bubbles, crashes & the financial cycle: the limits to ...€¦ · sander van der hoog bubbles,...

The Big QuestionsEurace@Unibi Model

Simulation ResultsConclusions

Bubbles, Crashes & the Financial Cycle:The Limits to Credit Growth

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

Bielefeld University

WEHIASophia Antipolis, 21-23 May 2015

Sander van der Hoog Bubbles, Crashes & the Financial Cycle



The Big Questions

I Which micro- or macro-prudential banking regulations arebeneficial to financial stability?

I Prevention and mitigation policies:

I How to prevent severe downturns from occurring?

I How to mitigate the cumulative economic losses?


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



Mechanisms in the modelCapital Adequacy RequirementReserve Ratio Requirement

Mechanisms in the model

1. Probability of Default (PD): Internal Risk-Based approach (IRB)

2. Interest rate rule for commercial banks

3. Debt-equity transformation: Insolvency / Illiquidity

4. Dividend payout rule

5. Credit rationing rule

6. Capital Adequacy Requirement (CAR)

7. Central Bank Reserve Ratio Requirement (RRR)

8. Future research: Capital Conservation Buffers & Counter-Cyclical Capital Buffers:





Probability of Default, Interest rate rule

1. Firm’s default probability

PDft = max{0.0003,1−e−νDf

t /E ft }, ν = 0.1

2. Interest rate offered by bank b to firm i

rbft = rECB

(1 + λ

B ·PDft + ε

bt

), ε

bt ∼ U[0,1]

rECB = 0.01

λ B = 3: penalty rate for high-risk firm, uniform across banksεb

t : bank’s ideosyncratic operating costs





Capital Adequacy Requirement

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

rwabit = PDit ·Lit . and RWAb

t =F

∑i=1

K (i)

∑k=0

PDkt ·Lkt , (1)

2. Constraint 6: Capital Adequacy Requirement (CAR)

RWAbt ≤ α ·Eb

t , α ≥ 0 (2)

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

V bt := α ·Eb

t −RWAbt (3)

4. Risk-constrained loan demand:

¯̀bit =

Lit if PDit ·Lit ≤ V bt

0 if 0≤ V bt ≤ PDit ·Lit

0 if V bt < 0.

(4)





Reserve Ratio Requirement

I Constraint 7: Reserve Ratio Requirement (RRR)

Mbt ≥ β ·Depb

t , β ∈ [0,1] (5)

I Excess liquidity "budget" of the bank:

W bt := Mb

t −β ·Depbt (6)

I Loan granted: risk- and liquidity constrained credit request

`bi ,t =

¯̀bi ,t if W b

t ≥ ¯̀bi ,t

φ · ¯̀bi ,t if 0≤W b

t ≤ ¯̀bi ,t

0 if W bt < 0.

(7)

Possibility of credit rationing: {φ : W bt −φ · ¯̀b

i ,t = 0}→ φ = W bt /

¯̀bi ,t

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

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




Amplitude of recessionsPrevention and mitigation: The Limits to Credit Growth

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


0 20 40 60 80 100 120

6000

6500

7000

7500

8000

8500

9000

Recessions and expansions

Quarters

Out

put




Parameter sensitivity analysis

α-sensitivity: Cap. Adq. Req.I Basel III: 4.5−10.5%

α = 22.2−9.5I Lower: amplitude of recessions

increases

−80

00−

6000

−40

00−

2000

Parameter 1

full_

ampl

itude

_rec

essi

on0.00 0.01 0.02 0.05 0.10 0.20 0.50 0.90 0.99 1.00

−80

00−

6000

−40

00−

2000

β -sensitivity: Reserve Req.I EU: β = 0.01, US: β = 0.10, CA:

β = 0I Higher: amplitude of recessions

decreases





Parameter sensitivity analysis 2D-grid

alpha

beta

−1200

−1100

−1000

−900

−800

−700

4.0 6.0 8.0 10.0 12.0 16.0 20.0 24.0 28.0 32.0

0.00

0.02

0.10

0.25

0.35

0.45

0.90

1.00





Prevention and mitigation policies: The Limits to Credit Growth

Proposed regulations to limit excesses in banking (eg. Admati & Hellwig, 2013):

A. Default regulation: Capital ratio 12.5%, Reserve ratio 10%.

B. Banning bank dividend payouts→ Increases bank equity capital

C. Using non-risk-weighted capital ratios→ Prevents abuse of risk-weights

("risk-weight management optimization")

D. Cutting-off funding to all financially unsound firms→ Prevents leverage

E. Cutting-off funding to Ponzi firms only→ Prevents further leverage

F. Combined effect of BCD→ Does it help to prevent bubbles?

G. Combined effect of BCE→ Does it help to prevent bubbles?





Prevention and mitigation policies: The Limits to Credit Growth

Comparison across regulations A - G

−30

00−

2500

−20

00−

1500

−10

00−

500

Parameters

full_

ampl

itude

_rec

essi

on

A B C D E F G

−30

00−

2500

−20

00−

1500

−10

00−

500

amplitude of recessions(output lost)

−10

000

−80

00−

6000

−40

00−

2000

Parameters

full_

cum

m_l

oss_

rece

ssio

n

A B C D E F G

−10

000

−80

00−

6000

−40

00−

2000

cumulative loss of output(amplitude & duration)




Main Conclusions

I To prevent large cumulative losses that follow from recessions,it is required to cut-off funding to all financially unsound firms(speculative and Ponzi firms).

I Mere capital ratios, and increasing them incrementally, do nothelp to prevent credit bubbles.

I Imposing strict limits to growth on the excessive supply ofcredit seems to work best to mitigate the severity of economicdownturns.


Thank you for your attention!

Model documentation:

www.wiwi.uni-bielefeld.de/lehrbereiche/vwl/etace/Eurace_Unibi/Papers:

I S van der Hoog & H Dawid (2015):Bubbles, Crashes and the Financial Cycle, Working Paper Bielefeld University.

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. Bünstorf (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/lehrbereiche/vwl/etace/Eurace_Unibi/



Outlook & Future research

I Macroprudential regulation

I Systemic risk (SIFIs, SIBs)

I Bank-firm networksI size effectsI balance sheet contagion

I Empirically-grounded bank behavior

I Credit quotasI Credit rationing of SMEsI Tighter integration of Basel III regulation




Scenario: Capital Adequacy Requirement

Output

0 100 200 300 400 500

1500

2000

2500

3000

Months

Eur

osta

t_ou

tput

alfa

2.0 8.0

Bank activity (α = 2)

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

Firm activity (α = 2)

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




Scenario: Minimum Reserve Requirement

Output

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 (β = 0.50)

0 100 200 300 400 500

05

1015

20

Months

Ban

k_ac

tive_

mul

ti


Firm activity (β = 0.50)

0 100 200 300 400 500

05

1015

20

Months

Fir

m_i

nsol

venc

y_S

L




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 (α = 2)

0 100 200 300 400 5000

510

1520

Months

Ban

k_ac

tive_

mul

ti


Firm activity (α = 2)

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


0.10 0.50

Bank activity (β = 0.50)

0 100 200 300 400 5000

510

1520

Months

Ban

k_ac

tive_

mul

ti


Firm activity (β = 0.50)

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



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



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/liquidity constraint)

No constraint

0 100 200 300 400 500

05

1015

20

Months

Ban

k_ac

tive_

mul

ti


Capital constraint (α = 2)

0 100 200 300 400 500

05

1015

20

Months

Ban

k_ac

tive_

mul

tiBank_active_none Bank_active_exposure Bank_active_liquidity

Liquidity constraint (β = 0.5)

0 100 200 300 400 500

05

1015

20

Months

Ban

k_ac

tive_

mul

ti





Scenarios: Firm Fragility

Firm E/A-ratio = 1/leverage

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




Prevention and mitigation - Bank dividend payout−

3000

−25

00−

2000

−15

00−

1000

−50

0

Parameters

full_

ampl

itude

_rec

essi

on

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90

−30

00−

2500

−20

00−

1500

−10

00−

500

amplitude of recessions

−10

000

−80

00−

6000

−40

00−

2000

Parameters

full_

cum

m_l

oss_

rece

ssio

n

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90

−10

000

−80

00−

6000

−40

00−

2000

cumulative loss




Bank accounting

1. Bank profit

πbt = rb

i Lbi − rb(∑h Mb

h +∑i Mbi ) + rECB(Mb

t −Dbt )

2. Bank cash and reserves

Mbt+1 = Mb

t + ∆Mbh + ∆Mb

i + (1− τ)max[0,πbt ]−db(1− τ)max[0,πb

t ]




Debt-equity transformation

3a. Insolvency bankruptcy

Debt renegotiation is addressed by re-scaling the total debt Dft with a debt rescaling

parameter ϕ.Target debt is given by:

D∗ = ϕAft with 0≤ ϕ ≤ 1 . (8)

After debt restructuring, the equity of the firm is now positive:

E∗ = (1−ϕ)Aft > 0. (9)

The new debt/equity-ratio is given by the constant D∗/E∗ = ϕ/(1−ϕ) < 1.




Debt-equity transformation

3b. Illiquidity bankruptcy

Debt-renegotiation is not necessary per se, rescaling of the debt is either based on thelevel of total assets or on the level of the original debt:

D∗ =

{ϕAf

t if ϕAft ≤ Df

tϕDf

t if ϕAft > Df

t .with 0≤ ϕ ≤ 1 . (10)

The new debt/equity-ratio is given by the following piece-wise function:

D∗/E∗ =

{ϕ/(1−ϕ) if ϕAf

t ≤ Dft

ϕ/(A/D−ϕ) if ϕAft > Df

t .(11)




Dividend payout rule

I 〈Rf 〉nR : average revenues over previous nR months (nR = 3,6,12)

I 〈Πf 〉nE : average net earnings (after-tax profits) over the last nE months

〈Rf 〉nR =1

nR

nR−1

∑i=0

Rft−i (12)

〈Πf 〉nE =1

nE

nE−1

∑i=0

Πft−i (13)

I Prevent liquidity hoarding by firms: Liquidity Buffer Stock

4. Dividend payout rule:

Div f =

{d · 〈Πf 〉4 if M f

t ≤ µ · 〈Rf 〉6〈Πf 〉4 if M f

t > µ · 〈Rf 〉6.d = 0.7,µ = 0.5 (14)




Exogenous Credit Rationing

5a. Full/Partial credit rationing is based on the (exogenously prescribed, ex ante)constraints of the bank (CAR, CRR).

I Full rationing for CAR constraint:

¯̀bit =


0 if 0≤ V bt ≤ PDit ·Lit

0 if V bt < 0.

(15)

I Partial rationing ("filling up to constraint") for CAR constraint:

¯̀bit =


V bt /PDit if 0≤ V b

t ≤ PDit ·Lit0 if V b

t < 0.(16)


bubbles, crashes & the financial cycle: the limits to ...€¦ · sander van der hoog bubbles,...

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