bubbles, crashes & the financial cycle

www.uni-bielefeld.de

Sander van der Hoog and Herbert DawidChair for Economic Theory and Computational Economics

Bielefeld University

12th International Post-Keynesian ConferenceKansas City, Sept. 2014

Bubbles, Crashes & the Financial Cycle

IntroductionEurace@Unibi Model

Simulation ResultsSummary & Outlook

OutlineThe Business & Financial CycleFinancial Instability HypothesisBalance sheets

Outline of topics

I Agent-based Macroeconomics

I Leverage cycle – Geanakoplos

I Financial Instability Hypothesis – Minsky

I Basel III and the procyclicality of capital adequacy requirements

I Macro-prudential banking regulation

Sander van der Hoog Bubbles, Crashes & the Financial Cycle




The Business & Financial Cycle

1976-80

US real-estate boom

1980

DIMCA

2011:

End of Regulation Q

1989:

S&L Crisis

1980: Depository Institutions Deregulation and Monetary Control Act: Deregulation of Savings and Loans institutions

2011: Regulation Q: prohibition of interest-bearing demand deposit accounts





Financial Instability Hypothesis

I Equity/Asset-ratio: Measure for financial robustnessI Fragility synchronized with business cycle? (Fragile booms, deleveraging

recovery)

Output and E/A ratio





Empirical Motivations

Features of macroeconomics with a financial cycle (Borio, 2012):I the financial boom should not just precede the bust but cause it (a la

Minsky).I the presence of debt and capital stock overhangs (excess stocks,

non-full utilization rates).

Findings:I Recessions following a crisis after a fragile boom tend to have much

larger declines in consumption, investment, output, and employment.(Shularick & Taylor, 2012)

I Balance sheet recessions: Recessions driven by deleveraging lead to aprolonged slump. (Koo, 2011)





Balance sheets

FirmAssets LiabilitiesLiquidity+ revenues– wage bill– taxes– dividends+ interest deposits– interest on loans Loans from banks+ new loans + new loans

– bad debtInventory+ output– salesCapital stock Equity+ investment + profits

+ bad debt

BankAssets LiabilitiesCB reserves (−0.1%) Deposits– interest deposits +/– withdrawals+ interest on loans + new loans– taxes– dividends+/– CB reserves

Loans to firms CB debt (+0.15%)

+ new loans +/– CB reserves– bad debt +/– interest

Equity+ profits– bad debt


Activity Role Agent Agent Role Activity

E u r a c e @ U n i b i

Bank

InvGoodFirm

Household

asset demandsavings decision

FinancialMarket

(index bond)

ECBMonetarypolicy

Gov

Policymaker

Investor

ConsGoodFirm

Consumer

Cons.Goods Market

(local malls)

cgood demandconsumption choice

Producercgood supplyposted prices

labor supplyreservation wage

Employee labor demandwage schedule

LaborMarket(search & matching)

Creditor Debtorcredit supplyrank credit risk

credit demandrank interest

CreditMarket(credit

rationing)

Employer

InvestorProducerCapitalGoodsMarket

igood supplyvintage menuposted prices

igood demandvintage choices



Monetary Policy & Banking RegulationCapital Adequacy RequirementReserve Requirement

Literature: The Credit Channel of Monetary Policy Transmission

1. The broad borrowers’ balance sheet channel:(Bernanke & Blinder 1988)

I Credit demand side

I Focusses on external finance premium: probability of defaultExternal finance premium: inversely related to borrower’s net worth.

I Changes in the value of assets on the balance sheet of a firm affect thefirm’s ability to borrow.

2. The narrow bank lending channel:(Bernanke & Gertler 1995)

I Supply of bank loans determined by financial health of banks.

I Changes in the value of assets on the balance sheet of a bank affects thebank’s ability to lend.





Capital Adequacy Requirement

1. Firm’s default probability

PDft = max{3× 10−4, 1− e−νDf

t /E ft }, ν = 0.1

2. Interest rate offered by bank b to firm i

r bft = rECB

(1 + λB · PDf

t + εbt

), εb

t ∼ U[0, 1]

rECB = 0.01

λB = 3: penalty rate for high-risk firm, uniform across banks

εbt : bank’s ideosyncratic operating costs





Capital Adequacy Requirement

1. Risk-exposure of credit request (Expected Loss at Default):

x ft = PDf

t · Lft (1)

2. Constraint: Capital Adequacy Requirement (CAR)∑f

x ft ≡ X b

t ≤ αEbt , α ≥ 0 (2)

3. Risk-exposure ”budget” of the bank:

V bt ≡ αEb

t − X bt (3)

4. Loan granted:

`ft =

Lf

t if x ft ≤ V b

t No rationingθ · Lf

t = V bt /PDf

t if 0 ≤ V bt ≤ x f

t Partial rationing0 if V b

t ≤ 0 Full rationing(4)

Possibility of credit rationing: {θ : V bt − PDf

t · `ft = 0} → θLf

t = V bt /PDf

t





Reserve Requirement

I Constraint: Reserve Requirement

Mbt ≥ β · Depb

t (5)

I Excess liquidity ”budget” of the bank:

W bt ≡ Mb

t − β · Depbt (6)

I Loan granted:

`bft =

Lf

t if W bt ≥ Lf

t No rationingφ · Lf

t = W bt if 0 ≤ W b

t ≤ Lft Partial rationing

0 if W bt < 0 Full rationing

(7)

Possibility of credit rationing: {φ : W bt − φ · Lf

t = 0} → φ = W bt /L

ft

I Illiquid banks stop lending to all firms (bank lending channel)

I Risky firms cannot get loans (borrower’s balance sheet channel)




Amplitude of recessionsFirm activityBank activityNetwork dynamics

Parameter sensitivity analysis

0 200 400 600 800 1000

2000

3000

4000

5000

Months

Eur

osta

t_ou

tput

alfa_20_gamma

1.0 2.0 4.0 8.0 16.0 32.0

α-sensitivity: Cap. Adq. Req.

I Default: α = 32 (3%)I Lower: amplitude of recessions

increases

0 200 400 600 800 100020

0030

0040

0050

00

Months

Eur

osta

t_ou

tput

beta_20_gamma_10_alfa

0.01 0.02 0.05 0.10 0.20 0.50

β-sensitivity: Reserve Req.

I Default: β = 0.05 (5%)I Higher: amplitude of recessions

decreases





Parameter sensitivity analysis

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−80

00−

6000

−40

00−

2000

Parameters

batc

h_fu

ll_am

plitu

de_r

eces

sion

1.0 2.0 4.0 8.0 16.0 32.0

−80

00−

6000

−40

00−

2000

α-sensitivity: Cap. Adq. Req.

I Default: α = 32 (3%)I Lower: amplitude of recessions

increases

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−70

00−

6000

−50

00−

4000

−30

00−

2000

−10

00

Parameters

batc

h_fu

ll_am

plitu

de_r

eces

sion

0.01 0.02 0.05 0.10 0.20 0.50−

7000

−60

00−

5000

−40

00−

3000

−20

00−

1000

β-sensitivity: Reserve Req.

I Default: β = 0.05 (5%)I Higher: amplitude of recessions

decreases





Firm activity

Number of illiquid firms

No constraint

0 100 200 300 400 500

05

1015

20

Months

Fir

m_i

nsol

venc

y_S

L

Firm_insolvency_SFirm_insolvency_L

Firm_illiquidity_SFirm_illiquidity_L

Capital constraint (α = 2)

0 100 200 300 400 500

05

1015

20

Months

Fir

m_i

nsol

venc

y_S

LFirm_insolvency_SFirm_insolvency_L


Liquidity constraint (β = 0.50)

0 100 200 300 400 500

05

1015

20

Months

Fir

m_i

nsol

venc

y_S

L







Bank activity

Number of active banks (unconstrained + constrained by equity/liquidityconstraint)

No constraint

0 100 200 300 400 500

05

1015

20

Months

Ban

k_ac

tive_

mul

ti

Bank_active_none Bank_active_exposure Bank_active_liquidity

Capital constraint (α = 2)

0 100 200 300 400 500

05

1015

20

Months

Ban

k_ac

tive_

mul

ti


Liquidity constraint (β = 0.5)

0 100 200 300 400 500

05

1015

20

Months

Ban

k_ac

tive_

mul

ti






Network dynamics

Shown: lending relationships between banks - firmsInitial state: Each firm (80) has a single loan with one random bank (20)

t = 0 t = 500 t = 900 t = 1000

Figure : Black: banks, Blue: firms. γ = 18.5, α = 10, β = 0.10.




Summary

Capital Adequacy Requirement (α)

1. More limits on excessive risk-taking

2. Amplitude recessions increases

3. More banks fail

4. More firms go illiquidI constraint does not discriminateI constraint self-reinforcing

5. Steep, sudden deleveraging

6. Concentration in banking sector

Reserve Requirement (β)

1. More limits on liquidity supply

2. Amplitude recessions decreases

3. Banks stay alive

4. Large firms go illiquidI large firms largest credit demandI liq. constraint helps small firms

5. Gradual deleveraging in waves

6. Bank equity can recover




Outlook

I Macroprudential regulation

I Systemic riskI Bank-firm networks

I Empirically-grounded bank behavior

I Credit quotasI Credit rationing of SMEs


Thank you for your attention!

Model documentation:

www.wiwi.uni-bielefeld.de/vpl1/research/eurace-unibi.htmlPapers:

I H Dawid, S Gemkow, P Harting, S van der Hoog & M Neugart (2014):Agent-Based Macroeconomic Modeling and Policy Analysis: The Eurace@UnibiModel. In: S-H Chen, M Kaboudan (Eds), Handbook on ComputationalEconomics and Finance. Oxford University Press.

I H Dawid, S Gemkow, P Harting, S van der Hoog & M Neugart (2012):The Eurace@Unibi Model: An Agent-Based Macroeconomic Model for EconomicPolicy Analysis. Working Paper University Bielefeld.

I H Dawid, S Gemkow, P Harting, S van der Hoog & M Neugart (2011):Eurace@Unibi Model v1.0 User Manual. Working Paper Bielefeld University.

I H Dawid & P Harting (2012): Capturing Firm Behavior in Agent-Based Models ofIndustry Evolution and Macroeconomic Dynamics, in: G. Bunstorf (Ed), AppliedEvolutionary Economics, Behavior and Organizations. Edward Elgar, pp.103-130.

I H Dawid & M Neugart (2011): Agent-based Models for Economic Policy Design,Eastern Economic Journal 37, 44-50.

www.wiwi.uni-bielefeld.de/vpl1/research/eurace-unibi.html

Scenario: Capital Adequacy RequirementOutput

0 100 200 300 400 500

1500

2000

2500

3000

Months

Eur

osta

t_ou

tput

alfa

2.0 8.0

Bank activity

0 100 200 300 400 5000

510

1520

Months

Ban

k_ac

tive_

mul

ti


Firm activity

0 100 200 300 400 500

05

1015

20

Months

Fir

m_i

nsol

venc

y_S

L



0 100 200 300 400 500

050

0010

000

1500

020

000

Months

Ban

k_eq

uity

alfa

2.0 8.0

Bank equity

0 100 200 300 400 500

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Months

F_E

AR

atio

alfa

2.0 8.0

Firm fragility

0 100 200 300 400 5000.

040

0.04

50.

050

0.05

50.

060

0.06

50.

070

Months

Fir

m_m

ean_

inte

rest

alfa

2.0 8.0

Mean interest

Scenario: Minimum Reserve RequirementOutput

0 100 200 300 400 500

2000

2200

2400

2600

2800

Months

Eur

osta

t_ou

tput

min_cash_reserve_ratio

0.10 0.50

Bank activity

0 100 200 300 400 5000

510

1520

Months

Ban

k_ac

tive_

mul

ti


Firm activity

0 100 200 300 400 500

05

1015

20

Months

Fir

m_i

nsol

venc

y_S

L



0 100 200 300 400 500

5000

1000

015

000

2000

0

Months

Ban

k_eq

uity


0.10 0.50

Bank equity

0 100 200 300 400 500

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Months

F_E

AR

atio


0.10 0.50

Firm fragility

0 100 200 300 400 5000.

045

0.05

00.

055

0.06

00.

065

0.07

0

Months

Fir

m_m

ean_

inte

rest


0.10 0.50

Mean interest



Scenarios: Firm Fragility

Firm E/A-ratio

Capital constraint

0 100 200 300 400 500

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Months

F_E

AR

atio

alfa

2.0 8.0

Liquidity constraint

0 100 200 300 400 500

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Months

F_E

AR

atio


0.10 0.50

Liquidity constraint

0 100 200 300 400 500

0.04

50.

050

0.05

50.

060

0.06

50.

070

Months

Fir

m_m

ean_

inte

rest


0.10 0.50




Literature

I Hyman P. Minsky (1982): The Financial Instability Hypothesis:Capitalistic Processes and the Behavior of the Economy

I Hyman P. Minsky (1986, 2008): Stabilizing an Unstable EconomyI Delli Gatti, Desiderio, Gaffeo, Cirillo & Gallegati, 2010: Macroeconomics

from the Bottom-UpI Dosi, Fagiolo, Napoletano & Roventini, 2012: Income distribution, credit

and fiscal policies in an agent-based keynesian model. LEM PapersSeries 2012/03,

I Ashraf, Gershman & Howitt, 2011: Banks, Market Organization, andMacroeconomic Performance: An Agent-Based Computational Analysis

I Schularick & Taylor, 2012: Credit booms gone bust: Monetary policy,leverage cycles, and financial crises, American Economic Review 102(2), 1029-61.

I Claessens, Kose & Terrones, 2011: How do business and financialcycles interact?


bubbles, crashes & the financial cycle

Economy & Finance