TITLE:
Forecasting Foreign Direct Investment to Zambia: A Time Series Analysis
AUTHORS:
Stanley Jere, Bornwell Kasense, Obvious Chilyabanyama
KEYWORDS:
Foreign Direct Investment, Simple Exponential Smoothing, Holt-Winters Exponential Smoothing, Autoregressive Integrated Moving Average, Forecasting
JOURNAL NAME:
Open Journal of Statistics,
Vol.7 No.1,
February
28,
2017
ABSTRACT: Three methods are considered in this paper: Simple exponential smoothing (SES), Holt-Winters exponential smoothing (HWES) and autoregressive integrated moving average (ARIMA). The best fit model was then used to forecast Zambia’s annual net foreign direct investment (FDI) inflows from 1970 to 2014. Foreign direct investment is foreign capital investment to Zambia. Throughout the paper the methods are illustrated using Zambia’s annual Net FDI inflows. A comparison of the three methods shows that the ARIMA (1, 1, 5) is the best fit model because it has the minimum error. Forecasting results give a gradual increase in annual net FDI inflows of about 44.36% by 2024. Forecasting results plays a vital role to policy makers. Decision making, coming up with good policies and suitable strategic plans, depends on accurate forecasts. Zambian FDI policy makers can use the results obtained in this study and create suitable strategic plans to promote FDI.