Understanding the Causal Factors of Family and Community ... · Federal Reserve Board Washington, D.C. July 13, 2010 James Heckman Understanding the Causal Factors. Summary ... A2

Summary

Understanding the Causal Factors ofFamily and Community that Promote

Good Health

James HeckmanUniversity of Chicago

Session: Working to Improve Communities and Health

Healthy Communities ConferenceFederal Reserve Board

Washington, D.C.July 13, 2010

James Heckman Understanding the Causal Factors

Summary

Developmental origin of health

Investigate causal factors promoting health

Capabilities θt (basic determinants of life sucess)

θt = (θCt , θNt , θHt)↑ ↑ ↑

cognitive non-cognitive health(“soft skills”)


Summary

Outcomes Yt

Yt = ψ(θt , %t)↑

effort

%t = φ (Rt)↑

incentives

Explain a wide variety of outcomes from a low dimensional set of capabilitiesand incentives


Summary

It investment (family, schools, communities, social networks)

Qt,E environments (community, family, neighborhood variables)

Technology of capability formation

θt+1 = ft(θt , It , θt,E )


Summary

A Life Cycle Framework for Organizing Studies and Integrating Evidenceθt = (θC , θN , θH) capabilities at t

It is investment at t (family, community, schools)θtE environmental variables

Technology of Skill Formation: θt+1 = ft(θt , It , θt,E )

E-1

0E

1E

2E

0

1

2

-1

0H

1C 1NC 1H

2C 2NC 2H

TC TNC TH


Summary

Literature abounds with correlations.

The key question in all of this is “what is causal?”

For policy, we need to determine causes.

Example: Russian peasants before WWI.


Summary

Consider one community development strategy — improved schoolingthat promotes schooling attainment. (Conti and Heckman)

Investigate the role of cognitive ability, personality traits, and early healthendowments, and the effects of education on health.


Summary

There is a strong correlation between education and health.

But is this causal?

Does it say that schooling policy (building schools or improving theirquality) is the relevant lever to pull?

Or is it the factors that promote schooling?

Can we change those factors?


Summary

Child endowments at age 10 are strong predictors of health disparities atage 30.

Selection on endowments into schooling explains more than half ofobserved difference in poor health, depression, and obesity.

Schooling has a causal effect on these behaviors but a substantial part ofthe correlational effect is due to factors that are present before schoolingbegins.


Disparities by Education

0.2

0 1

0.15

0.2

Males

Females

0.05

0.1

0.15

0.2

Males

Females

‐0.05

0

0.05

0.1

0.15

0.2

Log Hourly Wage

FT Employment

Regular Exercise

Cannabis Ever

Obesity Fair/Poor Health

Depression Daily Smoking

Males

Females

‐0.1

‐0.05

0

0.05

0.1

0.15

0.2

Log Hourly Wage

FT Employment

Regular Exercise

Cannabis Ever



Males

Females

‐0.2

‐0.15

‐0.1

‐0.05

0

0.05

0.1

0.15

0.2

Log Hourly Wage

FT Employment

Regular Exercise

Cannabis Ever



Males

Females

‐0.2

‐0.15

‐0.1

‐0.05

0

0.05

0.1

0.15

0.2

Log Hourly Wage

FT Employment

Regular Exercise

Cannabis Ever



Males

Females

Note: Authors’ calculations using BCS70.

Densities of Endowments by Schooling Level

(1) Sorting on cognitive ability.

(a) Males (b) Females

0.2

5.5

.75

1F

requ

ency

−2 −1 0 1 2Cognitive

A1. Cognitive Endowment.

0.2

5.5

.75

1F

requ

ency

−2 −1 0 1 2Cognitive

A2. Cognitive Endowment.

Post-Compulsory Compulsory Post-Compulsory Compulsory

Source: Conti, Heckman, Urzua (2010)

Densities of Endowments by Schooling Level

(2) Sorting on noncognitive ability.

(a) Males (b) Females

0.2

5.5

.75

1F

requ

ency

−2 −1 0 1 2Noncognitive

B1. Noncognitive Endowment.

0.2

5.5

.75

1F

requ

ency

−2 −1 0 1 2Noncognitive

B2. Noncognitive Endowment.

Post-Compulsory Compulsory Post-Compulsory Compulsory


Joint Distributions of Endowments

Figure: Cognitive and Noncognitive - Males

Note: The )igures show the joint distributions of cognitive, noncognitive and health endowments. They are generated using simulated data from our model. The estimated correlations between cognitive and noncognitive is 0.547, between cognitive and health 0.154, and between noncognitive and health is 0.060. Finally, for each endowment the mean is zero.

p1

p16

p32 p48

p64

p80

p100 0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

p1 p12

p24 p36

p48 p60

p72 p84

p100

p1

p16

p32

p48

p64

p80 p100 0

0.003

0.006

0.009

0.012

0.015

0.018

p1 p12

p24 p36

p48 p60

p72 p84

p100

p1

p16

p32

p48

p64

p80

p100 0

0.003

0.006

0.009

0.012

0.015

p1 p12

p24 p36

p48 p60

p72 p84

p100

A. Cognitive and Noncognitive

C. Noncognitive and Health

B. Cognitive and Health

Cognitive CognitiveNoncognitive Health

NoncognitiveHealth


The correlation between the cognitive and noncognitive endowments is 0.544(p=0.000).


Figure: Cognitive and Health - Males


p1

p16

p32 p48

p64

p80

p100 0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

p1 p12

p24 p36

p48 p60

p72 p84

p100

p1

p16

p32

p48

p64

p80 p100 0

0.003

0.006

0.009

0.012

0.015

0.018

p1 p12

p24 p36

p48 p60

p72 p84

p100

p1

p16

p32

p48

p64

p80

p100 0

0.003

0.006

0.009

0.012

0.015

p1 p12

p24 p36

p48 p60

p72 p84

p100





NoncognitiveHealth


The correlation between the cognitive and health endowments is 0.176(p=0.000).


Figure: Noncognitive and Health - Males


p1

p16

p32 p48

p64

p80

p100 0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

p1 p12

p24 p36

p48 p60

p72 p84

p100

p1

p16

p32

p48

p64

p80 p100 0

0.003

0.006

0.009

0.012

0.015

0.018

p1 p12

p24 p36

p48 p60

p72 p84

p100

p1

p16

p32

p48

p64

p80

p100 0

0.003

0.006

0.009

0.012

0.015

p1 p12

p24 p36

p48 p60

p72 p84

p100





NoncognitiveHealth


The correlation between the noncognitive and health endowments is 0.093(p=0.000).

Health Differential due to Education

0.2

0 1

0.15

Selection ATE

0.05

0.1

0 M M M

M M M M

F F FF

F F F F

‐0.05M

0 15

‐0.1

‐0.2

‐0.15

M=Males, F=Females.

Summary

Need a deeper analysis of policy effects.

Some may benefit from a policy, others may lose.


Distribution of Treatment Effects

Daily Smoking, Males (ATE=-0.14)

0.2

.4.6

Fra

ctio

n

−1 0 1Individual Average Treatment Effect

Behind the ATE, there are gains and losses for different individuals...

Distribution of Treatment Effects

Obesity, Females (ATE=0.001)

0.2

.4.6

Fra

ctio

n

−1 0 1Individual Average Treatment Effect

...which may result in a small average treatment effect.

Summary

Summary

Life cycle developmental approach to health.

Dynamic synergy of capabilities in producing each other and fosteringinvestment.

Determine critical and sensitive periods.

Determine causal effects of interventions as a basis for policy.

In study of education on health, education has a causal effect.

Suggests we need to broaden thinking about the policies that promote health.


Documents

Understanding the Causal Factors of Family and Community ... · Federal Reserve Board Washington, D.C. July 13, 2010 James Heckman Understanding the Causal Factors. Summary ... A2