1/1 Individual Risk Attitudes New Evidence from a Large, Representative, Experimentally-Validated Survey Thomas Dohmen, Armin Falk, David Huffman, Uwe.

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Individual Risk Attitudes

New Evidence from a Large, Representative, Experimentally-Validated Survey

Thomas Dohmen, Armin Falk, David Huffman, Uwe Sunde

(IZA and University of Bonn)

Jürgen Schupp, Gert G. Wagner

(DIW, Berlin, and IZA, Bonn)

Oxford, July 2006

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Motivation Risk and uncertainty are pervasive in

economic life.

As a consequence, individual attitudes towards risk play a central role in economic theory. Predicted to have a decisive impact on almost

every important economic decision.

The aim of this paper is to improve understanding and measurement of individual risk attitudes.

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Research questions Do risk attitudes vary across individuals? What are the determinants of individual

differences? Are hypothetical measures of risk attitudes

reliable predictors of actual risky behavior? What is the impact of context on willingness to

take risks? Is there a single underlying preference that

determines risk-taking in all contexts? How does the impact of personal characteristics

vary with context? Can survey questions incorporating situation-

appropriate context outperform standard lottery measures of risk preference?

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Data Large, representative sample: 22,019

individuals. 2004 Wave of the Socioeconomic Panel

(SOEP) Extensive socio-demographic information.

New survey measures. New survey measures.

Complementary field experiment: 450 individuals. Subjects answer same survey measures as in

SOEP. Also make risky choices for real money.

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Survey Measures General Risk Question

How do you see yourself: Are you generally a person who is fully prepared to take risks or do you try to avoid taking risks? Please tick a box on the scale, where the value 0 means: ‘unwilling to take risks’ and the value 10 means: ‘fully prepared to take risks’.

11-point response scale: completely unwilling to completely willing. Open-ended: Respondent free to think about curvature of

utility,but also imagine stakes and probabilities involved in taking risks.

Context Questions Same scale, but ask about: Car driving, health, financial matters,

sports and leisure, career.

Hypothetical Investment Question Willingness to invest in a realistic investment opportunity, with

explicit stakes and probabilities. Holds beliefs constant, measures risk preference.

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Outline of the talk Distribution of risk attitudes. Determinants. Does the survey measure predict

behavior? Alternative measure of risk preference. Impact of context on risk attitudes. Compare predictive power of different

measures. Evidence on occupational sorting and

regional mobility. Intergenerational transmission of risk

attitudes and assortative mating.

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Heterogeneity and Determinants

General Risk Question

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Distribution of Willingness to Take Risks0

.05

.1.1

5.2

Fra

ction

0 2 4 6 8 100=completely unwilling; 10=completely willing

All Respondents - SOEP 2004

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Gender and Willingness to Take Risks-.

06

-.04

-.02

0.0

2.0

4D

iffe

rence in F

raction

0 2 4 6 8 100=completely unwilling; 10=completely willing

Gender Differences

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Age and Willingness to Take Risks

0.2

.4.6

.81

Fra

ctio

n U

nwill

ing

0.2

.4.6

.81

Fra

ctio

n W

illin

g

20 30 40 50 60 70 80 90Age in Years

High Willingness to Take Risks 10 9 8 7 6Low Willingness to Take Risks 4 3 2 1 0

Men

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Age and Willingness to Take Risks

0.2

.4.6

.81

Fra

ctio

n U

nwill

ing

0.2

.4.6

.81

Fra

ctio

n W

illin

g

20 30 40 50 60 70 80 90Age in Years

High Willingness to Take Risks 10 9 8 7 6Low Willingness to Take Risks 4 3 2 1 0

Women

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Parental Ed. and Willingness to Take Risks

0.0

5.1

.15

.2F

ract

ion

0 2 4 6 8 10Response to General Risk Question

(0=completely unwilling; 10=completely willing)

Father's education: Abitur not completed

0.0

5.1

.15

.2F

ract

ion

0 2 4 6 8 10Response to General Risk Question

(0=completely unwilling; 10=completely willing)

Mother's education: Abitur not completed

0.0

5.1

.15

.2F

ract

ion

0 2 4 6 8 10Response to General Risk Question

(0=completely unwilling; 10=completely willing)

Father's education: Abitur completed

0.0

5.1

.15

.2F

ract

ion

0 2 4 6 8 10Response to General Risk Question

(0=completely unwilling; 10=completely willing)

Mother's education: Abitur completed

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Height and Willingness to Take Risks

0.2

.4.6

.81

Fra

ctio

n U

nwill

ing

0.2

.4.6

.81

Fra

ctio

n W

illin

g

150 155 160 165 170 175 180 185 190 195Height in cm

High Willingness to Take Risks 10 9 8 7 6Low Willingness to Take Risks 4 3 2 1 0

Men

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Height and Willingness to Take Risks

0.2

.4.6

.81

Fra

ctio

n U

nwill

ing

0.2

.4.6

.81

Fra

ctio

n W

illin

g

150 155 160 165 170 175 180 185 190 195Height in cm

High Willingness to Take Risks 10 9 8 7 6Low Willingness to Take Risks 4 3 2 1 0

Women

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Determinants of Risk Attitudes (Probit)

Dependent Variable: General Risk Attitude (1=Willing to Take Risks) (Marginal Effects) (1) Female -0.111*** (0.009)Age -0.005*** (0.000)Height (in cm) 0.005*** (0.001)Abitur Mother 0.062*** (0.016)Abitur Father 0.036***

(0.012)

Individual Wealth and Income NoHousehold Wealth and Income NoAdditional Controls NoObservations 19438

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Determinants of Risk Attitudes (Probit)

Dependent Variable: General Risk Attitude (1=Willing to Take Risks) (Marginal Effects) (1) (2)Female -0.111*** -0.093*** (0.009) (0.011)Age -0.005*** -0.003*** (0.000) (0.000)Height (in cm) 0.005*** 0.003*** (0.001) (0.001)Abitur Mother 0.062*** 0.038*** (0.016) (0.018)Abitur Father 0.036*** -0.011

(0.012) (0.013)

Individual Wealth and Income No YesHousehold Wealth and Income No NoAdditional Controls No YesObservations 19438 16284

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Determinants of Risk Attitudes (Probit)

Dependent Variable: General Risk Attitude (1=Willing to Take Risks) (Marginal Effects) (1) (2) (3)Female -0.111*** -0.093*** -0.104*** (0.009) (0.011) (0.011)Age -0.005*** -0.003*** -0.003*** (0.000) (0.000) (0.000)Height (in cm) 0.005*** 0.003*** 0.003*** (0.001) (0.001) (0.001)Abitur Mother 0.062*** 0.038*** 0.027 (0.016) (0.018) (0.017)Abitur Father 0.036*** -0.011 -0.005

(0.012) (0.013) (0.013)

Individual Wealth and Income No Yes NoHousehold Wealth and Income No No YesAdditional Controls No Yes YesObservations 19438 16284 17435

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Can Survey QuestionsPredict Behavior?

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Experimental Design 450 subjects. Representative sample of adult population in Germany. Subjects answer the general risk question. Subjects also make 20 choices for real money Each choice is between a lottery and a safe option:

Lottery: 300 Euros or 0 Euros, with equal probability. Safe option: X Euros for sure, where X varies across choices. X=0 in first choice, increases to 190 in 20th choice (by 10’S)

One choice is randomly selected and implemented. Measure of risk taking: how high does X have to be, to

induce a switch from the lottery to the safe option?

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Lottery Choices and Survey Answers

6080

100

120

Ave

rage

Saf

e V

alue

at S

witc

h P

oint

0 1 2 3 4 5 6 7 8 9 10Response to General Risk Question

Fitted Line

(0=completely unwilling; 10=completely willing)

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Validation of Survey Risk Measure

(1) (2) (3)Willingness to Take Risk in General 5.614*** 4.447*** 4.010***

[1.082] [1.109] [1.446]

Controls for Gender, Age, Height No Yes YesOther Controls No No Yes

Constant 57.097*** -68.309 -33.005[5.836] [70.621] [127.048]

R-squared 0.06 0.09 0.25Obs 450 450 313

Dependent Variable: Value of Safe Option at Switch Point

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Alternative Measureof Risk Attitudes

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Survey measure Hypothetical Investment Scenario

Choose how much of 100,000 Euros to invest in a hypothetical asset.

doubles the investment, or returns half, with equal probability.

Possible amounts: 0, 20K, 40K, 60K, 80K, 100K

Holds beliefs constant across individuals. Differences can be attributed to differences in

curvatures of utility. Incorporates context of real financial decision.

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Investment in Hypothetical Asset

0.2

.4.6

Fra

ctio

n

0 20 40 60 80 100Amount invested in thousands of Euros

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Determinants of Investment (Probit)

Dependent Variable: Amount Invested (0 to 100,000)(1)

Female -5,997.97*** [811.62]Age -352.65*** [20.51]Height (in cm) 204.98*** [48.85]Abitur Mother 1,420.56 [1,291.08]Abitur Father 6,521.58***

[986.43]

Individual Wealth and Income NoHousehold Wealth and Income NoOther Controls NoObs. 19,419

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Determinants of Investment (Probit)

Dependent Variable: Amount Invested (0 to 100,000)(1) (2)

Female -5,997.97*** -6,597.82*** [811.62] (978.35)Age -352.65*** -233.77*** [20.51] (46.46)Height (in cm) 204.98*** 102.51* [48.85] (59.93)Abitur Mother 1,420.56 -144.79 [1,291.08] (1508.10)Abitur Father 6,521.58*** 2,429.78**

[986.43] (1128.95)

Individual Wealth and Income No YesHousehold Wealth and Income No NoOther Controls No YesObs. 19,419 16,264

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Determinants of Investment (Probit)

Dependent Variable: Amount Invested (0 to 100,000)(1) (2) (3)

Female -5,997.97*** -6,597.82*** -6,793.28*** [811.62] (978.35) (936.11)Age -352.65*** -233.77*** -200.19*** [20.51] (46.46) (44.42)Height (in cm) 204.98*** 102.51* 105.15* [48.85] (59.93) (57.73)Abitur Mother 1,420.56 -144.79 89.58 [1,291.08] (1508.10) (1434.26)Abitur Father 6,521.58*** 2,429.78** 2,595.48**

[986.43] (1128.95) (1085.43)

Individual Wealth and Income No Yes NoHousehold Wealth and Income No No YesOther Controls No Yes YesObs. 19,419 16,264 17,417

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CRRA Coefficients (interior responses)

0.1

.2.3

.4D

ensi

ty

0 5 10 15 20 25 30 35 40gamma

CRRA Interval Midpoints

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General Risk Attitude and CRRA Coeff.

010

,000

20,0

0030

,000

Am

ount

Inve

sted

0 1 2 3 4 5 6 7 8 9 10Response to General Risk Question

(0=completely unwilling; 10=completely willing)

Average Investment Average Investment of MenAverage Investment of Women

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Context and Risk Attitudes

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Correlation of Risk Attitudes Across Domains

General Car Financial Sports/ Career Health Driving Matters Leisure

Mean 4.420 2.927 2.406 3.486 3.605 2.934

Mean (Men) 4.909 3.523 2.882 3.961 4.039 3.317 Mean (Women) 3.967 2.346 1.963 3.044 3.190 2.580

General 1.000 Car Driving 0.490 1.000 Financial Matters 0.506 0.520 1.000 Sports/Leisure 0.563 0.542 0.503 1.000 Career 0.609 0.507 0.498 0.605 1.000 Health 0.474 0.503 0.458 0.522 0.531 1.000

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Determinants in Different Contexts

Do the exogenous factors have the same impact across domains?

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Determinants in Different Contexts

Do the exogenous factors have the same impact across domains?

Gender, Age, Parental Education, and Height Affect risk attitudes in most domains. Effects are qualitatively similar to

general risk. But magnitudes differ across

domains, e.g. gender matters more in driving than in financial matters.

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Primary Determinants of Risk AttitudesDependent Variable: Willingness to Take Risks (Binary Measure) in:

General Car Driving Financial Sports/ Career Health Matters Leisure (1) (2) (3) (4) (5) (6)

Female -0.111*** -0.091*** -0.078*** -0.095*** -0.082*** -0.062*** (0.009) (0.008) (0.006) (0.008) (0.009) (0.007)Age -0.005*** -0.004*** -0.001*** -0.007*** -0.005*** -0.003*** (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)Height 0.005*** 0.002*** 0.001*** 0.003*** 0.003*** 0.001***

(0.001) (0.000) (0.000) (0.000) (0.001) (0.000)Abitur Mother 0.063*** 0.02 0.029*** 0.041*** 0.047*** 0.014 (0.016) (0.012) (0.010) (0.013) (0.015) (0.011)Abitur Father 0.035*** -0.004 0.015** 0.065*** 0.034*** 0.017** (0.012) (0.009) (0.007) (0.011) (0.011) (0.009) Pseudo-R² 0.064 0.074 0.062 0.114 0.058 0.042log Pseudo-Likelihood -11471 -7935 -5816 -9185 -9475 -7988Obs. 19438 18313 19274 19186 17683 19431

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Comparing Predictive Power

of Alternative Measures

Within and Across Contexts

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Predicting Behavior in Different Contexts

Regress behavioral outcomes sequentially on each risk measure separately. General risk, 5 domain-specific, and

hypothetical investment choice.

Behavioral outcomes span the five contexts identified in the SOEP Real-world portfolio choice, participation in

sports , occupational choice, smoking, migration, life satisfaction, traffic violations.

Compare predictive power of different measures, within and across contexts.

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Determinants of Behavior in Different Domains

Dependent variable: Investment in Active Sports Employment SelfemployedStocks in Public Sector

(1) (2) (3) (4)Willingness to take risks(binary measure) in ...... General 0.035*** 0.083*** -0.014** 0.006*** [0.011] [0.009] [0.007] [0.002]

(-4708.9) (-8726.2) (-6361.1) (-1446.4)Positive amount invested 0.085*** 0.086*** 0.016** -0.001in hypothetical asset [0.011] [0.008] [0.007] [0.002] (-4683.1) (-8716.1) (-6360.2) (-1450.7)Willingness to Take Risks(binary measure) in ...... Car driving 0.10 0.038*** -0.009 0.001

[0.014] [0.011] [0.008] [0.003](-4713.4) (-8768.8) (-6362.7) (-1450.7)

... Financial matters 0.244*** 0.079*** 0.003 0.007**[0.018] [0.013] [0.011] [0.003]

(-4618.2) (-8756.9) (-6363.3) (-1448.2)... Sports and leisure 0.060*** 0.184*** 0.01 0.003

[0.013] [0.009] [0.008] [0.003](-4703.0) (-8579.2) (-6362.6) (-1450.0)

...Career 0.053*** 0.084*** -0.012* 0.018***[0.013] [0.009] [0.007] [0.003]

(-4704.2) (-8731.7) (-6361.9) (-1421.3)...Health 0.014 0.033*** 0.012 0.002

[0.014] [0.011] [0.009] [0.003](-4713.2) (-8770.5) (-6362.4) (-1450.6)

Observations 8,610 16,066 13,925 13,925

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Determinants of Behavior in Different Domains

Dependent variable: Smoking Mobility from Mobility from Overall LifeEast to West West to East Satisfaction

(5) (6) (7) (8)Willingness to take risks(binary measure) in ...... General 0.052*** 0.018* 0.006*** 0.345*** [0.008] [0.011] [0.003] [0.029]

(-9333.2) (-848.7) (-437.8) (0.09)Positive amount invested -0.003 0.001 -0.001 0.142***in hypothetical asset [0.008] [0.010] [0.002] [0.029] (-9354.2) (-850.2) (-441.9) (0.08)Willingness to Take Risks(binary measure) in ...... Car driving 0.036*** -0.014 -0.002 0.123***

[0.010] [0.012] [0.002] [0.042](-9347.3) (-849.6) (441.4) (0.08)

... Financial matters -0.018 -0.002 -0.001 0.247***[0.012] [0.018] [0.003] [0.043]

(-9353.1) (-850.2) (-441.9) (0.08)... Sports and leisure 0.001 0.005 0.004* 0.251***

[0.009] [0.013] [0.003] [0.033](-9354.3) (-850.1) (-440.6) (0.09)

...Career 0.034*** -0.018 0.002 0.171***[0.009] [0.011] [0.002] [0.032]

(-9346.2) (-848.8) (-441.7) (0.08)...Health 0.128*** -0.014 -0.003 0.045

[0.011] [0.013] [0.002] [0.038](-9276.4) (-849.7) (-441.2) (0.08)

Observations 16,120 2,971 8,211 16,117

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Traffic Offenses and Willingness to Take Risks

0.0

2.0

6.1

.14

.18

Offe

nse

Rat

es

0.1

.2.3

.4.5

Fra

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20 30 40 50 60 70 80 90Age in Years

Willingness to Take Risks 10 9 8 7 6 Unweighted Offense Rate Weighted Offense Rate use lic.

Men

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Traffic Offenses and Willingness to Take Risks

0.0

2.0

4.0

6.0

8.1

Offe

nse

Rat

es

0.1

.2.3

.4.5

Fra

ctio

n W

illin

g

20 30 40 50 60 70 80 90Age in Years

Willingness to Take Risks 10 9 8 7 6 Unweighted Offense Rate Weighted Offense Rate use lic.

Women

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Comparing Predictive Power Most measures predict behavior across several

contexts. Suggestive of a single risk trait. Provides additional evidence that the measures are

behaviorally relevant.

However, best predictor of behavior in a given context is always corresponding domain-specific question. Measure of risk attitudes should incorporate situation-

specific context, in order to predict specific behavior. E.g. ask about willingness to take risks in health matters,

in order to predict risky health behaviors, rather than using a measure of willingness to take risks in financial matters.

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Conclusions

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Conclusions Self-reported willingness to take risks

varies across individuals.

Exogenous factors explain individual differences: Women and older individuals are more

cautious. Children of highly-educated parents and taller

individuals take more risks.

Survey measures are behaviorally relevant: predict actual risk-taking behavior in a field experiment.

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Conclusions

Heterogeneity at least partly driven by differences in risk preferences, rather than subjective beliefs.

Exogenous factors affect risk preferences in a similar way across domains, but magnitude varies.

CRRA coefficients consistent with range typically assumed in economic models.

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Conclusions

Risk attitudes are strongly but imperfectly correlated across contexts.

All survey measures predict across several contexts.

But best predictor of behavior in a specific context is a question framed in terms of that context.

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Additional Material

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Occupational Earnings Risk

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

5.80 6.00 6.20 6.40 6.60 6.80 7.00

Conditional log Occupation Wage

Occ

up

atio

n E

arn

ing

s R

isk

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Risk Attitudes and Occupational Sorting

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

4.00 4.50 5.00 5.50 6.00 6.50 7.00

Mean of Individual Risk Preferences in 2-digit Occupation

Occ

up

atio

n E

arn

ing

s R

isk

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Risk Attitudes and Regional Mobility in Germany

0

0.05

0.1

0.15

0.2

0.25

1 2 3 4 5 6 7 8 9 10 11

Willingness to take risks

Sh

are

Stayers

Movers

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Static Regressions, Ever Moved in 2000-2004

Marg. Marg. Marg. Marg.Effect S.E. Effect S.E. Effect S.E. Effect S.E.

Risk Index .0054 (.0008) .0022 (.0007)

"Risk Lover" 0.0259 (.0045) .0121 (.0035)

Age (2000) -.0018 (.0002) -.0018 (.0002)

Female .0053 (.0031) .0052 (.0031)

Married (2000) -.0361 (.0045) -.0363 (.0045)

Years of Education (2000) .0049 (.0006) .0049 (.0006)

Origin/NationalityWest GermanEast German .0055 (.0036) .0056 (.0036)Born Abroad .0053 (.0055) .0047 (.0055)

Pseudo-R2 .0088 .1075 .1081.0088

ref. ref.

(4)(1) (2) (3)

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Intergenerational Transmission

of Risk Attitudes

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44

.55

5.5

66

.5C

hild

's a

vera

ge

ge

ne

ral r

isk

atti

tud

e

0 1 2 3 4 5 6 7 8 9 10Mother's risk attitude

Child's risk attitude (average)

Weighted regression line

44

.55

5.5

66

.5C

hild

's a

vera

ge

ge

ne

ral r

isk

atti

tud

e

0 1 2 3 4 5 6 7 8 9 10Father's risk attitude

Child's risk attitude (average)

Weighted regression line0

.05

.1.1

5.2

Fra

ctio

n

0 2 4 6 8 10Mother's willingness to take risks in general

(0=completely unwilling; 10=completely willing)

Mothers's risk attitudes

0.0

5.1

.15

.2F

ract

ion

0 2 4 6 8 10Father's willingness to take risks in general

(0=completely unwilling; 10=completely willing)

Father's risk attitudes

Significant determinants of risk attitudes: Gender, Age, Height

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Dependent Variable(1) (2) (3)

Mother's willingness to take risks in general 0.029*** 0.028*** 0.029***[0.004] [0.004] [0.005]

Father's willingness to take risks in general 0.024*** 0.022*** 0.024***[0.004] [0.004] [0.004]

1 if female -0.104*** -0.101***[0.026] [0.027]

Age of respondent (years) -0.009*** -0.009***[0.002] [0.003]

Height of respondent (cm) 0.006*** 0.006***[0.002] [0.002]

Age of mother (years) 0.002 0.003[0.003] [0.003]

Age of father (years) 0.001 0.001[0.002] [0.002]

Height of mother (cm) -0.001 -0.001[0.002] [0.002]

Height of father (cm) -0.001 -0.001[0.002] [0.002]

Additional controls no no yesPseudo-R-squared 0.03 0.057 0.066

Observations 3331 3320 3320

Willingness to Take Risk in General

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Specificity of transmission process

Do parents pass on a relatively general, unspecific disposition towards risk?

Or do they pass on a bundle of distinct risk attitudes?

Each domain regressed simultaneously on all domains If transmission is distinct: ‘diagonal’

should be most important

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Dependent Variable: Willingness to take risks in the domain of(1) (2) (3) (4) (5) (6)

General Car driving Financial matters Sports & leisure Career HealthGeneral: Mother 0.026*** 0.002 -0.002 0.006 0.006 -0.010**

[0.007] [0.005] [0.003] [0.007] [0.006] [0.005]General: Father 0.020*** -0.004 -0.004 -0.009 0.003 0.002

[0.007] [0.006] [0.003] [0.007] [0.007] [0.005]Car driving: Mother -0.011 0.025*** 0.001 -0.006 -0.002 0

[0.007] [0.005] [0.003] [0.007] [0.006] [0.005]Car driving: Father 0.003 0.019*** 0 0.001 -0.001 -0.006

[0.006] [0.005] [0.003] [0.006] [0.006] [0.004]Financial matters: Mother 0.006 -0.014** 0.009*** -0.016* 0.007 0.005

[0.008] [0.007] [0.003] [0.008] [0.007] [0.005]Financial matters: Father 0.01 -0.001 0.007** 0.01 -0.013** -0.005

[0.007] [0.005] [0.003] [0.007] [0.006] [0.005]Sports & leisure: Mother -0.007 0.004 -0.003 0.041*** -0.01 -0.006

[0.008] [0.006] [0.003] [0.008] [0.007] [0.005]Sports & leisure: Father -0.015** -0.001 0 0.032*** 0.003 -0.003

[0.007] [0.005] [0.003] [0.007] [0.006] [0.004]Career: Mother 0.005 -0.011** 0.002 0.003 0.013** 0.006

[0.007] [0.006] [0.003] [0.007] [0.007] [0.005]Career: Father 0.001 0.002 0.004 -0.005 0.019*** -0.007

[0.006] [0.005] [0.003] [0.007] [0.006] [0.005]Health: Mother 0.005 0.001 0 -0.001 0.003 0.013***

[0.007] [0.005] [0.003] [0.007] [0.006] [0.005]

Health: Father -0.014** -0.005 0 -0.014** 0 0.018***

[0.006] [0.005] [0.003] [0.006] [0.006] [0.004]

Additional controls yes yes yes yes yes yesPseudo R-squared 0.283 0.216 0.216 0.301 0.266 0.22Observations 2585 2585 2585 2585 2585 2585

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Positive Assortative Mating

in Risk Attitudes

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Assortative mating Assortative mating reinforces strength

and importance of intergenerational transmission

Similarity of partners’ preferences? Less conflict in bargaining, better

coordination, agency perspective Partners tend to be similar

Age, social background, physical attractiveness or height but also behaviors (e.g., smoking, leisure activities)

Similarity in outcomes and behavior affected by preference sorting in the marriage market

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Assortative mating: risk attitudes

(1) (2) (3)Female partner's willingness 0.352*** 0.311*** 0.291***to take risks in general [0.011] [0.011] [0.012]Age of male spouse in years -0.017*** -0.019***

[0.006] [0.006]Height of male spouse in cm 0.026*** 0.021***

[0.004] [0.004]Age of female spouse in years -0.008 -0.008

[0.006] [0.006]Height of female spouse in cm -0.004 -0.007

[0.004] [0.004]Controls for parental background of spouses No Yes YesControls for education degree of spouses No No YesControls for childhood socialization No No YesControls for religion No No YesConstant 3.418*** 0.75 1.495 [0.051] [0.864] [0.958]

Observations 7272 7189 6996R-squared 0.12 0.16 0.17

Dependent Variable: Willingness to take risks in general (male partner)

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Robustness checks on restricted samples

OLS Coefficient Estimates of Spouse's Willingness to Take Risks(only cohabiting married couples)

Sample restriction No controlsExogenous factors

Social back-ground

0.365*** 0.330*** 0.309***[0.012] [0.012] [0.013]N=6373 N=6312 N=61580.364*** 0.330*** 0.308***[0.013] [0.013] [0.013]N=5881 N=5838 N=57170.349*** 0.319*** 0.306***[0.015] [0.015] [0.015]N=4259 N=4227 N=41620.304*** 0.266*** 0.268***[0.031] [0.031] [0.032]N=994 N=987 N=9700.260*** 0.233*** 0.228***[0.041] [0.042] [0.043]N=559 N=551 N=532

with non-contradictory information on marriage date

all cohabiting married

with children

with one child

without children

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Subjects‘ Responses to General Risk Question0

.05

.1.1

5.2

Fra

ctio

n

0 1 2 3 4 5 6 7 8 9 10Response to General Risk Question

(0=completely unwilling; 10=completely willing)

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Distribution of Lottery Choices

0.0

5.1

.15

Fra

ctio

n

0 50 100 150 200Safe Value at Switch Point

Choices of Subjects in Experiment