• Assumption of state non contingent interest rates has• Assumption of state non-contingent interest rates has an important impact on shock propagation.
M d d d i id• Money demand and inside money:
– relatively unimportant as a source of shocks– modest contribution to forecast ability
• Out-of-Sample evidence suggests the model deservesOut of Sample evidence suggests the model deserves to be taken seriously.
Risk ShocksRisk Shocks
• ImportantImportant
Wh th i t t?• Why are they important?
• What shock do they displace, and why?
Figure: Year-over-year GDP Growth Rate - Data (black) versus what data would have been with only the risk shock
US
Risk shock important
EA
Variance Decomposition of Financial Shocks, US Data
risk shock, trisk shock, t
Output19
I t t fInvestment
38
Important for output and investment
Consumption5
Very important for Risk Spread97
R l V l f St k M k t
Very important for financial variables
Real Value of Stock Market80
Although the data like signals on standard technology shocks they prefer signals on riskshocks, they prefer signals on risk.
Why Risk Shock is so Importanty p• A. Our econometric estimator ‘thinks’
risk spread ~ risk shock.p
• B In the data: the risk spread is stronglyB. In the data: the risk spread is strongly negatively correlated with output.
• C. In the model: bad risk shock generates a response that resembles a recessiona response that resembles a recession.
• A+B+C suggests risk shock important• A+B+C suggests risk shock important.
Correlation (risk spread(t),output(t-j)), HP filtered data, 95% Confidence Interval
The risk spread is significantly negatively correlated with output and leads a little.
Notes: Risk spread is measured by the difference between the yield on the lowest rated corporate bond (Baa) and the highest ratedcorporate bond (Aaa). Bond data were obtained from the St. Louis Fed website. GDP data were obtained from Balke and Gordon(1986). Filtered output data were scaled so that their standard deviation coincide with that of the spread data.
Another Reason the Risk Shock is so Important
Positive shock to risk triggers what looks• Positive shock to risk triggers what looks like a recession
US, Impulse Response to Riskiness Shock (contemporaneous)
Credit procyclical risk spread countercyclical
0.05
Output Investment
0Consumption
Credit procyclical, risk spread countercyclical
0 1
-0.05
0
perc
ent
-0.2
0
0.2
perc
ent
-0.05
perc
ent
-0.15
-0.1
-0.6
-0.4p
-0.1
p
0
Real Net Worth
100
Premium (Annual Rate)
-0 5
Total Loans (Real)Risk spread (AR)
-2
-1
perc
ent
50
100
basi
s po
ints
-1.5
-1
0.5
perc
ent
10 20 30
-3
10 20 300
b
10 20 30-2.5
-2
What Shock Does the Risk Shock Displace, and why?
Th i k h k d t f th• The risk shock crowds out some of the role of the marginal efficiency of i t t h kinvestment shock.
Business Cycle FrequenciesModel risk shock, t survival, t marginal efficiency of investment, it
OutputBaseline 19 2 22CEE-SW na na 46CEE SW na na 46
InvestmentBaseline 38 5.2 53CEE-SW na na 91
ConsumptionBaseline 5 1 2CEE-SW na na 3
External Finance Premiumli 9 3 0
Risk shock appears to crowd out the marginal efficiency of investment shockBaseline 97 3 0
CEE-SW na na naReal Value of Stock Market
marginal efficiency of investment shock
Baseline 80 10 2CEE-SW na na na
Why does Risk Crowd out yMarginal Efficiency of
I t t?Investment?Price of capital
Supply shifter:marginal efficiencyPrice of capital marginal efficiencyof investment, i,t
Demand shifters:risk shock, t;wealth shock wealth shock, t
Quantity of capital
• Marginal efficiency of investment shockMarginal efficiency of investment shock can account well for the surge in investment and output in the 1990s asinvestment and output in the 1990s, as long as the stock market is not included in the analysisthe analysis.
Wh th t k k t i i l d d th• When the stock market is included, then explanatory power shifts to financial
k t h kmarket shocks.
Variance Decomposition of Inside Money Shocks
Business Cycle Frequenciesy qBank demand for excess reserves, t Bank technology shock, xt
b Household money demand shock, t
Output0 0 5 00 0.5 0
Investment0 0 0
ConsumptionConsumption0 1 0
Risk spread0 0 00 0 0
Real value of stock market0 0 0
Contribution to variance: trivial
Out of Sample RMSEs• There is not a loss of forecasting power with
the additional complications of the model.
• The model does well on everything, exceptThe model does well on everything, except the risk spread.
• Calculations for 1,2,…,12 ahead forecasts:First date of forecast 2001Q3– First date of forecast, 2001Q3
– DSGE models re-estimated every other quarter– BVAR re-estimated each quarter (standard– BVAR re-estimated each quarter (standard
Minnesota priors).
Other support for the modelOther support for the model• Model predicted default rates positively
correlated with measures of default in the data.
0.0235 4Default Probability (lhs)
Expected Default Probability, NFC (rhs)
0.0185
2
0.0085
0.0135
1990Q1 1993Q1 1996Q1 1999Q1 2002Q1 2005Q1 2008Q10
Our Measure of Idiosyncratic Risk versus Bloom et alRisk, versus Bloom, et al
0.51.15Series1Series4Ri ki Sh k (3 t MA)
0 4
1.05
Riskiness Shock (3-quarter MA)Cross-firms Sale Growth Spread (3-quarter MA)
0.4
0.95
0.3
0.85
0.75
0.20.651981Q2 1986Q2 1991Q2 1996Q2 2001Q2 2006Q2
Conclusion• Incorporating financial frictions changes inference
about the sources of shocks and of propagationrisk shock– risk shock.
– New nominal rigidity: nominal non-state contingent interest rate
• Models with financial frictions can be used to ask i t ti li tiinteresting policy questions:– When there is an increase in risk spreads, how
should monetary policy respond?y p y p– How should monetary policy be structured to avoid
excess asset market volatility?What are the pro’s and con’s of ‘unconventional– What are the pro s and con s of unconventional monetary policy’?
Top Related