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Text as Data in Environmental Economics and Policy

Author

Listed:
  • Eugenie Dugoua
  • Marion Dumas
  • Joëlle Noailly

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

  • Eugenie Dugoua & Marion Dumas & Joëlle Noailly, 2022. "Text as Data in Environmental Economics and Policy," Review of Environmental Economics and Policy, University of Chicago Press, vol. 16(2), pages 346-356.
    • Handle: RePEc:ucp:renvpo:doi:10.1086/721079
    DOI: 10.1086/721079
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    1. Antony Millner & Hélène Ollivier, 2016. "Beliefs, Politics, and Environmental Policy," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 10(2), pages 226-244.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Lauderdale, Benjamin E. & Herzog, Alexander, 2016. "Measuring Political Positions from Legislative Speech," Political Analysis, Cambridge University Press, vol. 24(3), pages 374-394, July.
    8. 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.
    9. 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).
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    Cited by:

    1. Leon Bremer, 2023. "Fuzzy firm name matching: Merging Amadeus firm data to PATSTAT," Tinbergen Institute Discussion Papers 23-055/VIII, Tinbergen Institute.
    2. Noailly, Joëlle & Nowzohour, Laura & van den Heuvel, Matthias & Pla, Ireneu, 2024. "Heard the news? Environmental policy and clean investments," Journal of Public Economics, Elsevier, vol. 238(C).
    3. Joëlle Noailly ; Laura Nowzohour; Matthias van den Heuvel, 2022. "Does Environmental Policy Uncertainty Hinder Investments Towards a Low-Carbon Economy?," CIES Research Paper series 74-2022, Centre for International Environmental Studies, The Graduate Institute.
    4. Andranik Tumasjan, 2024. "The many faces of social media in business and economics research: Taking stock of the literature and looking into the future," Journal of Economic Surveys, Wiley Blackwell, vol. 38(2), pages 389-426, April.

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    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

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