Bayesian Modelling of Kenya Extreme Debt with Correction for Budgetary Leakage

Abstract

Total public debt levels in Kenya are exponentially increasing due to rising budget deficit, poor public fund management as well as movement of various macro-economic indicators such as balance of payments, inflation, Gross Domestic Product, exchange rates, and grants leading to worries on whether or not the high debt levels would be sustainable in future. The major concern is that a huge portion of the country’s revenue is committed to debt repayment and budgetary leakage strains the repayment efforts, thereby accelerating the country's debt unsustainability. This study sought to model extreme debt in Kenya with correction for budgetary leakage using a Bayesian approach to Extreme Value Theory (EVT) the main aim being to estimate the maximum debt tolerable for the country. A non-stationary Generalized Pareto Distribution (GPD) model is used for modeling the public debt extremes which depend on some covariates (macro-economic indicators) and Bayesian methods used to directly estimate the threshold and the GPD parameters. A major contribution of this study is the introduction of a compensator to allow for possible leakage due budgetary leakage through corruption, tax evasion, money laundering, and other forms of financial fraud, modelling it as a function of budget deficit. The established debt threshold is approximately KShs. 2 trillion which is the standard amount that should be borrowed, beyond which values are considered extremes. The results indicate that the movements in the macro-economic debt indicators significantly affect total public debt levels, and that budgetary leakage reduces Kenya's debt tolerance. The research concluded that the current debt level of around KShs. 5 trillion is still sustainable but high budgetary leakage may accelerate the country's long-run debt unsustainability. For further work, it is recommended to use a time-varying threshold to capture seasonality of the public debt series.