Health effects of climate change and mitigating effects of climate policies: Evidence from Bangladesh

Eskande , Shaikh; Mahmud, Minhaj Uddin
Wo king Pape
Heal h e ec s o clima e change and mi iga ing e ec s o
clima e policies: E idence om Bangladesh
ADB Economics Wo king Pape Se ies, No. 756
P o ided in Coope a ion wi h:
Asian De elopmen Bank (ADB), Manila
Sugges ed Ci a ion: Eskande , Shaikh; Mahmud, Minhaj Uddin (2024) : Heal h e ec s o clima e
change and mi iga ing e ec s o clima e policies: E idence om Bangladesh, ADB Economics
Wo king Pape Se ies, No. 756, Asian De elopmen Bank (ADB), Manila,
h ps://doi.o g/10.22617/WPS240569-2
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ADB ECONOMICS
WORKING PAPER SERIES
NO. 756
Decembe 2024
Heal h E ec s o Clima e Change and Mi iga ing E ec s o Clima e Policies
E idence om Bangladesh
This pape explo es he mi iga ing e ec s o clima e policies in add essing clima e-induced heal h
ad e si ies. I in es iga es he e ec o in u e o exposu e o ain all a ia ions on child heal h in Bangladesh,
inding nega i e e ec s on child en’s an h opome ic ou comes. I exploi s he he e ogenei y in loca ion
and iming o dis ic -le el alloca ions o clima e p ojec s unde he Bangladesh Clima e Change T us Fund
o iden i y ha some o hese ain all-induced heal h ad e si ies can be mi iga ed h ough clima e policies.
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HEALTH EFFECTS OF CLIMATE
CHANGE AND MITIGATING
EFFECTS OF CLIMATE POLICIES
EVIDENCE FROM BANGLADESH
Shaikh Eskande and Minhaj Mahmud
ASIAN DEVELOPMENT BANK
The ADB Economics Wo king Pape Se ies
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ADB Economics Wo king Pape Se ies
Shaikh Eskande and Minhaj Mahmud
No. 756 | Decembe 2024
Shaikh Eskande (eskande @uab.edu) is an assis an
p o esso a he School o Public Heal h, Uni e si y
o Alabama Bi mingham and a isi ing ellow a he
G an ham Resea ch Ins i u e on Clima e Change
and he En i onmen , London School o Economics
and Poli ical Science. Minhaj Mahmud (mmahmud@
adb.o g) is a senio economis a he Economic
Resea ch and De elopmen Impac Depa men ,
Asian De elopmen Bank.
Heal h E ec s o Clima e Change and Mi iga ing E ec s
o Clima e Policies: E idence om Bangladesh
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ABSTRACT
This pape explo es he mi iga ing e ec s o clima e policies in add essing clima e-induced heal h
ad e si ies. We i s in es iga e he e ec o in u e o exposu e o ain all a ia ions on child heal h
ou comes in Bangladesh and ind ha in u e o exposu e o ain all a ia ions nega i ely a ec s
child en’s an h opome ic ou comes. We hen exploi he he e ogenei y in loca ion and iming o
dis ic -le el alloca ions o clima e p ojec s unde he Bangladesh Clima e Change T us Fund o
iden i y ha some o hese ain all-induced heal h ad e si ies can be mi iga ed h ough clima e
policies. Ou indings a e obus o al e na i e empi ical speci ica ions and ha e impo an policy
implica ions.
Keywo ds: clima e change, clima e inance, heal h, ain all
JEL codes: Q54, Q58, I38
________________________
We g a e ully acknowledge excellen esea ch assis ance om Mus a a Kamal and help ul commen s and
sugges ions by he pa icipan s o ADB Economis s Fo um 2023 and Asian Economic De elopmen
Con e ence 2024.

1. In oduc ion
The e is g owing e idence sugges ing ha clima e change and ex eme wea he e en s ha e
de imen al e ec s on human heal h, li es, and li elihoods. Ex eme empe a u e, sea-le el ise,
salini y, loods, s o ms, and d ough s a e some o he mos common clima e change-induced
e en s (F umkin e al. 2008, Pa z e al. 2000). A ailable li e a u e sugges s ha some clima e
e en s ha e a di ec impac on heal hca e in as uc u e and hus indi ec consequences on
indi idual heal h. Fo example, se e al empi ical pape s ha e ound ex eme empe a u es o
p edic mo ali y (Cu ie o e al. 2002; Haja e al. 2006; Goldbe g e al. 2011; Son e al. 2016;
Rod igues, San ana, and Rocha 2019) and hospi aliza ion (Bobb e al. 2014; Schwa z, Same ,
and Pa z 2004; Son, Bell, and Lee 2014). The 2020 Lance Coun down epo (Wa s e al. 2020)
concludes ha he heal h impac s o clima e change a e wo sening o e ime wi h u he
de e io a ing clima e, and coun ies and popula ions wi h he e ogenous a ibu es expe ience
hose impac s disp opo iona ely. Simila ly, clima e e en s may educe ood p oduc ion and
hampe ood dis ibu ion o ha e he same de imen al e ec s on people’s heal h. A sys ema ic
e iew o he e idence o heal h e ec s o d ough s by S anke e al. (2013), o example, e eals
ha d ough s as a consequence o clima e change can lead o ad e se indi ec heal h ou comes
such as malnu i ion and in ec ious disease. A ecen s udy iden i ied, in e alia, ha he e can be
long- e m sus ained e ec s o clima e ex emes on he a ec ed child en including lowe heal h
s a us du ing adul hood (Eskande and Ba bie 2022).
While he li e a u e documen ing he heal h e ec s o clima e change has been g owing,
igo ous empi ical e idence ocusing on he mos ulne able coun ies such as Bangladesh is s ill
e y limi ed. Fu he mo e, he exis ing esea ch based on seconda y, high- equency da a is
limi ed o a ew de eloped economies since he da a equi ed o such esea ch is a ailable o
only hese coun ies. Fo example, a ecen s udy by Guimbeau e al. (2024) ocused on ocean
salini y and i s impac on child an h opome ic measu es in Bangladesh. Mullins and Whi e (2020)
ound ha communi y heal h cen e s in he Uni ed S a es ha e been success ul in educing he
hea - ela ed mo ali y (bu no cold) by 14.2%. Mo e ecen ly, Nyq is e al. (2023) showed ha in
Uganda, access o communi y heal hca e cen e s educed in an mo ali y amid ad e se wea he
shocks. Howe e , he e is a lack o e idence on mi iga ing he e ec s o clima e ac ions o educe
heal h ulne abili y in such a con ex , which emains a lacuna o policies.1
1 Sus ainable De elopmen Goal 13 “Clima e Ac ion” emphasizes he need o s eng hen esilience and adap i e
capaci y o clima e- ela ed ex eme e en s.
2
In his pape , we conside he po en ial mi iga ing e ec s o clima e inance on heal h
ad e si ies a ising om equen disas e exposu es such as ain all a ia ions in he con ex o
Bangladesh. Using h ee ounds o he household su ey da a om Bangladesh, we empi ically
es ima e he childhood heal h e ec s o in u e o exposu e o ain all a ia ions and he mi iga ing
e ec s o clima e policy on hese ain all-induced heal h ad e si ies. Ou esul s i s in o m ha
in u e o exposu e o ain all a ia ions signi ican ly educes exposed child en’s an h opome ic
ou comes, especially hei heigh - o -age (s un ing) and weigh - o -age (unde weigh ) z sco es.
We hen iden i y ha clima e inancing p ojec s ela ed o adap a ion and mi iga ion ha e some
mi iga ing e ec s on such ad e si ies, by imp o ing child en’s an h opome ic ou comes.
Especially o de eloping economies like Bangladesh, hese indings a e e y impo an since
bo h he public and p i a e sec o s ace epea ed budge c ises du ing and a e a disas e and
ou indings, he e o e, could a leas be gene alized o coun ies expe iencing simila si ua ions
and impac s.
While he clima e isks a e uni e sal, he adeo ha a de eloping economy like
Bangladesh aces equi es addi ional a en ion as hese ha m ul e ec s o clima e change and
disas e s a e u he heigh ened in such a con ex (In e go e nmen al Panel on Clima e Change
2012). The sca ci y, o o en absence, o isk mi iga ion o insu ance p og ams o p o ec li e,
p ope y, and ag icul u al c ops necessi a es p i a e coping s a egies by he a ec ed households.
In such cases, he poo e households se hei p ima y ocus on mee ing immedia e subsis ence
needs while expe iencing equen clima e e en s, and, he e o e, may ha e o comp omise on
hei p epa a ion o acing such u u e clima ic shocks. Clima e policies such as clima e
legisla ion, ac ion plans, and inancing mechanisms adop ed by go e nmen s owa d isk
mi iga ion and/o adap a ion could limi he ha m ul e ec s o clima e change in such a con ex .
Due o i s geog aphic loca ion and land cha ac e is ics, Bangladesh is p one o ecu en
looding and equen opical s o m e en s: 26% o he popula ion a e a ec ed by cyclones and
70% li e in lood-p one egions (Cash e al. 2014). The Bangladesh Clima e Change T us Fund
(BCCTF) is a na ional und es ablished in 2010 by he Go e nmen o Bangladesh o inance
clima e change ac i i ies in he coun y. I is suppo ed by con ibu ions om he go e nmen ,
in e na ional dono s, and p i a e sec o o ganiza ions. The BCCTF is esponsible o p o iding
inancial esou ces o a a ie y o clima e change ac i i ies in Bangladesh. BCCTF suppo ed
p ojec s such as he de elopmen o ea ly wa ning sys ems o ex eme wea he e en s, he
p omo ion o enewable ene gy sou ces, and he de elopmen o clima e- esilien in as uc u e.
We exploi he he e ogenei y in he loca ion and iming o dis ic -le el alloca ions o clima e
3
p ojec s unde he BCCTF o iden i y i ain all-induced heal h ad e si ies can be mi iga ed h ough
clima e policies.
The ou line o his pape is as ollows: Sec ion 2 desc ibes ou da a and he empi ical
s a egy and Sec ion 3 epo s he esul s o he heal h e ec s o ain all a ia ions. Sec ion 4
epo s he esul s o he mi iga ing e ec s o clima e policy. Finally, Sec ion 5 concludes he
pape .
2. Da a and Empi ical S a egy
We use h ee ounds o he Bangladesh In eg a ed Household Su ey (BIHS), 2011–2012, 2015,
and 2018–19, o he child en’s heal h ou come a iables. BIHS is a na ionally ep esen a i e u al
household su ey conduc ed by he In e na ional Food Policy Resea ch Ins i u e(IFPRI), de ails
o which can be ound in Ahmed (2013). Table 1 p o ides desc ip i e s a is ics.
Table 1: Va iable Desc ip ion and Summa y S a is ics
Va iables
Desc ip ion
Mean
SD
Minimum
Maximum
Child’s a ibu es
Males
Child’s gende : 1 i male, 0 i emale
0.511
0.500
0
1
Age
Child’s age in ( ull) mon hs
29.50
16.84
0
60
Weigh
Child’s weigh in kilog am
10.51
2.941
2.100
23.70
Heigh
Child’s heigh in cen ime e
82.92
13.01
45.10
110
Mo he ’s a ibu es
Mo he ’s age
Mo he ’s age in ( ull) yea s
27.33
5.835
16
65
Mo he ’s weigh
Mo he ’s weigh in kilog am
48.26
9.094
26.90
94.30
Mo he ’s heigh
Mo he ’s heigh in cen ime e
150.8
5.686
101.4
195.4
Decision making
Indica o o empowe men : 1 i emales a e
in ol ed in ood ela ed decisions, 0 i no
0.792
0.406
0
1
Mo he ’s schooling
Schooling indica o : 1 i he mo he has
some schooling, 0 i no
0.795
0.404
0
1
Household-le el
a ibu es
Ag icul u e
P opo ion o wo king-age household
membe s wo king in sel -employed
ag icul u e
0.136
0.163
0
0.833
Food insecu i y
Sel - epo ed measu e o ex eme po e y: 1
i he household equen ly su e s om
hunge , 0 i no .
0.0911
0.288
0
1
Child ma iage
Numbe o aged 18 o below cu en ly
ma ied, widowed, di o ced, o sepa a ed
women in he household
0.0163
0.131
0
2
Regional a ibu es
RWI
Rela i e weal h index, dis ic le el measu e
-0.00453
0.356
-0.963
1.184
C op di e si ica ion
He indahl–Hi schman index o alue o
ag icul u al p oduc ion, dis ic le el measu e
0.260
0.0381
0
0.386
Con inued on he nex page
4
Va iables
Desc ip ion
Mean
SD
Minimum
Maximum
Heal h ou comes
HAZ
Leng h/heigh - o -age (cm)
-1.572
1.430
-10.62
8.301
WAZ
Weigh - o -age (kg)
-1.436
1.123
-8.609
3.566
WHZ
Weigh - o -leng h (kg)
-0.674
1.233
-12.10
9.057
Clima e measu es
Rain all a ia ions
De ia ion o a e age in u e o ain all om
espec i e long- e m a e age le el
-3.086
35.48
-92.00
185.2
Rain all a ia ions
T1
De ia ion o a e age i s imes e ain all
om espec i e long- e m a e age le el
-2.402
54.37
-236.0
404.9
Rain all a ia ions
T2
De ia ion o a e age second imes e
ain all om espec i e long- e m a e age
le el
-3.349
54.61
-236.3
407.3
Rain all a ia ions
T3
De ia ion o a e age hi d imes e ain all
om espec i e long- e m a e age le el
-3.507
55.19
-185.9
372.3
Flood
F equency o loods in dis ic , 1990-2020: 0
Low (0-5), 1 Medium (6-11) o 2 High (12-
18)
0: 44.06%
1: 31.45%
2: 24.49%
S o m
F equency o s o ms in dis ic , 1990-2020: 0
Low (0-5), 1 Medium (6-11) o 2 High (12-
18)
0: 44.06%
1: 39.94%
2: 16.00%
Ex eme
empe a u e
F equency o ex eme empe a u e e en s in
dis ic , 1990-2020: 0 Low (0-4), 1 Medium
(5-8) o 2 High (9-12)
0: 9.82%
1: 72.92%
2: 17.26%
Clima e policy
BCCTF
Dis ic -le el alloca ion unde he BCCTF
p ojec , aka pe capi a
81.37
115.9
0
607.7
CC
BCCTF ea ed coho s: 1 i he coho is
ea ed by BCCTF clima e unds (i.e., yea s
2012-18), 0 i no (i.e., yea s 2007-11)
0.504
0.500
0
1
DD
BCCTF ea ed dis ic s: 1 i he dis ic is
ea ed by BCCTF clima e unds, 0 i no
0.850
0.357
0
1
CC2
BCCTF ea ed child: 1 i he child is in a
ea ed dis ic in ea ed yea (i.e., CC=1
and DD=1), 0 i o he wise
0.208
0.406
0
1
No. o Obs.
6,802
BCCTF = Bangladesh Clima e Change T us Fund, CC = child coho , CC2 = child coho 2, DD = dis ic
dummy, HAZ = heigh - o -age z-sco e, WAZ = weigh - o -age z-sco e, WHZ = weigh - o -leng h z-sco e.
No es: Summa y s a is ics a e o he es ima ed sample o 6,802 child en aged 0–60 mon hs whose mo he s
we e su eyed in any o he h ee ounds o he Bangladesh In eg a ed Household Su ey (BIHS) da a.
Sou ce: Au ho s’ calcula ions using he Bangladesh In eg a ed Household Su ey da ase (Ahmed 2013,
In e na ional Food Policy Resea ch Ins i u e [IFPRI] 2016, IFPRI 2020).
2.1. Child en’s Heal h Ou comes
Among o he s, he BIHS da ase epo s age, bi h mon h, bi h yea , heigh , and weigh o child en
aged 0-60 mon hs whose mo he s we e in e iewed du ing he h ee su ey ounds. Comple e
da a a e a ailable o a o al o 6,802 child en (3,475 males and 3,327 emales), who we e bo n
be ween 2007 and 2018, wi h an a e age age o 29.50 mon hs, weigh o 10.51 kilog ams (kg),
11
Following he hypo hesis 1, we a e in e es ed in he es ima ed coe icien o 𝑐𝑐𝑑𝑑𝑖𝑖𝑖𝑖, and we
expec ha g ea e (smalle ) clima e isk (i.e., ain all a ia ions) dec eases (inc eases) heal h
ou comes, i.e., 𝛼𝛼�1< 0.
Hypo hesis 2 hen e e s o he e ec s o public suppo aiming a mi iga ing he ha ms o
clima e shock conside ed in he pape . We ocus on he 2010 BCCTF ha p o ides he unding
alloca ions o di e en clima e change- ela ed p ojec s in Bangladesh. We in es iga e he
mi iga ing e ec s o BCCTF on clima e-induced heal h ad e si ies desc ibed he e. Fo his
pu pose, we employ he ollowing eg ession:
ℎ𝑖𝑖𝑑𝑑𝑖𝑖𝑖𝑖 =𝛽𝛽0+𝛽𝛽1𝑐𝑐𝑑𝑑𝑖𝑖𝑖𝑖 +𝛽𝛽2𝑇𝑇𝑖𝑖+𝛽𝛽3𝐹𝐹𝑑𝑑+𝛽𝛽4𝑐𝑐𝑑𝑑𝑖𝑖𝑖𝑖𝑇𝑇𝑖𝑖+𝛽𝛽5𝑐𝑐𝑑𝑑𝑖𝑖𝑖𝑖𝐹𝐹𝑑𝑑+𝛽𝛽6𝑇𝑇𝑖𝑖𝐹𝐹𝑑𝑑+𝛽𝛽7𝑐𝑐𝑑𝑑𝑖𝑖𝑖𝑖𝑇𝑇𝑖𝑖𝐹𝐹𝑑𝑑+𝑋𝑋𝑖𝑖𝑑𝑑𝑖𝑖𝑖𝑖
′𝛿𝛿+𝜎𝜎𝑖𝑖
+𝜆𝜆𝑖𝑖+𝜌𝜌𝑟𝑟+𝜂𝜂𝑖𝑖𝑖𝑖 +𝜃𝜃𝑖𝑖𝑟𝑟 +𝜑𝜑𝑖𝑖𝑟𝑟 +𝜔𝜔𝑑𝑑
𝑓𝑓+𝜔𝜔𝑑𝑑
𝑠𝑠+𝜔𝜔𝑑𝑑
𝑥𝑥+𝜖𝜖𝑖𝑖𝑑𝑑𝑖𝑖𝑖𝑖, (2)
whe e ℎ𝑖𝑖𝑑𝑑𝑖𝑖𝑖𝑖, 𝑐𝑐𝑑𝑑𝑖𝑖𝑖𝑖, 𝑋𝑋𝑖𝑖𝑑𝑑𝑖𝑖𝑖𝑖
′ and he se o ixed e ec s a e as de ined o equa ion (1). 𝑇𝑇𝑖𝑖 deno es a
s agge ed measu e o clima e policy ins umen (de ined as 1 i child 𝑖𝑖 is ea ed by clima e policy
and 0 i no ), whe eas 𝐹𝐹𝑑𝑑 is a measu e o ac ual alloca ion o BCCTF unding (de ined as he
in e se hype bolic sine ans o ma ion o dis ic -le el pe -capi a BCCTF alloca ion).
The e o e,, we a e in e es ed in he es ima ed coe icien o he in e ac ion be ween 𝑐𝑐𝑑𝑑𝑖𝑖𝑖𝑖,
𝑇𝑇𝑖𝑖, and 𝐹𝐹𝑑𝑑. Following hypo hesis 2, we expec ha clima e policies educe clima e-induced heal h
ad e si ies so ha 𝛽𝛽
󰆹7> 0.
The ec o o con ols 𝑋𝑋𝑖𝑖𝑑𝑑𝑖𝑖𝑖𝑖
′ includes selec ed child-, mo he -, and household-le el
a ibu es ha a e iden i ied in ela ed li e a u e o ha e po en ial con ounding e ec s on he heal h
ad e si ies o ain all a ia ions and he mi iga ing e ec s o clima e policies. In all eg ession
speci ica ions, we con ol o he child’s gende (i.e., 1 i male and 0 i emale), age (in ull mon hs),
and squa ed age. Mo he -le el con ols include age (in ull yea s), weigh (in kg), and heigh (in
cm) o he mo he . We also con ol o household-le el p e alence o ood insecu i y (i.e., 1 i he
household has ecen ly encoun e ed an ex eme po e y si ua ion such as una ailabili y o ood,
0 i no ). We addi ionally con ol o egional c op di e si y and ela i e weal h index.
Equa ions (1) and (2) include a se ies o empo al and spa ial ixed e ec s o con ol o
unobse ed he e ogenei y ha migh a ise om seasonal and egional a ia ions. In pa icula ,
mon h-o -bi h ixed e ec s accoun o seasonal a ia ions, whe eas mon h- and yea -o -bi h
ixed e ec s con ol o idiosync a ic changes ha a e common ac oss su ey clus e s. AEZ ixed
e ec s con ol o he unobse ed ime-in a ian cha ac e is ics speci ic o he ag oecological
zone. In addi ion, AEZ-mon h ixed e ec s con ol o local seasonal a ia ions, AE-yea ixed
e ec s con ol o AEZ-speci ic annual pa e ns in heal h ou comes, and mon h-yea ixed e ec s

12
con ol o yea -speci ic seasonal a ia ions. Mo eo e , lood, s o m, and ex eme empe a u e
ixed e ec s con ol o dis ic -speci ic he e ogenei y in he equency o disas e s.
Con olling o abo e- ixed e ec s allows us o iden i y he causal e ec s o ain all a ia ions
on heal h ou comes and also he mi iga ing e ec s o clima e policies on ain all-induced heal h
ad e si ies (e.g., Dell e al. 2014). Pa ame e 𝛼𝛼1 in equa ion (1) allows o di e en ial e ec s o
ain all on child heal h ou come and we hypo hesize ha 𝛼𝛼�1< 0. On he o he hand, pa ame e
𝛽𝛽7 allows o di e en ial e ec s o clima e policies in educing ain all-induced child heal h
ad e si ies and we hypo hesize ha 𝛽𝛽
󰆹7> 0. We assume ha
𝑐𝑐𝑐𝑐𝑐𝑐(𝜖𝜖𝑖𝑖𝑑𝑑𝑖𝑖𝑖𝑖,𝑐𝑐𝑑𝑑𝑖𝑖𝑖𝑖|ℛ1)= 0
𝑐𝑐𝑐𝑐𝑐𝑐(𝜖𝜖𝑖𝑖𝑑𝑑𝑖𝑖𝑖𝑖,𝑐𝑐𝑑𝑑𝑖𝑖𝑖𝑖𝑇𝑇𝑖𝑖𝐹𝐹𝑑𝑑|ℛ2)= 0, (3)
whe e ℛ1 and ℛ2 deno e he se o explana o y a iables in equa ions (1) and (2) espec i ely.
Ou iden i ying assump ion, he e o e, is he independence be ween he dis u bances and he
measu e o ain all a ia ions, condi ional on pe manen di e ences be ween he dis ic s o bi h
and o he con ol a iables. This implies ha he e a e no omi ed a iables ha could be
co ela ed wi h ain all a ia ions, child heal h ou comes and clima e policies. Howe e , 𝜖𝜖𝑖𝑖𝑑𝑑𝑖𝑖𝑖𝑖 =
𝜂𝜂𝑖𝑖𝑑𝑑𝑖𝑖𝑖𝑖 +𝑢𝑢𝑖𝑖, whe e 𝑢𝑢𝑖𝑖 is he whi e noise e o e m, bu 𝜂𝜂𝑖𝑖𝑑𝑑𝑖𝑖𝑖𝑖 may be co ela ed ac oss 𝑖𝑖 wi hin 𝑑𝑑.
We clus e he s anda d e o s a he sub-dis ic o hana le el o o e come his p oblem, which
allows o illage-le el co ela ions in he e o e ms.
We i s adop an o dina y leas squa es (OLS) me hod o es ima e equa ions (1) and (2).
Howe e , his is highly likely ha ain all a ia ions a e collinea wi h some o he ixed e ec s. To
add ess his, we also employ a double-lasso a iable selec ion s a egy o selec he ixed e ec s
(e.g., Belloni e al. 2014, Guimbeau e al. 2024). This s a egy i s eg esses he a iables o
in e es on he ull se o con ol a iables and ixed e ec s o selec a subse o con ol a iables,
and hen eg esses he ou come a iable on he a iables o in e es and selec ed con ols and
ixed e ec s in he second s ep. The double-lasso s a egy is a obus model selec ion amewo k
ha selec s a smalle subse o con ol a iables om all po en ial con ols.
3. Heal h E ec s o Rain all Va ia ions
Table 2 epo s he heal h e ec s o ain all a ia ions. Panels A and B epo OLS and
LASSO esul s, espec i ely. O e all, all models a e s a is ically signi ican , and es ima ed
coe icien s ha e expec ed signs.
13
Table 2: Heal h E ec s o Rain all Va ia ions
(1)
(2)
(3)
(4)
(5)
(6)
A. OLS esul s
B. LASSO esul s
Va iables
HAZ
WAZ
WHZ
HAZ
WAZ
WHZ
Rain all a ia ions
-0.0022***
-0.0018**
-0.0009
-0.0015**
-0.0014**
-0.0008
(0.0008)
(0.0007)
(0.0008)
(0.0007)
(0.0006)
(0.0007)
Males
-0.0438
0.0214
0.0084
-0.0596*
0.0056
-0.0012
(0.0373)
(0.0295)
(0.0322)
(0.0321)
(0.0255)
(0.0300)
Age
-0.0913***
-0.0394***
0.0024
-0.0912***
-0.0372***
0.0049
(0.0066)
(0.0056)
(0.0077)
(0.0073)
(0.0058)
(0.0073)
Squa ed age
0.0013***
0.0004***
-0.0001
0.0013***
0.0004***
-0.0002
(0.0001)
(0.0001)
(0.0001)
(0.0001)
(0.0001)
(0.0001)
Food insecu i y
-0.1954***
-0.1800***
-0.0782
-0.2270***
-0.1811***
-0.0541
(0.0576)
(0.0508)
(0.0567)
(0.0552)
(0.0443)
(0.0510)
Mo he ’s age
-0.0043
-0.0082***
-0.0078**
-0.0058**
-0.0085***
-0.0068***
(0.0038)
(0.0027)
(0.0030)
(0.0030)
(0.0023)
(0.0026)
Mo he ’s weigh
0.0179***
0.0267***
0.0227***
0.0178***
0.0278***
0.0245***
(0.0021)
(0.0020)
(0.0023)
(0.0020)
(0.0016)
(0.0019)
Mo he ’s heigh
0.0423***
0.0227***
-0.0050
0.0421***
0.0221***
-0.0058*
(0.0036)
(0.0028)
(0.0037)
(0.0033)
(0.0025)
(0.0031)
Cons an
-7.4281***
-5.2635***
-0.7633
(0.5501)
(0.4003)
(0.5233)
No. o Obs.
6,760
6,760
6,760
6,802
6,802
6,802
R2
0.2887
0.2860
0.1687
Chi2
680.5***
830.6***
190.6***
Bi h yea FE
YES
YES
YES
YES
YES
YES
Bi h mon h FE
YES
YES
YES
YES
YES
YES
AEZ FE
YES
YES
YES
YES
YES
YES
Bi h yea × Bi h
mon h FE
YES
YES
YES
YES
YES
YES
Bi h yea × AEZ FE
YES
YES
YES
YES
YES
YES
Bi h mon h × AEZ
FE
YES
YES
YES
YES
YES
YES
Flood FE
YES
YES
YES
YES
YES
YES
S o m FE
YES
YES
YES
YES
YES
YES
Ex eme
Tempe a u e FE
YES
YES
YES
YES
YES
YES
AEZ = ag o-ecological zone, FE = Fixed E ec s, HAZ = heigh - o -age z-sco e, LASSO = leas absolu e
sh inkage and selec ion Ope a o , OLS = o dina y leas squa es, WAZ = weigh - o -age z-sco e, WHZ =
weigh - o -heigh z-sco e.
No es: Robus s anda d e o s clus e ed a hana le el in pa en heses. ***, **, and * ep esen s a is ical
signi icance a 1-, 5-, and 10-pe cen le els, espec i ely. All a iables ollow hei espec i e de ini ions in
Table 1. Dependen a iables a e epo ed in column heade s. We es ima e he heal h e ec s o ain all
a ia ions using OLS (columns 1–3) and LASSO (columns 4–6) eg essions acco ding o equa ion (1),
whe e ou es ima ed coe icien o in e es is gi en by he coe icien s o he a iable “Rain all a ia ions.”
All eg essions include he ull se o ixed e ec s and con ol a iables.
Sou ce: Au ho s’ calcula ions using he Bangladesh In eg a ed Household Su ey da ase (Ahmed 2013,
In e na ional Food Policy Resea ch Ins i u e [IFPRI] 2016, IFPRI 2020).
14
We only ocus on he coe icien s o LASSO es ima es. Column (4) shows ha a one-uni
inc ease (dec ease) in in u e o ain all a ia ions leads o 0.0015-uni dec ease (inc ease) in HAZ.
Simila ly, column (5) shows ha a one-uni inc ease (dec ease) in in u e o ain all a ia ions leads
o 0.0014-uni dec ease (inc ease) in WAZ, while column (6) shows ha a one-uni inc ease
(dec ease) in in u e o ain all a ia ions leads o 0.0008-uni dec ease (inc ease) in WHZ.
We iden i y signi ican he e ogenei y among male and emale child en in e ms o HAZ: male
child en ha e lowe HAZ han emale child en. In gene al, HAZ and WAZ indices dec ease a an
inc easing a e wi h age, al hough he espec i e age coe icien s a e s a is ically insigni ican o
WHZ. As expec ed, child en om ood-insecu e households, and hose bo n o olde mo he s,
ha e lowe heal h s a us. Mo he ’s weigh has signi ican and posi i e e ec s on all he measu es
o child heal h s a us, whe eas he mo he ’s heigh a ec s HAZ and WAZ posi i ely, bu WHZ
nega i ely.
We also conduc se e al obus ness analyses. Appendix Table A1 also epo s he esul s
o bina y heal h ou come a iables whe e we de ine “s un ed” as HAZ<-2, “unde weigh ” as
WAZ<-2, and “was ed” as WHZ<-2. O e all, esul s con i m he p esence o heal h ad e si ies
om exposu e o ain all a ia ions and he e o e suppo ou main esul s in Table 2, i.e., ain all
a ia ions inc ease he p obabili y o s un ing by 0.05%, unde weigh by 0.05%, and was ed by
0.03%.
Ou esul s a e b oadly consis en wi h esul s o a speci ica ion wi h imes e ain all
a ia ions. Appendix Table A2 epo s he esul s whe e we di ide o al in u e o ain all a ia ions
o a ia ions du ing h ee imes e s sepa a ely. O e all, we iden i y ha HAZ is signi ican ly
a ec ed by he second imes e ain all a ia ions, whe eas WAZ is signi ican ly a ec ed by he
second and hi d imes e ain all a ia ions.
Conside ing he widescale use o i iga ion o ag icul u e in Bangladesh, i is possible ha
nega i e ain all a ia ions may ha e low o ze o ad e se e ec s on ag icul u al ou pu s and
he e o e on heal h ou comes. Appendix Table A3 epo s sepa a e esul s o d ough and lood
si ua ions ha a e de ined as nega i e and posi i e ain all a ia ions, i.e., 𝑐𝑐𝑑𝑑𝑖𝑖𝑖𝑖 < 0 and 𝑐𝑐𝑑𝑑𝑖𝑖𝑖𝑖 > 0,
espec i ely. As expec ed, we do no iden i y any s a is ically signi ican heal h ad e si ies om
ain all a ia ions du ing he d ough si ua ion. Howe e , ain all a ia ions du ing lood si ua ions
ha e s a is ically signi ican nega i e e ec s on heal h ou comes.
Appendix Table A4 epo s quan ile eg ession esul s. While we s ill obse e he signi ican
and nega i e e ec o ain all a ia ions on HAZ, he e a e no such ad e si ies o WAZ anymo e.
15
Toge he wi h ou main esul s and esul s o lood si ua ions, i is possible ha WAZ e ec s o
ain all a ia ions migh be mo e p o oundly el du ing hea y loods ha c ea e widesp ead ood
sca ci ies.
3.1. He e ogenous Heal h E ec s
Table 3 epo s he esul s o he he e ogenous impac , whe e we in e ac ed indica o a iables
o gende , ood insecu i y, mo he ’s heal h, and popula ion densi y wi h ain all a ia ions o
iden i y espec i e he e ogenei y.
Table 3: He e ogenous Heal h E ec s
(1)
(2)
(3)
(4)
(5)
(6)
A. Gende
B. Food insecu i y
Va iables
HAZ
WAZ
WHZ
Va iables
HAZ
WAZ
WHZ
Rain all a ia ions
-0.0017**
-0.0015**
-0.0008
Rain all a ia ions
-0.0014*
-0.0013**
-0.0007
(0.0008)
(0.0007)
(0.0008)
(0.0007)
(0.0006)
(0.0007)
Males
-0.0580*
0.0063
-0.0010
Food insecu i y
-0.2310***
-0.1879***
-0.0599
(0.0321)
(0.0255)
(0.0300)
(0.0554)
(0.0454)
(0.0520)
Rain all a ia ions
× Males
0.0005
0.0002
-0.0000
Rain all a ia ions ×
Food insecu i y
-0.0007
-0.0009
-0.0006
(0.0009)
(0.0007)
(0.0008)
(0.0017)
(0.0014)
(0.0016)
No. o Obs.
6,802
6,802
6,802
No. o Obs.
6,802
6,802
6,802
Se o FEs
YES
YES
YES
Se o FEs
YES
YES
YES
Con ols
YES
YES
YES
Con ols
YES
YES
YES
Chi2
682.7***
832.0***
190.7***
Chi2
680.5***
830.8***
190.7***
(7)
(8)
(9)
(10)
(11)
(12)
C. Mo he 's heal h
D. Popula ion densi y
Va iables
HAZ
WAZ
WHZ
Va iables
HAZ
WAZ
WHZ
Rain all a ia ions
-0.0009
-0.0020**
-0.0018**
Rain all a ia ions
-0.0015*
-0.0014**
-0.0010
(0.0009)
(0.0008)
(0.0009)
(0.0008)
(0.0006)
(0.0007)
Sho
-0.4663***
-0.2716***
0.0098
High densi y
0.1568***
0.1360***
0.0522
(0.0454)
(0.0367)
(0.0442)
(0.0494)
(0.0408)
(0.0465)
Rain all a ia ions
× Sho
-0.0007
0.0006
0.0011
Rain all a ia ions ×
High densi y
0.0013
0.0010
0.0007
(0.0012)
(0.0010)
(0.0011)
(0.0010)
(0.0008)
(0.0009)
Thin
-0.3116***
-0.3892***
-0.2746***
(0.0471)
(0.0377)
(0.0446)
Rain all a ia ions
× Thin
-0.0003
0.0021**
0.0031***
(0.0012)
(0.0010)
(0.0012)
Sho × Thin
0.0124
-0.0106
-0.0274
(0.0655)
(0.0526)
(0.0624)
Rain all a ia ions
× Sho × Thin
-0.0003
-0.0025*
-0.0033**
(0.0018)
(0.0015)
(0.0017)
No. o Obs.
6,802
6,802
6,802
No. o Obs.
6,802
6,802
6,802
Se o FEs
YES
YES
YES
Se o FEs
YES
YES
YES
Con ols
YES
YES
YES
Con ols
YES
YES
YES
Chi2
622.4***
673.3***
108.5***
Chi2
687.7***
823.3***
191.6***
FE = Fixed E ec , HAZ = heigh - o -age z-sco e, LASSO = Leas Absolu e Sh inkage and Selec ion
Ope a o , WAZ = weigh - o -age z-sco e, WHZ = weigh - o -leng h z-sco e.
No es: Robus s anda d e o s clus e ed a hana le el in pa en heses. ***, **, and * ep esen s a is ical
signi icance a 1-, 5-, and 10-pe cen le els, espec i ely. All a iables ollow hei espec i e de ini ions in
Table 1. Dependen a iables a e epo ed in column heade s. We explo e he he e ogenei y in he heal h
Con inued on he nex page
16
e ec s o ain all a ia ions using LASSO eg essions, whe e we ex ended equa ion (1) by in oducing
addi ional in e ac ion e ms wi h ain all a ia ions o each case in Panels A–D which p o ides ou
es ima ed coe icien o in e es . All eg essions include he ull se o ixed e ec s and con ol a iables.
Sou ce: Au ho s’ calcula ions using he BIHS da ase (Ahmed 2013, In e na ional Food Policy Resea ch
Ins i u e [IFPRI] 2016, IFPRI 2020).
Panel A epo s he e ogenei y impac on gende . While he e a e signi ican nega i e e ec s
o ain all a ia ions on HAZ and WAZ and male child en ha e signi ican ly lowe HAZ, male
child en ha ing in u e o exposu e o ain all a ia ions do no ha e any signi ican addi ional heal h
ad e si ies.
Panel B epo s he he e ogenous impac o he household’s ood insecu i y s a us. Like ou
main esul s in Table 2, hese esul s con i m ha he e a e signi ican nega i e e ec s o ain all
a ia ions on HAZ and WAZ and ood-insecu e child en ha e signi ican ly lowe HAZ and WAZ.
Howe e , we do no iden i y any exace ba ing e ec s o ood insecu i y as he es ima ed
coe icien s o he in e ac ion e m, hough nega i e, a e s a is ically insigni ican .
Panel C epo s he he e ogenous impac o he mo he ’s heal h. We measu e a mo he ’s
heal h by median heigh (i.e., 1 i below median heigh o sho , 0 i abo e median heigh ) and
median weigh (i.e., 1 i below median weigh o hin, 0 i no hin o abo e median weigh ).
In e es ingly, he esul s show ha child en bo n o sho mo he s ha e signi ican ly lowe HAZ
and WAZ, and child en bo n o hin mo he s ha e signi ican ly lowe HAZ, WAZ and WHZ. The e
a e no addi ional ad e si ies om in u e o ain all a ia ions o child en o sho o hin mo he s.
Howe e , while child en bo n o sho and hin mo he s ha e simila heal h s a us, hose who
expe ienced in u e o ain all a ia ions and bo n o sho and hin mo he s ha e signi ican ly lowe
WAZ and WHZ.
Panel D epo s he e ogenei y by dis ic -le el popula ion densi y pe squa e kilome e . I is
belie ed ha egions wi h mo e acili ies a e inhabi ed by mo e people, and because o hei
p oximi y o big u ban cen e s, hey also ecei e disas e and clima e isk educ ion in es men s
as e . Consis en wi h his na a i e, ou esul s con i m ha child en bo n in mo e densely
popula ed dis ic s ha e be e heal h s a us. Howe e , al hough posi i e, s a is ically insigni ican
coe icien s o he in e ac ion e m in o m ha high densi y does no ha e any mi iga ing e ec s
on ain all-induced heal h ad e si ies.

17
3.2. Po en ial Mechanisms o Heal h E ec s
Disas e s and clima e e en s damage ag icul u al ou pu s and he e o e c ea e ood sho ages in
a ec ed egions. In u e o exposu e o such ad e si ies he e o e could a ec he physical g ow h
and de elopmen o exposed child en. On he o he hand, weal hie egions migh ha e g ea e
adap i e capaci y o shocks and he e o e may expe ience lowe , i no ze o, ad e si ies. To
con i m hese no ions, we conside ela i e weal h index and c op di e si ica ion as po en ial
mechanisms behind ain all-induced heal h ad e si ies. Table 4 epo s he esul s whe e we
include ela i e weal h index and c op di e si ica ion as addi ional con ols o see whe he he
es ima ed esul s a y om hose in Table 2.
Table 4: Heal h Ad e si y Mechanisms
(1)
(2)
(3)
(4)
(5)
(6)
Weal h Index
e si ica ion
Va iables
HAZ
WAZ
WHZ
HAZ
WAZ
WHZ
Rain all a ia ions
-0.0016**
-0.0014**
-0.0008
-0.0015**
-0.0013**
-0.0008
(0.0007)
(0.0006)
(0.0007)
(0.0007)
(0.0006)
(0.0007)
RWI
0.1787***
0.1152***
0.0031
(0.0493)
(0.0384)
(0.0464)
C op di e si ica ion
-0.9222
-0.3988
0.1323
(0.5799)
(0.4754)
(0.5531)
Males
-0.0592*
0.0057
-0.0009
-0.0598*
0.0060
-0.0024
(0.0321)
(0.0256)
(0.0301)
(0.0320)
(0.0255)
(0.0300)
Age
-0.0921***
-0.0379***
0.0046
-0.0915***
-0.0375***
0.0047
(0.0073)
(0.0058)
(0.0073)
(0.0072)
(0.0058)
(0.0072)
Squa ed age
0.0013***
0.0004***
-0.0001
0.0013***
0.0004***
-0.0001
(0.0001)
(0.0001)
(0.0001)
(0.0001)
(0.0001)
(0.0001)
Food insecu i y
-0.2122***
-0.1764***
-0.0597
-0.2136***
-0.1781***
-0.0651
(0.0556)
(0.0446)
(0.0513)
(0.0555)
(0.0445)
(0.0512)
Mo he ’s age
-0.0052*
-0.0082***
-0.0069***
-0.0057*
-0.0087***
-0.0072***
(0.0030)
(0.0023)
(0.0026)
(0.0030)
(0.0023)
(0.0026)
Mo he ’s weigh
0.0173***
0.0273***
0.0242***
0.0180***
0.0278***
0.0244***
(0.0020)
(0.0016)
(0.0019)
(0.0020)
(0.0016)
(0.0019)
Mo he ’s heigh
0.0428***
0.0225***
-0.0057*
0.0422***
0.0221***
-0.0060*
(0.0033)
(0.0025)
(0.0031)
(0.0033)
(0.0025)
(0.0031)
Obse a ions
6,802
6,802
6,802
6,802
6,802
6,802
Chi2
689.4
833.2
186.3
687.9
822.8
187.8
Bi h yea FE
YES
YES
YES
YES
YES
YES
Bi h mon h FE
YES
YES
YES
YES
YES
YES
AEZ FE
YES
YES
YES
YES
YES
YES
Bi h yea × Bi h mon h
FE
YES
YES
YES
YES
YES
YES
Bi h yea × AEZ FE
YES
YES
YES
YES
YES
YES
Bi h mon h × AEZ FE
YES
YES
YES
YES
YES
YES
Flood FE
YES
YES
YES
YES
YES
YES
S o m FE
YES
YES
YES
YES
YES
YES
Ex eme Tempe a u e FE
YES
YES
YES
YES
YES
YES
Con inued on he nex page
18
AEZ = ag o-ecological Zone, FE = Fixed E ec s, HAZ = heigh - o -age z-sco e, LASSO = Leas Absolu e
Sh inkage and Selec ion Ope a o , RWI = ela i e weal h index, WAZ = weigh - o -age z-sco e, WHZ =
weigh - o -leng h z-sco e.
No es: Robus s anda d e o s clus e ed a hana le el in pa en heses. ***, **, and * ep esen s a is ical
signi icance a 1-, 5-, and 10-pe cen le els, espec i ely. All a iables ollow hei espec i e de ini ions in
Table 1. Dependen a iables a e epo ed in column heade s. We explo e he ole o RWI and c op
di e si ica ion as ansmission mechanisms. Using LASSO eg essions, we addi ionally include hese
a iables in ou speci ica ion in equa ion (1). Ou es ima ed coe icien o in e es is gi en by he coe icien s
o he a iable “Rain all a ia ions.” All eg essions include he ull se o ixed e ec s and con ol a iables.
Sou ce: Au ho s’ calcula ions using he Bangladesh In eg a ed Household Su ey (BIHS) da ase (Ahmed
2013, In e na ional Food Policy Resea ch Ins i u e [IFPRI] 2016, IFPRI 2020).
Panel A epo s esul s whe e we include he ela i e weal h index as an addi ional con ol
a iable. As expec ed, child en om weal hie egions ha e s a is ically signi ican ly highe HAZ
and WAZ, and highe bu insigni ican WHZ.
Panel B epo s esul s whe e we include egional c op di e si ica ion, a measu e o
ag icul u al di e si y, as an addi ional con ol a iable. Al hough s a is ically insigni ican , we
obse e nega i e ela ionships o HAZ and WAZ wi h c op di e si ica ion.
3.3. Selec ion Issues
I is possible ha he heal h ad e si ies om exposu e o in u e o ain all a ia ions a ise om
di e en sou ces o sel -selec ion bias. Fo example, male child bias, he p e alence o child
ma iage, and he mo he ’s heal h, en i lemen , and educa ion migh in luence ou es ima es in
Table 2. Fo his, we collapse da a o he hana-bi h-yea le el, calcula e measu es o hese
po en ial sou ces o selec ion bias, and hen un wo-way ixed e ec eg essions o hem on
ain all a ia ions.
Table 5: Selec ion Issues
(1)
(2)
(3)
(4)
(5)
Va iables
Male bias
Selec i e
e ili y
En i led
mo he
Educa ed
mo he
Child
ma iage
Rain all a ia ions
-0.0002
0.0010
-0.0002
0.0001
0.0001
(0.0003)
(0.0011)
(0.0002)
(0.0002)
(0.0002)
Cons an
0.5107***
2.6488***
0.8058***
0.8041***
0.0433***
(0.0078)
(0.0013)
(0.0056)
(0.0055)
(0.0042)
No. o Obs.
2,569
2,569
2,569
2,569
2,569
R2
0.1160
0.3971
0.2640
0.3156
0.1729
No. o hana
271
271
271
271
271
Se o FEs
NO
NO
NO
NO
NO
Con ols
NO
NO
NO
NO
NO
FE = Fixed E ec s, OLS = O dina y Leas Squa es.
Con inued on he nex page
19
No es: Robus s anda d e o s clus e ed a hana le el in pa en heses. ***, **, and * ep esen s a is ical
signi icance a 1-, 5-, and 10-pe cen le els, espec i ely. All a iables ollow hei espec i e de ini ions in
Table 1. Dependen a iables a e epo ed in he column heade s. We explo e he possibili ies o di e en
selec ion issues by collapsing da a o hana-bi h-yea le el, and hen unning OLS eg essions on ain all
a ia ions. We do no include any con ol a iables o ixed e ec s.
Sou ce: Au ho s’ calcula ions using he Bangladesh In eg a ed Household Su ey da ase (Ahmed 2013,
In e na ional Food Policy Resea ch Ins i u e [IFPRI] 2016, IFPRI 2020).
Table 5 epo s he esul s whe e we explo e hese possibili ies. Fi s , i he e is a bias o
male child en, ou esul s can be biased since he e can be gende ed di e ences in ulne abili y
o wea he ex emes (e.g., A o a-Jonsson 2011, Pea se 2017). To check his possibili y, we un
a eg ession o he -bi h-yea le el a e age p opo ion o male child en on a e age ain all
a ia ions o see whe he he e is any sys ema ic gende selec ion in ou es ima ing sample.
Howe e , ou es ima ed coe icien , epo ed in column (1), is s a is ically insigni ican and
he e o e ules ou he possibili y o gende selec ion.
Nex , women may selec hei e ili y and decide no o gi e bi h du ing wea he and
economic ad e si ies. I his is he case, he e will be a signi ican ly nega i e ela ionship be ween
ain all a ia ions and incidences o bi h. To check his possibili y, we collapse da a o he hana-
bi h yea le el and coun he o al numbe o child en bo n in a pa icula yea in each locali y.
We hen use his hana-bi h yea panel o eg ess he o al numbe o child en bo n in ha yea
on exposu e o ain all a ia ions. S a is ically insigni ican esul s in column (2) con i m ha
mo he s in ou es ima ing sample did no selec hei e ili y decisions.
Columns (3) and (4) epo esul s o en i lemen (measu ed by hei pa icipa ion in he
household’s ood- ela ed decisions) and educa ion (measu ed by ha ing any schooling) o he
mo he . I is possible ha p egnan women would ecei e p io i ies when women a e in ol ed in
he household’s ood- ela ed decisions and when women a e educa ed. I his is he case, hen
he mo he ’s en i lemen and educa ion should ha e some mi iga ing e ec s on hei child’s
ain all-induced heal h ad e si ies, and we would ha e o include hem in ou main speci ica ions
as addi ional con ols. To explo e hese possibili ies, we un eg essions o hana-bi h-yea le el
a e age en i lemen and educa ion o mo he s on a e age ain all a ia ions. Es ima ed
coe icien s a e s a is ically insigni ican , and he e o e, con i m ha mo he ’s en i lemen and
educa ion do no necessa ily ha e mi iga ing e ec s in ou es ima ing sample.
Finally, ain all a ia ions migh a ec he incidence o child ma iage. The ex en o een
p egnancy and o he ela ed p oblems migh be g ea e in egions wi h g ea e incidences o child
ma iage. This migh bias ou main esul s since child en bo n o younge mo he s may be mo e
20
ulneable o clima e and wea he a iabili ies (e.g., Rylande e al. 2013). To explo e his
possibili y, we collapse da a o he hana-bi h-yea le el and coun he o al numbe o ma ied
women aged below 18 yea s. We hen use his hana-bi h-yea panel o eg ess o al numbe o
child ma iages on ain all a ia ions. S a is ically insigni ican esul s con i m ha he e is no
egional bias a ising om excessi e incidences o child ma iage in ou es ima ing sample.
4. Mi iga ing E ec s o Clima e Policy
4.1. Mi iga ing E ec s o Clima e Fund
We now in es iga e he mi iga ing e ec s o clima e policy wi h ega d o heal h ad e si ies om
in u e o exposu e o ain all a ia ions acco ding o equa ion (2). Since we use a s agge ed
ea men o he measu e o clima e policy, i is impo an o check o balancing p ope y and
pa allel ends. Fi s , Appendix Table A5 shows ha mos o he con ol a iables ha e signi ican
a ia ions ac oss bi h yea and bi h dis ic . The e o e, i is impo an o include he componen s
o he ec o 𝑋𝑋𝑖𝑖𝑑𝑑𝑖𝑖𝑖𝑖
′ as con ols in all ou eg essions. Then, Appendix Table A6 shows he esul s
o p e- ea men coho s and un ea ed dis ic s. Resul s o p e- ea men coho s in Panel A
show ha he p e- ea men coho s om ea ed dis ic s wi h in u e o exposu e o ain all
a ia ions ha e s a is ically signi ican ly lowe HAZ and WAZ. Resul s a e s a is ically insigni ican
o un ea ed dis ic s (Panel B). Toge he , hese esul s imply ha o any causal impac o clima e
policies in educing ain all-induced heal h ad e si ies, es ima ed coe icien s o in e es mus be
posi i e and s a is ically signi ican .
Table 6 epo s he mi iga ing e ec s o clima e policy on heal h ad e si ies om in u e o
exposu e o ain all a ia ions o h ee an h opome y measu es acco ding o equa ion (2). Panels
A and B epo OLS and LASSO esul s, espec i ely. O e all, all models ha e o e all s a is ical
signi icance, and es ima ed coe icien s exhibi expec ed di ec ions o ela ionship wi h he
espec i e ou come a iable. Since esul s a e simila ac oss es ima ing s a egies, we only
desc ibe he coe icien s om LASSO eg essions. We also es ic ou discussion o he main
coe icien s o ou in e es .
27
Figu e A2: Bangladesh Clima e Change T us Fund Alloca ion
BCCTF = Bangladesh Clima e Change T us Fund.
Sou ce: Au ho s’ calcula ions using he BCCTF da ase .

28
Table A1: Heal h E ec s o Rain all Va ia ions—Bina y Ou come Va iables
(1)
(2)
(3)
(4)
(5)
(6)
A. OLS esul s
B. LASSO esul s
Va iables
S un ed
Unde weigh
Was ed
S un ed
Unde weigh
Was ed
Rain all a ia ions
0.0007**
0.0007**
0.0002
0.0005*
0.0005**
0.0003*
(0.0003)
(0.0003)
(0.0002)
(0.0003)
(0.0002)
(0.0002)
Males
0.0147
-0.0170
-0.0027
0.0201*
-0.0110
-0.0004
(0.0133)
(0.0120)
(0.0079)
(0.0113)
(0.0108)
(0.0077)
Age
0.0184***
0.0096***
-0.0019
0.0188***
0.0083***
-0.0020
(0.0022)
(0.0023)
(0.0020)
(0.0023)
(0.0023)
(0.0018)
Squa ed age
-0.0003***
-0.0001***
0.0000
-0.0003***
-0.0001**
0.0000
(0.0000)
(0.0000)
(0.0000)
(0.0000)
(0.0000)
(0.0000)
Food insecu i y
0.0573***
0.0781***
-0.0003
0.0613***
0.0714***
0.0005
(0.0220)
(0.0228)
(0.0148)
(0.0206)
(0.0206)
(0.0144)
Mo he ’s age
0.0014
0.0020*
0.0005
0.0015
0.0026***
0.0005
(0.0012)
(0.0011)
(0.0007)
(0.0010)
(0.0010)
(0.0007)
Mo he ’s weigh
-0.0059***
-0.0080***
-0.0030***
-0.0058***
-0.0086***
-0.0034***
(0.0008)
(0.0008)
(0.0005)
(0.0007)
(0.0007)
(0.0005)
Mo he ’s heigh
-0.0130***
-0.0087***
0.0003
-0.0131***
-0.0083***
0.0006
(0.0012)
(0.0013)
(0.0009)
(0.0011)
(0.0010)
(0.0008)
Cons an
2.3294***
1.7744***
0.2414*
(0.1872)
(0.1737)
(0.1314)
No. o Obs.
6,760
6,760
6,760
6,802
6,802
6,802
R2
0.2247
0.2093
0.1358
Chi2
491.1***
501.9***
75.33***
Se o FEs
YES
YES
YES
YES
YES
YES
FE = ixed e ec s, HAZ = heigh - o -age z-sco e, LASSO = Leas Absolu e Sh inkage and Selec ion
Ope a o , OLS = o dina y leas squa es, WAZ = weigh - o -age z-sco e, WHZ = weigh - o -heigh z-sco e.
No es: Robus s anda d e o s clus e ed a hana le el in pa en heses. ***, **, and * ep esen s a is ical
signi icance a 1-, 5-, and 10-pe cen le els, espec i ely. All a iables ollow hei espec i e de ini ions in
Table 1. Dependen a iables a e epo ed in he column heade s, whe e s un ed is de ined as HAZ<-2,
unde weigh as WAZ<-2, and was ed as WHZ<-2. We es ima e he heal h e ec s o ain all a ia ions using
OLS (columns 1–3) and LASSO (columns 4–6) eg essions acco ding o equa ion (1), whe e ou es ima ed
coe icien o in e es is gi en by he coe icien s o he a iable “Rain all a ia ions”. All eg essions include
he ull se o ixed e ec s and con ol a iables.
Sou ce: Au ho s’ calcula ions using he Bangladesh In eg a ed Household Su ey da ase (Ahmed 2013,
In e na ional Food Policy Resea ch Ins i u e [IFPRI] 2016; IFPRI 2020).
29
Table A2: Heal h E ec s o T imes e Rain all Va ia ions
(1)
(2)
(3)
(4)
(5)
(6)
OLS esul s
LASSO esul s
Va iables
HAZ
WAZ
WHZ
HAZ
WAZ
WHZ
Rain all a ia ions T1
-0.0009
-0.0002
0.0003
-0.0000
0.0002
0.0004
(0.0005)
(0.0004)
(0.0005)
(0.0004)
(0.0003)
(0.0004)
Rain all a ia ions T2
-0.0009*
-0.0007*
-0.0005
-0.0008*
-0.0007**
-0.0005
(0.0005)
(0.0004)
(0.0005)
(0.0004)
(0.0003)
(0.0004)
Rain all a ia ions T3
-0.0005
-0.0009**
-0.0007
-0.0006
-0.0008**
-0.0005
(0.0005)
(0.0004)
(0.0005)
(0.0004)
(0.0003)
(0.0004)
Males
-0.0439
0.0218
0.0090
-0.0529
0.0074
-0.0041
(0.0373)
(0.0295)
(0.0322)
(0.0322)
(0.0254)
(0.0299)
Age
-0.0913***
-0.0394***
0.0024
-0.0891***
-0.0370***
0.0048
(0.0066)
(0.0056)
(0.0077)
(0.0073)
(0.0059)
(0.0074)
Squa ed age
0.0013***
0.0004***
-0.0001
0.0012***
0.0004***
-0.0001
(0.0001)
(0.0001)
(0.0001)
(0.0001)
(0.0001)
(0.0001)
Food insecu i y
-0.1949***
-0.1811***
-0.0801
-0.2311***
-0.1849***
-0.0574
(0.0574)
(0.0509)
(0.0570)
(0.0552)
(0.0444)
(0.0512)
Mo he ’s age
-0.0043
-0.0082***
-0.0078**
-0.0058*
-0.0086***
-0.0070***
(0.0038)
(0.0027)
(0.0030)
(0.0030)
(0.0023)
(0.0026)
Mo he ’s weigh
0.0179***
0.0267***
0.0227***
0.0179***
0.0276***
0.0241***
(0.0021)
(0.0020)
(0.0023)
(0.0020)
(0.0016)
(0.0019)
Mo he ’s heigh
0.0423***
0.0227***
-0.0051
0.0421***
0.0222***
-0.0056*
(0.0036)
(0.0028)
(0.0037)
(0.0033)
(0.0025)
(0.0031)
Cons an
-7.4250***
-5.2569***
-0.7513
(0.5490)
(0.4009)
(0.5251)
No. o Obs.
6,760
6,760
6,760
6,802
6,802
6,802
R2
0.2888
0.2861
0.1691
Chi2
670.5***
817.8***
184.8***
Bi h yea FE
YES
YES
YES
YES
YES
YES
Bi h mon h FE
YES
YES
YES
YES
YES
YES
AEZ FE
YES
YES
YES
YES
YES
YES
Bi h yea × Bi h mon h
FE
YES
YES
YES
YES
YES
YES
Bi h yea × AEZ FE
YES
YES
YES
YES
YES
YES
Bi h mon h × AEZ FE
YES
YES
YES
YES
YES
YES
Flood FE
YES
YES
YES
YES
YES
YES
S o m FE
YES
YES
YES
YES
YES
YES
Ex eme Tempe a u e FE
YES
YES
YES
YES
YES
YES
AEZ = ag o-ecological zone, BCCTF = Bangladesh Clima e Change T us Fund, FE = ixed e ec s, HAZ =
heigh - o -age z-sco e, IHS = in e se hype bolic sine, LASSO = leas absolu e sh inkage and selec ion
ope a o , OLS = o dina y leas squa es, WAZ = weigh - o -age z-sco e, WHZ = weigh - o -leng h z-sco e.
No es: Robus s anda d e o s clus e ed a hana le el in pa en heses. ***, **, and * ep esen s a is ical
signi icance a 1-, 5-, and 10-pe cen le els, espec i ely. All a iables ollow hei espec i e de ini ions in
Table 1. Dependen a iables a e epo ed in column heade s. We es ima e he heal h e ec s o ain all
a ia ions using OLS (columns 1–3) and LASSO (columns 4–6) eg essions acco ding o equa ion (1),
whe e ou es ima ed coe icien o in e es is gi en by he coe icien s o he a iables “Rain all a ia ions
T1”, “Rain all a ia ions T2” and “Rain all a ia ions T3”. All eg essions include he ull se o ixed e ec s
and con ol a iables.
Sou ce: Au ho s’ calcula ions using he Bangladesh In eg a ed Household Su ey da ase (Ahmed 2013,
In e na ional Food Policy Resea ch Ins i u e [IFPRI] 2016; IFPRI 2020).
30
Table A3: Heal h E ec s Du ing D ough and Flood Si ua ions
(1)
(2)
(3)
(4)
(5)
(6)
D ough si ua ion
Flood si ua ion
Va iables
HAZ
WAZ
WHZ
HAZ
WAZ
WHZ
Rain all a ia ions
0.0011
0.0001
-0.0008
-0.0041***
-0.0017*
0.0011
(0.0016)
(0.0013)
(0.0015)
(0.0012)
(0.0010)
(0.0011)
Males
-0.0470
0.0194
0.0057
-0.0734
0.0081
0.0102
(0.0417)
(0.0336)
(0.0398)
(0.0509)
(0.0403)
(0.0471)
Age
-0.1004***
-0.0455***
0.0034
-0.0761***
-0.0250***
0.0044
(0.0088)
(0.0072)
(0.0091)
(0.0121)
(0.0091)
(0.0119)
Squa ed age
0.0014***
0.0005***
-0.0001
0.0010***
0.0002
-0.0001
(0.0001)
(0.0001)
(0.0001)
(0.0002)
(0.0001)
(0.0002)
Food insecu i y
-0.1897***
-0.1279**
-0.0118
-0.3741***
-0.3568***
-0.1975**
(0.0724)
(0.0553)
(0.0635)
(0.0873)
(0.0750)
(0.0857)
Mo he ’s age
-0.0011
-0.0030
-0.0023
-0.0099**
-0.0151***
-0.0127***
(0.0039)
(0.0031)
(0.0035)
(0.0047)
(0.0035)
(0.0040)
Mo he ’s weigh
0.0153***
0.0283***
0.0271***
0.0232***
0.0277***
0.0199***
(0.0026)
(0.0021)
(0.0025)
(0.0032)
(0.0026)
(0.0030)
Mo he ’s heigh
0.0401***
0.0191***
-0.0091**
0.0474***
0.0268***
-0.0029
(0.0044)
(0.0032)
(0.0043)
(0.0048)
(0.0040)
(0.0044)
No. o Obs.
4,109
4,109
4,109
2,693
2,693
2,693
Chi2
393.7***
489.1***
129.4***
321.3***
351.6***
66.49**
Bi h yea FE
YES
YES
YES
YES
YES
YES
Bi h mon h FE
YES
YES
YES
YES
YES
YES
AEZ FE
YES
YES
YES
YES
YES
YES
Bi h yea × Bi h mon h FE
YES
YES
YES
YES
YES
YES
Bi h yea × AEZ FE
YES
YES
YES
YES
YES
YES
Bi h mon h × AEZ FE
YES
YES
YES
YES
YES
YES
Flood FE
YES
YES
YES
YES
YES
YES
S o m FE
YES
YES
YES
YES
YES
YES
Ex eme Tempe a u e FE
YES
YES
YES
YES
YES
YES
AEZ = ag o-ecological zone, FE = ixed e ec s, HAZ = heigh - o -age z-sco e, IHS = in e se hype bolic
sine, LASSO = leas absolu e sh inkage and selec ion ope a o , OLS = o dina y leas squa es, WAZ =
weigh - o -age z-sco e, WHZ = weigh - o -heigh z-sco e.
No es: Robus s anda d e o s clus e ed a hana le el in pa en heses. ***, **, and * ep esen s a is ical
signi icance a 1-, 5-, and 10-pe cen le els, espec i ely. All a iables ollow hei espec i e de ini ions in
Table 1. Dependen a iables a e epo ed in he column heade s. We es ima e he heal h e ec s o ain all
a ia ions using LASSO eg essions acco ding o equa ion (1) o d ough and lood si ua ions ha a e
de ined as nega i e and posi i e ain all a ia ions, i.e., 𝑐𝑐𝑑𝑑𝑖𝑖𝑖𝑖 < 0 and 𝑐𝑐𝑑𝑑𝑖𝑖𝑖𝑖 > 0, espec i ely. Ou es ima ed
coe icien o in e es is gi en by he coe icien s o he a iable “Rain all a ia ions”. All eg essions include
he ull se o ixed e ec s and con ol a iables.
Sou ce: Au ho s’ calcula ions using he Bangladesh In eg a ed Household Su ey da ase (Ahmed 2013,
In e na ional Food Policy Resea ch Ins i u e [IFPRI] 2016, IFPRI 2020).
31
Table A4: Heal h E ec s o Rain all Va ia ions: Quan ile Reg essions
(1)
(2)
(3)
Va iables
HAZ
WAZ
WHZ
Rain all a ia ions
-0.0010**
0.0001
-0.0000
(0.0005)
(0.0006)
(0.0005)
Males
0.0998**
0.0000
0.0690*
(0.0418)
(0.0519)
(0.0359)
Age
-0.0146***
-0.0204***
-0.0229***
(0.0054)
(0.0052)
(0.0029)
Squa ed age
0.0001
0.0002***
0.0002***
(0.0001)
(0.0001)
(0.0000)
Food insecu i y
-0.0136
0.0138
0.0462
(0.0544)
(0.0628)
(0.0842)
Mo he ’s age
0.0019
0.0027
-0.0011
(0.0047)
(0.0029)
(0.0036)
Mo he ’s weigh
-0.0033
-0.0011
0.0015
(0.0033)
(0.0020)
(0.0024)
Mo he ’s heigh
0.0029
0.0044
-0.0001
(0.0046)
(0.0028)
(0.0036)
Cons an
1.4330**
0.9430**
1.7823***
(0.6831)
(0.4261)
(0.5297)
No. o Obs.
6,802
6,802
6,802
Se o FEs
NO
NO
NO
FE = ixed e ec s, HAZ = heigh - o -age z-sco e, WAZ = weigh - o -age z-sco e, WHZ = weigh - o -heigh
z-sco e.
No es: Robus s anda d e o s clus e ed a hana le el in pa en heses. ***, **, and * ep esen s a is ical
signi icance a 1-, 5-, and 10-pe cen le els, espec i ely. All a iables ollow hei espec i e de ini ions in
Table 1. Dependen a iables a e epo ed in he column heade s. Quan ile eg essions ollow he
speci ica ion (1) excluding he ixed e ec s. Ou es ima ed coe icien o in e es is gi en by he coe icien s
o he a iable “Rain all a ia ions”.
Sou ce: Au ho s’ calcula ions using he Bangladesh In eg a ed Household Su ey da ase (Ahmed 2013,
In e na ional Food Policy Resea ch Ins i u e [IFPRI] 2016, IFPRI 2020).
32
Table A5: Balancing P ope ies
(1)
(2)
(3)
(4)
(5)
(6)
(7)
CC 0
CC 0
CC 1
CC 1
Va iables
DD 0
DD 1
DD 0
DD 1
(2) – (1)
(3) – (1)
(4) – (1)
Males
0.526
(0.500)
0.496
(0.500)
0.496
(0.501)
0.525
(0.499)
-0.0299
-0.0298
-0.0006
Age
34.25
(16.93)
33.57
(17.20)
25.48
(15.37)
25.37
(15.47)
-0.6814
- 8.7756***
-8.8840***
Weigh
11.03
(2.901)
10.93
(2.965)
10.07
(2.844)
10.09
(2.869)
-0.0922
-0.952***
-0.936***
Heigh
85.56
(12.78)
84.91
(13.18)
80.89
(12.46)
80.86
(12.59)
-0.6495
-4.6717***
-4.6951***
Mo he ’s age
27.10
(5.941)
27.73
(5.973)
27.33
(5.537)
26.99
(5.707)
0.6328**
0.2304
-0.1047
Mo he ’s weigh
46.76
(8.460)
46.78
(8.490)
49.65
(9.562)
49.72
(9.416)
0.0271
2.8970***
2.9660***
Mo he ’s heigh
150.3
(5.216)
150.6
(5.886)
150.7
(5.608)
151.0
(5.577)
0.3101
0.4348
0.7184***
Decision making
0.687
(0.464)
0.722
(0.448)
0.845
(0.363)
0.871
(0.336)
0.0356*
0.1577***
0.1838***
Mo he ’s schooling
0.705
(0.456)
0.732
(0.443)
0.853
(0.355)
0.862
(0.344)
0.0268
0.1478***
0.1573***
Ag icul u e
0.201
(0.193)
0.175
(0.178)
0.0841
(0.123)
0.0950
(0.131)
-0.0259***
-0.1170***
-0.1060***
Food insecu i y
0.101
(0.301)
0.118
(0.323)
0.0714
(0.258)
0.0667
(0.250)
0.0174
-0.0293*
-0.0340***
Child ma iage
0.00549
(0.0740)
0.00530
(0.0774)
0.0294
(0.181)
0.0268
(0.166)
-0.0002
0.0239***
0.0213***
RWI
-0.0382
(0.355)
-0.00870
(0.355)
-0.0414
(0.370)
0.0116
(0.354)
0.0295*
-0.0032
0.0499***
C op di e si ica ion
0.246
(0.0355)
0.261
(0.0377)
0.249
(0.0405)
0.262
(0.0377)
0.0154
0.0034
-0.0161***
HAZ
-1.824
(1.386)
-1.820
(1.397)
-1.394
(1.280)
-1.317
(1.443)
0.0043
0.4301***
0.5065***
WAZ
-1.644
(1.100)
-1.607
(1.099)
-1.320
(1.061)
-1.252
(1.128)
0.0377
0.3242
0.3920***
WHZ
-0.742
(1.193)
-0.679
(1.196)
-0.678
(1.119)
-0.657
(1.290)
0.0631
0.0644
0.0856
No. o Obs.
546
2,828
476
2,952
BCCTF = Bangladesh Clima e Change T us Fund, HAZ = heigh - o -age z-sco e, IHS = in e se hype bolic
sine, OLS = o dina y leas squa es, RWI = ela i e weal h index, WAZ = weigh - o -age z-sco e, WHZ =
weigh - o -heigh z-sco e.
No es: Balancing p ope ies a e o he es ima ing sample o 6,802 child en aged 0–60 mon hs whose
mo he s we e su eyed in any o he h ee ounds o he Bangladesh In eg a ed Household Su ey (BIHS)
da a. CC deno es BCCTF- ea ed coho s, i.e., 1 i he coho is ea ed by BCCTF clima e unds (i.e., yea s
2012–2018), 0 i no (i.e., yea s 2007–2011), whe eas DD deno es BCCTF ea ed dis ic s, i.e., 1 i he
dis ic is ea ed by BCCTF clima e unds, 0 i no .
Sou ce: Au ho s’ calcula ions using he Bangladesh In eg a ed Household Su ey da ase (Ahmed 2013,
In e na ional Food Policy Resea ch Ins i u e [IFPRI 2016], IFPRI 2020).

33
Table A6: Pa allel T ends
(1)
(2)
(3)
(4)
(5)
(6)
P e- ea men coho s
Un ea ed dis ic s
Va iables
HAZ
WAZ
WHZ
HAZ
WAZ
WHZ
Rain all a ia ions
0.0019
0.0026
0.0019
0.0019
0.0026
0.0019
(0.0020)
(0.0016)
(0.0018)
(0.0020)
(0.0016)
(0.0018)
T ea ed dis ic s
-0.0237
0.0026
0.0454
(0.0829)
(0.0579)
(0.0614)
Rain all a ia ions × T ea ed
dis ic s
-0.0045**
-0.0056***
-0.0029
(0.0022)
(0.0018)
(0.0020)
T ea ed coho s
0.4217***
0.3058***
0.0491
(0.0870)
(0.0650)
(0.0615)
Rain all a ia ions × T ea ed
coho s
-0.0038
-0.0010
0.0006
(0.0027)
(0.0021)
(0.0023)
Cons an
-1.8123***
-1.6283***
-0.7310***
-1.8123***
-1.6283***
-0.7310***
(0.0758)
(0.0510)
(0.0544)
(0.0767)
(0.0516)
(0.0550)
No. o Obs.
3,374
3,374
3,374
1,022
1,022
1,022
R2
0.0026
0.0060
0.0012
0.0274
0.0258
0.0051
Se o FEs
NO
NO
NO
NO
NO
NO
Con ols
NO
NO
NO
NO
NO
NO
FE = ixed e ec s, HAZ = heigh - o -age z-sco e, WAZ = weigh - o -age z-sco e, WHZ = weigh - o -heigh
z-sco e.
No es: Robus s anda d e o s in pa en heses. ***, **, and * ep esen s a is ical signi icance a 1-, 5-, and
10-pe cen le els, espec i ely. All a iables ollow hei espec i e de ini ions in Table 1. Dependen
a iables a e epo ed in he column heade s. The es ima ed sample is es ic ed o he un ea ed
households only, he e o e p o iding a es o pa allel end assump ion.
Sou ce: Au ho s’ calcula ions using he Bangladesh In eg a ed Household Su ey da ase (Ahmed 2013,
In e na ional Food Policy Resea ch Ins i u e [IFPRI] 2016; IFPRI 2020).
34
Table A7: Mi iga ing E ec s o Clima e Policies: Bina y Ou come Va iables
(1)
(2)
(3)
(4)
(5)
(6)
OLS esul s
LASSO esul s
Va iables
S un ed
Unde weigh
Was ed
S un ed
Unde weigh
Was ed
Rain all a ia ions
0.0007
0.0002
-0.0001
0.0005
0.0000
0.0000
(0.0005)
(0.0005)
(0.0003)
(0.0005)
(0.0004)
(0.0003)
T ea ed child en
-0.0050
-0.0340
0.0206
-0.0097
0.0019
0.0093
(0.0740)
(0.0720)
(0.0459)
(0.0694)
(0.0623)
(0.0502)
Rain all a ia ions × T ea ed
child en
0.0011
0.0030**
0.0017
0.0014
0.0035**
0.0017
(0.0014)
(0.0013)
(0.0011)
(0.0015)
(0.0014)
(0.0011)
IHS(BCCTF)
-0.0058
-0.0060
-0.0022
-0.0044
-0.0044
-0.0017
(0.0051)
(0.0041)
(0.0028)
(0.0040)
(0.0039)
(0.0026)
Rain all a ia ions × IHS(BCCTF)
-0.0000
0.0002
0.0001
0.0000
0.0002*
0.0001
(0.0001)
(0.0001)
(0.0001)
(0.0001)
(0.0001)
(0.0001)
T ea ed child en × IHS(BCCTF)
0.0087
0.0146
0.0006
0.0074
0.0067
0.0018
(0.0160)
(0.0139)
(0.0094)
(0.0139)
(0.0125)
(0.0099)
Rain all a ia ions × T ea ed
child en × IHS(BCCTF)
-0.0002
-0.0006**
-0.0003
-0.0002
-0.0008***
-0.0003
(0.0003)
(0.0003)
(0.0002)
(0.0003)
(0.0003)
(0.0002)
Males
0.0146
-0.0169
-0.0026
0.0194*
-0.0118
-0.0010
(0.0134)
(0.0121)
(0.0079)
(0.0115)
(0.0110)
(0.0078)
Age
0.0184***
0.0098***
-0.0019
0.0189***
0.0083***
-0.0021
(0.0022)
(0.0023)
(0.0020)
(0.0023)
(0.0023)
(0.0018)
Squa ed age
-0.0003***
-0.0001***
0.0000
-0.0003***
-0.0001**
0.0000
(0.0000)
(0.0000)
(0.0000)
(0.0000)
(0.0000)
(0.0000)
Food insecu i y
0.0568**
0.0773***
-0.0008
0.0585***
0.0699***
-0.0030
(0.0220)
(0.0227)
(0.0148)
(0.0208)
(0.0209)
(0.0143)
Mo he ’s age
0.0015
0.0021*
0.0005
0.0014
0.0023**
0.0007
(0.0012)
(0.0011)
(0.0007)
(0.0010)
(0.0010)
(0.0007)
Mo he ’s weigh
-0.0059***
-0.0080***
-0.0030***
-0.0058***
-0.0083***
-0.0034***
(0.0008)
(0.0008)
(0.0005)
(0.0007)
(0.0007)
(0.0005)
Mo he ’s heigh
-0.0129***
-0.0086***
0.0003
-0.0131***
-0.0086***
0.0006
(0.0012)
(0.0013)
(0.0009)
(0.0011)
(0.0010)
(0.0008)
Cons an
2.3373***
1.7869***
0.2422*
(0.1898)
(0.1728)
(0.1305)
No. o Obs.
6,760
6,760
6,760
6,802
6,802
6,802
R2
0.2252
0.2107
0.1367
Chi2
480.7***
489.5***
76.05**
Se o FEs
YES
YES
YES
YES
YES
YES
BCCTF = Bangladesh Clima e Change T us Fund, FE = ixed e ec s, HAZ = heigh - o -age z-sco e, IHS
= in e se hype bolic sine, LASSO = leas absolu e sh inkage and selec ion ope a o , OLS = o dina y leas
squa es, WAZ = weigh - o -age z-sco e, WHZ = weigh - o -heigh z-sco e.
No es: Robus s anda d e o s clus e ed a hana le el in pa en heses. ***, **, and * ep esen s a is ical
signi icance a 1-, 5-, and 10-pe cen le els, espec i ely. All a iables ollow hei espec i e de ini ions in
Table 1. Dependen a iables a e epo ed in he column heade s, whe e s un ed is de ined as HAZ<-2,
unde weigh as WAZ<-2, and was ed as WHZ<-2. We es ima e he mi iga ing e ec s o clima e policy on
he heal h e ec s o ain all a ia ions using OLS (columns 1–3) and LASSO (columns 4–6) eg essions
acco ding o equa ion (2). Ou es ima ed coe icien s o in e es a e gi en by he coe icien s o he
in e ac ion e m “Rain all a ia ions × T ea ed child en × IHS(BCCTF)”. All eg essions include he ull se
o ixed e ec s and con ol a iables.
Sou ce: Au ho s’ calcula ions using he Bangladesh In eg a ed Household Su ey da ase (Ahmed 2013,
In e na ional Food Policy Resea ch Ins i u e [IFPRI] 2016, IFPRI 2020).
35
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