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

Abstract

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.