A Macroeconomic Model of
Endogenous Systemic Risk Taking
D. Martinez-Miera and J. Suarez
Discussion Rafal Raciborski
DG ECFIN, European Commission
Norges Bank, Oslo, 29 - 30 November 2012
Disclaimer
The views expressed are the author’s alone and do not necessarily correspond to those of the
European Commission.
Context
• It's been almost 5 years that the world has been in the financial and economic crisis…
• …with its causes still not yet fully understood…
• …but with a contribution of the financial sector generally unquestioned
Most economists would agree the financial sector (banks in particular) may contribute to and perhaps
generate systemic risk
This paper
• Discusses one particular channel via which
systemic risk may originate in the banking sector
– Idea most closely linked to the 'risk-shifting literature’
• Embeds it into a general equilibrium model
– May be disputed whether the systemic risk is truly endogenous; more on it later
• Solves nonlinearly to discuss optimal bank capital requirements
The model: general idea
• General result (Jensen&Meckling, 1976;
Stiglitz&Weiss, 1981; Allen&Gale, 2000):
– Limited liability non-convexities in the profit maximizer's problem
– The maximizer may then prefer a riskier project, pushing its risk on other agents (=risk shifting)
• Banks protected by deposit insurance (limited liability) they like riskier projects
• But: riskier behavioursystemic risk
– Assume that riskier projects are systematically linked
•
The model: available projects
• 2 types of projects:
1. Less risky projects (in terms of its variance and its mean):
idiosyncratic risk
2. More risky projects: risk perfectly correlated
• Higher variance of the risky projects to induce risk- shifting in the banks
• Correlation of risky projects=systemic risk
• Lower unconditional mean of the risky project
probably makes things harder; conveys the idea of systemic risk being "bad"
The model: equilibrating force
Due to limited liability banks like riskier projects;
why don't we observe only the riskier ones being chosen (share of risky projects x=1)?
• Crucial variable: stochastic marginal value of one unit of a banker's wealth
• Upon the realization of the systemic risk:
– Wealth of 'risky banks' is wiped out
– Scarce driven up for save banks: last bank standing effect (in the spirit of Perotti&Suarez, 2002)
• In equilibrium banks indifferent between projects x
•
Welfare
• Banks’ agency problem affects negatively the economy via 2 channels:
– Static losses: picking inefficient projects
– Dynamic losses: loss of bank equity (and, hence, lending capacity) in the event of a systemic shock
• Measurement:
– All agents risk neutral; but GDP does not reflect welfare well
– GDP (=added value) excludes capital losses
– Does output (y=GDP+undepreciated K) correlate perfectly with welfare in your model?
Capital requirements
• Increased capital requirements γ make capital scarcer ( higher) higher incentive to choose safer projects higher proportion of bank
equity invested in safer projects
• But, banks’ lending capacity reduced lower average efficiency
• Trade-off optimal γ
•
Results
• For the benchmark calibration:
– With low γ=7% fraction of capital invested in systemic projects very large (70%)
– Systemic shocks very painful (31% drop of GDP) – Optimal γ large (14%)
– Optimal γ welfare higher by about 1%
• Number of extensions
– Interesting perverse results
•
Minor remarks (I)
• You assume a pooling equilibrium
– Are there other types of equilibria?
– If so, how do we know yours is the relevant one?
• One of your main contributions: quantitative results (“high optimal γ”); but your model
‘very stylized’. For example:
– Crucial role of the slope of
– It would be less steep if labour were variable…
•
Minor remarks (II)
• An issue with calibration?
– You assume 35% depreciation in failed firms – For γ=7%, 70% of all projects are systemic
– This gives 35%×70%=25% capital depreciation in the economy in the event of a systemic shock
– Also the fall in GDP (30%) very large
• Develop the sensitivity analysis
– “The choices for the values of […] ψ and φ are quite tentative.”
General equilibrium?
Is systemic risk endogenous?
• Yes: share of bad projects x=f(,regulation)
• No: systemically-risky projects are always there to be picked only the severity of the crisis endogenous
I believe we cannot do w/o opening the black box – see next 2 slides
•
Take the black box as given
What are the systemic projects?
• Allen&Gale (2000): oil shock – convincing, but with a limited application (Norway!)
• Your footnote 1: housing bust:
– Is it systemic? What makes it so?
– Was it (before 2007) considered risky? (The notion that “house prices never fall”)
• Even so: Is it plausible? Convince the reader!
• What happens in your model if you have 2 types of risky projects: identical payoffs, but projects of the 2nd type independent
Bring your channel to the data
“Systemic Banking Crises facts” (Boissay et al.):
a) SBC’s are rare and deep
b) SBC’s are closely linked to credit developments
Ad. a) Your model can obviously match it, but:
– by imposing exogenous prob. of a systemic crisis – endogenous risk correlation in recessions,
Brunnermeier&Sannikov, 2011 (parsimony)
Ad. b) Nothing to say about it
– again, endogenous link (Boissay et al., 2012)
– hard to make policy advice w/o a crucial channel
Need to open up the black box
Interesting perverse effect?
• Your results sensitive to the exogenous probability of a systemic crisis
– Benchmark: ε=0.03
• One view: makes your results fragile
• Alternative view: innovations that make the economy safer (ε↘) make crises deeper…
Worth exploring?
