1

Temperature Extremes, Health, and Human Capital

Comments by Alan BarrecaTulane University, IZA, NBER

2

It’s complicated(But, that’s cool for everyone)

3

Limitations

• Climate is correlated with unobservables. E.g. poor are more likely to live in South.

• We need to identify from unusual weather shocks for a place and time of year (if study is done well)

• External validity issues.

4

4 C Scary for climatologists and economists.

But, everyone?

5

Hot days 90+ F (32+ C)

1 day

40+ days!

1970-2010 2070-2099

6

Nonlinear

Do previous studies account for nonlinearities? • E.g. Is the critical impact at 90 F?• Use coarse functional forms? E.g. Quadratic?

Maybe call them “tipping points” or “thresholds”

7

Everyone - Timing and timeline

For children, timing really matters.• In utero• School year

The timeline after the health shock also matters. • Reinforcing vs. compensating (put plainly?)• Part of adaptation?

8

Days with temperatures 90+ F (32+ C)

9

Schooling outcomes

• We want to know how hot weather impacts test scores and attendance

• Vast majority of these days happen outside of school years.

• Will be hard to identify

10

Everyone – Birth weight

1. Temperature -> Birth weight2. Birth weight -> Long-term outcomes3. Temperature -> Long-term outcomes ?

Everyone may be confused by (2) Birth weight is a proxy for “health” (everyone)

11

Mechanisms - define

• Direct vs. indirect: Health nodes (direct). E.g. Influenza, malariaEconomic nodes (indirect). E.g. Parental income

• Short vs. long:Short: School attendanceLong: Years of schooling

Temperature

Disease

Health

Parents

12

Suggestions to reach everyone

1. Unusual weather shocks2. Nonlinear effects3. Timing and timeline4. Mechanisms