Be niell, Inés; Ma chionni, Ma iana; Ped azzi, Julián; Viollaz, Ma iana
Wo king Pape
Women poli ical leade s as agen s o en i onmen al
change
IDB Wo king Pape Se ies, No. IDB-WP-1704
P o ided in Coope a ion wi h:
In e -Ame ican De elopmen Bank (IDB), Washing on, DC
Sugges ed Ci a ion: Be niell, Inés; Ma chionni, Ma iana; Ped azzi, Julián; Viollaz, Ma iana (2025) :
Women poli ical leade s as agen s o en i onmen al change, IDB Wo king Pape Se ies, No. IDB-
WP-1704, In e -Ame ican De elopmen Bank (IDB), Washing on, DC,
h ps://doi.o g/10.18235/0013521
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Women Poli ical Leade s as
A
gen s
o En i onmen al Change
Inés Be niell
Ma iana Ma chionni
Julián Ped azzi
Ma iana Viollaz
WORKING PAPER No IDB-WP-1704
In e -
A
me ican De elopmen Bank
Gende and Di e si y Di ision
May 2025
* CEDLAS - IIE - Uni e sidad Nacional de La Pla a
** CEDLAS - IIE - Uni e sidad Nacional de La Pla a and CONICET
Women Poli ical Leade s as Agen s
o En i onmen al Change
Inés Be niell*
Ma iana Ma chionni**
Julián Ped azzi**
Ma iana Viollaz*
In e -
A
me ican De elopmen Bank
Gende and Di e si y Di ision
May 2025
Ca aloging-in-Publica ion da a p o ided by he
In e -Ame ican De elopmen Bank
Felipe He e a Lib a y
Women poli ical leade s as agen s o en i onmen al change / Inés Be niell,
Ma iana Ma chionni, Julián Ped azzi, Ma iana Viollaz.
p. cm. — (IDB Wo king Pape Se ies ; 1704)
Includes bibliog aphical e e ences.
1. En i onmen al policy-B azil. 2. Clima ic changes-Go e nmen policy-B azil.
3. Women in conse a ion o na u al esou ces-B azil. 4. En i onmen al
impac analysis-B azil. 5. Gende mains eaming-B azil. I. Be niell, Inés. II.
Ma chionni, Ma iana. III. Ped azzi, Julián. IV. Viollaz, Ma iana. V. In e -
Ame ican De elopmen Bank. Gende and Di e si y Di ision. VI. Se ies.
IDB-WP-1704
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Abs ac 1
This pape explo es how emale poli ical leade s impac en i onmen al ou comes and cli-
ma e change policy ac ions using da a om mixed-gende mayo al aces in B azil. We ely on
a Reg ession Discon inui y design ha compa es municipali ies whe e women na owly won
he elec ion wi h hose whe e men na owly won. This s a egy allows us o iden i y he
causal effec o a woman winning he mayo al elec ion. We find ha , compa ed o male
mayo s, emale mayo s significan ly educe g eenhouse gas emissions and de o es a ion in he
municipali ies wi h Amazon biome. Specifically, when a woman wins he elec ion, an-nual
g eenhouse gas emissions dec ease by 1,510 housand ons o CO2e pe municipali y in he
Amazon. This effec alone ep esen s 23% o he a e age annual emissions o all munic-
ipali ies wi hin he Amazon biome and 6.4% o B azil’s na ionwide a e age. This educ ion is
d i en by a educ ion in emissions in ensi y (CO2e/GDP) in he Land Use sec o , wi hou
changes in municipal economic ac i i y. Pa o he educ ion in emissions in he Land Use
sec o is a ibu able o a decline in de o es a ion. Specifically, emale-led municipali ies in
he Amazon expe ience a educ ion in de o es a ion, wi h a 3 pe cen age-poin dec ease in he
loss o o es o ma ions ela i e o he baseline o es co e . This ep esen s a 32% educ ion
compa ed o de o es a ion le els in he compa ison municipali ies. We examine po en ial
mechanisms ha could explain he posi i e en i onmen al impac o na owly elec ing a
emale mayo o e a male coun e pa and find ha in Amazon municipali ies, emale elec ed
mayo s alloca e mo e space o he en i onmen in hei go e nmen p oposals and a e mo e
likely o in es in en i onmen al ini ia i es. Diffe ences in he en o cemen o en i onmen al
egula ions and he le el o educa ion o elec ed emale and male mayo s do no explain he
esul s.
JEL classifica ions: J16, D72, Q54, Q56, Q58
Keywo ds: Gende , Clima e change, Mayo al elec ions, Amazon, B azil, La in Ame ica
1This esea ch ecei ed unding om he Gende and Di e si y Knowledge Ini ia i e, a GDLab, In e -
Ame ican De elopmen Bank, as pa o he p ojec “Clima e Change and I s Nexus wi h Gende and
Di e si y.” We a e pa icula ly indeb ed o Felipe Jo dan and Isabelle Cho o hei ex ensi e and
in aluable eedback. We a e also e y g a e ul o C is ian Bona ida, Ma ias Ciaschi, Guille mo C uces,
Guille mo Falcone, Leona do Gaspa ini, Ca los Lama che, Ignacio Lunghi, and Ma iano Rabassa, as well
as he GDLab eam, o hei insigh ul sugges ions. We also hank semina pa icipan s a Uni e sidad
Nacional de La Pla a, Uni e sidad de Buenos Ai es, and he LIX Annual Mee ing o Asociación A gen ina
de Economía Polí ica a Uni e sidad Nacional de Sal a o help ul discussion. The usual disclaime applies.
1 In oduc ion
Clima e change is a p essing global conce n ha equi es adequa e and imely poli-
cies. Rising g eenhouse gas emissions a e apidly inc easing a e age global empe a u es
and al e ing ain all pa e ns. These en i onmen al changes ha e significan social and
economic implica ions, including job losses, educed p oduc i i y and hou s o wo k, de-
ficien de elopmen o ounda ional cogni i e skills, changes in mig a ion pa e ns, and
inc eased po e y (e.g., G aff Zi in and Neidell,2014;Jafino e al.,2020;Sage e al.,
2020;Salemi,2021;Pazos e al.,2024).
Clima e change in e sec s wi h gende in impo an ways. Fi s , poli ical leade ship
plays a i al ole in add essing clima e change, and p e ious esea ch shows ha a leade ’s
gende can influence policy decisions (Cha opadhyay and Duflo,2004). Women leade s
end o p omo e be e social ou comes, including inc eased spending and be e heal h
and educa ion, educed gende -based iolence, lowe le els o co up ion, imp o ed in-
s i u ional quali y, and highe a es o economic g ow h (Dolla e al.,2001;Jayasu iya
and Bu ke,2013;Bhalo a and Clo s-Figue as,2014;B uce e al.,2022;Delapo e and
Pino,2022;Bochenko a e al.,2023). Second, s udies indica e ha pe cep ions o clima e
change diffe by sex, wi h women gene ally exhibi ing mo e awa eness and conce n han
men (E gas and Yo k,2012;Dechezlep ê e e al.,2022). These diffe ences a e o en
a ibu ed o women’s adi ional oles as ca egi e s, subsis ence ood p oduce s, and
wa e and uelwood collec o s, as well as gende diffe ences in alues such as coope a ion
and a en i eness (E gas and Yo k,2012). Gi en hese pa e ns, we expec emale lead-
e s o adop dis inc en i onmen al app oaches compa ed o male leade s. Fu he mo e,
since clima e change exace ba es exis ing gende inequali ies—disp opo iona ely affec -
ing women and gi ls h ough esou ce sca ci y, inc eased isks o iolence du ing c ises
like d ough s, and highe likelihood o displacemen du ing clima e disas e s (Hab ezion,
2016;Ma cos Mo ezuelas,2021;Dehingia e al.,2024)—i is plausible o an icipa e an
addi ional effec i leade s a e mo e likely o implemen policy ac ions ha add ess he
needs o hei own gende (Cha opadhyay and Duflo,2004).
The e o e, we hypo hesize ha emale poli ical leade s migh pe o m be e han
men in add essing clima e change. We es his hypo hesis using in o ma ion on mixed-
gende close mayo al elec o al aces in B azilian municipali ies. The e a e se e al easons
o ocusing ou analysis on B azil. The coun y holds 60% o he Amazon ain o es , he
la ges opical o es in he wo ld, which plays a key ole in global clima e egula ion. In
addi ion, B azil has mo e han fi e housand municipali ies wi h in o ma ion on a ious
ou comes ela ed o clima e change and on policy a iables ele an o ou analysis.
Finally, B azil is a highly decen alized coun y, and i s municipali ies ha e decision-
making powe on en i onmen al issues.
P e ious e idence suppo s ou hypo hesis. The c oss-coun y s udies o Zhike and
Deng (2019), E gas and Yo k (2012) and Asongu e al. (2022) epo a nega i e associa-
ion be ween women’s poli ical empowe men and o al ca bon dioxide (CO2) emissions,
2
women’s poli ical ep esen a ion and CO2 emissions pe capi a, and be ween women’s
poli ical ep esen a ion and ulne abili y o clima e change, espec i ely, using da a om
de eloped and de eloping coun ies a ound he wo ld. Simila ly, o he c oss-coun y s ud-
ies use in o ma ion om coun ies and egions o a ious de elopmen le els o show ha
he e is a posi i e ela ionship be ween he sha e o women in pa liamen and he a ifi-
ca ion o en i onmen al ea ies (No gaa d and Yo k,2005), s ingency o clima e change
policies (Ma isakalyan and Ta e di,2019), p oduc ion o enewable ene gy (Bansal and
D’Agos i,2023), and consump ion o enewable ene gy (Slamon,2023).
Only a ew s udies, howe e , p o ide causal analysis on his opic. Fo ins ance,
Be aldi and Fosco (2024) analyze he case o I aly using a diffe ence-in-diffe ence in-
s umen al a iables app oach. They find ha an inc ease in he pe cen age o emale
councilo s in I aly dec eases ai pollu ion, and he effec is likely explained by an inc ease
in he densi y o bicycle lanes, u ban g een spaces, bicycle and ca sha ing se ices, use
o cen alized hea ing sys ems, and use o affic blockage. Close o ou s udy, Jagnani
and Mahade an (2021) implemen an RD s a egy o show ha he elec ion o women
legisla o s in India leads o a educ ion in c op-fi e inciden s, while Neumman López
(2024) uses an RD s a egy based on mixed-gende elec o al aces in Mexico o show
ha elec ing a woman as municipal p esiden o e a man imp o es wa e managemen ,
a measu e ela ed o he consequences o clima e change. To he bes o ou knowledge,
he e is no causal e idence abou how emale poli ical leade s impac di ec measu es
o clima e change—i.e., g eenhouse gas emissions and de o es a ion—compa ed o hei
male coun e pa s in La in Ame ica, pa icula ly wi hin he Amazon egion, o on how
hei policy decisions ega ding clima e change media e his ela ionship.
Iden i ying he causal effec o emale poli ical leade s on en i onmen al and policy
ou comes is challenging because o he p esence o o he ac o s, such as socie al a i udes
owa d women, ha may be co ela ed wi h bo h women winning an elec ion and he
ou come a iables. To ackle his issue, we adop a Reg ession Discon inui y (RD) design
ha compa es ou comes in municipali ies whe e a woman won an elec ion by a na ow
ma gin agains a male candida e wi h municipali ies whe e he winne was, by a na ow
ma gin, a man (Lee e al.,2004). The in ui ion behind his compa ison is ha in close
elec ion aces, he p obabili y o winning is he same o women and men. Then, munic-
ipali ies wi h a male mayo who won by a na ow ma gin a e a good coun e ac ual o
municipali ies wi h emale mayo s who also won by a na ow ma gin. P e ious s udies
ha e applied his app oach in B azil o analyze he impac o emale leade ship on o he
ou comes such as co up ion (B ollo and T oiano,2016), heal h ou comes (B uce e al.,
2022), and gende -based iolence (Bochenko a e al.,2023;Delapo e and Pino,2022).
We analyze ou come a iables ela ed o g eenhouse gas emissions and de o es a ion
a he municipal le el. These wo ou comes a e ela ed, since de o es a ion is one o he
main con ibu o s o he le els o emissions. In ac , in La in Ame ica, a ound 40% o he
g eenhouse gas emissions in 2019 o igina ed om land use changes, such as con e ing
o es s o pas u es o ag icul u al lands, and he bu ning o o es esidues (B assiolo
3
e al.,2023). Fo g eenhouse gas emissions, we conside he a e age annual emissions
pe municipali y wi hin each ou -yea mayo al e m, bo h in ons o ca bon dioxide
equi alen (CO2e) and ela i e o municipal economic ac i i y (CO2e/GDP). Addi ion-
ally, we dis inguish be ween o al municipal emissions and sec o -specific emissions. As
o de o es a ion, we ocus on changes in o es o ma ions in each municipali y o e he
ou -yea e m o he mayo s’ manda es, measu ed as a pe cen age o he municipal o es
co e . We conduc ou analysis o all B azilian municipali ies wi h close mixed-gende
elec ions and he subsamples o municipali ies wi h ege a ion ypical o he Amazon
biome (Amazon municipali ies) and hose wi hou i (non-Amazon municipali ies).
Addi ionally, we inno a e by analyzing he mechanisms behind he impac s o ha ing
a woman elec ed as a mayo on clima e change- ela ed ou comes. These po en ial mecha-
nisms include he impo ance assigned o he en i onmen in elec ed mayo s’ go e nmen
p oposals, public spending and ins i u ions de o ed o en i onmen al p o ec ion in each
municipali y, and en o cemen o en i onmen al egula ions. Fo he fi s mechanism we
conside he pe cen age o wo ds in a candida e’s go e nmen p oposal ha a e ela ed
o he en i onmen . Fo he second se o mechanisms we define h ee ou come a iables:
an indica o o whe he he municipali y has es ablished an en i onmen al council, a sec-
ond cap u ing whe he he municipali y incu ed any en i onmen al expendi u es du ing
each mayo al e m, and a measu e o he pe cen age o he municipal budge alloca ed
o en i onmen al expendi u es o e each e m. En o cemen effo s a e measu ed as he
numbe o fines issued due o de o es a ion in ac ions de ec ed in each municipali y.
Ou findings show ha he e is a posi i e impac on en i onmen al ou comes a
he municipal le el when a woman wins a mayo al elec ion agains a man by a na ow
ma gin and ha hese effec s a e d i en by municipali ies wi h Amazon biome. In hese
municipali ies, when a woman wins he elec ion, annual g eenhouse gas emissions dec ease
by 1,510 housand ons o CO2e pe municipali y. This effec alone ep esen s 23% o
he a e age annual emissions o all municipali ies wi hin he Amazon biome and 6.4% o
B azils na ionwide a e age. Impo an ly, his educ ion is due o a educ ion in emissions
in ensi y (CO2e/GDP) in he Land Use sec o , wi hou changes in municipal economic
ac i i y. Pa o he educ ion on emissions in he Land Use sec o is a ibu able o a
decline in de o es a ion. Female-led municipali ies in he Amazon expe ience a educ ion
in de o es a ion, wi h a 3 pe cen age-poin dec ease in he loss o o es o ma ions ela i e
o municipal o es co e . This ep esen s a 32% educ ion compa ed o de o es a ion
le els in he compa ison municipali ies.
These esul s a e obus o changes in key pa ame e s o ou RD specifica ion and o
adjus men s in he es ima ion sample, including changes in he bandwid h choice, ke nel,
and polynomial o de , and excluding obse a ions nea he cu off. We also show ha
he main esul s a e no d i en by he subse o municipali ies ha we e pa o he Lis
o P io i y Municipali ies (LPM), a ede al ini ia i e ha sough o educe de o es a ion
a es es ablishing a ge s o educ ion o municipali ies wi h he highes de o es a ion
a es and sanc ions in case o non-compliance.
4
A po en ial challenge in iden i ying he effec s o he gende o he winning poli i-
cian is ha emale candida es in close elec ions may possess compensa ing a ibu es,
such as highe abili y, o o e come gende biases o he o e s (Ma shall,2024). These
a ibu es could influence ou comes, causing ou es ima es o eflec a compound effec
o bundled ea men a he han an isola ed gende effec . In ou analysis, mos p e-
de e mined cha ac e is ics a e balanced nea he cu off, excep ha emale mayo s a e
mo e educa ed. While highe educa ion could influence ou esul s i i co ela es wi h
en i onmen ally p o ec i e policies, we p esen e idence showing ha educa ion does no
significan ly affec ou key ou comes. Addi ionally, we show ha o e s p obably did no
p io i ize en i onmen al issues when o ing, making compensa o y diffe en ials a ge ing
such conce ns unlikely and no biasing ou esul s. Howe e , unobse able ac o s, such
as non-cogni i e skills, poli ical expe ience, o ne wo ks, can ac as compensa ing diffe -
en ials ha help women win elec ions and implemen en i onmen al policies. The e o e,
we acknowledge ha ou es ima es may cap u e bo h gende effec s and hese addi ional
influences.
The analysis o mechanisms indica es ha emale leade s espond diffe en ly o cli-
ma e change in e ms o public policy, especially in Amazon municipali ies. In his
a ea, policy p oposals om emale elec ed mayo s con ain 0.16 pe cen age poin s mo e
en i onmen al- ela ed e ms compa ed o hose om male elec ed mayo s, which ep-
esen s a 50% inc ease ela i e o he baseline. Addi ionally, when a woman wins he
elec ion, he likelihood o hese municipali ies in es ing in en i onmen al ini ia i es in-
c eases by 13 pe cen age poin s. The e idence also sugges s diffe ences in he en o cemen
o en i onmen al egula ions do no explain ou main esul s.
This pape con ibu es o h ee s ands o li e a u e. Fi s , we add o he li e a u e
ha analyzes he impac s o emale poli ical leade s on a ious ou comes. As p e iously
men ioned, he elec ion o women as poli ical leade s impac s posi i ely on child en’s
heal h and educa ion, economic g ow h a es, and quali y o ins i u ions, and nega i ely
on co up ion and iolence agains women. Second, we ela e o he li e a u e explo ing
he poli ical economy o en i onmen al ou comes. P e ious e idence shows ha de o -
es a ion a he municipal le el ends o be highe when mayo s a e a me s—a powe ul
in e es g oup ha opposes o conse a ion policies (B agança and Dahis,2022)—o
when campaign dona ions come om landholde s (Ka o ich and Moffe e,2024); in con-
as , de o es a ion and g eenhouse gas emissions a e lowe when he mayo is a young
poli ician, likely due o hei g ea e exposu e o clima e change-o ien ed educa ion and
o ecen cul u al shi s owa ds en i onmen al p o ec ion, compa ed o senio mayo s
(Dahis e al.,2023). Finally, we also add o he en i onmen al jus ice li e a u e by show-
ing ha women poli ical leade s achie e be e en i onmen al ou comes when in office,
he eby gi ing oice and ep esen a ion o he g oup o women who a e disp opo iona ely
impac ed by clima e change.
The emainde o he pape is o ganized as ollows. Sec ion 2del es in o he ins i u-
ional con ex , ocusing on B azil’s ede al o ganiza ion and delinea ing he powe s es ed
5
in s a e sobse ed du ing he ou -yea mayo al e m .F emaleMayo equals 1 i a
woman won he mayo al ace in he elec ion held in he yea p io o he s a o e m
in municipali y iand s a e s.F emaleV o eMa ginis is he unning a iable in his RD
design, and i is defined as he o e sha e o he emale candida e minus he o e sha e
o he male candida e. The polynomial unc ion (FemaleV o eMa ginis ) ep esen s
he fi ed polynomials in he emale o e ma gin on bo h sides o he h eshold, which is
es ima ed ollowing Calonico e al. (2014).8In ou main analysis, we use a fi s -deg ee
polynomial and show in he obus ness sec ion ha ou findings hold o highe -o de
polynomials. ϵis ep esen s he e o e m. The baseline specifica ion o Equa ion 1
includes mayo al e m fixed effec s (γ ) and s a e fixed effec s (λs). In o he specifica ions
we include addi ional con ols o imp o e p ecision in ou es ima es (Calonico e al.,
2019). These con ols include p ede e mined municipali y cha ac e is ics (popula ion
size and alue added by sec o ), con empo aneous mayo al cha ac e is ics (age, le el o
educa ion, ma i al s a us, and pa y o affilia ion), and he alue o he dependen a iable
in he yea p io o he s a o e m . We clus e s anda d e o s a he municipal le el.
βis he coefficien o in e es . While we canno gua an ee ha ou s a egy isola es
he causal effec o he mayo ’s gende on he ou comes o in e es (see Sec ion 5.5),
i does cap u e he causal effec o a combined ea men , i.e., he impac o a woman
winning he elec ion (Ma shall,2024), p o ided ha he densi y o he unning a iable
is con inuous a he h eshold and ha p ede e mined cha ac e is ics a e balanced. To
show ha nea he cu off, municipali ies wi h a emale mayo a e simila o hose wi h
a male mayo in e ms o obse able cha ac e is ics, we es ima e equa ion 1 o a ange
o cha ac e is ics a bo h he mayo le el—poli ical pa y, educa ion, age, ma i al s a-
us, among o he s—and municipal le el— o al popula ion, emale popula ion, pe capi a
GDP, li e acy a e, among o he s. Figu e 1a epo s he -s a is ics o β om equa ion 1,
whe e such cha ac e is ics a e he ou come a iables. We find ha ou sample is balanced
in mos p ede e mined cha ac e is ics, wi h he excep ion o he candida es educa ion.
We complemen hese esul s wi h a g aphical illus a ion o he RD effec s o each
p e-de e mined a iable, p o iding addi ional e idence ha hey do no exhibi disc e e
jumps a he cu off (see Figu es A.2 and A.3 in he Appendix).9Addi ionally, in Fig-
u e 1b we conduc a simila analysis o he subsample o municipali ies wi h ege a ion
ypical o he Amazon biome (Amazon municipali ies), confi ming ha he cha ac e is-
ics a e also gene ally balanced wi hin his subsample. This subsample is pa icula ly
8I is wo h cla i ying ha he op imal bandwid h in ou RD design does no define wha cons i u es
aclose elec ion. Ra he , i de e mines he ange o obse a ions used o fi he local polynomial o
es ima ion (Calonico e al.,2014) Thus, ou coefficien o in e es is iden ified om elec ions wi h na ow
ma gins (i.e., close elec ions), aided by a local polynomial es ima ed using obse a ions sligh ly u he
om he ze o-ma gin cu off.
9P e ious s udies u ilizing an RD design in mixed-gende close elec ions in B azil ha e demons a ed
he balance o p ede e mined municipal and mayo al cha ac e is ics a he h eshold, suppo ing he
alidi y o ou iden ifica ion s a egy. Like ou findings, hese s udies show ha hese cha ac e is ics
a e gene ally balanced, wi h he excep ion o educa ion, whe e emale mayo s end o be mo e educa ed
han hei male coun e pa s. Fo ins ance, see he wo k o B ollo and T oiano (2016) on co up ion and
Bochenko a e al. (2023) on iolence agains women.
12
ele an o ou analysis, as Sec ion 5shows ha he en i onmen al effec s o elec ing a
woman a e concen a ed in he Amazon egion.
Secondly, al hough unlikely in ou con ex , we e i y he absence o manipula ion o
he unning a iable in a local neighbo hood nea o he cu off (FemaleV o eMa ginis =
0). We un he manipula ion es based on he densi y discon inui y de eloped in Ca -
aneo e al. (2018), and find a p- alue o 0.6, i.e., we ail o ejec he null hypo hesis
o no diffe ence in he densi y o municipali ies wi h a emale mayo and wi h a male
mayo a he cu off. Figu e A.4 in he Appendix g aphically illus a es he con inui y
in he densi y es app oach: he densi y es ima es on bo h sides o he cu off a e e y
simila , and he confidence in e als o e lap o bo h he en i e sample o municipali ies
wi h mixed-gende elec ions and he subsample o municipali ies in he Amazon egion.
One po en ial iden ifica ion conce n wi h ou RD s a egy is he p esence o spa ial
spillo e s be ween municipali ies. Fo example, i a emale mayo leads o a dec ease in
de o es a ion and emissions in he own municipali y bu wo sens en i onmen al ou comes
in neighbo ing municipali ies go e ned by men, ou poin es ima es could be a ificially
infla ed. Mo eo e , such spa ial spillo e effec s sugges ha ou analysis cap u es only
pa ial effec s— he local en i onmen al impac in municipali ies go e ned by women–
a he han he gene al equilib ium effec on o e all de o es a ion and emissions d i en
by emale mayo s. In an ex eme case, educ ions in de o es a ion and emissions in
municipali ies led by women could be ully offse i nega i e spillo e s in neighbo ing
municipali ies go e ned by men a e la ge enough. While hese spillo e s wa an a cau-
ious in e p e a ion o he es ima ed effec s magni ude, i is impo an o no e ha i we
es ima e ha emale mayo s imp o e en i onmen al ou comes in hei municipali ies, he
di ec ion o he effec should emain unchanged, e en in he p esence o spa ial spillo e s.
13
Figu e 1: Co a ia es Balance a ound he Th eshold
(a) To al
Li e acy a e (2000)
Sh. Men (2000)
Sh. Women (2000)
Sh. U ban popula ion (2000)
Sh. Ru al popula ion (2000)
Sh. Ac i e popula ion (2000)
Sh. Ac i e men (2000)
Sh. Ac i e women (2000)
Sh. Employed popula ion (2000)
Sh. Employed men (2000)
Sh. Employed women (2000)
Sh. Low−Skill (2000)
Sh. Med−Skill (2000)
Sh. High−Skill (2000)
Sha e Ag o (2000)
Sha e Indus ial (2000)
Sha e Se ices (2000)
Sha e Public adminis a ion (2000)
To al Popula ion (2000)
To al Men popula ion (2000)
To al Women popula ion (2000)
To al u ban popula ion (2000)
To al Ru al popula ion (2000)
To al Popula ion > 10 (2000)
Li e a e popula ion (2000)
GDP (2000)
College
Ma ied
Age
PT
PMBD
DEM
PSDB
−4 −3 −2 −1 0 1 2 3 4 5 6
T−s a is ic
(b) Amazon egion
Li e acy a e (2000)
Sh. Men (2000)
Sh. Women (2000)
Sh. U ban popula ion (2000)
Sh. Ru al popula ion (2000)
Sh. Ac i e popula ion (2000)
Sh. Ac i e men (2000)
Sh. Ac i e women (2000)
Sh. Employed popula ion (2000)
Sh. Employed men (2000)
Sh. Employed women (2000)
Sh. Low−Skill (2000)
Sh. Med−Skill (2000)
Sh. High−Skill (2000)
Sha e Ag o (2000)
Sha e Indus ial (2000)
Sha e Se ices (2000)
Sha e Public adminis a ion (2000)
To al Popula ion (2000)
To al Men popula ion (2000)
To al Women popula ion (2000)
To al u ban popula ion (2000)
To al Ru al popula ion (2000)
To al Popula ion > 10 (2000)
Li e a e popula ion (2000)
GDP (2000)
College
Ma ied
Age
PT
PMBD
DEM
PSDB
−4 −3 −2 −1 0 1 2 3 4 5 6
T−s a is ic
No es: The figu es show he -s a is ics om ou RD (Equa ion 1) using p ede e mined municipal and
mayo cha ac e is ics as ou comes o all municipali ies wi h mixed-gende elec ions (Panel a) and o he
subsample o Amazon municipali ies (Panel b). Es ima es ob ained using local linea es ima o s wi h a
iangula ke nel. Op imal bandwid h based on Calonico e al. (2014). Robus s anda d e o s clus e ed
a he municipal le el. The ed, blue and g een lines indica e he 1%, 5% and 10% significance le el
h esholds espec i ely.
5 Main Resul s
In his sec ion we p esen he main esul s abou he impac on en i onmen al ou comes
o women winning municipal elec ions in B azil. Ou analysis ocuses on g eenhouse
gas emissions and de o es a ion, wo key indica o s ha can cap u e effo s o mi iga e
clima e change.
Figu e 2begins by p o iding p elimina y e idence on he ela ionship be ween he
14
ma gin o ic o y and g eenhouse gas emissions. The ho izon al axis measu es he ma gin
o ic o y in a o o a woman, defined as he diffe ence be ween he pe cen age o
o es ecei ed by he emale candida e and he pe cen age o o es ecei ed by he male
candida e in mixed-gende municipal elec ions. A posi i e ma gin o ic o y indica es
a win o he woman. The figu e shows a discon inui y in emissions a he municipal
le el depending on whe he women o men won: in municipali ies whe e a woman won
(i.e., o he igh o ze o), g eenhouse gas emissions a e lowe compa ed o municipali ies
whe e a man won, bo h ac oss he en i e coun y (Figu e 2a) and when ocusing solely on
municipali ies wi hin he Amazon biome (Figu e 2b). The g aphical e idence sugges s
an imp o emen in en i onmen al ou comes a he municipal le el when a woman wins
he elec ion.10
Figu e 2: Female Mayo and Emissions (in ons o CO2e)
(a) All municipali ies
−200000
0
200000
400000
600000
Emissions (in ons o CO2e)
−12 −6 0 6 12
Di e ence in o es sha e
(b) Amazon municipali ies
−2000000
0
2000000
4000000
6000000
Emissions (in ons o CO2e)
−12 −6 0 6 12
Di e ence in o es sha e
No e: These figu es g aphically illus a e he effec o emale mayo s on o al g eenhouse gas emissions
in municipali ies wi h mixed-gende elec ions, bo h ac oss he en i e coun y (le panel) and wi hin
he Amazon egion ( igh panel). Emissions a e measu ed in ons o COe, a e aged pe yea o e each
ou -yea mayo al e m. The solid lines illus a e fi s -deg ee polynomials fi ed o he unning a iable
on ei he side o he h eshold. G ay do s co espond o a e ages o bins o he unning a iable, wi h
e ical lines showing he 90% confidence in e als o hese a e ages.
In wha ollows, we epo he o mal es ima es based on he RD design desc ibed in
Sec ion 4. O e all, hese esul s alida e he p elimina y findings om Figu e 2.
5.1 Effec on G eenhouse Gas Emissions
Table 2shows he RD es ima es ega ding g eenhouse gas emissions in ons o CO2e,
calcula ed as he annual a e age o e he ou yea s o each mayo al e m. Column 1
10Figu es A.5a and A.5b in he Appendix p esen ano he desc ip i e analysis ha sugges s en i on-
men al ou comes a he municipal le el imp o e ela i ely mo e when a woman wins he elec ion. These
figu es show he e olu ion o o al emissions and he sha e o de o es a ion, on a e age, o he ou yea s
be o e and du ing he ou yea s in office, sepa a ely o male and emale mayo s. The sample includes
mixed-gende close elec ions, whe e a man and a woman a e he wo main candida es. The figu es sugges
ha while emissions and de o es a ion dec ease o bo h gende s, he decline is sus ained when a woman
wins he elec ion, whe eas, when a man wins, he le els emain simila by he end o he e m.
15
co esponds o he baseline model in equa ion 1, which only includes con ols o mayo al
e m and s a e fixed effec s. This is ou p e e ed specifica ion. Columns 2 o 4 g adually
in oduce addi ional con ols—municipali y con ols, mayo con ols, and he ou come
om he p e ious yea . In pa icula , column 3 includes con ols a he mayo ’s le el—
age, le el o educa ion, ma i al s a us, and pa y o affilia ion. No ably, he esul s a e
highly obus ac oss specifica ions, indica ing ha he effec we iden i y om a woman
winning he elec ion is no due o diffe ences be ween emale and male mayo s in e ms o
educa ion, poli ical pa y, o o he included obse able cha ac e is ics. In wha ollows,
we p ima ily ocus on he baseline model in column 1 o desc ibe ou findings.
Panel A in he able epo s a s a is ically significan educ ion in annual CO2e
emissions in municipali ies wi h emale mayo s compa ed o hose wi h male mayo s.
Specifically, in municipali ies whe e women na owly won he elec ion, annual emissions
a e, on a e age, 219 housand ons o CO2e lowe han in municipali ies whe e men won
by a simila ma gin. This ep esen s a 75% educ ion in he a e age annual municipal
emissions pe mayo al e m when a woman is elec ed.11
Nex , we e-es ima e ou RD model o wo subsamples: municipali ies wi h ege-
a ion ypical o he Amazon biome (Amazon municipali ies) and hose wi hou (non-
Amazon municipali ies). Panels B and C o Table 2 epo hese esul s, confi ming ha
he Amazon municipali ies a e d i ing he effec iden ified o he en i e sample. When
a woman wins he elec ion in Amazon municipali ies, annual g eenhouse gas emissions
dec ease by 1,510 housand ons o CO2e pe municipali y. This effec is la ge han ha
es ima ed o he o al se o municipali ies. In con as , we find no e idence o effec s
on emissions in he non-Amazon municipali ies.
The key akeaway om hese esul s is he s a is ically significan and nega i e effec
o emale leade ship on emissions, pa icula ly in he Amazon egion. Howe e , he
magni ude o he es ima ed impac should be in e p e ed wi h cau ion. As is o en he
case in his ype o s udies, es ima ed effec s end o be ela i ely la ge, eflec ing local
ea men effec s a ound he h eshold.12 Indeed, in a obus ness check accoun ing o
po en ial ou lie s, ou effec emains nega i e and s a is ically significan , al hough i s
magni ude is educed by hal (see Sec ion 5.4).
Tha said, i is use ul o illus a e he scale o hese effec s wi h some back-o - he-
en elope calcula ions. I we ocus on he 113 Amazon municipali ies wi h mixed-gende
elec ions, hey collec i ely p oduce an a e age o 88 housand ons o CO2e pe yea
11We compu e he baseline mean ou come o elec o al e m as he a e age annual CO2e emissions
in he p eceding e m. This is specifically calcula ed o municipali ies whe e men candida es won he
elec ion co esponding o e m , wi h he ma gin o ic o y alling wi hin he op imal bandwid h.
12La ge effec sizes a e commonly epo ed in he li e a u e when using simila me hodologies. Fo
ins ance, Dahis e al. (2023) s udy he impac o young poli icians on emissions in B azil and find
es ima ed effec s anging om 72% o o e 130%. Simila ly, Jagnani and Mahade an (2021) show ha
he elec ion o women legisla o s in India leads o a educ ion in c op-fi e inciden s, wi h effec s be ween
33% and 100%. These la ge effec s a e no unique o en i onmen al ou comes—Bochenko a e al. (2023)
find impac s on domes ic homicide a es be ween 50% and 70%. O he examples include Esla a (2024)
and Chau in and T icaud (2024), whe e es ima ed effec s ela i e o mean consis en ly exceed 60%.
16
Table 2: Female Mayo and Emissions (in ons o CO2e)
(1) (2) (3) (4)
Panel A: To al
Female mayo -218,756** -225,477** -230,113** -265,355**
(101,193) (101,179) (101,512) (104,064)
Mean ou come 291,668 291,668 291,668 291,668
Bandwid h 12.8 12.8 12.8 12.8
Obse a ions [1156, 1035] [1156, 1035] [1156, 1035] [1156, 1035]
Panel B: Amazon egion
Female mayo -1,509,865*** -1,348,315** -1,098,764** -1,428,845**
(585,299) (558,625) (546,566) (575,735)
Mean ou come 1,449,452 1,449,452 1,449,452 1,449,452
Bandwid h 12.8 12.8 12.8 12.8
Obse a ions [140, 125] [140, 125] [140, 125] [140, 125]
Panel C: Non-amazon egion
Female mayo -27,744 -36,305 -42,404 -44,069
(37,958) (37,936) (41,676) (40,598)
Mean ou come 184,980 184,980 184,980 184,980
Bandwid h 16.2 16.2 16.2 16.2
Obse a ions [1275, 1051] [1275, 1051] [1275, 1051] [1275, 1051]
Yea & S a e FE Yes Yes Yes Yes
Municipali y con ols No Yes Yes Yes
Mayo con ols No No Yes Yes
Ou come -1 No No No Yes
No es: The dependen a iable is he a e age annual emissions in ons o CO2e o e he ou -yea e m in all
municipali ies wi h mixed-gende elec ions (Panel A), he subsample o Amazon municipali ies (Panel B), and he
subsample o non-Amazon municipali ies (Panel C). Municipali y con ols include popula ion size, GDP, and sha e
o alue added by sec o (ag icul u e, indus y, se ices, and public adminis a ion). Mayo con ols a e age, le el o
educa ion, ma i al s a us and pa y o affilia ion (PT, PSDB, DEM, PMDB). Es ima es ob ained using local linea
es ima o s wi h a iangula ke nel. Op imal bandwid h based on Calonico e al. (2014). Robus s anda d e o s
clus e ed a he municipal le el in pa en heses * p < 0.1, ** p < 0.05 and *** p < 0.01.
du ing he pe iod unde analysis.13 Wi hou he effec o emale mayo s in hese munic-
ipali ies, annual emissions would ha e eached 160 housand ons o CO2e—i.e., an 81%
inc ease o his g oup. No ably, his change alone ep esen s 23% o he a e age annual
emissions o all municipali ies wi hin he Amazon biome and 6.4% o B azil’s na ionwide
a e age. I we conside ed ex ending ou findings o he es o he Amazon municipali ies
(i.e., o hose excluded om ou sample due o he absence o mixed-gende elec ions),
inc easing he sha e o emale mayo s om 2% o jus 20%—hal he p opo ion in ou
sample—could educe emissions by 104 housand ons o CO2e. This ep esen s a 35%
dec ease ela i e o he cu en annual emissions o hese municipali ies. While such ex-
apola ion equi es cau ion, his es ima e p o ides a use ul illus a ion o he po en ial
scale o hese effec s.
Fu he mo e, he effec o women winning municipal elec ions on emissions is p i-
ma ily d i en by changes in land use wi hin Amazon municipali ies. Table 3shows ha
13Fo his calcula ion, we conside he a e age numbe o municipali ies pe elec o al ound by di iding
he numbe o municipali y- e ms epo ed in Table A.1 by ou , as he da ase spans ou elec o al ounds
and hei espec i e mayo al e ms.
17
he es ima ed effec is an annual educ ion in emissions om land use ac i i ies o 1,462
housand ons o CO2e pe municipali y when women won he elec ion ela i e o when
men won. In con as , we find e y small and s a is ically insignifican effec s o a woman
winning he elec ion on emissions in o he sec o s, such as ag icul u e, ene gy, o was e
(columns 2, 3, and 5, espec i ely).14
Table 3: Female Mayo and Emissions by Sec o (in ons o CO2e)
To al Ag icul u e Ene gy Land use Was e
(1) (2) (3) (4) (5)
Panel A: To al
Female mayo -218,756** 5,628 2,913 -232,379** 882
(101,193) (17,163) (5,017) (93,063) (781)
Mean ou come 291,668 91,178 17,003 172,653 6,348
Bandwid h 12.8 13.6 7.4 13.1 11.7
Obse a ions [1156, 1035] [1224, 1063] [722, 680] [1179, 1041] [1077, 977]
Panel B: Amazon egion
Female mayo -1,509,865*** -40,342 -7,676 -1,461,500*** 2,215
(585,299) (93,096) (9,404) (550,012) (1,399)
Mean ou come 1,449,452 262,855 25,436 1,130,693 8,179
Bandwid h 12.8 10.8 11.7 13.2 6.4
Obse a ions [140, 125] [130, 110] [133, 114] [144, 125] [84, 77]
Panel C: Non-amazon egion
Female mayo -27,744 8,114 4,717 -45,960 920
(37,958) (10,685) (5,489) (33,695) (780)
Mean ou come 184,980 71,466 15,388 85,424 6,162
Bandwid h 16.2 14.7 7.3 15.6 14.1
Obse a ions [1275, 1051] [1178, 1003] [633, 598] [1235, 1035] [1141, 978]
Yea & S a e FE Yes Yes Yes Yes Yes
No es: The dependen a iable is he a e age annual emissions in ons o CO2e o e he ou -yea e m in all municipali ies
wi h mixed-gende elec ions (Panel A), he subsample o Amazon municipali ies (Panel B), and he subsample o non-Amazon
municipali ies (Panel C). The esul s co espond o ou baseline specifica ion, simila o ha in Column 1 o Table 2, which
con ols o yea and s a e fixed effec s. Es ima es ob ained using local linea es ima o s wi h a iangula ke nel. Op imal
bandwid h based on Calonico e al. (2014). Robus s anda d e o s clus e ed a he municipal le el in pa en heses * p < 0.1, **
p < 0.05 and *** p < 0.01.
5.2 Emissions In ensi y s. Economic Ac i i y
Using an IPAT decomposi ion amewo k as a lens (Eh lich and Hold en,1971), he
educ ion in emissions in ons o CO2e can be unde s ood as s emming ei he om a
decline in emissions in ensi y (CO2e/GDP) o om a con ac ion in economic ac i i y.
Table 4p esen s he RD es ima es o emissions in ons o CO2e pe 1,000 BRL (B azilian
14These esul s o emissions a e based on a e age emissions measu ed o e he en i e ou -yea mayo al
e m. We also conduc ed a yea -by-yea analysis o bo h he ull sample o municipali ies and he
subsample o Amazon municipali ies. Whe he we conside o al emissions o hose specifically om he
Land Use sec o , we find no clea empo al pa e n wi hin he mayo al e m. The poin es ima es do no
sugges any significan changes o e ime, and no s a is ically significan diffe ences we e ound ac oss he
yea s. Addi ionally, o examine whe he he dec ease in emissions unde emale mayo s pe sis s o e e ses
in subsequen e ms, we es ima ed ou main specifica ion using ou comes om he nex mayo al e m.
While we also obse e a decline in u u e emissions, he effec s a e mos ly no s a is ically significan .
Resul s a e a ailable upon eques .
18
Reais) o GDP, calcula ed as he annual a e age o e he ou yea s o each mayo al e m,
which allows us o assess he fi s channel. The esul s show ha emissions in ensi y
dec eases when a woman mayo is elec ed by a na ow ma gin compa ed o when a man
is elec ed. This effec is d i en by changes in land use wi hin Amazon municipali ies.
When a woman wins he elec ion in hese municipali ies, o al g eenhouse gas emissions
in he Land Use sec o dec ease by 3.5 ons o CO2e pe 1,000 BRL o GDP. In con as ,
we find no e idence o effec s on emissions in ensi y in o he sec o s o in non-Amazon
municipali ies.
Table 4: Female Mayo and Emissions In ensi y (CO2e/GDP) by Sec o
To al Ag icul u e Ene gy Land use Was e
(1) (2) (3) (4) (5)
Panel A: To al
Female mayo -0.546** 0.036 -0.001 -0.584** -0.000
(0.274) (0.054) (0.006) (0.254) (0.001)
Mean ou come 1.124 0.435 0.039 0.618 0.023
Bandwid h 10.4 14.2 11.5 10.4 11.7
Obse a ions [989, 892] [1262, 1089] [1055, 956] [985, 890] [1077, 980]
Panel B: Amazon egion
Female mayo -3.504** 0.020 0.001 -3.509** -0.006
(1.652) (0.296) (0.015) (1.606) (0.004)
Mean ou come 3.871 0.799 0.041 2.996 0.025
Bandwid h 10.9 12.9 12.6 10.9 12.6
Obse a ions [130, 110] [141, 125] [139, 122] [130, 110] [140, 124]
Panel C: Non-amazon egion
Female mayo -0.103 0.055 -0.001 -0.159 0.001
(0.142) (0.045) (0.007) (0.131) (0.001)
Mean ou come 0.847 0.406 0.039 0.381 0.023
Bandwid h 13.9 13.2 12.8 13.5 12.3
Obse a ions [1131, 971] [1081, 943] [1033, 924] [1101, 952] [1001, 904]
Yea & S a e FE Yes Yes Yes Yes Yes
No es: The dependen a iable is emissions in ensi y, measu ed in ons o CO2e pe 1,000 BRL o GDP, calcula ed as he
annual a e age o e he ou yea s o each mayo al e m, in all municipali ies wi h mixed-gende elec ions (Panel A), he
subsample o Amazon municipali ies (Panel B), and he subsample o non-Amazon municipali ies (Panel C). The esul s
co espond o ou baseline specifica ion, simila o ha in Column 1 o Table 2, which con ols o yea and s a e fixed
effec s. Es ima es ob ained using local linea es ima o s wi h a iangula ke nel. Op imal bandwid h based on Calonico
e al. (2014). Robus s anda d e o s clus e ed a he municipal le el in pa en heses * p < 0.1, ** p < 0.05 and *** p <
0.01.
Rega ding he second channel, we use ou RD model o assess he impac o a woman
winning an elec ion on economic ac i i y. Ou findings indica e ha he obse ed educ-
ions in emissions a e d i en solely by changes in in ensi y and no by shi s in economic
ac i i y. In ac , Table 5shows ha when we apply he same RD design using municipal
GDP, whe he in le els o in logs, as he ou come a iable, he effec o a woman winning
he elec ion is ne e s a is ically significan , which means ha he educ ion in emissions
p ima ily ope a es h ough imp o ed CO2e efficiency, i.e., ewe emissions pe GDP.
19
Table 5: Female Mayo and Economic Ac i i y
GDP Log GDP
(1) (2)
Panel A: To al
Female mayo -194776 -0.018
(177825) (0.091)
Mean ou come 385,406 12.065
Bandwid h 8.0 12.8
Obse a ions [781, 737] [1152, 1033]
Panel B: Amazon egion
Female mayo 40460 -0.176
(129346) (0.219)
Mean ou come 381,909 12.329
Bandwid h 8.2 13.7
Obse a ions [103, 95] [149, 126]
Panel C: Non-amazon egion
Female mayo -158560 -0.006
(191352) (0.098)
Mean ou come 402,326 12.053
Bandwid h 10.4 13.5
Obse a ions [857, 766] [1068, 913]
Yea & S a e FE Yes Yes
No es: The dependen a iables a e municipali y GDP (Column 1) and
i s loga i hm (Column 2), in all municipali ies wi h mixed-gende elec ions
(Panel A), he subsample o Amazon municipali ies (Panel B), and he
subsample o non-Amazon municipali ies (Panel C). The eg essions con-
ol o yea and s a e fixed effec s. Es ima es ob ained using local linea
es ima o s wi h a iangula ke nel. Op imal bandwid h based on Calonico
e al. (2014). Robus s anda d e o s clus e ed a he municipal le el in
pa en heses * p < 0.1, ** p < 0.05 and *** p < 0.01.
5.3 Effec on De o es a ion
Acco ding o MapBiomas (2024), o e 90% o de o es a ion in he Amazon is d i en by
he c ea ion o pas u eland, a majo con ibu o o g eenhouse gas emissions in he Land
Use sec o . De o es a ion plays a c i ical ole in emissions, p ima ily by eleasing ca bon
s o ed in ees and soil. When de o es a ion is educed, he o es ’s ca bon seques a ion
capaci y is p ese ed, leading o lowe emissions. To be e unde s and how changes in
land use con ibu e o he nega i e impac on emissions ha we find, we now examine
he impac o a woman winning he elec ion on de o es a ion.
Table 6p esen s he RD es ima es o de o es ed hec a es as a sha e o o es co e
a he municipal le el. The findings indica e ha women winning elec ions lead o
a educ ion in de o es a ion exclusi ely in Amazon municipali ies. Acco ding o he
baseline specifica ion in Column 1, a woman’s ic o y in hese municipali ies educes he
20
de o es ed a ea by 3 pe cen age poin s ela i e o he o al o es co e , which ep esen s
a 35% dec ease ela i e o he baseline le el. These esul s a e consis en and highly
obus ac oss diffe en specifica ions. In con as , no significan effec s on de o es a ion
a e obse ed in non-Amazon municipali ies.15
Table 6: Female Mayo and De o es a ion (as a sha e o o es co e )
(1) (2) (3) (4)
Panel A: To al
Female mayo -0.004 -0.004 -0.005 -0.005
(0.004) (0.005) (0.005) (0.005)
Mean ou come 0.049 0.049 0.049 0.049
Bandwid h 11.8 11.8 11.8 11.8
Obse a ions [1054, 950] [1054, 950] [1054, 950] [1054, 950]
Panel B: Amazon egion
Female mayo -0.033* -0.032* -0.033* -0.029*
(0.018) (0.017) (0.017) (0.016)
Mean ou come 0.104 0.104 0.104 0.104
Bandwid h 11.5 11.5 11.5 11.5
Obse a ions [130, 110] [130, 110] [130, 110] [130, 110]
Panel C: Non-amazon egion
Female mayo -0.005 -0.004 -0.004 -0.005
(0.004) (0.004) (0.004) (0.004)
Mean ou come 0.045 0.045 0.045 0.045
Bandwid h 12.6 12.6 12.6 12.6
Obse a ions [974, 862] [974, 862] [974, 862] [974, 862]
Yea & S a e FE Yes Yes Yes Yes
Municipali y con ols No Yes Yes Yes
Mayo con ols No No Yes Yes
Ou come -1 No No No Yes
No es: The dependen a iable is he o al de o es ed a ea o o es in each municipali y
o e each ou -yea e m as a sha e o he o al o es co e in each municipali y du ing he
baseline yea (i.e., he yea p io o he s a o each e m) in all municipali ies wi h mixed-
gende elec ions (Panel A), he subsample o Amazon municipali ies (Panel B), and he
subsample o non-Amazon municipali ies (Panel C). Municipali y con ols include popula ion
size, GDP and sha e o alue added by sec o (ag icul u e, indus y, se ices, and public
adminis a ion). Mayo con ols a e age, le el o educa ion, ma i al s a us and pa y o
affilia ion (PT, PSDB, DEM, PMDB). Es ima es ob ained using local linea es ima o s wi h
a iangula ke nel. Op imal bandwid h based on Calonico e al. (2014). Robus s anda d
e o s clus e ed a he municipal le el in pa en heses * p < 0.1, ** p < 0.05 and *** p <
0.01.
15P ima y and seconda y o es s oge he make up 70% o he na u al ege a ion co e in Amazon
municipali ies. Among hese o es o ma ions, 83% co espond o p ima y o es —i.e., na u al o es
ha has emained in ac since he beginning o he se ies (1987) h ough he yea o analysis—while
he emaining 17% is seconda y o es —i.e., o es ha has egene a ed a e he o iginal ege a ion
was emo ed o significan ly al e ed by human ac i i y. The esul s in Table 6a e p ima ily d i en by
changes in p ima y o es . In con as , we find no effec s o women winning he elec ion on changes in
seconda y o es . When we eplica e ou analysis conside ing changes in he en i e na u al ege a ion
co e —including sa anna, mang o e, we land, g assland, and o he non- o es na u al o ma ions— a he
han jus o es , he esul s emain obus . Resul s a e a ailable upon eques .
21
Figu e 3: Poli ical P oposals, Public Spending and Ins i u ions
(a) Go e nmen p oposals
Adminis a ion
Child
Cul u e
Educa ion
En i onmen al
Heal h
Secu i y
Social Assis ance
Women
−1 −.5 0 .5 1
RDD coe icien
Amazon To al
(b) En i onmen al policies
% En i onmen al expendi u e
Any En i onmen al expendi u e
C ea e En i onmen al council
−.2 0 .2 .4 .6
RDD coe icien
Amazon To al
No es: These figu es show he βcoefficien and i s 90% confidence in e al om es ima ing Equa ion 1
o all municipali ies wi h mixed-gende elec ions and o he subsample o Amazon municipali ies. The
dependen a iables a e he ollowing: numbe o wo ds ela ed o each opic in ela ion o he o al
numbe o wo ds in he p oposal (Panel a) and a bina y a iable indica ing i he mayo c ea ed an en i-
onmen al council du ing he ou -yea e m, ano he bina y indica o showing whe he he municipali y
made any en i onmen al expendi u e, and a a iable measu ing he pe cen age o he municipal budge
alloca ed o en i onmen al expendi u es (Panel b). Es ima es ob ained using local linea es ima o s wi h
a iangula ke nel and op imal bandwid h based on Calonico e al. (2014). All es ima es accoun o
s a e and ound fixed effec s.
ics, and ope a ion o municipal public ins i u ions ca ied ou by he Ins i u o B asilei o
de Geog afia e Es a ís ica (IBGE). Based on hese da a, we cons uc se e al a iables
ha se e as p oxies o he effo municipali ies de o e o en i onmen al policy. Ou
ou comes o in e es a e: a bina y a iable indica ing i he municipali y es ablished an
en i onmen al council du ing he mayo s’ manda e, ano he bina y indica o showing
whe he he municipali y made any en i onmen al expendi u e o e he ou -yea e m
o he mayo s manda es, and a a iable measu ing he pe cen age o he municipal bud-
ge alloca ed o en i onmen al expendi u es in each ou -yea e m. Table A.1 shows he
a e ages o he a iables ela ed o Public spending and Ins i u ions. In he sample wi h
mixed-gende elec ions, 55% o he municipali ies ha e an en i onmen al council and,
while 57% o he municipali ies made any en i onmen al expendi u e, his expendi u es
ep esen s only 0.48% o he o al budge on a e age. Al hough he pe cen age o munic-
ipali ies wi h an en i onmen al council is sligh ly highe in he emaining municipali ies
(60%), he e a e no s a is ically significan diffe ences be ween municipali ies wi h and
wi hou mixed-gende elec ions o he o he a iables.
The esul s in Figu e 3b sugges ha , once in office, emale leade s espond diffe en ly
o clima e change in e ms o he alloca ion o esou ces o en i onmen al managemen .
Specifically, in line wi h he findings p esen ed in Sec ion 5, he diffe ence is e iden
in municipali ies wi h Amazon biome. When a woman wins he elec ion in Amazon
municipali ies, he likelihood o hese municipali ies in es ing in en i onmen al ini ia i es
inc eases by 13 pe cen age poin s, and he sha e o he budge alloca ed o hese ini ia i es
ises by 0.2 pe cen age poin s, hough his effec is no s a is ically significan . Amazon
28
municipali ies led by women a e also mo e likely o c ea e an en i onmen al council
compa ed wi h hose led by men, bu his effec is no significan in s a is ical e ms.
En o cemen o en i onmen al egula ions. To explo e his po en ial mechanism,
we examine whe he emale and male mayo s diffe in he numbe o en i onmen al
fines issued du ing hei mayo al e m due o en i onmen al in ac ions de ec ed in hei
municipali ies.18 We use da a on he numbe o en i onmen al fines issued h oughou
he mayo al e m due o de o es a ion in ac ions de ec ed in each municipali ies. These
da a come om he B azilian Ins i u e o En i onmen and Renewable Na u al Resou ces.
Acco ding o his sou ce, municipali ies wi h mixed-gende elec ions issued an a e age
o h ee fines ela ed o de o es a ion in ac ions (see Table A.1), and his numbe is no
significan ly diffe en om he a e age numbe o fines issued in o he municipali ies.
Al hough diffe ences be ween emale and male mayo s in inspec ion ac i i ies may
lead o disc epancies in he numbe o fines, he di ec ion o he effec is no clea . Fo
ins ance, highe en o cemen effo s could educe he numbe o fines in equilib ium i
land use s upda e hei pe cei ed p obabili y o being caugh , he eby educing illegal
de o es a ion. Figu e 4shows no s a is ically significan gende diffe ences in he numbe
o fines due o de o es a ion in ac ions in he en i e sample o municipali ies o hose wi h
Amazon biome. Gi en he limi a ion o he numbe o en i onmen al fines as a p oxy
o en o cemen effo men ioned abo e, we in e p e his esul as sugges i e e idence o
diffe en ial en o cemen effo s be ween emale and male mayo s no d i ing ou main
esul s.
18Al hough he ins i u ion esponsible o issuing en i onmen al in ac ion epo s is he B azilian
Ins i u e o En i onmen and Renewable Na u al Resou ces, a ede al ins i u ion, he esponsibili y o
en i onmen al inspec ions is sha ed wi h he s a es, municipali ies, and he ede al dis ic .
29
Figu e 4: Female Mayo and Numbe o En i onmen al Fines
To al ines
−40 −20 0 20 40
RDD coe icien
Amazon To al
No es: These figu es show he βcoefficien and i s 90% confidence in e al om es ima ing equa ion 1
o all municipali ies wi h mixed-gende elec ions and o he subsample o Amazon municipali ies. The
dependen a iables a e he ollowing: o al de o es ed a ea in hec a es pe municipali y o e each ou -
yea manda e (Panel a), emissions pe uni o municipal GDP (Panel b), and o al numbe o fines due
o de o es a ion in ac ions pe mayo al e m (Panel c). Es ima es ob ained using local linea es ima o s
wi h a iangula ke nel and op imal bandwid h based on Calonico e al. (2014). All es ima es accoun
o s a e and ound fixed effec s.
7 Conclusions
Clima e change has significan social and economic nega i e implica ions and equi es
adequa e and imely policies. Unde s anding he ole o women in policy decisions e-
ga ding clima e change is impo an gi en he e idence indica ing ha many social ou -
comes imp o e when he leade is a woman and ha women a e gene ally mo e awa e and
conce ned han men abou clima e change. In his pape , we ha e analyzed how emale
poli ical leade s impac clima e change policy ac ions and en i onmen al ou comes using
da a om mixed-gende close mayo al aces in B azilian municipali ies and applying a
Reg ession Discon inui y design.
Ou findings e eal a significan posi i e effec on en i onmen al ou comes a he
municipal le el when a woman na owly de ea s a male opponen in a mayo al elec ion,
pa icula ly in Amazon municipali ies. In hese municipali ies, annual g eenhouse gas
emissions dec ease by 1,510 housand ons o CO2e when a woman is elec ed mayo .
This implies ha , wi hou he effec o emale mayo s, annual emissions would ha e
inc eased by 81% in mixed-gende elec ion municipali ies in he Amazon. No ably, his
change alone ep esen s 23% o he a e age annual emissions o all municipali ies wi hin
he Amazon biome and 6.4% o B azil’s na ionwide a e age.
Mo eo e , he educ ion in emissions is d i en by a dec ease in emissions in ensi y
(CO2e/GDP) wi hin he Land Use sec o , wi hou changes in municipal economic ac-
i i y. Pa o he educ ion on emissions in he Land Use sec o is a ibu able o a
decline in de o es a ion. Specifically, emale-led municipali ies in he Amazon expe ience
a educ ion in de o es a ion compa ed o male-led municipali ies, wi h a 3 pe cen age
30
poin dec ease in he de o es ed a ea ela i e o o al ege a ion co e , ep esen ing a
32% educ ion compa ed o he baseline de o es a ion le els.
Fu he mo e, ou explo a ion o he unde lying mechanisms indica e ha emale may-
o s adop dis inc app oaches o clima e change public policy, pa icula ly in he Amazon
egion. The policy p oposals pu o h by emale elec ed mayo s ea u e 0.16 pe cen -
age poin s mo e e e ences o en i onmen al- ela ed e ms han hose p oposed by hei
male coun e pa s, ep esen ing a 50% inc ease ela i e o he baseline. Mo eo e , he
elec ion o a woman significan ly inc eases he likelihood o in es ing in en i onmen al
ini ia i es by 13 pe cen age poin s. Impo an ly, ou findings sugges ha diffe ences in
he en o cemen o en i onmen al egula ions do no explain ou findings.
Finally, we show ha hese esul s a e obus ac oss a ious checks. Specifically, hey
hold when applying diffe en bandwid hs, excluding municipali ies loca ed e y close
o he cu off, and employing diffe en ke nel and polynomial unc ions. Addi ionally,
ou findings hold when excluding municipali ies he e we e pa o he Lis o P io i y
Municipali ies, indica ing ha he esul s a e no d i en by his policy, and we also show
ha diffe ences in he obse ed skill le els o emale and male mayo s do no explain he
esul s.
While ou s udy ocuses on he Amazon, a egion o c i ical global en i onmen al
significance, u he esea ch is needed o explo e whe he simila pa e ns eme ge in
o he con ex s. Expanding his analysis o diffe en geog aphic egions, pa icula ly
hose acing dis inc en i onmen al and go e nance challenges, could p o ide a b oade
unde s anding o he ole o emale leade ship in clima e policy. Fo ins ance, examining
he impac o emale poli ical leade s in egions affec ed by indus ial pollu ion, wa e
sca ci y, o ex eme wea he e en s could shed ligh on whe he hei influence ex ends
beyond de o es a ion and land use policies. Addi ionally, i would be o g ea in e es o
in es iga e how he p esence o s ong na ional en i onmen al policies o ex e nal in e -
na ional p essu es, such as global en i onmen al ag eemen s o clima e finance mecha-
nisms, migh in e ac wi h gende diffe ences in leade ship. By expanding his analysis o
a b oade ange o egions, we could be e assess whe he women’s leade ship has con-
sis en ly posi i e en i onmen al impac s o i such effec s a e con ex -dependen , hus
offe ing mo e gene alizable insigh s in o he ole o women in clima e go e nance.
Summa izing, ou analysis shows ha elec ing a woman as mayo leads o signifi-
can imp o emen s in clima e- ela ed ou comes compa ed o elec ing a male mayo in
Amazon municipali ies. These effec s likely s em om gende diffe ences in public policy
decisions. Al hough ex apola ing hese esul s o o he con ex s is no s aigh o wa d,
his e idence unde sco es he alue o inc easing womens poli ical pa icipa ion, as i no
only s eng hens en i onmen al go e nance bu also add esses key clima e challenges. In
sho , ou findings highligh he ole o women as agen s o en i onmen al change.
31
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35
A Tables and Figu es
Figu e A.1: Dis ibu ion o Mixed-gende Elec ions
(a) Round 2004 (b) Round 2008
(c) Round 2012 (d) Round 2016
No e: Mixed-gende elec ions a e defined as elec ions whe e he wo candida es wi h he la ges sha e o
o es a e a man and a woman. “O he s” a e he es o he municipali ies.
36
Table A.1: Desc ip i e S a is ics
Municipali ies wi h Res o
mixed-gende elec ions municipali ies
Mean Obs. Mean Obs. Diffe ence P- alue
Panel A: Geog aphic and economic cha ac e is ics
To al a ea in ha. 170213 3,888 145671 16,890 24541 0.01
GDP ( housands o cons an B azilian eais) 719438 3,889 852787 16,893 -133349 0.28
GDP pe capi a (cons an B azilian eais) 21360 3,889 23982 16,893 -2623 0.00
Ag icul u e alue added/GDP 0.176 3,889 0.187 16,893 -0.010 0.00
Indus y alue added/GDP 0.116 3,889 0.127 16,893 -0.011 0.00
Se ices alue added/GDP) 0.357 3,889 0.375 16,893 -0.018 0.00
Public adminis a ion alue added/GDP 0.296 3,889 0.256 16,893 0.040 0.00
Panel B: Popula ion cha ac e is ics
To al popula ion 25,862 3,889 27,429 16,893 -1,566 0.48
Sha e o u ban popula ion in 2000 0.574 3,864 0.585 16,695 -0.010 0.01
Sha e o u al popula ion in 2000 0.426 3,864 0.415 16,695 0.010 0.01
Sha e o ac i e women in 2000 0.372 3,864 0.394 16,695 -0.022 0.00
Sha e o employed women in 2000 0.313 3,864 0.335 16,695 -0.021 0.00
Sha e o low skilled in 2000 0.850 3,864 0.839 16,695 0.012 0.00
Sha e o medium skilled in 2000 0.120 3,864 0.131 16,695 -0.011 0.00
Sha e o high skilled in 2000 0.016 3,864 0.019 16,695 -0.003 0.00
Panel C: Mayo cha ac e is ics
Female 0.42 3,889 0.02 16,893 0.40 0.00
College 0.53 3,889 0.45 16,893 0.08 0.00
Ma ied 0.73 3,889 0.79 16,893 -0.06 0.00
Age 47.23 3,889 47.77 16,893 -0.54 0.00
Pa y PT 0.08 3,887 0.09 16,893 -0.01 0.17
Pa y PMBD 0.19 3,887 0.20 16,893 -0.00 0.75
Pa y DEM 0.08 3,887 0.08 16,893 -0.00 0.31
Pa y PSDB 0.14 3,887 0.14 16,893 -0.01 0.35
O he poli ical pa y 0.51 3,887 0.49 16,893 0.02 0.03
Panel D: Emissions pe municipali y
Emissions Ag icul u e 101,252 3,889 95,258 16,893 5,994 0.08
Emissions Ene gy 36,971 3,855 38,741 16,778 -1,770 0.63
Emissions Was e 8,285 3,889 8,915 16,893 -630 0.02
Emissions Land use 82,885 3,888 70,858 16,890 12,027 0.43
Emissions To al 229,047 3,889 213,496 16,893 15,552 0.36
Emissions To al Amazon 779,483 453 774,242 1,538 5,241 0.97
Emissions To al non-Amazon 170,750 3,295 177,300 14,985 -6,550 0.40
Panel E: De o es a ion pe municipali y
To al de o es a ion/baseline o es 0.05 3,770 0.05 16,552 0.00 0.09
To al Amazon de o es a ion/baseline o es 0.10 453 0.08 1,538 0.02 0.00
To al non-Amazon de o es a ion/baseline o es 0.04 3,295 0.04 14,985 -0.00 0.65
Panel F: En i onmen al go e nance and expendi u es
Municipali y wi h an En i onmen al Council 0.55 3,889 0.60 16,893 -0.04 0.00
Municipali y wi h en i onmen al expendi u e 0.57 3,875 0.59 16,836 -0.01 0.12
Pe cen age o en i onmen al expendi u e 0.48 3,875 0.47 16,836 0.01 0.32
To al en i onmen al fines 3.08 3,889 2.57 16,893 0.51 0.09
Pe cen age o en i onmen al ela ed wo ds 0.28 1,892 0.28 6,884 -0.00 0.76
No es: The able conside s all municipali ies whe e elec ions we e esol ed in he fi s ound, wi hou he need o a e un and wi hou i egula i ies. These
municipali ies a e di ided in o wo g oups: municipali ies wi h mixed-gende elec ions (defined as hose whe e he wo candida es wi h he la ges sha e
o o es a e a man and a woman) and he emaining municipali ies. The o al numbe o obse a ions e e s o he municipali y- e m uni s. Diffe ence
and p- alues e e o he diffe ence be ween he means o he wo samples and he s a is ical significance o his diffe ence. Emissions a e measu ed as he
a e age annual emissions in ons o CO2e o each ou -yea e m o he mayo s manda es. De o es a ion is he o al de o es a ion o o es co e in each
municipali y o e he ou -yea e m o he mayo s’ manda es, measu ed as a pe cen age o he o al o es co e in each municipali y du ing he baseline
yea , which is he yea p io o he s a o each e m. The sha e o ac i e women in 2000 is measu ed as he o al numbe o economically ac i e women
aged 10 yea s o olde di ided by he o al numbe o women aged 10 yea s o olde in 2000, while he sha e o employed women in 2000 is calcula ed as
he o al numbe o employed women aged 10 yea s o olde di ided by he o al numbe o economically ac i e women aged 10 yea s o olde in 2000.
The sha e o low-skilled, medium-skilled, o high-skilled indi iduals is measu ed as he o al numbe o people aged 10 yea s o olde wi h 0 o 8 yea s o
educa ion, 9 o 13 yea s o educa ion, o 14 o mo e yea s o educa ion in 2000, espec i ely, di ided by he o al numbe o people aged 10 yea s o olde
in 2000.
37
Figu e A.8: Sensi i i y o Obse a ions Nea he Cu off
A. All municipali ies wi h mixed-gende elec ions.
(a) Emissions in ons o CO2e
.
−500000
−400000
−300000
−200000
−100000
0
RDD coe icien
0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
Exclude Abs(sha e)<= X
(b) Emissions in ons o CO2e
Land use
−500000
−400000
−300000
−200000
−100000
RDD coe icien
0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
Exclude Abs(sha e)<= X
(c) De o es a ion as
sha e o o es co e
−.015
−.01
−.005
0
.005
RDD coe icien
0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
Exclude Abs(sha e)<= X
B. Amazon municipali ies.
(d) Emissions in ons o CO2e
.
−3000000
−2000000
−1000000
0
RDD coe icien
0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
Exclude Abs(sha e)<= X
(e) Emissions in ons o CO2e
Land use
−3000000
−2000000
−1000000
0
RDD coe icien
0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
Exclude Abs(sha e)<= X
( ) De o es a ion as
sha e o o es co e
−.08
−.06
−.04
−.02
0
RDD coe icien
0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1
Exclude Abs(sha e)<= X
No es: These figu es show he βcoefficien and i s 90% confidence in e al om es ima ing equa ion 1
10 imes, s a ing om no exclusions ( he baseline case) and p og essi ely excluding obse a ions wi hin
0.1%, 0.2%, 0.3%, up o 1% o he cu off. Es ima es a e ob ained using local linea es ima o s wi h a
iangula ke nel. The op imal bandwid h is based on Calonico e al. (2014).
Table A.3: Female Mayo and Emissions: Diffe en Ke nel and Polynomial O de
To al Emissions in ons o CO2e Land Use Emissions in ons o CO2e
(1) (2) (3) (4) (5) (6) (7) (8)
Panel A: To al
Female mayo -218,756** -234,122** -230,211** -278,043** -232,379** -258,011** -242,291** -263,267**
(101,193) (112,829) (110,210) (121,037) (93,063) (102,760) (102,288) (108,029)
Mean ou come 291,668 262,323 339,591 285,693 172,653 181,222 217,123 160,848
Bandwid h 12.8 20.8 8.6 14.6 13.1 23.3 8.5 16.4
Obse a ions [1156, 1035] [1644, 1304] [830, 774] [1296, 1113] [1179, 1041] [1742, 1373] [826, 769] [1411, 1185]
Panel B: Amazon egion
Female mayo -1,527,424*** -1,199,905* -1,547,957** -1,148,758* -1,477,081*** -1,103,449* -1,476,340** -1,090,148*
(587,018) (641,794) (648,061) (681,953) (552,254) (591,302) (613,005) (631,903)
Mean ou come 1,440,656 1,394,211 1,713,731 1,534,648 1,138,774 1,117,241 1,394,030 1,115,417
Bandwid h 13.0 14.3 8.9 9.9 13.4 13.6 8.9 12.0
Obse a ions [142, 125] [154, 133] [107, 99] [122, 104] [143, 125] [147, 125] [107, 99] [135, 120]
Yea & S a e FE Yes Yes Yes Yes Yes Yes Yes Yes
O de polynomial 1 2 1 2 1 2 1 2
Ke nel T iangula T iangula Uni o m Uni o m T iangula T iangula Uni o m Uni o m
No es: The dependen a iable is he a e age annual emissions in ons o CO2e o e he ou -yea e m in all municipali ies wi h mixed-gende elec ions (Panel A), he subsample
o Amazon municipali ies (Panel B). Es ima es ob ained using local linea es ima o s wi h a iangula ke nel. Op imal bandwid h based on Calonico e al. (2014). Robus
s anda d e o s clus e ed a he municipal le el in pa en heses * p < 0.1, ** p < 0.05 and *** p < 0.01.
44
Table A.4: Female Mayo and De o es a ion: Diffe en Ke nel and Polynomial O de
De o es a ion as a sha e o o es co e
(1) (2) (3) (4)
Panel A: To al
Female mayo -0.004 -0.003 -0.006 -0.004
(0.004) (0.005) (0.005) (0.006)
Mean ou come 0.049 0.049 0.049 0.049
Bandwid h 11.8 17.0 8.0 14.3
Obse a ions [1054, 950] [1407, 1172] [761, 710] [1243, 1064]
Panel B: Amazon egion
Female mayo -0.033* -0.030 -0.031* -0.039*
(0.018) (0.020) (0.017) (0.022)
Mean ou come 0.104 0.103 0.104 0.104
Bandwid h 11.5 17.8 11.9 13.9
Obse a ions [130, 110] [175, 151] [131, 113] [148, 125]
Yea & S a e FE Yes Yes Yes Yes
O de polynomial 1 2 1 2
Ke nel T iangula T iangula Uni o m Uni o m
No es: The dependen a iables is de o es a ion as sha e o he baseline o es co e in each munici-
pali y o e he ou -yea e m. Panel A es ima es equa ion 1in he o al sample and Panel B es ic s
he sample o Amazon biome municipali ies. Es ima es ob ained using local linea es ima o s wi h
a iangula ke nel. Op imal bandwid h based on Calonico e al. (2014). Robus s anda d e o s
clus e ed a he municipal le el in pa en heses * p < 0.1, ** p < 0.05 and *** p < 0.01.
Figu e A.9: Excluding Municipali ies in he LPM.
(a) Emissions in ons o CO2e
.
LU Emissions
To al emissions
−6 −4 −2 0
RDD coe icien
Amazon To al
(b) De o es a ion as a sha e
o o es co e
De o es a ion (sha e)
−.06 −.04 −.02 0
RDD coe icien
Amazon To al
No es: These figu es show he βcoefficien and i s 90% confidence in e al om es ima ing Equa ion
1 o all municipali ies wi h mixed-gende elec ions and o he subsample o Amazon municipali ies.
The dependen a iables a e he ollowing: he a e age annual emissions in ons o CO2e o e he ou -
yea e m in all municipali ies (Panel a) and de o es a ion as sha e o he baseline o es co e in each
municipali y o e he ou -yea e m (Panel b). Es ima es ob ained using local linea es ima o s wi h a
iangula ke nel and op imal bandwid h based on Calonico e al. (2014). All es ima es accoun o s a e
and ound fixed effec s.
45
Figu e A.10: Diffe en ial Skills be ween Female and Male Mayo s
(a) College effec :
Emissions in ons o CO2e
LU Emissions (le els)
To al emissions (le els)
−1000000 −500000 0 500000 1000000
RDD coe icien
Amazon To al
(b) College effec :
De o es a ion as sha e o o es co e
De o es a ion (sha e)
−.02 −.01 0 .01 .02 .03
RDD coe icien
Amazon Non−amazon
No es: These figu es show he βcoefficien and i s 90% confidence in e al om es ima ing equa ion 1,
using mayo ’s educa ion le el (indica o o ha ing college educa ion) as ea men a iable o all munic-
ipali ies wi h mixed-gende elec ions and o he subsample o Amazon municipali ies. The dependen
a iables a e he ollowing: he a e age annual emissions in ons o CO2e o e he ou -yea e m in all
municipali ies (Panel a) and de o es a ion as sha e o he baseline o es co e in each municipali y o e
he ou -yea e m (Panel b). Es ima es ob ained using local linea es ima o s wi h a iangula ke nel
and op imal bandwid h based on Calonico e al. (2014). All es ima es accoun o s a e and ound fixed
effec s.
46
