English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

The political economy of coal across 12 countries: Analysing qualitative interviews with topic models

Authors

Manych,  Niccolò
External Organizations;

/persons/resource/mhansen

Müller-Hansen,  Finn
Potsdam Institute for Climate Impact Research;

/persons/resource/Jan.Steckel

Steckel,  Jan Christoph
Potsdam Institute for Climate Impact Research;

External Ressource
No external resources are shared
Fulltext (public)
There are no public fulltexts stored in PIKpublic
Supplementary Material (public)
Citation

Manych, N., Müller-Hansen, F., Steckel, J. C. (2023): The political economy of coal across 12 countries: Analysing qualitative interviews with topic models. - Energy Research and Social Science, 101, 103137.
https://doi.org/10.1016/j.erss.2023.103137


Cite as: https://publications.pik-potsdam.de/pubman/item/item_29422
Abstract
Understanding the ongoing investments in coal-fired power plants requires an analysis of the political economy. Here, we conduct a computational analysis of 212 interviews from 12 countries on the political economy of coal using topic modelling (TM). Our study highlights relevant topics by actor group and country. While most topics are similarly distributed across all actor groups, we find distinct clusters of countries in which similar topics play important roles. For example, in Indonesia and India, sustaining low electricity tariffs is brought forward as a reason to invest in coal, whereas in South Africa and Kenya the civil society is considered instrumental in the choice of coal or alternatives. To validate our findings, we compare them to outcomes of qualitative case studies and to papers grouping countries based on quantifiable factors. As this study is among the first to apply TM to interview data, we thereby highlight strengths and challenges for such application and the interpretability of results. We argue that topic models are effective supplements to qualitative case studies, particularly when analysing large amounts of text.