Modelling Climate Finance Flows in Sub-Saharan Africa

Climate finance stakeholders across Africa have long sought to understand the complex nature of the climate cash flow architecture. Distribution models are critical mathematical tools for generating the general characteristics of the cash flow that are used to inform policy decisions. In this paper, we undertake a comprehensive investigation of the climate funds flowing into sub-Saharan Africa (SSA) by suggesting candidate climate finance models that can be used by policy makers to design simulations that can aid in assessing climate risks, identify more efficient climate finance schemes, and obtain optimal control parameter settings under different scenarios. This is achieved by considering climate finance as a form of insurance. Different dimensions of the data are examined following four distinct groupings of the data set. This is to account for different views of risk by the various climate finance participants. The frequency and severity of the approved funds are analyzed with the aid of various mathematical distribution models and regression analyses. The dynamics of a given variable relative to varying scenarios are examined. The findings obtained confirm the presence of emerging risks induced by the nature of the flow. Central Africa for instance records the lowest theme-specific projects and mitigation finance accounts for more than half of all the climate funds while sectoral-wise, adaptation finance is majorly concentrated in the energy sector. The perpetuation of the observed inequalities across the themes, subregions and sector-specific climate-related projects portends grave consequences as these risks begin to accumulate over time. The Burr mixture model best fitted the approved projects' cost distribution and the factors driving the frequency and severity of approved projects ranged from Central Africa to projects in the general environment sector. One of the policy recommendations emphasized was the need to adopt a risk-adjusted distribution model for climate finance allocation in SSA.