Foreign Direct Investment Inflow Modelling and Forecasting; A Case Study of Zimbabwe

By virtue of the stochastic nature of economic variables that exists today in any country, most nations are in a continuous attempt to increase their economic growth rates. Accurate foreign direct investment (FDI) inflows forecasting is certainly an inexpensive way to meet the aforementioned goal since this leads to improved planning and more accurate national budget proposals. In particular, for Zimbabwe, successful FDI forecasting can be of much importance, since it is a growing economy, FDI plays a pivotal role in its economic growth and the importance of proper planning and realistic budgeting is closely linked to economic stability and peace in the country. Thus is of prime importance for the country to forecast its expected foreign direct investment accurately. One way of determining the expected FDI is to analyse the historical data using time series analysis techniques. Forecasts enable efficient planning and equip nations with information that is of critical importance in strategic decision-making. Through the study of literature, we discuss several popular forecasting techniques and through empirical research, we explore time series techniques, this paper investigates the application of the ARIMA model in forecasting FDI inflow for Zimbabwe. The methodology is applied successfully to the FDI inflow data of Zimbabwe. ARIMA (0, 1, 1) was concluded to be the most appropriate model. Model diagnostics were done and it was realized that no model assumption was violated. Fitted values were regressed against observed values and it was realized that a very strong linear relationship was evident with an R2 value of over 76% which is very plausible