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FORECASTING THE SOUTH AFRICAN ECONOMY WITH GIBBS SAMPLED BVECMs

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  • Rangan Gupta

Abstract

The paper uses the Gibbs sampling technique to estimate a heteroscedastic Bayesian Vector Error Correction Model (BVECM) of the South African economy for the period 1970:1‐2000:4, and then forecasts GDP, consumption, investment, short and long term interest rates, and the CPI over the period of 2001:1 to 2005:4. We find that a tight prior produces relatively more accurate forecasts than a loose one. The out‐of‐sample‐forecast accuracy resulting from the Gibbs sampled BVECM is compared with those generated from a Classical VECM and a homoscedastic BVECM. The homoscedastic BVECM is found to produce the most accurate out of sample forecasts.

Suggested Citation

  • Rangan Gupta, 2007. "FORECASTING THE SOUTH AFRICAN ECONOMY WITH GIBBS SAMPLED BVECMs," South African Journal of Economics, Economic Society of South Africa, vol. 75(4), pages 631-643, December.
    • Handle: RePEc:bla:sajeco:v:75:y:2007:i:4:p:631-643
    DOI: 10.1111/j.1813-6982.2007.00141.x
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    References listed on IDEAS

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    1. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    2. David A. Dickey & Dennis W. Jansen & Daniel L. Thornton, 1994. "A Primer on Cointegration with an Application to Money and Income," Palgrave Macmillan Books, in: B. Bhaskara Rao (ed.), Cointegration, chapter 2, pages 9-45, Palgrave Macmillan.
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    Cited by:

    1. 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.
    2. Mirriam Chitalu Chama-Chiliba & Rangan Gupta & Nonophile Nkambule & Naomi Tlotlego, 2011. "Forecasting Key Macroeconomic Variables of the South African Economy Using Bayesian Variable Selection," Working Papers 201132, University of Pretoria, Department of Economics.
    3. Nyoni, Thabani, 2019. "Is the United States of America (USA) really being made great again? witty insights from the Box-Jenkins ARIMA approach," MPRA Paper 91353, University Library of Munich, Germany.
    4. Annari De Waal & Rene頖an Eyden & Rangan Gupta, 2015. "Do we need a global VAR model to forecast inflation and output in South Africa?," Applied Economics, Taylor & Francis Journals, vol. 47(25), pages 2649-2670, May.
    5. Rangan Gupta & Sonali Das, 2010. "Predicting Downturns in the US Housing Market: A Bayesian Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 41(3), pages 294-319, October.
    6. Rangan Gupta, 2009. "Bayesian Methods Of Forecasting Inventory Investment," South African Journal of Economics, Economic Society of South Africa, vol. 77(1), pages 113-126, March.
    7. Rangan Gupta & Alain Kabundi, 2010. "Forecasting macroeconomic variables in a small open economy: a comparison between small- and large-scale models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 168-185.
    8. Pop, Raluca-Elena, 2017. "A small-scale DSGE-VAR model for the Romanian economy," Economic Modelling, Elsevier, vol. 67(C), pages 1-9.
    9. Rangan Gupta & Sonali Das, 2008. "Spatial Bayesian Methods Of Forecasting House Prices In Six Metropolitan Areas Of South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 76(2), pages 298-313, June.

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    More about this item

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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