Abstract
The model is applied to yield curve data from selected Central African countries, including Cameroon, Congo, and Gabon. This involves: (i) Presenting the observed yield curve data, (ii) Estimating model parameters to align with the theoretical framework, and (iii) Reconstructing the latent states (underlying factors) of the interest rate model using the Kalman filter algorithm.
The comparative analysis between the latent states simulated by the Kalman filter and the theoretical model highlights the algorithm's efficiency in parameter optimization. Furthermore, the empirical validation in two stages substantiates the robustness and applicability of the model to capture the interest rate dynamics of Central African economies. Beyond its regional focus, this novel framework demonstrates versatility, offering potential applications in modeling interest rate behavior across other emerging and OECD economies.