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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. Copyright (c) 2007 The Author. Journal compilation (c) 2007 Economic Society of South Africa.

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Bibliographic Info

Article provided by Economic Society of South Africa in its journal South African Journal of Economics.

Volume (Year): 75 (2007)
Issue (Month): 4 (December)
Pages: 631-643

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Handle: RePEc:bla:sajeco:v:75:y:2007:i:4:p:631-643

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Cited by:
  1. 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.
  2. 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.
  3. 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.
  4. Annari de Waal & Renee van Eyden & Rangan Gupta, 2013. "Do we need a global VAR model to forecast inflation and output in South Africa?," Working Papers 201346, University of Pretoria, Department of Economics.

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