Author
Listed:
- Bapon Shm Fakhruddin
(Committee on Data of the International Science Council (CODATA), 75016 Paris, France
Research & Evaluation Office (REO), Auckland 1142, New Zealand
Green Climate Fund (GCF), Songdo 22004, Republic of Korea)
- Shaily Gandhi
(Committee on Data of the International Science Council (CODATA), 75016 Paris, France
Geosocial Artificial Intelligence Research Group, Interdisciplinary Transformation University Austria, IT:U Research Campus, Freistädter Str. 400, OG1, 4040 Linz, Austria)
Abstract
Climate-related disasters are escalating in frequency and severity, yet global adaptation finance remains critically insufficiently structured to respond after disasters occur rather than before. This study empirically examines disaster loss data, climate finance flows, and financial instrument evidence to test two hypotheses: whether climate finance is disaster-reactive, and whether policy uncertainty constrains it. We integrate data from the Emergency Events Database (EM-DAT), covering seven climate-induced hazard types (droughts, extreme temperatures, floods, glacial lake outburst floods, wet mass movements, storms, and wildfires), in addition to the OECD Creditor Reporting System (CRS), the World Uncertainty Index (WUI), the ND-GAIN vulnerability index, and the World Governance Indicators, the Green Climate Fund Open Data Library, and the Artemis Deal Directory across 131 countries (2011–2024) for Hypothesis 1 and 100 countries (2012–2024) for Hypothesis 2. Fixed-effects panel regressions with Driscoll–Kraay standard errors confirm that prior-year disaster losses significantly predict subsequent climate finance flows (β = 0.040, p = 0.009; N = 1769 country-year observations), establishing a reactive financing pattern. Policy uncertainty interacting with high vulnerability is found to suppress adaptation finance flows (β = −2.587, p = 0.080, N = 878 country-year observations), with the effect concentrated among the most climate-exposed economies. We propose a risk-layered climate finance architecture aligning instruments with distinct hazard tiers across the Global South. Credible policy signals, strategic public investment, and systematic integration of insurance mechanisms are essential preconditions for unlocking scalable, forward-looking resilience finance.
Suggested Citation
Bapon Shm Fakhruddin & Shaily Gandhi, 2026.
"Climate Finance Architecture: Disaster Loss, Policy Uncertainty and Adaptation Investment Across the Global South,"
JRFM, MDPI, vol. 19(6), pages 1-22, June.
Handle:
RePEc:gam:jjrfmx:v:19:y:2026:i:6:p:412-:d:1961053
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jjrfmx:v:19:y:2026:i:6:p:412-:d:1961053. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address
(email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.