Macroeconomic Environment And Public Debt In Kenya

Purpose: To estimate the optimal levels of real economic growth rate needed to stabilize debt levels and carry out a stochastic debt simulation to determine the possible future debt path and its distribution in Kenya. Methodology: The paper used time series data from 1963 to 2015. Auto Regressive Distributed Lag (ARDL) bound test procedure was used to test for short run and long run relationships among the variables. A VAR model was estimated followed by a simulation process to forecast the future values of the variables in the modified equation of motion of debt. The stochastic simulation process involved the extraction of variance - covariance structure of shocks and Monte Carlo simulation to separately simulate paths for each of the determinants of debt which are needed to construct the fan chart. The simulated values of these variables were then used to estimate and forecast the debt to GDP ratio using the modified equation of motion of debt from 2016 to 2030. Findings: The study found that an average economic growth rate of 5.4 percent between 2016 and 2030 will be sufficient to stabilize the debt levels in the country. The simulated debt shows the debt levels increasing from 56.2 percent in 2015 to 71.2 percent in 2030. Compared to the country’s debt threshold of 74 percent by the World Bank, this puts the economy at high risk in the event of any adverse shocks. Further, if the government deliberately targets to increase economic growth by 5 percent of the previous year, it will reduce the debt levels from 56.2 in 2015 to 46 percent in 2030. Unique contribution to theory, practice and policy: The government needs to explore innovative financing mechanisms for the desired infrastructural projects such as Build Operate and Transfer which will spur economic growth and at the same time ensure debt sustainability. Key words: Debt stabilization, macroeconomic environment, public debt, stochastic simulation, fan chart.