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    <publishedYear>2024</publishedYear>
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    <language>eng</language>
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    <volume>15</volume>
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    <publisherName>Springer Science and Business Media LLC</publisherName>
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    <completedDate>2024-05-21</completedDate>
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    <title language="eng">Systematic review and meta-analysis of ex-post evaluations on the effectiveness of carbon pricing</title>
    <abstract language="eng">Today, more than 70 carbon pricing schemes have been implemented around the globe, but their contributions to emissions reductions remains a subject of heated debate in science and policy. Here we assess the effectiveness of carbon pricing in reducing emissions using a rigorous, machine-learning assisted systematic review and meta-analysis. Based on 483 effect sizes extracted from 80 causal ex-post evaluations across 21 carbon pricing schemes, we find that introducing a carbon price has yielded immediate and substantial emission reductions for at least 17 of these policies, despite the low level of prices in most instances. Statistically significant emissions reductions range between –5% to –21% across the schemes (–4% to –15% after correcting for publication bias). Our study highlights critical evidence gaps with regard to dozens of unevaluated carbon pricing schemes and the price elasticity of emissions reductions. More rigorous synthesis of carbon pricing and other climate policies is required across a range of outcomes to advance our understanding of “what works” and accelerate learning on climate solutions in science and policy.</abstract>
    <parentTitle language="eng">Nature Communications</parentTitle>
    <identifier type="issn">2041-1723</identifier>
    <identifier type="doi">10.1038/s41467-024-48512-w</identifier>
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    <author>Niklas Döbbeling-Hildebrandt</author>
    <submitter>Alwine Hoppe</submitter>
    <author>Klaas Miersch</author>
    <author>Tarun M. Khanna</author>
    <author>Marion Bachelet</author>
    <author>Stephan B. Bruns</author>
    <author>Max Callaghan</author>
    <author>Ottmar Edenhofer</author>
    <author>Christian Flachsland</author>
    <author>Piers M. Forster</author>
    <author>Matthias Kalkuhl</author>
    <author>Nicolas Koch</author>
    <author>William F. Lamb</author>
    <author>Nils Ohlendorf</author>
    <author>Jan Christoph Steckel</author>
    <author>Jan C. Minx</author>
    <collection role="HertieResearch" number="">Centre for Sustainability</collection>
    <collection role="HertieResearch" number="">ARIADNE</collection>
    <collection role="AY-23-24" number=""/>
    <thesisPublisher>Hertie School</thesisPublisher>
  </doc>
  <doc>
    <id>2298</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>379</pageFirst>
    <pageLast>382</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>7</volume>
    <type>article</type>
    <publisherName>Springer Nature</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2017-05-05</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A road map for global environmental assessments</title>
    <abstract language="eng">Increasing demand for solution-oriented environmental assessments brings significant opportunities and challenges at the science–policy–society interface. Solution-oriented assessments should enable inclusive deliberative learning processes about policy alternatives and their practical consequences.</abstract>
    <parentTitle language="eng">Nature Climate Change</parentTitle>
    <identifier type="issn">1758-678X</identifier>
    <identifier type="doi">10.1038/nclimate3307</identifier>
    <licence>Metadaten / metadata</licence>
    <author>Martin Kowarsch</author>
    <submitter>Lena Klein</submitter>
    <author>Christian Flachsland</author>
    <author>Jan C. Minx</author>
    <author> et al.</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Climate-change mitigation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Climate-change policy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Decision making</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Policy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Socioeconomic scenarios</value>
    </subject>
    <collection role="HertieResearch" number="">Centre for Sustainability</collection>
  </doc>
  <doc>
    <id>1912</id>
    <completedYear/>
    <publishedYear>2010</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>130</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>workingpaper</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2016-01-14</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">CITIES: Car Industry, Road Transport and an international Emission Trading Scheme. Policy options</title>
    <note>Free online Access / Freier online Zugriff: &#13;
http://ideas.climatecon.tu-berlin.de/documents/reports/CITIES%20REPORT.pdf</note>
    <licence>Metadaten / metadata</licence>
    <author>Felix Creutzig</author>
    <submitter>Simone Dudziak</submitter>
    <author>Christian Flachsland</author>
    <author>Emily McGlynn</author>
    <author>Jan C. Minx</author>
    <collection role="HertieResearch" number="">Centre for Sustainability</collection>
  </doc>
  <doc>
    <id>3874</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>72</volume>
    <type>article</type>
    <publisherName/>
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    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2021-05-10</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Who cares about coal? Analyzing 70 years of German parliamentary debates on coal with dynamic topic modeling</title>
    <abstract language="eng">Despite Germany’s Paris Agreement pledge and coal exit legislation, the political debate around carbon-intensive coal remains heated. Coal power and mining have played an important, yet changing role in the history of German politics. In this paper, we analyze the entire parliamentary debate on coal in the German parliament (Bundestag) from its inception in 1949 to 2019. For this purpose we extract the more than 870,000 parliamentary speeches from all protocols in the history of the Bundestag. We identify the 9167 speeches mentioning coal and apply dynamic topic modeling – an unsupervised machine learning technique that reveals the changing thematic structure of large document collections over time – to analyze changes in parliamentary debates on coal over the past 70 years. The trends in topics and their varying internal structure reflect how energy policy was discussed and legitimized over time: Initially, coal was framed as a driver of economic prosperity and guarantee of energy security. In recent years, the debate evolved towards energy transition, coal phase-out and renewable energy expansion. Germany’s smaller and younger parties, the Greens and the Left Party, debate coal more often in the context of the energy transition and climate protection than other parties. Our results reflect trends in other countries and other fields of energy policy. Methodologically, our study illustrates the potential of and need for computational methods to analyze vast corpora of text and to complement traditional social science methods.</abstract>
    <parentTitle language="eng">Energy Research &amp; Social Science</parentTitle>
    <identifier type="doi">10.1016/j.erss.2020.101869</identifier>
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    <author>Finn Müller-Hansen</author>
    <submitter>Caroline Forscht</submitter>
    <author>Max W. Callaghan</author>
    <author>Yuan Ting Lee</author>
    <author>Anna Leipprand</author>
    <author>Christian Flachsland</author>
    <author>Jan C. Minx</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Coal transition</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Energy policy</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Parliamentary debates</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Topic modeling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Computational text analysis</value>
    </subject>
    <collection role="HertieResearch" number="">Centre for Sustainability</collection>
    <thesisPublisher>Hertie School</thesisPublisher>
  </doc>
  <doc>
    <id>5803</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
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    <pageLast/>
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    <edition/>
    <issue/>
    <volume>4</volume>
    <type>article</type>
    <publisherName>Springer Science and Business Media LLC</publisherName>
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    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-03-28</completedDate>
    <publishedDate>--</publishedDate>
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    <title language="eng">Machine learning map of climate policy literature reveals disparities between scientific attention, policy density, and emissions</title>
    <abstract language="eng">Current climate mitigation policies are not sufficient to meet the Paris temperature target, and ramping up efforts will require rapid learning from the scientific literature on climate policies. This literature is vast and widely dispersed, as well as hard to define and categorise, hampering systematic efforts to learn from it. We use a machine learning pipeline using transformer-based language models to systematically map the relevant scientific literature on climate policies at scale and in real-time. Our “living systematic map” of climate policy research features a set of 84,990 papers, and classifies each of them by policy instrument type, sector, and geography. We explore how the distribution of these papers varies across countries, and compare this to the distribution of emissions and enacted climate policies. Results suggests a potential stark under-representation of industry sector policies, as well as diverging attention between science and policy with respect to economic and regulatory instruments.</abstract>
    <parentTitle language="eng">npj Climate Action</parentTitle>
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