Download Political Economy of Climate Change Policy

Political Economy of Climate Change
Policy
Smith School Working Paper Series
October 2013
Working Paper 13-06
Franklin Steves
Alexander Teytelboym
Author: Franklin Steves & Alexander Teytelboym
Political Economy of Climate Change Policy
FranklinSteves1andAlexanderTeytelboym2
11October2013
Abstract Anthropogenic climate change poses a threat to all people and governments, but the
responsetothatthreatvariesenormouslyacrosscountries.Someadoptpoliticallycostly
andeconomicallychallengingclimatechangemitigationpolicies,whileothersdenythat
climate change is occurring. Why do some countries adopt effective climate change
policieswhileothersdonot?Toanswerthisfundamentalquestion,thispaperanalyses
thepoliticaleconomydeterminantsofclimatechangepolicyaroundtheworld.Inorder
to measure climate change policy, we introduce a new index, the ‘Climate Laws,
Institutions and Measures Index’ (CLIMI), the first systematic attempt to measure
countries’ policy responses to the risk of climate change. CLIMI covers all the relevant
institutionsandsector‐specificpoliciesin95countries,representing90%oftheworld’s
GHG emissions. We then use CLIMI to examine the political and economic factors that
determine countries’ choices to implement policies to tackle climate change. We find
thatthelevelofdemocracyaloneisnotamajordriverofclimatechangepolicyadoption,
butthatpublicknowledgeofclimatechangeis.Notsurprisingly,ahighconcentrationof
carbon‐intensiveindustryintheeconomyhinderstheadoptionofclimatechangepolicy.
Countries in which the citizenry has a better public awareness of climate change have
moreeffectiveclimatepoliciesregardlessofthepresenceofdemocraticinstitutions.
1 Introduction Thereisaconsensusinthescientificcommunitythathumanitywillbeadversely
affected by anthropogenic climate change unless worldwide emissions of
greenhouse gases are cut dramatically in the next 40 years (IPCC, 2007).
Althoughclimatechangehasmovedtothetopoftheglobalpoliticalagendaover
the past two decades, national mitigation policies remain a subject of intense
debate(Stern,2007;Giddens,2009).
Scientists are still uncertain about the exact size and distribution of the long‐
termeconomicdamagesresultingfromclimatechange(IPCC,2007).Asaresult,
policymakersinsomecountriesremainreluctanttointroduceaggressiveclimate

This paper draws heavily on the Chapter 4 of the Low Carbon Transition Report (EBRD, 2011),
which we co-authored with Daniel Treisman. We would like to thank Alex Chirmiciu, Grzegorz
Peszko, Jeromin Zettelmeyer and Robert Hahn, and all participants at the EBRD OCE and the Smith
School seminars for their invaluable comments, which greatly improved this working paper. We would
also like to express special thanks to Kamila Kavankova and Stefan Sulek for their tireless research
work during the preparation of the CLIMI.
1
European Bank for Reconstruction and Development; [email protected]
2
Department of Economics, University of Oxford and Smith School for Enterprise and the
Environment; [email protected]
2
changemitigationpolicy(Giddens,2009).However,manycountrieshave–often
unilaterally–cuttheiremissionsoverthepasttwentyyears.
Giventhescaleofemissionreductionstheworldneedstoachievetokeepglobal
warming in check, it is important for policymakers and academics to focus on
howfutureemissionreductionswillbebroughtabout.However,thisisapublic
goodsproblem,sovoluntaryreductionsareunlikelytobesufficient.Moreover,
itisuninformativetomeasureacountry’scommitmenttoemissionreductionby
looking at its current emissions, which are affected by a variety of factors
including economic conditions and trade. Substantial long‐term reductions in
emissions can only be achieved if most countries adopt effective emission
reductionpolicies.
As this paper shows, many countries have already introduced climate change
mitigation policies. However, measuring and comparing their quality and
effectiveness across countries is fraught with difficulties. First, no two policies
are the same because they usually arise through different legislative processes.
Second, it is unclear to what extent the laws in the book are actually
implementedinpractice.Third,evaluatingpoliciesseparatelymaymissouton
importantsynergiesthatmakepolicypackagesmoreeffective.
Thispaperproposesanewandsimplerankingofnationallegislative,fiscaland
institutional frameworks that can make a long‐term impact on emission
reduction: the Climate Laws, Institutions and Measures Index, or CLIMI. Unlike
most climate policy indices CLIMI focuses on policy inputs – climate laws,
institutionsandmeasures–ratherthanpolicyoutcomes,viz.,emissions.Thisis
the first index that takes into account all major sectoral and cross‐sectoral
policiesandmeasuresaswellasallgovernmentinstitutionsfocussedonclimate
change for 95 countries. A country that scores highly on CLIMI is not only
committed to reducing emissions today, but is also building the institutional
capacitytoreduceemissionsinthefuture.
CLIMI, while imperfect, allows us to understand how and why climate change
policyismade.3Wefirstsetoutastylisedmodelofclimatechangepolicymaking,
drawingfromthelargerliteratureonthepoliticaleconomyofreform.Wethen
use this model to propose some hypotheses about the key obstacles to climate
changepolicyadoption,andtestthesehypothesesdrawingonavarietyofdata
sources.
The rest of this paper is organised as follows. In Section 2 we introduce the
ClimateLaws,InstitutionsandMeasuresIndex(CLIMI).Forthe sakeofbrevity,
we relegate most of the methodology and sensitivity testing to the Appendix.
Section3sketchesoutourpoliticaleconomyapproachtoclimatechangepolicy
andproposesseveralhypothesesabouttherelationshipbetweendifferentactors
in the formation of national climate change policies. Section Error! Reference
source not found. presents the empirical testing of the hypotheses from the
3
In this paper we use the terms ‘climate change policy’ and ‘climate policy’ interchangeably. Unless
otherwise specified, we use these terms to denote policies designed to mitigate climate change (and
thus global warming), as opposed to policies for adaptation to the impacts of climate change.
3
model, including a number of alternative specifications. Section 6 summarises
thefindingsandsuggestsseveraldirectionsforfurtherwork.
2 Measuring climate change policy To understand the factors driving emissions outcomes around the world, it is
importanttounderstandtowhatextentandinwhichwaysclimatechangepolicy
varies across countries. A number of international measures of climate change
outcomes,suchasCO2emissionsorcarbon‐intensity,alreadyexist.However,the
transmission mechanism from a government intention to CO2 emissions
reductions is through climate change policies and measures. Policies and
measures are based on, and embodied in, laws and institutions. There are no
internationally comparative measures of climate change policies, which
motivatedustoconstructCLIMI:ClimateLaws,InstitutionsandMeasuresIndex.
2.1 Policy commitments versus outcomes In order to tackle climate change, global cooperation is necessary. No single
country can cut its emissions quickly and deeply enough to prevent the
concentration of CO2 in the atmosphere from rising to dangerous levels. Yet
focussing solely on emissions, neglects how governments are trying to mitigate
climatechange.Therelationshipbetweenemissionsandpolicycommitmentis
notstraightforwardforseveralreasons:
 Emissions may rise despite good climate change policy due to economic
development objectives. This is particularly the case in some developing
countries with effective governments, which are struggling to contain
emissions produced by rapid fossil fuel‐based electrification and
urbanisationdespitesomeexcellentmitigationmeasures.
 Climate change policy may not be well implemented because of overall
government ineffectiveness. This does not mean that the government is
shirking from climate change effort. Instead, improving overall institutional
capacity of the government will improve the implementation of climate
changepoliciesandmeasures.
 Somecountrieshavemultipleobjectiveswhentheyadoptemissionreduction
policies.Forexample,somecountriesseektoinfluenceclimatechangepolicy
inothercountriesthroughnegotiations.Ononehand,CostaRicamayleadby
example aiming to decarbonise the economy fully within 20 years. On the
other, during the 15th session of the Conference of Parties (COP) in
Copenhagen, China refused to negotiate unless the EU agreed on CO2
reductionof20%by2020,whichwaslessambitiousthanthe30%cutEUhad
beenpreparedtoaccept(Guardian,2009).
 Thereisagreatvarietyofpossibleclimatechangemitigationpolicies.Policies
thatrelatedirectlyor,moreoften,indirectlytoCO2emissionreductionsare
often adopted within other legislative documents, and the mandate for
4

promotingthemmaynotliewithasingleauthority.Aplethoraofpolicies,in
areas such as energy security or urban transport sustainability, can have
positive climate change effects. It is therefore important to set out
comparablebenchmarksforallkeycarbon‐relatedsectorsandchecktowhat
extentvariousgovernmentclimatechangepolicieshavemetthem.
Good policies have a long‐run effect on emissions. Several economies with
highpercapitaemissions,suchasGermany,haveadoptedaggressivecarbon
reduction policies that are likely to lead to a significant reduction in
emissionsinthenextdecade.Manydevelopingcountriesdonotevenhavea
long‐term strategy even for reducing carbon intensity per unit of GDP and
their emissions will increase significantly, even though they may be easily
preventableinthecontextofrapideconomicdevelopment.
These concerns identify a considerable gap in the measurement of climate
changepolicycommitmentsandoutcomes,whichtheCLIMIisdesignedtofill.It
maybeusefulnotonlyforpolicy‐makers,butalsofortheanalysisofthedrivers
ofemissiontrends:climatechangepoliciesandthepoliticaleconomyaspectsof
climate change. It is important to underline that CLIMI is not merely an
improvement on an existing index; it offers an entirely new and objective
measureofclimatechangepoliciesaroundtheworld.
2.2 National Communications and data sources Comparingthequality,breadthanddepthofclimatepolicies,measures,lawsand
institutions across a wide range of countries is neither a simple nor an
uncontroversialtask.First,therangeofgovernmentpoliciesandmeasuresthat
caninfluenceclimatechangeisvast.4Itisthereforenecessarytoselect,exante,
fromtheuniverseofgovernmentpoliciesandmeasuresthosethataredirected
towards and are most effective in reducing carbon emissions and therefore
mitigatingglobalclimatechange.
A second major methodological problem relates to the availability of reliable
data on climate change policies and measures that are comparable across
countries. While there are a large number of country studies on the quality of
individual countries’ climate change policies, there are no available cross‐
country comparative assessments of climate change policies with global
coverage.
Wethereforechosetousethemostsystematicinformationoncountries’climate
change mitigation policies and measures that is publicly available: National
Communications to the United Nations Framework Convention on Climate
Change (UNFCCC). The National Communications include detailed accounts of
climate change mitigation and adaptation policies and measures adopted by
nationalgovernments.
4
For example, minimum energy-efficiency standards in residential building regulations can have a
significant impact on carbon emissions, whether or not the consequence is intended.
5
NationalCommunicationsmustbesubmittedbyallcountries,whichhavesigned
the UNFCCC. Under Article 4.1(b) “all parties… shall…formulate, implement,
publish and regularly update national and, where appropriate, regional
programmes containing measures to mitigate climate change by addressing
anthropogenic emissions by sources and removals by sinks of all greenhouse
gasesnotcontrolledbytheMontrealProtocol…”Allcountries,whichsignedthe
UNFCCC, except the United States, subsequently signed and ratified the Kyoto
Protocol5 (UNFCCC, 1998), which expired in 2012. The Protocol divided
countries into developed countries, which had legally binding emissions
commitments for the period 2008‐2012 (Annex I), and developing countries,
whichdidnot(non‐AnnexI).
The Protocol also elaborated the reporting requirements: Article 10(b) states
that “all parties…shall…formulate, implement, publish and regularly update
national and, where appropriate, regional programmes containing measures to
mitigateclimatechange…(i)[s]uchprogrammeswould,interalia,concernthe
energy,transportandindustrysectorsaswellasagriculture,forestryandwaste
management.” Since, under Article 4 of the Protocol, “[e]ach Party included in
AnnexIshallincorporateinitsannualinventoryofanthropogenicemissionsby
sources and removals by sinks of greenhouse gases not controlled by the
Montreal Protocol”, Annex I countries also tend to update their policies and
measures every year. Non‐Annex I countries publish their National
Communicationsconsiderablylessregularly,butbyJanuary2011only13outof
153non‐AnnexIcountrieshadnotsubmittedaNationalCommunication.6
National Communications offer an excellent starting point for a comparative
understanding of the breadth and quality of climate change mitigation policies.
First,countrieshaveaclearincentivetoreportallthepoliciesandmeasuresthat
they are taking.Thereforeitis unlikely that countrieswould intentionally omit
anyoftheirsignificantlegislationorprogrammeswhichaddressclimatechange
mitigation.Topreventmisreportingbasedonexaggeration,therelevantpolicies
were cross‐checked with existing databases of climate change policies, using
national legislation as well as expert and UNFCCC country focal point
consultations (see Appendix 7.7 for a full list of sources). Second, National
Communications are systematic. UNFCCC prepared detailed and standardised
guidelinesforreportingpoliciesandmeasuresintheNationalCommunications
for Annex I (UNFCCC, 2000) and non‐Annex I countries (UNFCCC, 2003, inter
alia).Thesectoralstructureoftheguidelinesisparticularlyreflectedintwoout
ofthefourpartsofCLIMI.
2.3 Country coverage We cover all countries which submitted a National Communication to the
UNFCCCbetween1January2005(theyeartheKyotoProtocolcameintoforce)
5
The Protocol became legally binding on all signatories on 16 February 2005 after Russia ratified it in
November 2004.
6
These are: Angola, Brunei Darussalam, Cyprus, Equatorial Guinea, Iraq, Kuwait, Liberia, Libya,
Myanmar, Oman, Qatar, Somalia, Timor-Leste.
6
and15January2011.7WealsoincludeChina,India,SouthAfrica,theRepublicof
Korea, Turkey and Azerbaijan, in order to represent the largest and fastest
growingemitters.8ThisallowsCLIMI,unlikepreviousindicesofitskind,tooffer
extensive country coverage, including developing countries and small‐island
states.Appendix7.2includesafulllistofcountries.
CLIMI thus provides an objective comparative assessment of the breadth and
quality of climate change mitigation legislation, policies, measures and
institutionsin95countries(includingallcountriesintheEU,allpost‐communist
transition economies, all large developing countries, many least developed
countriesandsmallislandstates),covering91percentofglobalemissionsand
73percentoftheworld’spopulation.
2.4 Structure CLIMImeasuresthebreadthandqualityoffourmainpolicyareas:international
cooperation and policy; domestic institutions and national climate change
mitigationpolicy;sectoralpolicies;andcross‐sectoralpolicies.Thecomponents
of CLIMI follow the standardised structure of the National Communications,
which was designed to highlight the most important areas of climate change
mitigation policies and measures. CLIMI therefore has 12 constituent variables
groupedintofourkeypolicyareas:
1. International cooperation: how quickly a government ratified the Kyoto
Protocolandwhetheritdevelopedtheinstitutionalcapacitytoparticipatein
theflexiblemechanisms(hostprojectsunderJointImplementation (JI)orthe
CleanDevelopmentMechanism(CDM)).9
2. Domesticclimateframework:thisincludesbroadclimatechangelawsand
targets, as well as the levels of institutional engagement in climate change
(ministeriallevel,independentcommittees,etc.).
3. Sectoral fiscal or regulatory measures or targets: these include targets
and regulations in each of the sectors identified in the reports of the
IntergovernmentalPanelonClimateChange,apartfromwaste,asdetailedin
Appendix7.3.
4. Cross‐sectoral fiscal or regulatory measures: these include carbon taxes
andemission‐tradingschemes.
Most scores are assigned on a three level scale: 0/0.5/1. There are two
exceptions within the International Cooperation policy area: Kyoto Protocol
ratificationisassignedonalinearscaleandJI/CDMprojectexistenceisabinary
measure. A score of 1 is supposed to signify worldwide best practice – not the
bestconceivablepolicy.Ascoreof0.5meansthatsignificantmitigationmeasures
7
We exclude Liechtenstein, Luxembourg, Monaco and San Marino.
For these two countries, we used a large number of sources to obtain the information that is normally
provided in the National Communications.
9
See Dolsak (2009) for a similar approach.
8
7
havebeenintentionallytaken,buttheyfallconsiderablyshortofbestpractice.A
score of 0 means the institution or policy is non‐existent, insignificant or its
statedfunctionisdeceptive.Appendix7.3describesindetailhowthescoresare
assignedandprovidesexamplesoftypicalpolicymeasures.
Weights are used to reflect, broadly, the contribution of each of the sectoral
policyareastopossiblecarbonemissionreductions.Theweightsareassignedin
thefollowingway:halfoftheCLIMIscoreisassignedtonationalinstitutionsand
nationwidepoliciesandtargets,andhalfofthescoreisassignedtosectoraland
cross‐sectoralpolicies.Withinthesectoralpolicies,differentsectorsareassigned
weights according to their contribution to worldwide emissions measured by
IPCC (2007). Subcomponents in other policy areas are weighted equally.
Appendix Error! Reference source not found. summarises these key
componentsandshowshowtheyareweighted.
Finally,itisworthnotingthatCLIMIhasnotintroducedanycontroversialways
of measuring climate change policy. As the references indicate, most
subcomponentshavebeenusedinotherindicesorasproxiesforclimatechange
cooperation.TheuniquenessofCLIMIisthatitonlytakesintoaccountpolicies
andmeasures,itdoessoobjectively,anditdoesnotmixpolicieswithoutcomes.
BeforewedescribetheresultsoftheCLIMI,itisworthreiteratingwhatCLIMIis
not. Importantly, CLIMI does not include an assessment of outcomes (e.g.
emissions), implementation quality oradaptation measures.Thus, it is possible
that emissions may be on a rising trend in countries that have a high score on
CLIMI.Forexample,China’sindustrialgrowthputspressureonemissions,butits
mitigationpolicies(whichlimitemissionsthatwouldnothaveoccurredanyway)
are increasingly ambitious. In addition, CLIMI measures the policies that
countries have adopted to mitigate climate change, but does not provide an
assessmentofthequalityofimplementationofthosepolicies.Instead,itrelieson
anassessmentoftheextensivenessofpolicymeasures.CLIMIdoesnotclaimto
be comprehensive to climate change policy coverage: for example, we do not
lookatR&Dpoliciesduetoseriousdatalimitations.Finally,CLIMIlooksonlyat
climate change mitigation; it does not look at either adaptation or broader
environmental policies, which are likely to have different political economy
mechanismsfromthoseweidentify.10
2.5 Relationship between CLIMI and outcomes ThecountriesthatscorebestonCLIMItendtobenorthernEuropeancountries,
mostlyEUmemberstates.ThecountriesthatscorelowestonCLIMItendtobe
low‐incomecountries,predominantlylocatedinsub‐SaharanAfrica,whichhave
littlepressuretoreducetheirrelativelylowemissionsandlowstatecapacityto
design what are oftenlegally andeconomically complex policies and measures.
Indeed,thereisaclearcorrelationbetweencountries’percapitaincomeandthe
adoptionofgoodclimatechangepolicies,ashighlightedin
10
CLIMI does not attempt to measure waste sector policies and measures, due to a practical difficulty
in their comparative ranking across countries. This is the smallest emissions sector in almost all
countries, accounting for only 2.8% emissions globally (IPCC, 2007).
8
ThefullresultsofCLIMIarereportedinAppendix7.1.
3 How climate policy is made: a political economy approach Whydosomecountriesadoptambitiousclimatechangepolicieswhileothersdo
not? The literature on the political economy of policy‐making and reform
suggests four sets offactors thatare likely to be important. These relate to the
international context, the structure of government, the degree of political
accountability,andthecharacteristicsofinterestgroups.Themodelpresentedin
this section is highly stylized and focuses only on the national context. Its
purposeistoshedsomelightonthecomplexpoliticaleconomyofclimatechange
policyratherthanmaketightpredictions.
First, the international context will affect how governments approach climate
policy.Themakingofsuchpolicycanbethoughtofasatwo‐levelinteraction(cf.
Putnam, 1988). At the higher level, the world’s governments interact
strategically,eachseekingtobenefitfromtheglobalclimatechangeregimewhile
reducing their costs. Since there is no international authority with strong
sanctioningpower,thiscanbeconsidereda“game”ofvoluntarycontributionsto
a public good: climate stabilisation. At the lower level, climate policies are
formulatedandimplementedwithineachcountrybynationalgovernmentsonce
theinternationallevelissettled.
Whiletheinternationalbargaininggameisimportant,thispaperfocusesonthe
domestic level. We take international agreements as given and ask why some
governmentsdofarmorethanotherstorapidlyconcretiseandimplementtheir
international commitments. Under international agreements such as the Kyoto
Protocol, countries do pledge to meet certain carbon‐reduction targets. These
pledgesthenserveasthebackgroundratherthanacrediblecommitmenttothe
gameofdomesticpolicy‐making.
Domestic policy‐making depends in the first instance on the structure of
government.Governmentsdifferinthenumberofinstitutionalvetoplayers–or
actors whose agreement is necessary for policies to be enacted – that they
contain (Tsebelis, 2002). The number of veto players depends on whether the
parliamentconsistsoftwochambers,eachwithstrongpowers;whetherthereis
apresident;andwhethertheconstitutionisfederalinthesenseofgrantingveto‐
power over central policy to regional governments or their representatives. In
addition,thenumberofvetoplayerswilldependonthenumberofpartiesinthe
ruling coalition, since defection by a coalition member can preclude a bill’s
passage.Themorevetoplayersthereareandthemoredivergenttheirviews,the
more difficult it is to change policy. One veto player, the agenda setter, gets to
maketheproposalstowhichothervetoplayersrespond.Hence,theidentityof
theagendasetterwillalsoaffectwhatpolicyischosen.
The motivation of these veto players depends on the degree of political
accountability. In democracies, parties and individual politicians in the
9
governmenthavereasontotakeintoaccounttheviewsoftheirconstituents.The
moreresponsivethedemocracy,themorethepreferencesoftheelectoratewill
matter.Thedegreeofresponsivenesswilldependontheelectoralrules,butalso
on the degree of media freedom, which affects the accuracy and amount of
information available to voters. The ability of voters to extract accurate
information from the media and other sources will depend on their level of
education.
Finally, the characteristics of interest groups will also affect the outcomes of
domestic policy‐making. In part, the landscape of interest groups will simply
reflect the underlying economic interests in the society, associated with the
economicstructure.However,particularinterestgroupswillbebetterorganised
in some places than others. Classic contributions to this literature suggest that
theoutcomesofpolicywillreflectthesetofpressures–orbids–fromcompeting
interest groups (Olson, 1965; Becker, 1983; Grossman and Helpman, 1994).
Error! Reference source not found. Figure 2 outlines the hypothesised
relationshipsamongthekeyactorswhodrivetheformationofclimatepolicyby
governments(representedasG1,G2...)
Figure2:Stylisedmodelofclimatechangepolicyformation
Level one: international
Private contribution to a
public good game
Level two: domestic
Political game—
different in
different
countries
Policy
G1
Policy
Policy
G2
G3
Policy
G4
...
Media
NGOs
Funding
Political
influence
Information
Public
Carbonintensive
industry
Low-carbon industry
Other
actors
G2
Veto
player 1
Veto
player 2
...
Agenda
setter
Thinkingaboutpolicyinteractionsinthiswaysuggestsanumberofreasonswhy
onecountrymightpursueclimatepolicymoreactivelythananother.First,some
countriesaremoredependentoncarbon‐intensiveindustriesthanothers.Ifthe
income of the majority of the electorate depends on such industries, then one
might expect democratic politicians to resist reforms that would threaten the
livelihoodoftheirconstituents(KahnandMatsuaka,1997).Ofcourse,thereare
local benefits, for example in terms of air quality. If the benefits of developing
clean industry exceed the costs of retiring heavy polluters, the voters could in
10
principlebecompensated.However,promisestodosomaynotbecredibleand
votersmayblocksupportforcleanindustry.
Even if the majority of voters do not depend on carbon‐intensive industry,
special interests working on behalf of the carbon‐intensive industry can still
achievepoliticalinfluencedisproportionatetotheshareofvotesitcanmobilise,
aslongasitiswellorganised.Thus,astrongpresenceofhigh‐carbonindustries
mayresultintheeffectiveblockingofreform.
However, other interest groups and issue‐oriented lobbies such as
environmental non‐governmental organisations (NGOs) may balance the
pressuresofcarbon‐intensiveindustry,informingboththepublicandpoliticians
about the benefits of climate policy (Botcheva, 1996). In addition, low‐carbon
industriesmaylobbyforpoliciesthatsupporttheiractivities.
Indeed, the battle over climate change policies will in part be a battle of ideas.
Supportersandopponentsofclimatepolicywillseektoinform–andsometimes
to misinform – both the public and politicians on the causes of climate change
and the costs and benefits of mitigation measures. Given this conflicting
information,alotmaydependonthesophisticationofthegeneralpublic–which
inturndependsonthelevelofeducation–andontheextenttowhichthemedia
arefreeandmotivatedtopursuethetruthratherthantorepresentcorporateor
governmentinterests.
Public beliefs will also be shaped by history. Many countries, which have an
abundanceof fossil fuels, also have an energy‐intensiveand wasteful industrial
structure. In these countries, there tends to be a widespread belief that energy
use is less costly to society than it actually is. This may be another reason to
expectslowerreformsincountrieswheretheenergy‐intensivesectorislarger.
If a government is not democratic, then the paths of influence will tend to go
directly from interest groups to government actors, with less influence by the
public along the way. If the energy‐intensive industry is well organised, it may
succeed in blocking the implementation of climate policy commitments that
benefitthepublicbutarecostlytoentrenchedinterests.
The nature of the political regime may affect reform in one other way: by
determining the time horizon of policy‐makers. Reducing CO2 emissions has
potentially huge long‐term benefits in terms of preventing climate change, but
also large short‐term costs. If leaders are focused on winning the next election
(asinademocracy),oronavoidinganimminentcoup(inanunstableautocracy),
their regard for the future may be lower than that of the broader society. By
contrast an (well‐informed) autocrat who expects to remain in power for 20
yearsmighttakethethreatofglobalwarmingmoreseriously.
Asshouldbeclear,mostofthevariableslikelytoaffectclimatepolicy–regime
type,pressfreedom,eventherelativesizeofcarbon‐intensiveindustries–may
haveconditionalorevenconflictingeffects.Howeconomicstructure,theextent
of democracy and other factors influence countries’ performance in climate
11
change mitigation is therefore an empirical question. This is the subject of the
followingsection.
.
Thereislittlecorrelationbetweencountries’vulnerabilitytoclimatechangeand
the adoption of climate change mitigation policies and measures. This reflects
the fact that the countries that are most vulnerable to climate change tend to
contribute little to the problem – and hence tend to focus their efforts on
adaptationratherthanmitigation.
Figure1:CorrelationbetweenpercapitaincomeandCLIMI
ThefullresultsofCLIMIarereportedinAppendix7.1.
4 How climate policy is made: a political economy approach Whydosomecountriesadoptambitiousclimatechangepolicieswhileothersdo
not? The literature on the political economy of policy‐making and reform
suggests four sets offactors thatare likely to be important. These relate to the
international context, the structure of government, the degree of political
accountability,andthecharacteristicsofinterestgroups.Themodelpresentedin
this section is highly stylized and focuses only on the national context. Its
purposeistoshedsomelightonthecomplexpoliticaleconomyofclimatechange
policyratherthanmaketightpredictions.
First, the international context will affect how governments approach climate
policy.Themakingofsuchpolicycanbethoughtofasatwo‐levelinteraction(cf.
12
Putnam, 1988).11 At the higher level, the world’s governments interact
strategically,eachseekingtobenefitfromtheglobalclimatechangeregimewhile
reducing their costs. Since there is no international authority with strong
sanctioningpower,thiscanbeconsidereda“game”ofvoluntarycontributionsto
a public good: climate stabilisation.12 At the lower level, climate policies are
formulatedandimplementedwithineachcountrybynationalgovernmentsonce
theinternationallevelissettled.
Whiletheinternationalbargaininggameisimportant,thispaperfocusesonthe
domestic level. We take international agreements as given and ask why some
governmentsdofarmorethanotherstorapidlyconcretiseandimplementtheir
international commitments. Under international agreements such as the Kyoto
Protocol, countries do pledge to meet certain carbon‐reduction targets. These
pledgesthenserveasthebackgroundratherthanacrediblecommitmenttothe
gameofdomesticpolicy‐making.13
Domestic policy‐making depends in the first instance on the structure of
government.Governmentsdifferinthenumberofinstitutionalvetoplayers–or
actors whose agreement is necessary for policies to be enacted – that they
contain (Tsebelis, 2002). The number of veto players depends on whether the
parliamentconsistsoftwochambers,eachwithstrongpowers;whetherthereis
apresident;andwhethertheconstitutionisfederalinthesenseofgrantingveto‐
power over central policy to regional governments or their representatives. In
addition,thenumberofvetoplayerswilldependonthenumberofpartiesinthe
ruling coalition, since defection by a coalition member can preclude a bill’s
passage.Themorevetoplayersthereareandthemoredivergenttheirviews,the
more difficult it is to change policy. One veto player, the agenda setter, gets to
maketheproposalstowhichothervetoplayersrespond.Hence,theidentityof
theagendasetterwillalsoaffectwhatpolicyischosen.14
The motivation of these veto players depends on the degree of political
accountability. In democracies, parties and individual politicians in the
government have reason to take into account the views of their constituents.15
Themoreresponsivethedemocracy,themorethepreferencesoftheelectorate
willmatter.Thedegreeofresponsivenesswilldependontheelectoralrules,but
alsoonthedegreeofmediafreedom,whichaffectstheaccuracyandamountof
11
See Putnam (1988). For an application of the two-level game approach to climate policy, see Kroll
and Shogren (2008).
12
The literature since Olson (1965) has shown the outcome of such games to be far less determinate
than originally thought. Many equilibria are possible, depending on the detailed structure of the game
(see, for example, Bagnoli and Lipman (1989) and Bergstrom et al. (1986)). But for some simple
functional forms and assumptions, Olson’s conjectures are confirmed. Most importantly, the public
good is often undersupplied relative to the social optimum.
13
We do, nevertheless, consider empirically whether membership in the EU is associated with more
active climate policies. The norms and extra scrutiny associated with EU membership could plausibly
motivate governments in the accession countries to demonstrate their commitment to the European
approach.
14
It is possible that a clearly defined agenda setter may not exist. Then several veto players could make
simultaneous proposals.
15
For example, Holland et al. (2011) discuss the effect of lobbying, campaign contributions, and local
interests on transportation emissions regulation in the United States.
13
information available to voters. The ability of voters to extract accurate
information from the media and other sources will depend on their level of
education.
Finally, the characteristics of interest groups will also affect the outcomes of
domestic policy‐making. In part, the landscape of interest groups will simply
reflect the underlying economic interests in the society, associated with the
economicstructure.However,particularinterestgroupswillbebetterorganised
in some places than others. Classic contributions to this literature suggest that
theoutcomesofpolicywillreflectthesetofpressures–orbids–fromcompeting
interest groups (Olson, 1965; Becker, 1983; Grossman and Helpman, 1994).
Error! Reference source not found. Figure 2 outlines the hypothesised
relationshipsamongthekeyactorswhodrivetheformationofclimatepolicyby
governments(representedasG1,G2...)
Figure2:Stylisedmodelofclimatechangepolicyformation
Level one: international
Private contribution to a
public good game
Level two: domestic
Political game—
different in
different
countries
Policy
G1
Policy
Policy
G2
G3
Policy
G4
...
Media
NGOs
Funding
Political
influence
Information
Public
Carbonintensive
industry
Low-carbon industry
Other
actors
G2
Veto
player 1
Veto
player 2
...
Agenda
setter
Thinkingaboutpolicyinteractionsinthiswaysuggestsanumberofreasonswhy
onecountrymightpursueclimatepolicymoreactivelythananother.First,some
countriesaremoredependentoncarbon‐intensiveindustriesthanothers.Ifthe
income of the majority of the electorate depends on such industries, then one
might expect democratic politicians to resist reforms that would threaten the
livelihoodoftheirconstituents(KahnandMatsuaka,1997).Ofcourse,thereare
local benefits, for example in terms of air quality. If the benefits of developing
clean industry exceed the costs of retiring heavy polluters, the voters could in
principlebecompensated.However,promisestodosomaynotbecredibleand
votersmayblocksupportforcleanindustry.
14
Even if the majority of voters do not depend on carbon‐intensive industry,
special interests working on behalf of the carbon‐intensive industry can still
achievepoliticalinfluencedisproportionatetotheshareofvotesitcanmobilise,
aslongasitiswellorganised.Thus,astrongpresenceofhigh‐carbonindustries
mayresultintheeffectiveblockingofreform.
However, other interest groups and issue‐oriented lobbies such as
environmental non‐governmental organisations (NGOs) may balance the
pressuresofcarbon‐intensiveindustry,informingboththepublicandpoliticians
about the benefits of climate policy (Botcheva, 1996). In addition, low‐carbon
industriesmaylobbyforpoliciesthatsupporttheiractivities.
Indeed, the battle over climate change policies will in part be a battle of ideas.
Supportersandopponentsofclimatepolicywillseektoinform–andsometimes
to misinform – both the public and politicians on the causes of climate change
and the costs and benefits of mitigation measures. Given this conflicting
information,alotmaydependonthesophisticationofthegeneralpublic–which
inturndependsonthelevelofeducation–andontheextenttowhichthemedia
arefreeandmotivatedtopursuethetruthratherthantorepresentcorporateor
governmentinterests.16
Public beliefs will also be shaped by history. Many countries, which have an
abundanceof fossil fuels, also have an energy‐intensiveand wasteful industrial
structure. In these countries, there tends to be a widespread belief that energy
use is less costly to society than it actually is. This may be another reason to
expectslowerreformsincountrieswheretheenergy‐intensivesectorislarger.
If a government is not democratic, then the paths of influence will tend to go
directly from interest groups to government actors, with less influence by the
public along the way. If the energy‐intensive industry is well organised, it may
succeed in blocking the implementation of climate policy commitments that
benefitthepublicbutarecostlytoentrenchedinterests.
The nature of the political regime may affect reform in one other way: by
determining the time horizon of policy‐makers. Reducing CO2 emissions has
potentially huge long‐term benefits in terms of preventing climate change, but
also large short‐term costs. If leaders are focused on winning the next election
(asinademocracy),oronavoidinganimminentcoup(inanunstableautocracy),
their regard for the future may be lower than that of the broader society. By
contrast an (well‐informed) autocrat who expects to remain in power for 20
yearsmighttakethethreatofglobalwarmingmoreseriously.17
16
See Snyder and Ballentine (1996) for a discussion of the battle of ideas – and the need to regulate
free speech effectively – in the development of ethnonationalism in the post-communist region.
17
Even the public may tend to overweigh the immediate future relative to the distant future in ways
that are “time-inconsistent” (O’Donoghue and Rabin, 1999). However, we see no obvious reason why
such tendencies would be more pronounced in some countries than others. For an application to the
political economy of climate climate change policy, see Hovi et al. (2009).
15
Asshouldbeclear,mostofthevariableslikelytoaffectclimatepolicy–regime
type,pressfreedom,eventherelativesizeofcarbon‐intensiveindustries–may
haveconditionalorevenconflictingeffects.Howeconomicstructure,theextent
of democracy and other factors influence countries’ performance in climate
change mitigation is therefore an empirical question. This is the subject of the
followingsection.
5 Empirical investigation of climate change policy adoption In his section, we use CLIMI to analyse empirically the relationship between
climate change policies and measures – the outcome of interest in this paper –
and the various aspects of the stylised model of climate policymaking outlined
above.
Intherealworld,somegovernmentswillbeconstrainedbyoverwhelmingpublic
oppositiontocarbon‐reductionpolicies–regardlessofthehardeconomicfacts–
whileinothercountriesthetideofpublicopinionwillleavepoliticalleaderswith
little choice but to implement policy measures that are economically painful in
theshortrun.Insomecountries,theinfluenceofthecarbon‐intensiveindustry
lobby will be channelled via opaque means or personal relationships, while in
othercountriesthedebatebetweencarbon‐intensiveandlow‐carbonindustries
willtakeplaceinthepublicarenawithopenengagementbycivilsocietyandthe
independentmedia.
Recognisingthiscomplexity,weestimateareduced‐formstatisticalmodel,based
on six major factors that the political economy literature identifies as likely to
driveclimatechangemitigationpolicy:
1. Publicknowledgeofthethreatrepresentedbyclimatechange.Giventhe
extent to which the government responds to public pressure, one would
expect public knowledge of climate change to lead to stronger policies. The
data used to measure this are taken from a 2009 Gallup poll, conducted in
175 countries, which asked people whether they see climate change as a
threat, how much they know about climate change, and whether climate
change is caused by human activity or is a natural phenomenon. However,
becausethepublic’sunderstandingofclimatechangewillitselfbeinfluenced
bynationalclimatepolicies,aninstrumentalvariableapproachisrequiredto
understandthislink(seebelow).
2. Thelevelofdemocracy.Thedirecteffectofdemocraticsystemsonclimate
change mitigation policy could be either positive or negative. Democratic
political systems are designed to transmit popular concerns and priorities
into the policy‐making process. In democratic countries where public
knowledge of the threats and causes climate change is pervasive, one may
expect climate policy to be ambitious. However, if the public is opposed to
climate policy because it may harm short‐term economic prospects,
democraticpoliticalsystemsmayinhibittheadoptionofambitiouspolicyin
16
this area. We employed the widely used Polity IV regime characteristics
datasetfor2007tomeasurethelevelofdemocracy.
3. Thestrengthofthecarbon‐intensiveindustrylobby.Thepoliticalweight
ofthecarbon‐intensiveindustrylobbyissimultaneouslythemostimportant
determinantofclimatechangepoliciesandmeasures,andthemostdifficult
to measure. Carbon‐intensive industry may hinder climate change policy
especiallyifitisemploysalargeproportionoftheelectorateandcontributes
substantially to tax revenue. For the purpose of this analysis, the share of
carbon‐intensive industries – manufacturing, mining and utilities – in each
country’sGrossDomesticProductwasusedasaroughproxy.
4. State administrative capacity. Once political leaders have announced a
courseofpolicyaction,thestatedintentionmayormaynotbetranslatedinto
statepolicy.Thiswilldepend,atleastinpart,ontheadministrativecapacity
of the bureaucracy to draft regulations and laws, and submit them for
legislativeandexecutiveapproval.Thisfactorisonlyimplicitlyaddressedin
the political economy literature, but might be important, particularly with
regard to the complex regulatory, legal and economic challenges associated
withclimatepolicy.Countrieswithstrongdemocracies,freemediaandweak
carbon‐intensive industry lobbies might nevertheless have weak climate
change policies because of insufficient capabilities to design and implement
suchpolicies–muchlessenforcethem,anissuenotdealtwithinthispaper.
The simple average of the World Bank’s “Government Effectiveness” and
“Regulatory Quality” Governance Indicators for 2007 was used to measure
stateadministrativecapacity.
5. Per capita and total CO2 emissions. There are two possible waysthat per
capitaortotalCO2emissionsmightaffectclimatechangepolicyadoption.On
theonehand,thecountrieswiththehighestpercapitaCO2emissionstendto
bethehighestincomecountrieswhichhavehistoricallygeneratedthemost
atmospheric carbon and upon which most of international emission
reductionsobligations(e.g.KyotoProtocol,CancunAgreement,DohaClimate
Gateway) are being placed. On the other hand, in countries with higher per
capitaCO2emissions,itislikelythatintroducingaggressivecarbonemission‐
reductiontargetswillberesistedmorefiercelybybothindividualsandfirms.
Countries that have lower total emissions may be more reluctant to cut
emissions because their contribution to climate change is small and hence
any decrease in emissions will only have a negligible effect on global
emissions.Wethereforetestempiricallywhatkindofimpactspercapitaand
totalCO2emissionshaveontheadoptionofclimatechangepolicy.
6. International commitments. In all countries the nature of internationally
negotiated carbon emission‐reduction targets will play a role in domestic
leaders’ and polities’ cost/benefit deliberations on climate change policy
innovation.WethereforecontrolforratificationoftheKyotoProtocolaswell
as the size of the emission‐reduction target to which Annex I countries
committed themselves. In addition, the most binding international
commitments are entailed by membership in the EU, which we control for
17
usingadummyvariableintheregressions.Wealsouseadummyvariableto
test whether being a post‐communist transition country has a significant
effect on the adoption of climate change policy, controlling for other
variables.
5.1 The determinants of public opinion on climate change Beforeturningtotheempiricaltestingoftheimpactofthehypothesisedpolitical
economydriversonclimatepolicyadoption,itisnecessaryfirstto‘unpack’the
relationship between the first hypothesised driver – public knowledge of the
threat represented by climate change – and the adoption of climate policy. As
mentioned above, the observed correlation between public knowledge of the
threat posed by climate change and better climate policy could reflect causal
effectsinbothdirections:betterknowledgeofthecausesofclimatechangecould
simultaneouslyinfluence,andbeinfluencedby,climatechangepolicies.
Toseewhetherpublicinformationaffectsclimatechangepolicies,itistherefore
important to focus on cross‐country differences in public knowledge that are
driven by factors unlikely to be influenced by climate policies, and that do not
influence policies independently. Three possible factors are considered in this
context:
1. Levels of tertiary education. Higher levelsof tertiary education produce a
more sophisticated population, which is likely to be better informed about
the scientific evidence on climate change. We use the latest data available
fromtheWorldBank’sWorldDevelopmentIndicators.
2. Freedomofthemedia.Independentandcriticalmediaplayacrucialrolein
assessinganddisseminatingscientificfindings,particularlyinsuchvitalareas
as climate change. A free media is a key factor in shaping public
understanding of climate change. We use Freedom House’s Freedom of the
Mediaindexfor2007forthisissue.
3. Vulnerability.Ifacountryisvulnerabletoclimatechange,thepopulationis
more likely to be aware of climate change in general and its causes in
particular. For this variable, we use the Climate Change Vulnerability Index
2011compiledbyMaplecroft,ariskanalysisandmappingfirm.18
Table 1 reports the results of regressing various aspects of public opinion on
climate change, as found in the 2009 Gallup poll, on the three independent
variables listed above. The coefficients indicate whether countries with,
respectively, a higher degree of education, more media freedom, and a greater
vulnerability to climate change were more likely (positive coefficient) or less
likely(negativecoefficient)toagreewiththestatementsdescribedinthecolumn
headings.
18
We are very grateful to Maplecroft for sharing the aggregated results of their Climate Change
Vulnerability Index 2011 with us for this analysis.
18
Table1:Determinantsofknowledgeofanthropogenicclimatechange
Dependent variable →
Climate change a
threat
Some knowledge
of climate change
Much
knowledge of
climate change
Model →
A
B
C
Education
0.019
0.051
.208***
Media freedom
0.029
0.153
-.149*** -.210*** -.190** -.291**
Vulnerability
-.386*** -.330***
-0.011
D
E
F
Global warming
Global warming
caused by humans has natural causes
G
.184*** .345*** .338*** .146***
-0.032
0.411
-0.447
-0.068
H
I
J
.180*** -.340*** -.394***
0.028
-.441*** -.416***
.319***
-0.046
.711**
.763***
EU
0.08
-0.031
-.215*
0.064
-.596***
Transition economy
-.250***
.143**
0.061
-.202***
.363***
Number of observations
71
71
83
83
83
83
81
81
81
81
R2
0.23
0.33
0.6
0.62
0.54
0.55
0.27
0.37
0.32
0.43
As model A in this table illustrates, when controlling for the average level of
educationandformediafreedom,theperceptionofclimatechangeasathreatis
driven almost entirely by a country’s actual vulnerability to climate change.19
ModelBdemonstratedthatthisrelationshipholdswhenwecontrolforwhether
respondents live in the EU – with its aggressive climate change policies and
widespread public debate – or in the post‐communist transition countries,
whose economies are the among the most energy intensive in the world and
wherethereislimitedpublicdebateonclimatechange‐relatedconcerns.
Models C‐F show that people in countries with more widespread tertiary
education and greater media freedom are more likely to state that they have
knowledge of climate change. Countries’ actual vulnerability to climate change
has no significant effect here. In contrast, models G‐H suggest that that
awarenessthatglobalwarmingiscausedbyhumansdependsoneducationand
countryvulnerability,whilemediafreedommakesnodifferenceinthiscontext.
For similar levels of education and country vulnerability, this awareness is
significantly weaker in the transition countries than in the rest of the world
(modelH).
Thesamepatternisvisibleintheinversequestion(modelsI‐J):peopleinmore
vulnerablecountriesandcountrieswithmoretertiaryeducationarelesslikelyto
believe that global warming is a natural phenomenon. Controlling for levels of
educationandvulnerability,thisbelieftendstobelessprevalentinEUcountries
andmoreprevalentinthepost‐communisttransitioneconomies.
5.2 Political factors in climate change policy adoption We are now in a position to test what variables affect the adoption of climate
change policy. We employ a two‐stage least squares regression approach to
estimate the instrumental variable specification. This enables us to partially
19
The Maplecroft Climate Change Vulnerability Index is scored on a 1-10 scale, with 1 representing
extreme vulnerability and 10 representing no vulnerability.
19
addresstheproblemofreversecausationoutlinedintheprecedingsectionand
therefore make stronger statements about the impact of public knowledge on
climatechangepolicy.
Inordertojustifytheinstrumentalvariableapproach,ourmodelneedstosatisfy
tworequirements:
1. Relevance: the instrumented variable needs to be correlated with the
instruments.Inthefirststage,werunaregressionusedinmodelsGandHin
Table1(poolingtherespondentswhobelievethatglobalwarmingiscaused
byhumanactivity).Thisisusedtoconstructpredictedvaluesofknowledgeof
climatechangeacrosscountries.Ourthreeinstrumentsexplainabout30per
centofthevariationinpublicunderstandingofclimatechange.Therelevance
requirementisthussatisfied.
2. Exogeneity: the causal impact of the instrument on the dependent variable
must only be via the instrumented variable (conditional on the other
independent variables). The predicted level of climate change knowledge in
the first stage cannot be influenced by climate change policies. Hence, we
must assume that tertiary education, vulnerability and free media can only
affect climate change mitigation policy via public knowledge of climate
change. This seems like a reasonable assumption. Governments act under
pressurefromtheconcernedelectorateandourinstrumentsexplainhowthe
electorateobtainsitsinformation.
Inthesecondstage,thepredictedlevelofclimatechangeknowledgeaswellas
the remaining potential determinants discussed at the beginning of the section
are then used to investigate the causes of cross‐country variations in climate
change policy. The results of this second stage regression, using CLIMI as the
outcomevariable,arepresentedinTable2.
Table2:Determinantsofclimatechangemitigationpolicy‐IVspecifications
Dependent variable →
Climate Laws, Institutions and Measures Index
Model →
OLS
A
B
C
D
E
F
Knowledge of climate
change
.833
3.012***
2.213*
2.254***
2.082**
2.087**
2.248**
Democracy
.173
-
0.218
-0.230
-0.133
-0.0441
-0.156
Carbon-intensive
industry size
-.581*
-
-
-0.687**
-0.730**
-0.942***
-0.871***
State administrative
capacity
.325
-
-
1.002**
0.682
Kyoto Protocol target
-
-2.319**
-2.119**
-
-
-2.806***
-2.708**
CO2 per capita
.262*
0.237*
0.196*
-
0.0990
0.223**
0.139
Total CO2 emissions
-
-0.0313
0.0168
0.0695
0.0501
0.0414
0.0453
EU
.478***
0.161
0.630**
0.389*
0.390**
0.430
0.393
20
0.562
Transition economy
.055
0.315
0.294
0.494**
0.371*
0.148
0.307
Other
Vulnerability
Income per
capita
-
-
-
-
-
-
Number of observations
73
75
71
77
71
71
71
R2
0.590
0.326
0.411
0.440
0.459
0.434
Instrumented
-
Knowledge of climate change
-
Media Freedom, Level of Education, Vulnerability
Instruments
The OLS specification does not reject the hypothesis that greater knowledge of
climate change is associated with more extensive climate change policies.
However,allIVspecificationsshowthat,ceterisparibus,higherlevelsofpopular
knowledge of climate change lead to the adoption of more extensive climate
change mitigation policies and measures. This result suggests that reverse
causationwasindeedaproblemandisentirelyinlinewithourpoliticaleconomy
hypothesis. This is illustrated graphically in Error! Reference source not
found.whichshowsthatcountrieswherealargerproportionofthepopulation
believe that climate change is anthropogenic tend also to have more ambitious
climatepolicies–andhencetoscorebetteronCLIMI.
21
Figure3:CorrelationbetweenknowledgeofanthropogenicclimatechangeandCLIMI
On the other hand, specifications C‐F show that the strength of the carbon‐
intensiveindustrylobbyisafactorholdingbackclimatechangepolicies(seein
particular models E and F). This is illustrated in Error! Reference source not
found., which plots countries’ carbon emissions per tonne of CO2 against their
scoresonCLIMI.
22
Figure4:CorrelationbetweencarbonintensityandCLIMI
Table2alsoshowsthat,onceknowledgeofclimatechangeistakenintoaccount,
and controlling for international commitments and CO2 emissions, democracy
and state administrative capacity are not significant predictors of good climate
changepolicies.Stateadministrativecapacityisasignificantpredictorofactive
climate change policies only when Kyoto commitments and per capita CO2
emissions are excluded from the regressions. It is perhaps surprising that the
level of democracy does not drive the adoption of climate change policies and
measures,oncewecontrolfortheotherfactorsthatinfluencetheclimatechange
policy‐making process, including popular awareness of climate change. As we
argued above, democratic political systems are intended to transmit popular
concerns and priorities into the policy‐making process. As we argued above, in
the area of climate change policy‐making concerns and priorities of the
electoratemaybecuttingbothways.
Similarly,modelsCandDshowthatEUmembersaresignificantlymorelikelyto
adopt climate change policies than non‐EU members – until Kyoto Protocol
commitments are controlled for.20 Thus, Kyoto targets are of overriding
significance for predicting cross‐country variation in climate change policies,
followedbyEUmembershipandstateadministrativecapacity.21
ModelFsummarisesthemainrobustresultsfromtheanalysis.Controllingforall
other policy‐influencing factors, including countries’ CO2 emission‐reduction
targetsunderKyoto,revealsseveralfindings:
 Popularknowledgeofclimatechangeisapowerfuldriverofclimatechange
policyadoption.ThisisarobustresultthatholdsacrossallIVspecifications
wereportedaboveandinAppendix7.8.Thismeansthatevencontrollingfor
democratic institutions, the public’s concerns about climate change are
reflected in climate policy. For every one per cent increase in public
knowledgeoftheanthropogeniccausesofclimatechange,thereisa2.25per
cent increase in countries’ score on CLIMI. Thus, for example, if the level of
publicknowledgeofclimatechangeinUkraineincreasedtothelevelseenin
Italy,Ukraine’sscoreonCLIMIwouldincreaseby52percent–tobeonapar
withNewZealand.
 The relative size of the carbon‐intensive industry is significantly and
negativelyassociatedwithclimatechangepolicyadoption.
20
The empirical finding that democracy is not a significant determinant of climate change policy
adoption is consistent with the theoretical argument by Aumann, Kurz and Neyman (1983) that voting
is irrelevant for pure (non-exclusive) public goods when resources are privately owned.
21
While democracy and state administrative capacity are not significant, we leave them in as control
variables to be sure that we are accurately capturing the effects of knowledge, the carbon-intensive
industry lobby, per capita emissions and EU membership on climate change mitigation policy.
23



Thereisnoclearevidencethatstateadministrativecapacitymatters:states
with low administrative capacity are just as likely to adopt climate change
policiesasstateswithhighadministrativecapacity.
EUmembercountriestendtoadoptmoreassertiveclimatepoliciesthannon‐
EU members, although this effect is less robust across specifications than
countries’ adoption ofemission‐reduction targets under the Kyoto Protocol.
Thisisnotsurprising.EUcountriessharemanyEU‐wideclimatepoliciesand
targets.Inaddition,EUbargainsasawholeininternationalnegotiations.
After taking account of these factors, climate change policies in post‐
communist transition countries do not appear to be different from those in
therestoftheworld.
While we have identified several drivers of climate change policy, we have not
consideredhowgovernmentscouldaffectthem.Thisisaninterestingdirection
for further policy research. Factors such as level of education, vulnerability to
climate change, and media freedom tend to evolve only very slowly over time.
Press freedom can change more quickly – for instance, after coups or popular
uprisings–butsucheventsarerelativelyrare.
6 Conclusions and future work Thispaperdevelopsanewrankingofclimatechangemitigationpoliciesanduses
a political economy approach to explain why some countries adopt extensive
climatechangepoliciesandmeasureswhileothersdonot.Ouranalysisleadstoa
seriesofimportantconclusions.
We found that, ceteris paribus, the level of democracy is not a major driver of
climate change policy adoption. This is important as it means that there is no
reason to assume that countries with non‐democratic regimes are unable to
make significant contributions to the global challenge of reducing carbon
emissions.Expectationsofcontributiontoglobalclimatestabilisationbyagiven
countryneednot,therefore,belimitedbythenatureofitspoliticalregime.
We also found that public knowledge of climate change is a powerful
determinantofclimatechangepolicyadoption:countriesinwhichthepublicis
aware of the causes of climate change are significantly more likely to adopt
climate change mitigation policies than countries in which public knowledge is
low.
Public knowledge of climate change, in turn, is shaped by a number of key
factors,includingthethreatposedbyclimatechangeinaparticularcountry,the
nationallevelofeducationandtheexistenceoffreemedia.Democracyandfree
mediatendtogohandinhand:therearefewifanycountrieswithfreemediabut
no democracy. Thus, the conclusion that democracy per se does not determine
climatechangepolicydoesnotmeanthatcertainkeyaspectsofdemocracy,such
asfreemedia,arenotimportantdriversofpolicyadoption.
24
Ouranalysisfoundthattherelativestrengthofthecarbon‐intensiveindustryisa
major deterrent to the adoption of climate change mitigation policies and
measures,regardlessofthelevelofdemocracyortheadministrativecapacityof
the state. In many resource‐rich economies, these industries are the largest
exportearners,thelargestemployersandthelargestcontributorstothenational
tax base. It comes as no surprise, therefore, that these carbon‐intensive
industries influence governments’ approaches to climate change policy.
Moreover,carbon‐intensiveindustriesareunlikelytobereplacedbylow‐carbon
industry in a short enough timescale to make a difference to mitigating global
climatechange.
There are several avenues for further work. First, CLIMI could benefit from
severalpotentialimprovements:
 Developingamoregranularscaleforsomemeasures.Forexample,emissions
reduction targets could be measured as a proportion of the most ambitious
target and carbon tax could be measured relative to the average household
energybill.
 Including an implementation quality weight. Since CLIMI only considers
adopted policies and measures, it does not take into account how well they
are implemented on the ground. Measuring implementation quality would
requireextensiveconsultationswithcountryexperts.
 Addinggovernmentresearchanddevelopmentspending.Manygovernments,
suchastheUnitedStates,committohighlevelsofR&Dspendingratherthan
topoliciesthataddressmarketfailures.Thisalternativestrategyalsoreflects
commitment. However, such data are not currently available for countries
outsidetheOECDregion.
 Inclusionofcomparativemitigationpoliciesinthewastesector.
It would be important to assess how climate change policies are affecting CO2
emissions.PoliciesincludesinCLIMIwilltaketimetohaveasubstantialeffecton
emissions and future work can determine which were most effective. Many
seemingly robust climate change policies in developed countries reduce
domestic emissions at the expense of imports produced in carbon‐intensive
economies. Hence, coordination of climate change mitigation policies across
different countries (e.g., within the EU) must be taken into account when
measuringtheireffectiveness.
It would also be fruitful to understand what factors influence the change in
climatechangepoliciesovertime.Theanalysispresentedinthispaperisonlya
snapshot encompassing many years of institutional change. In order to tackle
climate change, countries need to develop policies and build institutions that
committhemtoemissionreductionsoverseveralgenerations.
25
7 Appendix 7.1 CLIMI results Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
15
17
18
19
20
21
22
23
24
25
26
27
28
29
29
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
45
47
48
Country
UnitedKingdom
Finland
France
Switzerland
Spain
Norway
Denmark
Sweden
Slovenia
Netherlands
Ireland
Germany
Belgium
CzechRepublic
Austria
Italy
Japan
SouthKorea
Lithuania
Greece
NewZealand
Iceland
CostaRica
Romania
Poland
Mexico
China
Hungary
Singapore
Portugal
Brazil
Bulgaria
SouthAfrica
Peru
Latvia
SlovakRepublic
Indonesia
Argentina
Ukraine
Estonia
Turkey
Uruguay
India
Vietnam
Colombia
UnitedStates
Morocco
DominicanRepublic
CLIMI
0.801
0.787
0.783
0.77
0.758
0.749
0.722
0.701
0.698
0.691
0.667
0.665
0.66
0.653
0.641
0.641
0.636
0.629
0.615
0.608
0.602
0.561
0.517
0.497
0.496
0.486
0.485
0.483
0.468
0.468
0.464
0.457
0.456
0.437
0.433
0.422
0.402
0.401
0.398
0.383
0.381
0.369
0.358
0.345
0.34
0.34
0.339
0.319
Rank
49
50
51
52
53
54
55
56
56
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
72
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
90
90
93
93
95
26
Country
Canada
Bolivia
FYRMacedonia
Croatia
Mongolia
Egypt
Australia
Belarus
Uzbekistan
Moldova
Georgia
Fiji
Kazakhstan
KyrgyzRepublic
Armenia
Albania
Malta
Rwanda
UnitedArabEmirates
Jordan
SaoTomeandPrincipe
Samoa
Serbia
Russia
Tajikistan
Montenegro
Turkmenistan
Azerbaijan
DRCongo
Venezuela
Senegal
GuineaBissau
Bahrain
Cameroon
BosniaandHerzegovina
Mauritania
Coted'Ivoire
Congo
Burundi
Madagascar
Niger
Mozambique
SaudiArabia
Algeria
Suriname
SierraLeone
Tonga
CLIMI
0.316
0.296
0.293
0.29
0.288
0.267
0.265
0.262
0.262
0.247
0.238
0.233
0.226
0.214
0.201
0.199
0.183
0.182
0.159
0.156
0.143
0.142
0.139
0.134
0.134
0.133
0.115
0.108
0.091
0.09
0.088
0.087
0.086
0.084
0.081
0.071
0.064
0.049
0.037
0.029
0.025
0.023
0.023
0.023
0.016
0.016
0.011
7.2 Countries included in CLIMI AnnexIcountries
Australia
Austria
Belarus22
Belgium
Bulgaria
Canada
Croatia
CzechRepublic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Italy
Japan
Latvia
Lithuania
Netherlands
NewZealand
Norway
Poland
Portugal
Romania
Russia
SlovakRepublic
Slovenia
Spain
Sweden
Switzerland
Ukraine
UnitedKingdom
UnitedStates
Non‐AnnexIcountries
withNCsafter2005
Albania
Algeria
Argentina
Armenia
Bahrain
Bolivia
BosniaandHerzegovina
Brazil
Burundi
Cameroon
Colombia
CongoBrazzaville
CongoKinshasa
CostaRica
Coted'Ivoire
DominicanRepublic
Egypt
Fiji
FYRMacedonia
Georgia
GuineaBissau
Indonesia
Israel
Jordan
Kazakhstan24
Kyrgyzstan
Madagascar
Malta
Mauritania
Mexico
Moldova
Mongolia
Montenegro
Morocco
Mozambique
Niger
Peru
Rwanda
Samoa
SaoTomeandPrincipe
SaudiArabia
Senegal
Serbia
SierraLeone
Singapore
Suriname
Syria
Tajikistan
Tonga
Turkmenistan
UnitedArabEmirates
Uruguay
Uzbekistan
Venezuela
Vietnam
Non‐AnnexIcountries
withNCsbefore2005
Azerbaijan
China
India
Korea
SouthAfrica
Turkey23
22
Although listed in the Convention’s Annex I, Belarus is not included in the Protocol’s Annex B as it
was not a Party to the Convention when the Protocol was adopted (UNFCCC)
23
Although listed in the Convention’s Annex I, Turkey is not included in the Protocol’s Annex B as it
was not a Party to the Convention when the Protocol was adopted (UNFCCC)
24
Upon entry into force, Kazakhstan, which has declared that it wishes to be bound by the
commitments of Annex I Parties under the Convention, will become an Annex I Party under the
Protocol. As it had not made this declaration when the Protocol was adopted, Kazakhstan does not have
an emissions target listed for it in Annex B. (UNFCCC)
27
7.3 Structure of CLIMI Policyor
institutional
variablename
Kyotoratification
Scoringrange
Explanation,comments,examplesandcounter‐examples
References
Linearfrom0
(notratified)to1
(earliest
ratification:Fiji)
Countries,whichratifiedKyotoearlier,aremorecommittedto
internationalcooperationinclimatechange.
JIorCDMdomestic
projectsexistence
None(0),
existence(1)
(evenifnoCERs
havebeenissued
yet)
Existenceofnational
climatechange
policyorlaw
None(0),Policy
(0.5),Law(1)
National,ambitious
targetforthepost‐
Kyotoperiod
None(0),NAMAs
(0.5),anational
target(including,
QEWET)(1)
Countries,whichhaveapprovedanddevelopedJIorCDMprojects
domesticallyandhavesubmittedinformationaboutthemtothe
UNFCCC,havedevelopedanadequateinstitutionalframeworkto
implementflexiblemechanisms.Countries,whichonlyusetheir
fundstofinanceprojectsabroad,donotnecessarilyexhibitthis
institutionalframework.
Aclearlyformulated,extensive,cross‐sectoralpolicyadoptedbythe
governmentshowsunderstandingandcommitmenttodomestic
mitigation.Alawpassedbythelegislativebranch,whichcreatesa
legallybindingframeworkformitigationisthestrongestexpression
ofsuchcommitment.Appropriateamendmentstoexistingsectoral
lawsscoreonparwithseparatelegislation.
Anyambitiousmediumterm,post‐Kyotoemissionsreductiontarget
indomesticpoliciesorincommunicationstotheUNFCCCbyAnnexI
countriesgets1.EUcountries,whichareallowedanemissions
increaseunderEUburdensharing,buthavenotsettheirown
reductiontargetsget0.AnnexIcountries,whichareexpectedto
reachthetargetstheyhadsetthemselvesduetothecollapseoftheir
economiesduringthetransitionperiodget0.Non‐annexIcountries,
whichmentionexplicittargetsfromBAUintheirNAMAsget0.5.
Similarapproachis
takeninBättiget
al.(2008)and
Bättigand
Bernauer(2009)
Thisisapartofthe
ISEinEBRD
(2008)
28
Thisisapartofthe
ISEinEBRD
(2008)
Targetsare
includedin
AccountAbility
(2010)
Dedicatedclimate
changeinstitution
None(0),
government
committee(0.5),
autonomous
agency(1)
Energy
supply/renewable
energy
sources/energy
efficiency
Nopolicy(0),a
setofpolicies
promoting
renewableenergy
orenergy
efficiency(0.5),a
comprehensive
laworpolicywith
targetsin
renewablesource
inelectricity
productionor
energyefficiency
andeffective
implementation
andenforcement
instruments(1)
None(0),support
formass/public
transportand
renewableenergy
intransport(0.5),
emission
regulation(1)
Transport
Anysufficientlyrepresentative(oughttoincludescientistsand/or
professionaland/orcivilsociety)inter‐ministerialcommission,
workinggrouporcommitteededicatedtoreviewinganddrafting
climatechangepolicygets0.5.Asmalldepartmentonclimatechange
inanotherministrygets0.5.Aministrywithacoremandatefor
climatechangeoradedicated,professionallystaffed,independent
agencygets1.NGOsandad‐hocworkinggroupsgetnomerit.
Acomprehensivesetoffiscal/regulatorypoliciessuchasfeed‐in
tariffs,greencertificates,minimumRESrequirements,taxbreaks
etc.,oraclearly‐definedenergyefficiencystrategygets0.5;alawor
policywithmedium‐termtargetsforrenewableenergyinelectricity
(oroverallconsumption)orenergyintensityreductiontargetsanda
comprehensivesetofsecondaryregulationsgets1.
SeeBättigetal.
(2008)andBättig
andBernauer
(2009).For
weightsseeEBRD
(2008)
Acomprehensivesetofpolicieswhichaddresstransportemissions
(simplypromotingpublictransportisnecessarybutnotsufficient),
suchastaxbreakforlowemissionvehiclesorhighfueleconomy
standardoracommitmenttobiofuelsgets0.5;emissionsstandards
fornewcarsoremissionstargetsforthefleetwitheffective
implementationandenforcementinstrumentsget1.(Emission
standardsfornewcarsdonotautomaticallygivecountries,whichdo
notproducecars,1)
Forpastanalysis,
seeAnandSauer
(2004)andfora
reviewof
instrumentssee
Santosetal.
(2010a)and
Santoseta.
29
Thisisapartofthe
Indexof
SustainableEnergy
inEBRD(2008)
(2010b).Seealso
Burcketal.(2012).
Forweightssee
IPCC(2007).
Buildings
Agriculture
Forestry
None(0),energy
efficiencyin
buildingsor
residential
renewableenergy
use(0.5),
building
insulation/renov
ationtargets(1)
None(0),sectoral
fiscalor
regulatory
policiesaimedat
carbon
dioxide/methane
/
NOxreductionor
methanecapture
(0.5),targetsfor
efficiencyand
organicfarming
(1)
None(0),
reforestation/aff
orestationfiscal
mechanismsget
0.5,REDDor
Acomprehensivepolicythataddressesenergylossofbuildingsgets
0.5.Effectiveimplementationandenforcementinstrumentsand
targetsforrefurbishingthecurrenthousingstockinorderto
improveenergyefficiency,ortightregulationofenergyconsumption
requirementsinneworlargebuildings,ortargetsfornear‐zero
energybuildingsget1.
SeealsoBurcket
al.(2012).For
weightsseeIPCC
(2007).
Anypolicythatregulatesemissions,inparticularmethane,from
livestockandland‐usemanagement,gets0.5.Targetsforfarm
conversiontoencouragefarmingwithreducedemissionswith
effectiveimplementationandenforcementinstrumentsget1.
SeealsoBurcket
al.(2012).For
weightsseeIPCC
(2007).
Strictandenforcedregulationsonlogging,suchasdeforestationbans
oronlycuttingdownaproportionofannualsurplusorREDDorvery
largereforestationprogrammesget1.Taxincentives,reforestation
programmesorextensionofforestmanagementcoverageor
tradablecertificatesget0.5.Generalforestconservationpolicygets
Forweightssee
IPCC(2007).
30
Industry
Additionalcross‐
sectoralmeasures
national
reforestation/aff
orestationtargets
None(0),
comprehensive/s
ectoralGHG
regulatorypolicy
(withtargetsand
effective
implementation
andenforcement instruments)
(0.5),carbon
emission
regulationacross
industry,suchas
EUETS(1)
None(0),
regionalcross‐
sectoralpolicy
(0.5),national
existence(1)
0.
EUETSalsocoverstheenergysectorandwillsoonincludeaviation,
soallthecountrieswhichareinEUETSget1.Nocreditfor
regulatinggases,whicharealreadyregulatedoutsidetheUNFCCC.In
ordertoscore0.5,needtoshowaregulatoryframeworkforthe
reductionofmainGHGgases,suchascarbondioxideormethane,
evenifonlyparticularhigh‐emittingsectors(suchascementorsteel)
arecovered.
Forweightssee
IPCC(2007).Also
seeChapter14in
Stern(2007)for
emissionstrading.
Anyadditional,extensivecross‐sectoralemissionreducingpolicy
beyondthesectoralpoliciesalreadynoted,suchasacarbontaxora
whitecertificatessystem,getsmerit.Carbontaxisataxonemissions
fromfuels.Thiscross‐sectoraltaxmustbeaboveandbeyondexisting
sectoraltaxes,suchaspetrolduties.Thetaxmustcreateincentives
foralmostallenergyconsumers(suchashouseholds)toreducethe
consumptionoffossilfuels(e.g.byimprovinginsulationin
dwellings).Whitecertificatessystemallowsenergyconsumersto
receivetradablecertificatesforexample,forimprovementsinenergy
efficiencyofbuildings,get1.Extensivecross‐sectoralregionalpolicy,
whichiscommoninfederations,cangetupto0.5.
Foreconomic
arguments,see
Chapter14inStern
(2007).
31
7.4 CLIMI weights Policyarea
Internationa
lcooperation
Domestic
institutions
and national
climate
change
mitigation
framework
Policy
area
weight
0.10
0.40
Variable
Score
Sub
weight
Kyotoratification
JIorCDM
Cross sectoral climate
changelegislation
Carbon
emissions
target
0to1
0/1
0.50
0.50
0/0.5/1
0.33
0/0.5/1
0.33
Dedicated
climate
changeinstitution
0/0.5/1
0.33
0/0.5/1
0.30
0/0.5/1
0/0.5/1
0/0.5/1
0/0.5/1
0/0.5/1
0.13
0.07
0.13
0.17
0.2
0/0.5/1
1.0
Significant
sectoral
fiscal
or
regulatory
measures or
targets
0.40
Energy supply and
renewableenergy
Transport
Buildings
Agriculture
Forestry
Industry
Additional
cross‐
sectoral
fiscal
or
regulatory
measures
0.10
Cross‐sectoral policy
measures
32
7.5 Sensitivity analysis This section explains that although sectoral and policy weights were chosen
somewhat arbitrarily, they do not fundamentally affect the country ranking
accordingtotheCLIMI.
We repeated the following Monte Carlo simulations (see Schwab, 2010, p. 12)
1000times:
1) Generate12pseudo‐randomweights,whichaddto1.
2) Applytheseweightstothecountryscores.
3) CalculateCLIMI
4) Rankthecountries
We then calculated the average rank and standard deviation of the rank of the
countries.TheresultsarereportedinTable3.Thecorrelationbetweenthemean
CLIMIrankis0.98andissignificantatover0.01%levelofsignificance.
WealsocheckedwhetherCLIMIissensitiveto:
a) Usingcountry‐levelsectoralweights:weweightedeachsectoraccording
toitsemissioncontributionusingUNFCCCdata.
b) ExcludingtheKyotomeasure
c) ExcludingtheJI/CDMmeasure
d) Combinationsofa),b)andc).
Empiricalresultswereunaffectedacrossallsensitivityspecifications.
Table3:CLIMIsensitivityanalysis
Country
France
Finland
Switzerland
Spain
Slovenia
Norway
Lithuania
Netherlands
Germany
Ireland
UnitedKingdom
CzechRepublic
Sweden
Austria
Italy
Denmark
Korea
NewZealand
Japan
Belgium
China
Romania
Poland
Greece
Hungary
Mexico
Singapore
Bulgaria
Portugal
CLIMI
0.7831666
0.7871667
0.7701667
0.7578334
0.6975
0.7491667
0.6153333
0.6911666
0.6651667
0.6665
0.8005
0.6531667
0.7011667
0.6411667
0.6405
0.7218333
0.6291667
0.602
0.6358333
0.6598333
0.4848333
0.4968333
0.4953333
0.6078333
0.4828333
0.4855
0.468
0.4568333
0.4678333
Mean
Simulated
Rank
12.636
14.796
14.88
16.265
17.765
17.855
18.685
19.188
20.604
21.481
21.744
23.09
23.448
23.819
23.955
24.479
25.024
26.572
27.069
27.082
29.112
29.63
29.921
31.905
32.76
33.064
34.308
34.839
34.918
Standard
deviation
of
simulated
rank
12.2027
13.0093
12.4647
14.3596
16.0028
15.9188
16.6408
12.5136
16.6217
19.864
19.8786
16.1949
19.162
16.5801
19.1053
19.6389
19.4164
21.1068
21.177
19.4259
21.0354
16.8775
20.4234
20.0826
19.8418
16.9546
20.7226
19.0977
19.2355
33
CLIMI
rank
3
2
4
5
9
6
19
10
12
11
1
14
8
15
16
7
18
21
17
13
27
24
25
20
28
26
29
32
30
Rankofmean
simulatedrank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
Estonia
SlovakRepublic
Brazil
SouthAfrica
Iceland
Latvia
CostaRica
Argentina
Turkey
Peru
Ukraine
Indonesia
India
Colombia
Dominican
Republic
Uruguay
Vietnam
Uzbekistan
Canada
Bolivia
Morocco
UnitedStates
FYRMacedonia
Moldova
Georgia
Mongolia
Croatia
Belarus
Egypt
Jordan
Kyrgyzstan
Fiji
Rwanda
UnitedArab
Emirates
Albania
Armenia
Malta
Kazakhstan
Australia
Russia
Samoa
Senegal
Cameroon
Turkmenistan
Azerbaijan
CongoKinshasa
Mauritania
SaoTomeand
Principe
Tajikistan
Serbia
Coted'Ivoire
Montenegro
Venezuela
GuineaBissau
Congo
Brazzaville
Bahrain
Bosniaand
Herzegovina
Burundi
Madagascar
Niger
SaudiArabia
Mozambique
Algeria
Suriname
SierraLeone
Tonga
0.383
0.4218333
0.4635
0.456
0.5611666
0.4333333
0.5168333
0.4008333
0.3803333
0.437
0.3978333
0.402
0.3575
0.3398333
35.548
37.258
37.406
37.645
38.609
39.238
39.275
40.815
41.102
41.564
42.855
43.142
43.426
43.824
21.6994
20.5341
17.5884
20.517
21.0014
21.2036
23.2902
19.8696
20.8611
22.074
22.2923
18.6819
17.7806
18.4792
40
36
31
33
22
35
23
38
41
34
39
37
43
46
30
31
32
33
34
35
36
37
38
39
40
41
42
43
0.3188333
0.3693333
0.3443333
0.2621667
0.3153333
0.2963333
0.3393333
0.34
0.2933333
0.2476667
0.2376667
0.2883333
0.2901667
0.2623333
0.2668333
0.156
0.2138333
0.2333333
0.1821667
44.133
44.439
45.442
46.01
46.951
47.256
47.797
48.655
48.837
49.065
49.342
49.866
50.189
52.846
54.49
56.038
56.117
56.992
57.026
18.5374
20.9724
20.7096
20.0004
15.0496
22.8105
23.1387
19.0301
18.6778
18.6902
20.8565
21.681
17.9843
15.9657
19.3636
20.7747
20.894
25.4624
20.381
48
42
44
57
49
50
47
45
51
58
59
53
52
56
54
68
62
60
66
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
0.1595
0.1991667
0.201
0.1831667
0.2256667
0.2643333
0.134
0.1416667
0.088
0.0835
0.1151667
0.1081667
0.0905
0.0715
57.436
57.506
57.798
60.845
60.923
61.544
63.226
63.353
67.055
67.192
67.224
67.65
68.522
68.581
20.0786
18.8045
24.0438
21.5859
19.5841
22.3323
20.7136
19.0167
22.1888
22.1537
21.9503
20.7293
20.9979
20.5439
67
64
63
65
61
55
72
70
79
82
75
76
77
84
63
64
65
66
67
68
69
70
71
72
73
74
75
76
0.1433333
0.1336667
0.1386667
0.064
0.1335
0.0896667
0.0866667
68.819
69.083
69.35
70.886
71.053
72.461
72.851
15.7264
15.6555
15.2061
19.96
19.8794
16.3276
15.6482
69
73
71
85
74
78
80
77
78
79
80
81
82
83
0.0485
0.0856667
73.599
73.872
14.8122
15.1022
86
81
84
85
0.0806667
0.037
0.029
0.025
0.0235
0.0235
0.023
0.0165
0.0155
0.011
74.547
77.617
79.461
80.48
80.602
81.091
81.574
82.723
82.871
84.113
14.9357
17.8718
16.2195
15.1648
14.3013
14.1113
13.5308
12.2713
12.3851
11.0805
83
87
88
89
91
90
92
93
94
95
86
87
88
89
90
91
92
93
94
95
34
7.6 Acronyms Thefollowingacronymsareusedinthispaper:
CCPI ClimateChangePolicyIndex(GermanWatch)
CDM CleanDevelopmentMechanism
EBRD EuropeanBankforReconstructionandDevelopment
GHG Greenhousegases
IDR In‐DepthReview
IEA InternationalEnergyAgency
ISE IndexofSustainableEnergy
JI
JointImplementation
NAMA
NationallyAppropriateMitigationActions
QEWET
Quantifiedeconomy‐wideemissionstargetsfor2020
REDD ReducingEmissionsfromDeforestationandDegradation
RES Renewableenergysources
UNFCCC
UnitedNationalFrameworkConventiononClimateChange
35
7.7 Additional sources for CLIMI 











Austrian Energy Agency: Energy in Eastern and Central Europe
(http://www.enercee.net/)
Bundesministerium für Umwelt, Naturschutz und Reaktorsicherheit: Legal
sourcesonrenewableenergy(http://www.res‐legal.eu/)
ClimaticoPolicyMonitorBaselineReport2010(editedbyPaigeAndrewsand
MarieKaraisl)
Deutsche Bank Climate Change Advisors Global Climate Change Policy
Tracker(March2010)
IEAClimateChangeDatabase(http://www.iea.org/textbase/pm/index.html)
NationalCommunicationstotheUNFCCC
Nationallegislation,passedlawsandofficialpolicies
OfficialEUdocuments,suchasEUDirectives
OfficialUNFCCCpublications,suchasIDRs
Other national communications to the UN, such as the note verbale on the
CopenhagenAccord
RenewableEnergyandEnergyEfficiencyPartnership:PolicyandRegulation
Review(http://www.reeep.org/9353/policy‐database.htm)
UNFCCCClimateActionTracker(http://climateactiontracker.org/)
36
7.8 Alternative regression specifications Here we present some alternative regression (OLS and IV) specifications to
convincethereaderoftherobustnessofourempiricalresultsandconclusions.
Specification 1 Include:
 CO2/capita
 GNI/capita
 Vulnerability
Dependentvariable →
Specification→
CO2percapita
Incomepercapita
Vulnerability
Transitioneconomy
EU
Dirtyindustrysize
Democracy
Stateadministrativecapacity
Knowledgeofclimatechange
Numberofobservations
R2
ClimateLaws,InstitutionsandMeasuresIndex
A
‐.091
.616***
‐.353
81
.37
B
‐.076
.546***
‐.644*
.130
.575***
81
.44
C
.055
.392**
‐.557*
.000
.483***
‐.592**
81
.49
D
.202
.133
‐.512
‐.042
.447***
‐.454
.353
.188
77
.56
E
.262*
‐.018
‐.334
.055
.478***
‐.581*
.173
.325
.833
73
.59
Dependentvariable →
Specification→
ClimateLaws,InstitutionsandMeasuresIndex
1
2
Model→
A
B
C
D
E
F
Knowledgeofclimatechange 2.42**
2.40***
2.57**
2.43*** 2.24*** 2.33***
CO2percapita
.112
.311
.323
.112
.293
.311
Incomepercapita
.181
‐.056
‐.358
.181
‐.007
‐.286
Vulnerability
‐.000
.158
.187
Transitioneconomy
.397
.158
.293
.397
.167
.279
EU
.565**
.386
.374
.565**
.411**
.415*
Dirtyindustrysize
‐.861*** ‐.803**
‐.830*** ‐.761**
Democracy
‐.137
‐.096
Stateadministrativecapacity
1.03
.919
Numberofobservations
74
74
70
74
74
70
R2
.18
.29
.43
.18
.32
.47
Instrumented
Knowledgeofclimatechange
Knowledgeofclimatechange
Media Freedom, Level of Media Freedom, Level of
Instruments
Education
Education,Vulnerability
37
Specification 2 Excludeatmostoneof:
 CO2/capita
 GNI/capita
 Vulnerability
Dependentvariable →
Specification→
Knowledgeofclimatechange
Transitioneconomy
Dirtyindustrysize
Stateadministrativecapacity
Democracy
EU
Incomepercapita
Vulnerability
CO2percapita
Numberofobservations
R2
ClimateLaws,InstitutionsandMeasuresIndex
1
.833**
.055
‐.581*
.325
.173
.478***
‐.018
‐.334
.262*
73
.59
2
.826***
.060
‐.578**
.308
.171
.478***
‐.345
.253**
74
.60
3
.929***
.014
‐.617*
.401
.168
.406***
‐.108
.275*
73
.58
4
1.01***
.413**
‐.225
.257
.040
.441***
.420***
‐.312
79
.61
Dependentvariable →
ClimateLaws,InstitutionsandMeasuresIndex
Specification→
1
2
Knowledgeofclimatechange
2.57**
2.17**
Transitioneconomy
.292
.337
Dirtyindustrysize
‐.803**
‐.724**
Stateadministrativecapacity
1.03
.643
Democracy
‐.137
‐.132
EU
.374
.380
Incomepercapita
.358
Vulnerability
.187
‐.077
CO2percapita
.322
.168
Numberofobservations
70
71
R2
.43
.48
Instrumented
Knowledgeofclimatechange
Instruments
MediaFreedom,LevelofEducation
38
3
1.95
.208
‐.716**
.799
‐.013
.416
.250
.304*
70
.58
4
4.45***
.875***
‐.790**
1.56**
‐.633
.160
‐.142
.892
76
.15
Specification 3 Include:
 GNI/capita
 Vulnerability
ClimateLaws,InstitutionsandMeasuresIndex
Dependentvariable →
Model→
Incomepercapita
Vulnerability
Transitioneconomy
Dirtyindustrysize
CO2percapita
State
administrative
capacity
Democracy
EU
Knowledge of climate
change
Numberofobservations
R2 A
.593***
‐.235
B
.610***
‐.325
.208
C
.507***
‐.393
.049
‐.702**
.009
D
.216
‐.330
.131
.488
.050
E
.144
‐.301
.019
‐.493*
.177
F
.133
.512
‐.042
‐.454
.202
G
‐.018
‐.334
.055
‐.581*
.262*
.914**
.429
.188
.325
.383
.353
.447***
.173
.478***
.833**
94
94
81
81
77
77
73
.44
.44
.45
.48
.52
.56
.59
Dependentvariable→
ClimateLaws,InstitutionsandMeasuresIndex
Model→
A
Knowledgeofclimatechange 5.67***
Vulnerability
1.70*
Incomepercapita
‐.043
Transitioneconomy
Dirtyindustrysize
CO2percapita
Stateadministrativecapacity
Democracy
EU
Numberofobservations
80
R2
.
B
3.19***
.552
.299**
.551**
80
.19
C
2.54***
.324
.011
.181
‐.984***
.290
74
.23
D
2.90***
.504
‐.468
.373
‐.646*
3.28
1.60**
74
.22
Instrumented
Knowledgeofclimatechange
Instruments
MediaFreedom,LevelofEducation
39
E
2.77**
.407
‐.382
.356
‐.878**
.299
1.37**
‐.172
70
.37
F
2.57**
.187
.358
.292
‐.803**
.322
1.03
‐.137
.374
70
.43
Specification 4 Include:
 Vulnerability
 CO2/capita
Exclude:
 GNI/capita
ClimateLaws,InstitutionsandMeasuresIndex
Dependentvariable →
Model→
A
Vulnerability
1.14***
Transitioneconomy
Dirtyindustrysize
CO2percapita
Stateadministrativecapacity
Democracy
EU
Knowledgeofclimatechange
Numberofobservations
95
R2
.15
B
1.14***
.003
95
.15
C
‐.043
‐.267*
‐1.01***
.347***
82
.38
D
‐.222
.080
‐.533*
.143
1.18***
82
.47
E
F
G
‐.224
‐.445
‐.345
‐.026
‐.085
.060
‐.506* ‐.463* ‐.578**
.248** .268** .253**
.560
.307
.308
.420*
.382
.171
.454*** .478***
.826***
78
78
74
.52
.55
.60
Dependentvariable→
ClimateLaws,InstitutionsandMeasuresIndex
Model→
A
Knowledgeofclimatechange 5.22***
Vulnerability
1.60***
Transitioneconomy
Dirtyindustrysize
CO2percapita
Stateadministrativecapacity
Democracy
EU
Numberofobservations
81
R2
.
B
4.60***
1.41***
.605**
81
.
C
2.59***
.340
.176
‐.959***
.305***
75
.22
D
2.35***
.163
.423**
‐.560*
.123
1.07**
75
.33
Instrumented
Knowledgeofclimatechange
Instruments
MediaFreedom,LevelofEducation
40
E
2.35**
.129
.407*
‐.798**
.132
.958*
‐.164
71
.43
F
2.17**
‐.077
.337
‐.724**
.168
.643
‐.132
.380
71
.48
Specification 5 Excludeatmostoneof:
 CO2/capita
 Vulnerability
Dependentvariable →
Model→
Transitioneconomy
Dirtyindustrysize
Vulnerability
CO2percapita
Stateadministrativecapacity
Democracy
EU
Knowledgeofclimatechange
Incomepercapita
Numberofobservations
R2
ClimateLaws,InstitutionsandMeasuresIndex
A
.014
‐.617*
.275*
.401
.168
.406***
.929***
‐.108
73
.58
B
.413**
‐.225
‐.312
.257
.040
.441***
1.01***
.420***
79
.61
Dependentvariable→
Model→
Knowledgeofclimatechange
Transitioneconomy
Vulnerability
Dirtyindustrysize
CO2percapita
Stateadministrativecapacity
Democracy
EU
Incomepercapita
Numberofobservations
R2 Instrumented
Instruments
ClimateLaws,InstitutionsandMeasuresIndex
A
B
1.95
.208
‐.716**
.304*
.799
‐.013
.416
.250
4.45***
.875***
.892
‐.790**
1.56**
‐.633
.160
‐.142
76
.15
70
.58
Knowledgeofclimatechange
MediaFreedom,LevelofEducation
41
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