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Climate Change and Labor Market Dropouts:
Evidence from the Half Century
Masahiro Yoshida

Empirical Micro Workshop at Kyoto University
July 7, 2023

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Background: Global rise in males’ labor market dropouts
Since the late 1960s, labor market participation rate (LFPR) of
prime-aged men across almost all rich countries have started decreasing.

→ It peaked in 1968 at OECD countries. Ths U.S. is a leading alarming case.
(96.5% (1950) → 89.1%(2019))
Figure: LFPR (males aged 25-54; U.S.)

Note: OECD employment database and BLS.

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Trend by race and ethnicity (U.S.)
Blacks exhibit a lowest level and experienced the sharpest drop in LFPR.
(1970: 88% → 2019: 80%) Attachment of Hispanics is relatively stable.
Figure: LFPRs by race and ethnicity (males aged 25-54; 1970-2019)

Source: CPS

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Why care for declining males’ labor supply?
The impact is massive because prime-aged males have traditionally been mainincome-earners.
• First-order source of rising income inequality• Dropouts may lead to lower happiness (Krueger [2017]), even morbidity
and mortality. (Sullivan and Von Wachter [2009])• Higher dependency ratio threatens the social security system underpopulation aging.
• Fewer working males plausibly lead to lower partnership and fertility
rate. (Autor et al. [2019])
X In the U.S., a marriage rate and the fertility rate has been consistently
declining after the peak of 1972 and 1957, respectively.

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Why is males’ labor supply declining?
Unsurprisingly, the literature admits that a single driver cannot explain all.
• Labor demand drivers: computerization (1990-); robots (2004-);(Acemoglu and Restrepo [2020]); China shock (2001-) (Autor et al.
[2014]) and offshoring (1990-)• Labor supply drivers: disability insurance (Parsons [1980]); health(Krueger [2017]); computer game technology (Aguiar et al. [2021])
None spans long enough to reconcile the half-century worldwide
phenomenon.
(→ Another global and secular trend should be a fundamental culprit.)Introduction

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Global warming
Since the late 1960s, the world has experienced an unprecedented rise intemperature for the 2 millennia. (preceding the decline of males’ LFPR)
Figure: Global trend of temperature (left: 2 millennia; right: 1880-2020)

Source: IPCC, 2021: Summary for Policymakers. In: Climate Change 2021.

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Question 1: Does climate change induce dropouts?
Did climate change induce the labor market dropouts of prime-aged
males?
• A far larger proportion of males work outdoor than females.
(e.g. agriculture, forestry, construction, mining, Uber Eats driver)• Outdoor workers have larger exposure to climate change.
(→ cost of work steadily increases)• Outdoor workers are essential workers; measurable outcomes(e.g. harvesting; lumbering) are monitored and little room for moral
hazard once hired.(→ higher incentives to drop out)
• Less educated males have fewer outside options in indoor jobs.
Low-skilled indoor jobs are more intensive in ICT and communication.
(e.g. office clerk; call center operator; waiter)

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See the USA: Climate change and Male dropouts
The onset of warming and rising male dropouts roughly coincided around1970. Average hot days per year for an average American increased by 25.4
days in 5 decades.
Figure: Hot days (mean >70F) and prime-aged male LFPRs (1960-2019, USA)

Source: LFPR from BLS. The hot days are 20 year moving-average.

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Spread of air conditioners
In parallel to global warming, residential air conditioners (AC) rapidly spreadsince the 1960s. The relative cost of working outside vs. dropouts surged inthis period.
• AC cools down the temperature by lowering the humidity.
(→ bring comfortability)• AC adoption in hot areas is faster than a cold area. (Biddle [2008])(→ the relative cost expanded even more quickly in hot areas.)• Intriguingly, initially hot areas (e.g. Southeast, West, Southwest)
received the largest effect of climate change. (shown below)

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Question 2
How much did climate change explain the racial (and ethnic) gap ofmale LFPR trend?
• Blacks agglomerate in the hottest and most humid area (South andSoutheast; Alabama, Georgia, Mississippi).
• Hispanics agglomerate in the hottest and least humid area (West andSouthwest; California, Nevada, Arizona).

→ The difference of discomfort, especially in the summer, may account for
the racial (and ethnic) gap of LFPR trend relative to whites.

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Map: Geographic distribution of minorities
Historically, blacks agglomerate near the Mexican gulf and Atlantic ocean
from the Colonial age. Hispanics agglomerate near the Mexican border from
immigration since 1970s.
Figure: Minorities share across CZs (prime-aged males, 1970)

Source: Population Census, 1970.

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Empirical Strategy
Use a differential change in hot days across regional labor markets as a“natural” experiment, controlling for humidity.
• From meteorological daily big data, I document a dramatically richvariation of climate change across regions and years; in fact, someregions experienced cooling.
• Long-run variation of climate change is driven by topography, notsignificantly shaped by regional economic activities.
• At least, an individual chooses labor supply, taking the climate as given.
• Compliers of the treatment (i.e.; less-educated) plausibly have lessmobility. (Kennan and Walker [2011])

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Data
I assemble a panel of climates (long-run trend of daily weathers) and male
LFPRs across Commuting Zones (CZs) during the post-war decades in the
U.S. mainland.
• Variation of analysis 722 CZs × years (1970, 80, 90, 2000, 2010, 2019)• Climate change
X daily temperature and precipitation data from 2,000-3,000 stations from
GHCN-daily from National Climatic Data Center (NCDC).

X compute # of “hot days” under daily mean temperature over 70F (21.1C);“cold days” under 35F (1.7C). Using a decadal average as a climate.

• LFPR of males CZ-level: Census (1970-2000, by decades), and ACS(2010-2012, 2017-2019)

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Literature
The paper builds on the literature on the impact of extreme weather (orclimate change) and the cause of declining male LFPR.
1

Weather shocks
1

Mortality Barreca et al. [2016]; Deschenes and Moretti [2009]2

Production Deschênes and Greenstone [2007](agriculture); Somanathan
et al. [2021] (manufacturing); Dell et al. [2012] (GDP)32Time allocation Graff Zivin and Neidell [2014]

Declining LFPR of males
1

Krueger [2017] (morbidity); Autor and Duggan [2003]; Parsons [1980](disability); Aguiar et al. [2021] (gaming technology)

2

Autor et al. [2014] (trade); Acemoglu and Restrepo [2020] (robots); Autorand Dorn [2013] (computerization)

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Model: Working outdoors or Exit
• Consider a basic labor supply model where a market wage (w(s)) for skills and non-labor income NLI is given.
• A person with a skill s ∈ [0, 1] under hot days hd and cold days cd keeps
working outdoors if U work > U drop s.t.
U work = w(s) − c(hd, cd) −e|{z}; U drop = NLI.

unobservable cost

• Then, the LFPR is computed by summing up e s.t.
LFPR =Z ∆0f (e)de• Note that LFPR is strictly increasing in ∆ ≡ U work − U drop

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Propositions• Recall the net benefit of working outdoors is∆ ≡ U work − U drop = w(s) − ( NLI + cout (hd, cd) + e)
• A person is more likely to drop out if one of the 3 effects is salient.
X Climate effect: hd or cd is larger
X Income effect: NLI is high. (family income or public welfare)
X Substitution effect: w0 (s) is low (adverse labor demand shock)Introduction

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Why NOT go to indoor jobs?
• Now, add indoor
jobs:


U work (s) = win (s) − cin − ein(indoor)U work (s) = w(outdoor)outout ( s ) − cout ( hd, cd ) − e

0 ( s ) > w0 ( s )).
• Assume inside jobs are skill intensive (winout

• When hd , outdoor workers will switch to indoor jobs if
win (s) − wout (s) > cout (hd, cd) − cinholds; .1 Under some regularity, only skilled workers (large s) switch.
• When hd , cost-benefit analysis of less-educated men (low s) is:
work ( s ) > U work ( s ).
U drop > Uoutin

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Propositions: Occupation sorting
As climate gets severer, a dropout rate and a share of working indoors
increases while a share of working outdoors decreases.
Figure: Dropout or working indoors (e = 0)

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Why is dropping out feasible?
U drop = NLI has to be higher than the subsistence level.
• Intrafamily transfer from parents (Binder and Bound [2019]) or spouses• Welfare benefit as a “subsidy for dropping out”
X Rise of disability insurance benefit (Parsons [1980])
X Poverty measures (e.g. social security income; medicaid; food stamp)• Cohabiting with parents saves housing rent; houses typically has a spareroom in the U.S. (e.g. empty kids room)(→ These fall-back options appear to be only substantial for developed
economies in the post war period.)

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Daily weather big data
The daily weather (max/min temperature and precipitation) comes fromstations, recorded by GHCN-Daily. I take an inverse-distance weighted
average of records of 3 closest stations from CZ population centroids.
Figure: stations recording temperature (1900-2019); distribution (2019)

Source: GHCN-Daily from NOAA (National Oceanic and Atmospheric Administration).

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Construct a temperature
I compute a daily temperature Td as
Td = ωTmax + (1 − ω ) Tmin .

1

Mean temperature: ω = 0.5 (convention of literature)2

Business hour temperature: ω = 0.75 (business hours (8AM-6PM;
including commuting).
X Assuming linear temperature cycle between Tmax and Tmin .

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Annual temperature (level)
Significant heterogeneity of baseline temperature across regional labormarkets. South, Southeast, West area is hotter.
Figure: Baseline temperature across CZs (2010-19; level (left); hot days (right))

Source: Computed from GHCN-daily.

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Annual temperature (change)
Initially hot Southeast, West, Southwest areas have been increasingly
getting hotter. Some regions experienced cooling.
(→ Different shocks from automation, ICT or China shocks!)
Figure: Change of # of hot days (mean >70F) across CZs (1960-70 to 2010-19)

Source: Computed from GHCN-daily.

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Definition: Climate region
The U.S. includes 9 climate regions from tropical one to deserts.
Table: Annual hot days by climate regions (1970-2019)

Source: National Centers for Environmental Information (NCEI); NOAA

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Climate change by climate region
When climate is measured by hot days, hot regions are increasingly getting
hotter.
Table: Annual hot days across climate regions (1970-2019)

Source: Computed from GHCN-daily.

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Humidity
Humidity is lower in the west area close to mountains and higher in the eastarea near the Mexican gulf.
• Daily relative humidity is computed from a dew point and mean
temperature through a standard meteorological formula.
Figure: Humidity across CZs (2019)

Source: Computed from Global Summary of the Day (GSoD).

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Examples: Outlier cities
New Orleans in Louisiana is much more humid than Phenix in Arizona withcomparable temperature. (→ discomfort in summer is much different.)
Figure: Distribution of mean daily temperature and humidity (2002 only)

Source: Barreca (2012); Humidity is a specific humidity (g/kg).

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Precipitation
Humidity is heavily shaped by precipitation. East region has larger annual
precipitation and rainy days due to the U.S. geography. West region neardesserts (especially, California) suffers from droughts and even forest fires.
Figure: Precipitation across CZs (average in 2000-2019)

Source: Computed from GHCN-daily.

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Spread of Air conditioner
Hotter regions experience faster adoption rates of ACs. (Biddle [2008])(→ a gap of relative cost increasingly expands in hotter areas.)
Figure: Fraction of households with residential ACs (1960-1980)

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Stylized fact: LFPR trend by education (US)The dropout is stark for the less-educated. (→Many literature studies thesubstitution effect from adverse labor demand shocks)
Figure: LFPR by education attainment (males aged 25-54)

Note: BLS, NBER. (Source: Binder and Bound [2019])

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The proxy of working outdoors
Using Work Context survey from ONET, I construct an indicator where aperson regularly works outdoor (cf. at least once a week) for 873
occupations. 95% of outdoor workers are males (mostly less-educated).
Figure: The ratio of outdoor workers (left: 1970-2019; right: by education (2019)))

Note: ACS 2017-2019, and ONET.

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LFPR of prime-aged males
Male LFPR significantly dropped, especially in the South and Southeast
region.
Figure: LFPR of males across Commuting Zones (1970 vs. 2019)

Note: Bold line is a climate zone from NOAA.

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Bubble plots: CZ-level
A naive first-difference model shows that 10 more hot days reduces LFPR by
0.3%. ( p < 0.1%).
Figure: Exposure to hot days and male LFPRs during 1970-2019 (across CZs)

Note: Weighted by a prime-aged population in 1970, captured by the size of each bubble.

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Empirical model Regional covariates
I estimate the model by the panel data regression at CZ l and year t:
LFPRl,t =βh hd + βc cd|{z}effect of climate change+

Xl,t +|{z}

covariates

δ +δ|l {z }t+el,tlocation and year FE

30 regional covariates along the 5 categories:• Climate: precipitation, days with no rains, air conditioner adoption• Demography: age, race, immigrants and veterans; education• Family structure: share of never-married; divorced (separated); children• Health: ratio of disability (only 1970-)• NLI: personal or family NLI; ratio of farm; rented house• Welfare income: recipient ratio and mean level of welfare income (only1970-)

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Labor demand shocks
To incorporate labor demand shocks to induce substitution effects, I constructa shift-share Bartik shocks for employments and wages of prime-aged workers.
(See Goldsmith-Pinkham et al. [2020] for a background)
Bl,d = ∑ksl,k,d0| {z }

gk,d|{z}

locational l industry kemp. share national industry k growth rate

Construct a list of alternatives, but the estimates are largely unchanged.
• prime-aged males employment• Exclude self-employment• Non-college educated workers• Separately include outside and inside workers

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Baseline result (males; 1970-2019)
After controlling for all covariates, 10 more hot days reduces LFPR by
0.2% (p < 1%) during 1970-2019.
Table: Climate impact on male LFPRs (across CZs)

Note: ∗ ∗ ∗ : p < 1%; ∗∗ : p < 5%;∗ : p < 10%. Weighted by a prime-aged male population each year.
SE is clustered by states.

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Baseline result (females; 1970-2019)
Under the SAME specifications for females, the effects are close to zero andmostly insignificant. (→ Outdoor workers are predominantly males.)Table: Climate impact on female LFPRs (across CZs)

Note: ∗ ∗ ∗ : p < 1%; ∗∗ : p < 5%;∗ : p < 10%. Weighted by a prime-aged female population eachyear. SE is clustered by states.

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By education: Less-educated reacted more?
Consistently with the model, the effect is larger for less-educated. The
relationship is unobserved in females.
Table: Effects by education

Note: Full-controlled and FEs in year×CZs. Weighted by a 1970 prime-aged male population.

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Effects by periods or areas
The climate effect is fairly stable across years. Perhaps, surprisingly, the effectof hot days is almost uniform across the areas of different levels of hot days.
Table: Dynamic effects

Note: Full-controlled and FEs in year×CZs. Weighted by a prime-aged male population each year.
SEs are clustered by states.

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Alternative stories
1

Composition effect by mobility of workers• outside workers left warming areas to avoid labor discomfort.
X Compliers of the treatment have plausibly less mobility. (Kennan andWalker [2011]) Even if it’s high, my estimates are lower bound.

• early-retirees before 54 moved to high-warming areas to prefer heat as
residential amenity.
X Excluding the movers in recent 5 years strengthens the estimates.
1

Product market channel• Climate change hurt agriculture thus, suppress incomes at farms.
X agriculture employment accounts for less than 5% of U.S. prime-aged
population.
Controlling for a ratio of farm employment does not affect the estimate.
The estimate is flexible to spread of residential air conditioner. (below)

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How large is the effect?
Interacting the estimate with prime-aged population during 1970-2019, 10
more hot days (at biz hours) generate 200,000 male dropouts. (caveat:
including in-and-outs)• During 1970-2019, climate change (23.5 hot days (at biz hours) haveproduced 480,000 male dropouts.
• Climate change alone explains approximately 10% of prime-aged male
dropouts during 1970-2019.
• Linearly extrapolating the climate trend to 2030, at least 280,000 males
will drop out.

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In-and-out?: flexible work style
Climate change reduces weeks during a year, choosing a seasonal part-year
job. (c.f. the rise of in-and-out work style; Coglianese [2018])
Table: Climate impact on work style (limited to employees)

Note: ∗ ∗ ∗ : p < 1%; ∗∗ : p < 5%;∗ : p < 10%. Full-controlled and FEs in year×CZs.
Weighted by a 1970 prime-aged male population. SEs are clustered by states.

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In-and-out?: being your boss
Climate change reduces males’ normal employment rate and raises
self-employment rate (e.g. gig workers; working at home), plausibly due
to flexible work schedules in response to climate shocks.
Table: Climate impact on labor force attachment

Note: ∗ ∗ ∗ : p < 1%; ∗∗ : p < 5%;∗ : p < 10%. Full-controlled and FEs in year×CZs. Weighted by a1970 prime-aged population each year. SEs are clustered by states.

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References(1) Do outdoor workplace receives more effect?
Expectedly, exposure to outdoors accelerates the response. (especially, with aroof) Within indoor workplaces, air conditioners flip the impact.
Table: Climate effects by outdoor environments

Note: Full-controlled and FEs in year×CZs. Weighted by a 1970 prime-aged male population. SEs
are clustered by states.

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References(2) Do workers avoid discomfort?
DI is a function of temperature and relative humidity. Uncomfortable days
have DI > 75. (A majority of people feels uncomfortable)• The West or Southwest regions are comparably hot, but lessuncomfortable compared to the Southeast or South.
Figure: Discomfort index across CZs

Source: Computed from GHCN-daily.

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Discomfortable vs. hot days
Discomfort index, narrowing to business hours or non-rainy days gives larger
and more robust estimates.
Table: Estimates from other climate proxies

Note: ∗ ∗ ∗∗ : p < 0.1%;∗ ∗ ∗ : p < 1%; ∗∗ : p < 5%;∗ : p < 10%. Full-controlled and FEs in year×CZs.
Weighted by a 1970 prime-aged male population. SEs are clustered by states.

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References(3) Role of residential air conditioner?
By contrast to business air conditioner, spread of residential air conditioner(1970-2000) augments the dropouts in response to climate change as well asfamily income, welfare income, marital status, a ratio of farm.
Table: Results from other climate proxies

Note: ∗ ∗ ∗∗ : p < 0.1%;∗ ∗ ∗ : p < 1%; ∗∗ : p < 5%;∗ : p < 10%. Full-controlled and FEs inyear×CZs. Weighted by a 1970 prime-aged male population. SEs are clustered by states.

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References(4) Outside to inside?
Climate change decreases the share of outdoor salaried worker andunemployment. Excluding the shift to self-employments, this accounts forthe rise of dropouts.
Table: Outdoor vs. indoor vs. dropouts

Note: ∗ ∗ ∗ : p < 1%; ∗∗ : p < 5%;∗ : p < 10%. Full-controlled and FEs in year×CZs.
Weighted by a 1970 prime-aged male population. SEs are clustered by states.

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References(5) How to exit: go to prisons, not schools?
Non-employment rate in the institution (e.g. chiefly prison) significantly
increases in contrast to academic enrollment. (e.g. go to community college)
Table:

Note: ∗ ∗ ∗ : p < 1%; ∗∗ : p < 5%;∗ : p < 10%. Full-controlled and FEs in year×CZs.

Weighted by a 1970 prime-aged male population. SEs are clustered by states.

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Why are dropouts among blacks severest?
Decompose the climate response into elasticity vs. climate exposure.
1

Is labor supply elasticity of climate change larger for blacks?
X Given the outdoor working, the response to heat is higher for blacks? (e.g.
Obesity?)2

Is climate exposure larger for blacks?
1

The share of working outdoor is larger for blacks?

2

The number of hot days is larger for blacks?

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1. LS elasticity larger for blacks?
So far, no evidence is confirmed for 1. (→ I suspect that the climate exposure
is dominant.)• Regress DIDID: β B is close to 0 and insignificant.
LFPRl,d = βh hdl,d + βh hdl,d ×Outdoor l,d−10Black+ β B hdl,d ×Outdoor l,d−10 ×ratiol,d+···• Replacing to hispanics, the coefficient shows significantly positive.
(→ Hispanics appears to be resilient to heat shocks.)

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2-(a) The share of working outdoor is larger for blacks?
Opposite. Blacks are less likely to work outdoors than whites or hispanics
even after education is controlled.
(→ The remaining is the difference of hot days.)
Figure: The share of prime-aged outdoor workers by race (prime-aged males;
1970-2019)

Source: Census, ACS and ONET.

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2-(b) Is climate exposure larger for blacks?
Yes, a gap of 18 hod days for 5 decades. A simple envelope calculation:-0.2% for 10 days in a decade × ∆18 days exposure × 5 decades = -1.8%.

→ This accounts for 30% of black-white gap of LFPR trends during
1970-2019. (LFPR gap widened from 5% to 11%)
Figure: Hot days experienced by average blacks and whites (1950-2019)

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Summary
Throughout the human history, males have enjoyed comparative advantage inworking outdoors. The paper suggests that modern climate change hurt
their advantage.
• Climate change drives the decline of male LFPRs.
• Geographic variation of climate change may be responsible for dispersionof racial (black vs. white) LFPR trends.
• Policy implication: subsidy or OSHA regulation for deployment of air
conditioners at indoor workplaces. This would prevent further dropouts.

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For comments
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