Climate Change Impacts at the National Level: Known Trends, Unknown Tails, and Unknowables

Steininger, Karl W.; Wagner, Gernot; Watkiss, Paul; König, Martin

doi:10.1007/978-3-319-12457-5_22

Cited by 2 publications

(2 citation statements)

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“…The use of modeling is a well-established scientific fact regarding the assessment of climate change impacts, and researchers usually apply “highly aggregated and sometimes highly simplified damage functions” (Steininger et al. , 2015), while an alternative approach employs “bottom-up, physical impact assessment and respective monetization ”.…”

Section: Resultsmentioning

confidence: 99%

“…The use of modeling is a well-established scientific fact regarding the assessment of climate change impacts, and researchers usually apply "highly aggregated and sometimes highly simplified damage functions" (Steininger et al, 2015), while an alternative approach employs "bottom-up, physical impact assessment and respective monetization". The literature works on the development of integrated models (Kirchner et al, 2015), and alongside general models it considers the use of local indicators (Formayer et al, 2015), sometimes scholars use models of intertemporal general equilibrium analysis with incorporated forward-looking expectations (Elshennawy et al, 2016).…”

Section: Cluster Analysismentioning

confidence: 99%

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Scenario analysis and climate change: a literature review via text analytics

Aversa

2023

BFJ

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PurposeClimate change has a direct impact on companies. Therefore, the scenario analysis is used to provide companies and stakeholders in this specific sector with forward-looking measures and narratives of the world's future state. This work aims to provide an independent, wide and rigorous literature review on the topics of scenario analysis and climate change, analyzing a large set of referred papers included in economic journals on the Web of Science Clarivate Analytics data source. This review, by means of a mixed approach, can help address new policy strategies and business models.Design/methodology/approachThe work employs 416 abstracts and relative titles in the field of economics, employing data mining for qualitative variables and performing descriptive statistics and lexicometric measures, similarity analysis and clustering with Reinert's hierarchical method in order to extract knowledge. Furthermore, qualitative content analysis allows for the return of a comprehensive and complete universe of meaning, as well as the analysis of co-occurences.FindingsContent analysis reveals three main classification clusters and four unknown patterns: model area, risks, emissions and energy and carbon pricing, indicating research directions and limitations through an overview with an extensive reference bibliography. In the research, the prevalent use of quantitative instruments and their limitations emerge, while qualitative instruments are residual for climate change assessment; they also highlight the centrality of transition risk over adaptation measures and the combination of different types of instruments with reference to carbon pricing.Originality/valueScenario analysis is a relatively new topic in economics and finance research, and it is under-investigated by the academy. The analysis combines quantitative and qualitative research using text analytics.

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Section: Resultsmentioning

confidence: 99%