Is Africa’s current growth reducing inequality? Evidence from some selected african countries
The main objective of this study is to model and predict the real GDP rate using Bayesian approach. A Bayesian VAR (BVAR), a Bayesian linear model and switching regime Bayesian models were employed for the real GDP rate, inflation rate and interest rate. From the set of variables that were connected to real GDP, for identifying the most relevant ones using the data for Romanian economy, we applied the selection algorithm based on stochastic search. Weight of revenues in GDP, weight of budgetary deficit in GDP, investment rate and inflation rate are the most correlated variables with the real GDP rate. The averages of posterior coefficients of models were used to make forecasts. For Romania on the horizon 2011-2014, the unrestricted switching regime models generated the most accurate forecasts.
Volume (Year): 3 (2015)
Issue (Month): 1 (June)
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- Caraiani, Petre, 2010. "Forecasting Romanian GDP Using a BVAR Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 76-87, December.
- Albu, Lucian-Liviu, 2010. "Scenarios for post-crisis period based on a set of presumed changes in the interest rate – investment – GDP growth relationship," MPRA Paper 32753, University Library of Munich, Germany.
- Jesús Crespo Cuaresma & Martin Feldkircher & Florian Huber, 2014.
"Forecasting with Bayesian Global Vector Autoregressive Models: A Comparison of Priors,"
189, Oesterreichische Nationalbank (Austrian Central Bank).
- Florian Huber & Jesus Crespo-Cuaresma & Martin Feldkircher, 2014. "Forecasting with Bayesian Global Vector Autoregressions," ERSA conference papers ersa14p25, European Regional Science Association.
- Diron, Marie, 2006. "Short-term forecasts of euro area real GDP growth: an assessment of real-time performance based on vintage data," Working Paper Series 622, European Central Bank. Full references (including those not matched with items on IDEAS)
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