Lender Expertise and
Propagation of Credit Shocks
Garey Ramey
UC San Diego
July 2009
Previous literature: “Constrained borrower” view
Wealth constrained agency
Stiglitz and Weiss (1981), Bernanke and Gertler
(1989,1990), Kiyotaki and Moore (1997), Hölmstrom
and Tirole (1997,1998)
Previous literature: “Constrained borrower” view
Wealth constrained agency
Stiglitz and Weiss (1981), Bernanke and Gertler
(1989,1990), Kiyotaki and Moore (1997), Hölmstrom
and Tirole (1997,1998)
Injurious liquidation
Diamond and Dybvig (1983), Schleifer and
Vishny (1992), Hölmstrom and Tirole (1997),
Previous literature: “Constrained borrower” view
Wealth constrained agency
Stiglitz and Weiss (1981), Bernanke and Gertler
(1989,1990), Kiyotaki and Moore (1997), Hölmstrom
and Tirole (1997,1998)
Injurious liquidation
Diamond and Dybvig (1983), Schleifer and
Vishny (1992), Hölmstrom and Tirole (1997),
Key idea: Shocks propagate by affecting borrower collateral
This paper: “Constrained lender” view
1. Specialized lenders channel saving to investment –
“Brealey-Myers managers”
This paper: “Constrained lender” view
1. Specialized lenders channel saving to investment –
“Brealey-Myers managers”
2. Lenders form long-term contractual relationships with
projects, subject to agency costs
This paper: “Constrained lender” view
1. Specialized lenders channel saving to investment –
“Brealey-Myers managers”
2. Lenders form long-term contractual relationships with
projects, subject to agency costs
3. Averse shocks break up projects, lenders take time to
find new projects
This paper: “Constrained lender” view
1. Specialized lenders channel saving to investment –
“Brealey-Myers managers”
2. Lenders form long-term contractual relationships with
projects, subject to agency costs
3. Averse shocks break up projects, lenders take time to
find new projects
4. Household asset reallocation creates negative feedback
This paper: “Constrained lender” view
1. Specialized lenders channel saving to investment –
“Brealey-Myers managers”
2. Lenders form long-term contractual relationships with
projects, subject to agency costs
3. Averse shocks break up projects, lenders take time to
find new projects
4. Household asset reallocation creates negative feedback
Den Haan, Ramey and Watson, “Liquidity Flows and Fragility
of Business Enterprises,” JME, 2003
Results
1. Agency costs  shocks propagated through lenderproject relationships
Results
1. Agency costs  shocks propagated through lenderproject relationships
2. Household responses amplify propagation
Results
1. Agency costs  shocks propagated through lenderproject relationships
2. Household responses amplify propagation
3. Propagation is greater when shocks are more persistent
Results
1. Agency costs  shocks propagated through lenderproject relationships
2. Household responses amplify propagation
3. Propagation is greater when shocks are more persistent
4. Asset market feedbacks  shocks propagate across
sectors
Broader contribution:
New approach to modeling saving and investment
Broader contribution:
New approach to modeling saving and investment
Traditional model: Capital = accumulated output
Broader contribution:
New approach to modeling saving and investment
Traditional model: Capital = accumulated output
Lender expertise model: Capital = accumulated managerial
knowledge
Model
• Unit mass of households
• Unit mass of specialized lenders
• Periods t = 1,2,3,…
Model
• Unit mass of households
• Unit mass of specialized lenders
• Periods t = 1,2,3,…
• In each period, a lender is either matched with a project or
searching for a new project
nt  number of projects that produce in period t
Model
• Unit mass of households
• Unit mass of specialized lenders
• Periods t = 1,2,3,…
• In each period, a lender is either matched with a project or
searching for a new project
nt  number of projects that produce in period t
zt nt 1ait  output of project i
G (ait )  distributi on function of ait
Project surplus
Vt (ait )  project va lue
U t  value of unmatched lender
Project surplus
Vt (ait )  project va lue
U t  value of unmatched lender
St (ait )  project surplus  Vt(ait )  U t
Project surplus
Vt (ait )  project va lue
U t  value of unmatched lender
St (ait )  project surplus  Vt(ait )  U t

 max{zt nt 1ait  Et t 1[(1   )  St 1 (a ' )dG(a ' )  U t 1 ], 0}
0
 t 1  stochastic discount factor
  exogenous obsolesence probability
Agency cost
x  agency cost
 rent extracted from project surplus
Surplus must cover this cost or project is terminated –
Ramey and Watson (1997,1999,2000)
Agency cost
x  agency cost
 rent extracted from project surplus
Surplus must cover this cost or project is terminated –
Ramey and Watson (1997,1999,2000)
Rt  project te rmination margin
S t ( Rt )  x
ait  Rt  sufficient surplus to cover agency cost
ait  Rt  insufficie nt surplus, project is terminate d
Project search
vt  1  nt  number of searching lenders
pt  min{Avt ,1}  project finding probability
Project search
vt  1  nt  number of searching lenders
pt  min{Avt ,1}  project finding probability

U t  Et  t 1[ pt  S t 1 (a ' )dG(a ' )  U t 1 ]
0
Equilibrium conditions
zt nt 1Rt  (1    pt ) Et  t 1 zt 1nt11


 (a' Rt 1)dG(a' )  x
Rt 1
Equilibrium conditions
zt nt 1Rt  (1    pt ) Et  t 1 zt 1nt11


 (a' Rt 1)dG(a' )  x
Rt 1
nt 1  (1  G ( Rt 1 ))((1   )nt  pt vt )
Equilibrium conditions
zt nt 1Rt  (1    pt ) Et  t 1 zt 1nt11


 (a' Rt 1)dG(a' )  x
Rt 1
nt 1  (1  G ( Rt 1 ))((1   )nt  pt vt )

yt  zt nt  a ' dG(a ' )  aggregate output
Rt
Asset market
1
c
E0   t t  household utility function
t 0 1  

Household consumes agency cost  ct  yt

 yt 

 t 1   
 yt 1 
Asset market
1
c
E0   t t  household utility function
t 0 1  

Household consumes agency cost  ct  yt

 yt 

 t 1   
 yt 1 
Driving process
zt 1  zt e t 1
Numerical example
G (ait )  lognormal,   0,   .2
    .8,   .02,   .99,   1,   .8
A chosen so that Av   .22
Numerical example
G (ait )  lognormal,   0,   .2
    .8,   .02,   .99,   1,   .8
A chosen so that Av   .22
x  1 steady state :
R  .72, n  .78,
y  1.56, G( R)    .07
Numerical example
G (ait )  lognormal,   0,   .2
    .8,   .02,   .99,   1,   .8
A chosen so that Av   .22
x  1 steady state :
R  .72, n  .78,
y  1.56, G( R)    .07
x  0 steady state :
R  0, n  .92,
y  1.90, G( R)    .02
Extensions
1. Lender effort
Extensions
1. Lender effort
2. Physical capital
Extensions
1. Lender effort
2. Physical capital
3. Long-term contracting, liquidity hoarding
Extensions
1. Lender effort
2. Physical capital
3. Long-term contracting, liquidity hoarding
4. Countercyclical policy – “bailouts”