This study investigates the intricate dynamics of international multilateral climate finance disbursements from 2003 to 2022 via an extensive dataset from the Climate Funds Update (CFU). By employing panel data econometric models, including pooled ordinary least squares (OLS), fixed effects (FE), and random effects (RE) models, the study elucidates the impact of grants and approved funds on disbursement levels across different income groups. The analysis reveals that while grants do not significantly influence disbursements, the approval of funds plays a critical role in enhancing disbursement efficiency. The random effects model, validated through the Hausman test, emerges as the optimal model for this context. The findings underscore the importance of streamlined approval processes in ensuring effective climate finance disbursements and highlight the need for further investigation into the non-significance of grants. The forecasting results indicate a positive trend in disbursements from 2023 to 2027, with potential fluctuations driven by external factors. This study provides valuable insights for policymakers and stakeholders to optimize climate finance mechanisms and improve fund utilization for sustainable development.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11888150 | PMC |
| http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0318170 | PLOS |
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