Growth and Forecasts of FDI Inflows to North and West Africa - An Empirical Analysis
AbstractThe developing countries of Africa are in severe hunger of FDI inflows as these are receiving a meager 2.9 percent share of global FDI inflows and just 10 percent of aggregate FDI inflows to the developing world. The present study is an effort to examine the growth of FDI inflows to the two largest recipient regions of Africa, through the computation of compound annual growth rates by fitting an exponential function estimated by ordinary least square method. The study detected that during the last three decades, the growth of FDI inflows remained highest for Algeria and Cape Verde, in Northern Africa and West Africa respectively. Both these countries also remained ahead of the others, in their respective regions in growth of FDI as percentage of gross fixed capital formation. The forecasts of FDI inflows to the representative countries of North and West Africa have been generated by using Double Exponential Smoothing model for the period 2009 to 2020. The adequacy of the model is tested by computing autocorrelation coefficients and Ljung-Box Q statistics. The study revealed that in the ensuing decade, Egypt is expected to grow at the fastest pace as far as FDI inflows are concerned.
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Bibliographic InfoArticle provided by University of Petrosani, Romania in its journal Annals of the University of Petrosani - Economics.
Volume (Year): 9 (2009)
Issue (Month): 2 ()
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Web page: http://www.upet.ro/
double exponential smoothing; compound growth rates; forecasts; auto correlation coefficients; Ljung-Box Q-Statistics;
Find related papers by JEL classification:
- F21 - International Economics - - International Factor Movements and International Business - - - International Investment; Long-Term Capital Movements
- F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications
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"Forecasting models and prediction intervals for the multiplicative Holt-Winters method,"
International Journal of Forecasting,
Elsevier, vol. 17(2), pages 269-286.
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