A Hierarchical Multilevel Approach in Assessing Factors Explaining Country-Level Climate Change Vulnerability

George Halkos, Antonis Skouloudis, Chrisovalantis Malesios, Nikoleta Jones

Research output: Contribution to journalArticlepeer-review


Assessing vulnerability is key in the planning of climate change adaptation policies and, more importantly, in determining actions increasing resilience across different locations. This study presents the results of a hierarchical linear multilevel modeling approach that utilizes as dependent variable the Notre Dame Global Adaptation Initiative (ND-GAIN) Climate Change Vulnerability Index and explores the relative impact of a number of macro-level characteristics on vulnerability, including GDP, public debt, population, agricultural coverage and sociopolitical and institutional conditions. A 1995–2016 annual time series that yields a panel dataset of 192 countries is employed. Findings suggest that country-level climate change vulnerability is responding (strongly) to the majority of the explanatory variables considered. Findings also confirm that less-developed countries demonstrate increased vulnerability compared to the developed ones and those in transition stages. While these results indeed warrant further attention, they provide a background for a more nuanced understanding of aspects defining country-level patterns of climate vulnerability.
Original languageEnglish
Article number4438
Issue number11
Publication statusPublished - 29 May 2020

Bibliographical note

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).


  • Climate change vulnerability
  • Country-level index
  • Hierarchical linear multilevel (HLM) model


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