How Credit Affects Revealed Risk Preferences
Evidence from Home Equity Loans and Voluntary Unemployment
Insurance
Kristoffer Markwardt∗
∗ SFI
Alessandro Martinello∗
and University of Copenhagen
December, 2012
László Sándor+
+ Harvard
University
Introduction
Background
Data
Results
Liquidity and risk - empirical evidence
What you know already
• Dah!
% Risk exposure
% Risk aversion
% Savings
% Liquidity
=⇒
• Life cycle buffers (Carroll, 1997; 2001), committments (Chetty and
Szeidl, 2007), constraints (Deaton, 1991; Alessie et al., 1997)
• But also, wealth used as buffer stock
• Home equity loans (Hurst & Stafford, 2004)
• Intuition: % Buffer pool
% Risk I can take
=⇒
• Trading liquidity with risk? Risk
⇐⇒
Liquidity?
What we want to convince you of
• Yes: people who has more access to liquidity causally take more
risk than others:
Risk
⇐=
Liquidity
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Conclusions
Introduction
Background
Data
Results
Liquidity and risk - empirical evidence
What you know already
• Dah!
% Risk exposure
% Risk aversion
% Savings
% Liquidity
=⇒
• Life cycle buffers (Carroll, 1997; 2001), committments (Chetty and
Szeidl, 2007), constraints (Deaton, 1991; Alessie et al., 1997)
• But also, wealth used as buffer stock
• Home equity loans (Hurst & Stafford, 2004)
• Intuition: % Buffer pool
% Risk I can take
=⇒
• Trading liquidity with risk? Risk
⇐⇒
Liquidity?
What we want to convince you of
• Yes: people who has more access to liquidity causally take more
risk than others:
Risk
⇐=
Liquidity
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Conclusions
Introduction
Background
Data
Results
Liquidity and risk - empirical evidence
What you know already
• Dah!
% Risk exposure
% Risk aversion
% Savings
% Liquidity
=⇒
• Life cycle buffers (Carroll, 1997; 2001), committments (Chetty and
Szeidl, 2007), constraints (Deaton, 1991; Alessie et al., 1997)
• But also, wealth used as buffer stock
• Home equity loans (Hurst & Stafford, 2004)
• Intuition: % Buffer pool
% Risk I can take
=⇒
• Trading liquidity with risk? Risk
⇐⇒
Liquidity?
What we want to convince you of
• Yes: people who has more access to liquidity causally take more
risk than others:
Risk
⇐=
Liquidity
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Conclusions
Introduction
Background
Data
Results
Conclusions
Why us
Do we care?
• Relevant for optimal UI design, commitments, role of home equity
• Micro effects of credit expansions (pre-) and crunches (post-crisis)
!Problems. . .
1
2
Measure preferences for risk
Causality (⇐=):
• Liquidity endogenous
• Hard to separate wealth and liquidity shocks (Chetty and Szeidl 2012)
. . . solved: the case of Denmark!
1
2
UI voluntary and uniform: demand for UI ≈ revealed risk preferences
Mortgage reform of March 1992 (Leth-Petersen, 2010)
• Exogenous shock, only for housing equity holders
• Affected only access to credit (liquidity), not wealth
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Introduction
Background
Data
Results
Conclusions
Why us
Do we care?
• Relevant for optimal UI design, commitments, role of home equity
• Micro effects of credit expansions (pre-) and crunches (post-crisis)
!Problems. . .
1
2
Measure preferences for risk
Causality (⇐=):
• Liquidity endogenous
• Hard to separate wealth and liquidity shocks (Chetty and Szeidl 2012)
. . . solved: the case of Denmark!
1
2
UI voluntary and uniform: demand for UI ≈ revealed risk preferences
Mortgage reform of March 1992 (Leth-Petersen, 2010)
• Exogenous shock, only for housing equity holders
• Affected only access to credit (liquidity), not wealth
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Introduction
Background
Data
Results
Conclusions
Why us
Do we care?
• Relevant for optimal UI design, commitments, role of home equity
• Micro effects of credit expansions (pre-) and crunches (post-crisis)
!Problems. . .
1
2
Measure preferences for risk
Causality (⇐=):
• Liquidity endogenous
• Hard to separate wealth and liquidity shocks (Chetty and Szeidl 2012)
. . . solved: the case of Denmark!
1
2
UI voluntary and uniform: demand for UI ≈ revealed risk preferences
Mortgage reform of March 1992 (Leth-Petersen, 2010)
• Exogenous shock, only for housing equity holders
• Affected only access to credit (liquidity), not wealth
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Introduction
Background
Data
Results
Conclusions
86
88
90
92
94
Preview: percentage of insured over time
1986
1988
1990
1992
Home equity in 1991
1994
No equity in home
Equity: N1= 35710; No Equity: N0= 78116
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
1996
Introduction
Background
Data
Results
The credit market reform
Took effect on May 21, 1992; unexpected (Leth-Petersen, AER 2010)
Main elements:
• Expansion of maximum maturity of a real estate loan (from 20) to 30 years
• Right to remortgage loan
• Allows to use house as collateral for consumption loans
• Before 1992: loan only for house purchase
• 60% of house value from May 1992, 80% from December 1992
Loan against equity =⇒ unexpected liquidity shock
• Only to households with housing equity
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Conclusions
Introduction
Background
Data
Results
The credit market reform
Took effect on May 21, 1992; unexpected (Leth-Petersen, AER 2010)
Main elements:
• Expansion of maximum maturity of a real estate loan (from 20) to 30 years
• Right to remortgage loan
• Allows to use house as collateral for consumption loans
• Before 1992: loan only for house purchase
• 60% of house value from May 1992, 80% from December 1992
Loan against equity =⇒ unexpected liquidity shock
• Only to households with housing equity
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Conclusions
Introduction
Background
Data
Results
Conclusions
Unemployment insurance in DK
Voluntary!
Uniform insurance product
• Cost, requirements and benefits stable over time
• Centrally regulated → stable across funds
• Small differences in administrative costs and services (e.g. job search)
Convenient
• Benefit cap ≈ $1,800 per month
• Actuarially fair given 2.6% u.r.
=⇒
High insured %
Social security (fallback option) not considered here. . . almost!
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Introduction
Background
Data
Results
Conclusions
Economic environment
15
160
140
10
120
5
100
0
80
1980
1985
1990
GDP growth
Interest rate
1995
Unemployment rate
House price index
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
2000
Introduction
Background
Data
Results
Conclusions
Data - Danish registers
• 100% Danish population
• Primarily tax reports
• 1987-1996 (wealth tax)
• Info on income, wealth, insurance status, demographics, SES . . .
Selection criteria
Individuals left
All individuals in cohorts 1957 − 1962
Trim financial outliers
Balance sample
Drop ever out of labor force
Drop ever self-employed
Drop ever in education
Industry-related selection
Homeowner in 1992
Trim top & bottom 1% of liquidity shock
482519
462647
417500
308554
274019
245805
210234
123558
121086
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Introduction
Background
Data
Results
Conclusions
Key variables
Liquidity
shock
L1991 =
0.8 × H1991 − M1991
YP
Housing
• Publicly assessed value, December 31
• Loans granted on basis of market price
→ scale by public/market ratio, from housing transactions
Mortgage
• Market value, December 31
• Bond price fluctuations =⇒ measurement error; noise
• Only consistently reported → 1992
Permanent
income
• Comprise 22 years of wage income (’87-’08)
• Individuals on different parts of earnings path
→ include as many years as possible
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Introduction
Background
Data
Results
Conclusions
Key variables
Liquidity
shock
L1991 =
0.8 × H1991 − M1991
YP
Housing
• Publicly assessed value, December 31
• Loans granted on basis of market price
→ scale by public/market ratio, from housing transactions
Mortgage
• Market value, December 31
• Bond price fluctuations =⇒ measurement error; noise
• Only consistently reported → 1992
Permanent
income
• Comprise 22 years of wage income (’87-’08)
• Individuals on different parts of earnings path
→ include as many years as possible
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Introduction
Background
Data
Results
Conclusions
Descriptives: Home owners in 1991 by size of liquidity shock
Q1
Liquidity shock
Insurance rate 1989
Insurance rate 1991
Insurance rate 1993
Moved to 1991 housing
Housing value
Mortgage value
Permanent income
Disposable income
Liquid Assets
Debts
Employment rate
Unemployment risk
Industry, fewest
Industry, most
Age
Years of schooling
Spouse
# kids
Female
N
Q2
Q3
Q4
Population
-.98
-.34
-.02
.64
86
86.9
88.9
89.8
73.6
86.9
87.7
89.5
90.4
74.4
90
90.5
91.8
92.6
78.2
1986.8 1986.7 1986.1 1984.7
63688 58700 58616 64313
84358 59722 47611 33325
33959 35036 34580 32701 28257
33957 32903 32041 30922 27728
2833
2930
2995
3263
1838
14936 15976 16123 16294
8968
97.5
97.7
97.4
96.9
74.2
8.5
8.4
8.6
9.1
8.8
− Mining −
− Fishing −
?
− − −− Metal industry − − −
?
31.5
31.6
31.6
31.9
31.5
12.7
12.7
12.6
12.2
11.9
62.9
59.7
60.2
59.6
47.4
1.3
1.2
1.3
1.3
1.1
43.9
37.3
35.5
42
48.7
30272 30271 30272 30271 452583
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Introduction
Background
Data
Results
Conclusions
Descriptives: Home owners in 1991 by size of liquidity shock
Q1
Liquidity shock
Insurance rate 1989
Insurance rate 1991
Insurance rate 1993
Moved to 1991 housing
Housing value
Mortgage value
Permanent income
Disposable income
Liquid Assets
Debts
Employment rate
Unemployment risk
Industry, fewest
Industry, most
Age
Years of schooling
Spouse
# kids
Female
N
Q2
Q3
Q4
Population
-.98
-.34
-.02
.64
86
86.9
88.9
89.8
73.6
86.9
87.7
89.5
90.4
74.4
90
90.5
91.8
92.6
78.2
1986.8 1986.7 1986.1 1984.7
63688 58700 58616 64313
84358 59722 47611 33325
33959 35036 34580 32701 28257
33957 32903 32041 30922 27728
2833
2930
2995
3263
1838
14936 15976 16123 16294
8968
97.5
97.7
97.4
96.9
74.2
8.5
8.4
8.6
9.1
8.8
− Mining −
− Fishing −
?
− − −− Metal industry − − −
?
31.5
31.6
31.6
31.9
31.5
12.7
12.7
12.6
12.2
11.9
62.9
59.7
60.2
59.6
47.4
1.3
1.2
1.3
1.3
1.1
43.9
37.3
35.5
42
48.7
30272 30271 30272 30271 452583
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Introduction
Background
Data
Results
Conclusions
Descriptives: Home owners in 1991 by size of liquidity shock
Q1
Liquidity shock
Insurance rate 1989
Insurance rate 1991
Insurance rate 1993
Moved to 1991 housing
Housing value
Mortgage value
Permanent income
Disposable income
Liquid Assets
Debts
Employment rate
Unemployment risk
Industry, fewest
Industry, most
Age
Years of schooling
Spouse
# kids
Female
N
Q2
Q3
Q4
Population
-.98
-.34
-.02
.64
86
86.9
88.9
89.8
73.6
86.9
87.7
89.5
90.4
74.4
90
90.5
91.8
92.6
78.2
1986.8 1986.7 1986.1 1984.7
63688 58700 58616 64313
84358 59722 47611 33325
33959 35036 34580 32701 28257
33957 32903 32041 30922 27728
2833
2930
2995
3263
1838
14936 15976 16123 16294
8968
97.5
97.7
97.4
96.9
74.2
8.5
8.4
8.6
9.1
8.8
− Mining −
− Fishing −
?
− − −− Metal industry − − −
?
31.5
31.6
31.6
31.9
31.5
12.7
12.7
12.6
12.2
11.9
62.9
59.7
60.2
59.6
47.4
1.3
1.2
1.3
1.3
1.1
43.9
37.3
35.5
42
48.7
30272 30271 30272 30271 452583
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Introduction
Background
Data
Results
Conclusions
Discrete treatment
Conditional
86
86
88
88
90
90
92
92
94
94
Unconditional
1986
1988
1990
Home equity in 1991
1992
1994
1996
1986
1988
No equity in home
1990
Home equity in 1991
Equity: N1= 35710; No Equity: N0= 78116
Equity: N1= 35710; No Equity: N0= 78116
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
1992
1994
No equity in home
1996
Introduction
Background
Data
Results
Conclusions
Continuous treatment
.5
∆ %insured in 1988
.3
.1
−.1
−.3
−.5
−.7
−2
−1
0
1
1992 liquidity shock
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
2
Introduction
Background
Data
Results
Conclusions
Continuous treatment
−.5
∆ %insured in 1989
−.7
−.9
−1.1
−1.3
−1.5
−1.7
−2
−1
0
1
1992 liquidity shock
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
2
Introduction
Background
Data
Results
Conclusions
Continuous treatment
.3
∆ %insured in 1990
.1
−.1
−.3
−.5
−.7
−.9
−2
−1
0
1
1992 liquidity shock
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
2
Introduction
Background
Data
Results
Conclusions
Continuous treatment
1.6
∆ %insured in 1991
1.4
1.2
1
.8
.6
.4
−2
−1
0
1
1992 liquidity shock
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
2
Introduction
Background
Data
Results
Conclusions
Continuous treatment
2.2
∆ %insured in 1992
2
1.8
1.6
1.4
1.2
1
−2
−1
0
1
1992 liquidity shock
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
2
Introduction
Background
Data
Results
Conclusions
Continuous treatment
1.6
∆ %insured in 1993
1.4
1.2
1
.8
.6
.4
−2
−1
0
1
1992 liquidity shock
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
2
Introduction
Background
Data
Results
Conclusions
Continuous treatment
1.3
∆ %insured in 1994
1.1
.9
.7
.5
.3
.1
−2
−1
0
1
1992 liquidity shock
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
2
Introduction
Background
Data
Results
Conclusions
Continuous treatment
1.1
∆ %insured in 1995
.9
.7
.5
.3
.1
−.1
−2
−1
0
1
1992 liquidity shock
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
2
Introduction
Background
Data
Results
Conclusions
Continuous treatment
.9
∆ %insured in 1996
.7
.5
.3
.1
−.1
−.3
−2
−1
0
1
1992 liquidity shock
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
2
Introduction
Background
CONTINUOUS
Data
OLS
MARG
Year
Cohort
Industry
Education
0.959**
(0.117)
-0.462**
(0.0871)
0.224
(0.239)
-0.480**
(0.0120)
-2.149**
(0.185)
-4.218**
(0.464)
0.896**
(0.0253)
0.358**
(0.0736)
1.361**
(0.197)
1.090**
(0.132)
Yes
Yes
Yes
Yes
4.457**
(0.737)
-2.389**
(0.627)
-0.231
(0.916)
-0.495**
(0.0350)
-5.817**
(0.882)
-0.0295
(1.993)
0.0320
(0.125)
0.442
(0.421)
6.246**
(0.872)
4.048**
(0.760)
Yes
Yes
Yes
Yes
Observations
1089774
79650
1991 equity
1991 equity, post
1991 liquid assets
Permanent income
1991 debts
Disposable income
Unemployment risk
N. kids
Female
Couple
Results
FE
LOGIT
0.670**
(0.105)
Yes
No
Yes
No
0.122**
(0.00689)
-0.0136
(0.0110)
0.0604**
(0.00697)
-0.0395**
(0.000361)
-0.236**
(0.00572)
-0.267**
(0.0166)
0.108**
(0.00142)
0.0455**
(0.00429)
0.144**
(0.00845)
0.139**
(0.00797)
Yes
Yes
Yes
Yes
1089774
1089774
-0.465**
(0.0864)
3.817**
(0.271)
0.357**
(0.0185)
0.226**
(0.0603)
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Conclusions
FE LOGIT
-0.0421*
(0.0197)
0.961**
(0.0520)
0.0729**
(0.00409)
0.101**
(0.0146)
0.243**
(0.0252)
Yes
No
Yes
No
145242
Introduction
Background
DISCRETE
Data
OLS
MARG
Year
Cohort
Industry
Education
0.794**
(0.166)
-0.572**
(0.123)
0.257
(0.241)
-0.484**
(0.0124)
-2.081**
(0.186)
-4.458**
(0.461)
0.912**
(0.0262)
0.395**
(0.0761)
1.318**
(0.204)
1.038**
(0.136)
Yes
Yes
Yes
Yes
2.696**
(1.029)
-1.117
(0.844)
-0.102
(0.928)
-0.494**
(0.0361)
-5.659**
(0.902)
-0.538
(2.058)
0.0301
(0.129)
0.405
(0.436)
6.247**
(0.903)
4.203**
(0.788)
Yes
Yes
Yes
Yes
Observations
1024434
74835
Treated group
Treatment
1991 liquid assets
Permanent income
1991 debts
Disposable income
Unemployment risk
N. kids
Female
Couple
Results
FE
LOGIT
0.668**
(0.108)
Yes
No
Yes
No
0.0911**
(0.0101)
-0.00731
(0.0161)
0.0647**
(0.00688)
-0.0395**
(0.000373)
-0.224**
(0.00571)
-0.293**
(0.0172)
0.109**
(0.00146)
0.0499**
(0.00442)
0.136**
(0.00867)
0.130**
(0.00820)
Yes
Yes
Yes
Yes
1024434
1024434
-0.547**
(0.122)
3.800**
(0.279)
0.357**
(0.0191)
0.253**
(0.0624)
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Conclusions
FE LOGIT
-0.0208
(0.0300)
0.959**
(0.0535)
0.0723**
(0.00420)
0.111**
(0.0151)
0.238**
(0.0259)
Yes
No
Yes
No
137421
Introduction
Background
Data
Results
Conclusions
Robustness check: Stable households
OLS
MARG
FE
LOGIT
FE LOGIT
Continuous
-0.492**
(0.0953)
-2.431**
(0.674)
-0.441**
(0.0873)
-0.00958
(0.0122)
-0.0123
(0.0254)
Discrete
-0.639**
(0.135)
-1.049
(0.909)
-0.536**
(0.124)
-0.00832
(0.0179)
-0.00201
(0.0387)
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
No
Yes
989549
791475
72151
57414
989549
791475
989549
791475
120500
87941
Year
Cohort
Industry
Education
Other controlsa
Observations, cont
Observations, disc
Standard errors in parentheses; * p<0.05, ** p<0.01
a Other controls include liquid assets and debts in 1991, permanent income, disposable
income, unemployment risk, gender, # kids and a couple indicator.
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Introduction
Background
Data
Results
Conclusions
Placebo reforms
.3
∆ %insured in 1988
.1
−.1
−.3
−.5
−.7
−.9
−2
−1
0
1
Hypothetical liquidity shock
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
2
3
Introduction
Background
Data
Results
Conclusions
Placebo reforms
−.7
∆ %insured in 1989
−.9
−1.1
−1.3
−1.5
−1.7
−1.9
−2
−1
0
1
Hypothetical liquidity shock
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
2
Introduction
Background
Data
Results
Conclusions
Placebo reforms
.2
∆ %insured in 1990
0
−.2
−.4
−.6
−.8
−1
−2
−1
0
1
Hypothetical liquidity shock
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
2
Introduction
Background
Data
Results
Conclusions
Placebo reforms
1.6
∆ %insured in 1991
1.4
1.2
1
.8
.6
.4
−2
−1
0
1
Hypothetical liquidity shock
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
2
Introduction
Background
Data
Results
Conclusions
Placebo reforms
Real reform in 1992
1.6
2.2
1.4
2
∆ %insured in 1992
∆ %insured in 1991
Placebo reform in 1991
1.2
1
.8
1.8
1.6
1.4
1.2
.6
1
.4
−2
−1
0
1
2
−2
−1
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
0
1992 liquidity shock
Hypothetical liquidity shock
László Sándor
1
2
Introduction
Background
Data
Results
Conclusions
Conclusions
Sum up
• Small but significant effect of access to credit on demand for UI
• Transaction costs (US), cost-effectiveness of program, gross effect
• Robust to 6= specifications, placebos, common trend checks
Contributions
• Empirical evidence on effects of liquidity, undocumented
• Disentangle wealth from liquidity effect
• House price variation (Chetty & Szeidl, 2012; Hryshko et al.) confound
the two
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor
Introduction
Background
Data
Results
Conclusions
Conclusions
Sum up
• Small but significant effect of access to credit on demand for UI
• Transaction costs (US), cost-effectiveness of program, gross effect
• Robust to 6= specifications, placebos, common trend checks
Contributions
• Empirical evidence on effects of liquidity, undocumented
• Disentangle wealth from liquidity effect
• House price variation (Chetty & Szeidl, 2012; Hryshko et al.) confound
the two
How Credit Affects Revealed Risk Preferences
Kristoffer Markwardt
Alessandro Martinello
December, 2012
László Sándor