IDEAS home Printed from https://ideas.repec.org/p/ehl/lserod/115396.html
   My bibliography  Save this paper

Text as data in environmental economics and policy

Author

Listed:
  • Dugoua, Eugenie
  • Dumas, Marion
  • Noailly, Joëlle

Abstract

There is growing interest in using text as data in social science research, particularly in economics. The availability of large amounts of digitized text material such as social media posts, newspapers, firms' annual reports, and patents, combined with new computer techniques, makes it increasingly possible for researchers to use this type of information. The aim of this article is to discuss the potential of these techniques for the field of environmental economics and policy.

Suggested Citation

  • Dugoua, Eugenie & Dumas, Marion & Noailly, Joëlle, 2022. "Text as data in environmental economics and policy," LSE Research Online Documents on Economics 115396, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:115396
    as

    Download full text from publisher

    File URL: http://eprints.lse.ac.uk/115396/
    File Function: Open access version.
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Endre Tvinnereim & Kjersti Fløttum, 2015. "Explaining topic prevalence in answers to open-ended survey questions about climate change," Nature Climate Change, Nature, vol. 5(8), pages 744-747, August.
    2. Gary King & Patrick Lam & Margaret E. Roberts, 2017. "Computer‐Assisted Keyword and Document Set Discovery from Unstructured Text," American Journal of Political Science, John Wiley & Sons, vol. 61(4), pages 971-988, October.
    3. Constantine Boussalis & Travis G. Coan & Mirya R. Holman, 2018. "Climate change communication from cities in the USA," Climatic Change, Springer, vol. 149(2), pages 173-187, July.
    4. Kira R. Fabrizio & Eun-Hee Kim, 2019. "Reluctant Disclosure and Transparency: Evidence from Environmental Disclosures," Organization Science, INFORMS, vol. 30(6), pages 1207-1231, November.
    5. Ivan Savin & Stefan Drews & Sara Maestre-Andrés & Jeroen Bergh, 2020. "Public views on carbon taxation and its fairness: a computational-linguistics analysis," Climatic Change, Springer, vol. 162(4), pages 2107-2138, October.
    6. Song, Yingjie & Ji, Qiang & Du, Ya-Juan & Geng, Jiang-Bo, 2019. "The dynamic dependence of fossil energy, investor sentiment and renewable energy stock markets," Energy Economics, Elsevier, vol. 84(C).
    7. Ralf Barkemeyer & Suraje Dessai & Beatriz Monge-Sanz & Barbara Gabriella Renzi & Giulio Napolitano, 2016. "Linguistic analysis of IPCC summaries for policymakers and associated coverage," Nature Climate Change, Nature, vol. 6(3), pages 311-316, March.
    8. Lauderdale, Benjamin E. & Herzog, Alexander, 2016. "Measuring Political Positions from Legislative Speech," Political Analysis, Cambridge University Press, vol. 24(3), pages 374-394, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Savin, Ivan & Ott, Ingrid & Konop, Chris, 2022. "Tracing the evolution of service robotics: Insights from a topic modeling approach," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    2. Ivan Savin & Kristina Chukavina & Andrey Pushkarev, 2023. "Topic-based classification and identification of global trends for startup companies," Small Business Economics, Springer, vol. 60(2), pages 659-689, February.
    3. Qiao, Sen & Guo, Zi Xin & Tao, Zhang & Ren, Zheng Yu, 2023. "Analyzing the network structure of risk transmission among renewable, non-renewable energy and carbon markets," Renewable Energy, Elsevier, vol. 209(C), pages 206-217.
    4. Muhammad Kashif & Thomas Leirvik, 2022. "The MAX Effect in an Oil Exporting Country: The Case of Norway," JRFM, MDPI, vol. 15(4), pages 1-16, March.
    5. Sun, Xiaolei & Liu, Chang & Wang, Jun & Li, Jianping, 2020. "Assessing the extreme risk spillovers of international commodities on maritime markets: A GARCH-Copula-CoVaR approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    6. Sandra Wankmüller, 2023. "A comparison of approaches for imbalanced classification problems in the context of retrieving relevant documents for an analysis," Journal of Computational Social Science, Springer, vol. 6(1), pages 91-163, April.
    7. McCannon, Bryan & Zhou, Yang & Hall, Joshua, 2021. "Measuring a Contract’s Breadth: A Text Analysis," Working Papers 11013, George Mason University, Mercatus Center.
    8. Fraccaroli, Nicolò & Giovannini, Alessandro & Jamet, Jean-François & Persson, Eric, 2022. "Ideology and monetary policy. The role of political parties’ stances in the European Central Bank’s parliamentary hearings," European Journal of Political Economy, Elsevier, vol. 74(C).
    9. Shen, Yiran & Liu, Chang & Sun, Xiaolei & Guo, Kun, 2023. "Investor sentiment and the Chinese new energy stock market: A risk–return perspective," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 395-408.
    10. Bouteska, Ahmed & Ha, Le Thanh & Bhuiyan, Faruk & Sharif, Taimur & Abedin, Mohammad Zoynul, 2024. "Contagion between investor sentiment and green bonds in China during the global uncertainties," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 469-484.
    11. Andrea Amado & Koji Kotani & Makoto Kakinaka & Shunsuke Managi, 2023. "Carbon tax for cleaner-energy transition: A vignette experiment in Japan," Working Papers SDES-2023-6, Kochi University of Technology, School of Economics and Management, revised Oct 2023.
    12. Sami Diaf & Jörg Döpke & Ulrich Fritsche & Ida Rockenbach, 2020. "Sharks and minnows in a shoal of words: Measuring latent ideological positions of German economic research institutes based on text mining techniques," Macroeconomics and Finance Series 202001, University of Hamburg, Department of Socioeconomics.
    13. Sterner, Thomas & Ewald, Jens & Sterner, Erik, 2024. "Economists and the climate," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 109(C).
    14. Bingler, Julia Anna & Kraus, Mathias & Leippold, Markus & Webersinke, Nicolas, 2024. "How cheap talk in climate disclosures relates to climate initiatives, corporate emissions, and reputation risk," Journal of Banking & Finance, Elsevier, vol. 164(C).
    15. Jin Chen & Yue Chen & Wei Zhou, 2024. "Relation exploration between clean and fossil energy markets when experiencing climate change uncertainties: substitutes or complements?," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-17, December.
    16. Zhijie Sasha Dong & Lingyu Meng & Lauren Christenson & Lawrence Fulton, 2021. "Social media information sharing for natural disaster response," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(3), pages 2077-2104, July.
    17. Song, Huiling & Wang, Chang & Lei, Xiaojie & Zhang, Hongwei, 2022. "Dynamic dependence between main-byproduct metals and the role of clean energy market," Energy Economics, Elsevier, vol. 108(C).
    18. Nader Trabelsi & Aviral Kumar Tiwari & Buhari Dogan, 2024. "Water and Emerging Energy Markets Nexus: Fresh Evidence from Advanced Causality and Correlation Approaches," Energies, MDPI, vol. 17(13), pages 1-22, June.
    19. Svetlana Drobyazko & Suparna Wijaya & Pavel Blecharz & Sergii Bogachov & Milyausha Pinskaya, 2021. "Modeling of Prospects for the Development of Regional Renewable Energy," Energies, MDPI, vol. 14(8), pages 1-17, April.
    20. Erkan Işığıçok & Sadullah Çelik & Dilek Özdemir Yılmaz, 2023. "Analysis of Skills and Qualifications Required in Data Scientist Job Postings Based on the Pareto Analysis Perspective Using Text Mining," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(39), pages 10-25, December.

    More about this item

    JEL classification:

    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other
    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ehl:lserod:115396. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: LSERO Manager (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.