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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 References 1. 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