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A BVAR Model for the South African Economy

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Author Info

  • Rangan Gupta

    ()
    (Department of Economics, University of Pretoria)

  • Moses M. Sichei

    (Department of Economics, University of Pretoria)

Abstract

The paper develops a Bayesian vector autoregressive (BVAR) model of the South African economy for the period of 1970:1-2000:4 and forecasts GDP, consumption, investment, short-term and long term interest rates, and the CPI. We find that a tight prior produces relatively more accurate forecasts than a loose one. The out-of- sample-forecast accuracy resulting from the BVAR model is compared with the same generated from the univariate and unrestricted VAR models. The BVAR model is found to produce the most accurate out of sample forecasts. The same is also capable of correctly predicting the direction of change in the chosen macroeconomic indicators.

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Bibliographic Info

Paper provided by University of Pretoria, Department of Economics in its series Working Papers with number 200612.

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Length: 21 pages
Date of creation: Jun 2006
Date of revision:
Handle: RePEc:pre:wpaper:200612

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Related research

Keywords: BVAR Model; Forecast Accuracy; BVAR Forecasts; Univariate Forecasts; VAR Forecasts;

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Citations

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Cited by:
  1. Das, Sonali & Gupta, Rangan & Kabundi, Alain, 2009. "Could we have predicted the recent downturn in the South African housing market?," Journal of Housing Economics, Elsevier, Elsevier, vol. 18(4), pages 325-335, December.
  2. Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Using Large Data Sets to Forecast Housing Prices: A Case Study of Twenty US States," Working papers, University of Connecticut, Department of Economics 2009-13, University of Connecticut, Department of Economics.
  3. Caraiani, Petre, 2010. "Forecasting Romanian GDP Using a BVAR Model," Journal for Economic Forecasting, Institute for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 76-87, December.
  4. Patricio Jaramillo, 2009. "Estimación de Var Bayesianos para la Economía Chilena," Revista de Analisis Economico – Economic Analysis Review, Ilades-Georgetown University, Universidad Alberto Hurtado/School of Economics and Bussines, Ilades-Georgetown University, Universidad Alberto Hurtado/School of Economics and Bussines, vol. 24(1), pages 101-126, Junio.
  5. 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, University of Pretoria, Department of Economics 201132, University of Pretoria, Department of Economics.
  6. Rangan Gupta & Stephen M. Miller, 2009. ""Ripple Effects” and Forecasting Home Prices in Los Angeles, Las Vegas, and Phoenix," Working Papers, University of Nevada, Las Vegas , Department of Economics 0902, University of Nevada, Las Vegas , Department of Economics.
  7. Balcilar, Mehmet & Gupta, Rangan & Shah, Zahra B., 2011. "An in-sample and out-of-sample empirical investigation of the nonlinearity in house prices of South Africa," Economic Modelling, Elsevier, Elsevier, vol. 28(3), pages 891-899, May.
  8. Rangan Gupta & Sonali Das, 2008. "Predicting Downturns in the US Housing Market: A Bayesian Approach," Working Papers, University of Pretoria, Department of Economics 200821, University of Pretoria, Department of Economics.
  9. Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working Papers, University of Pretoria, Department of Economics 200927, University of Pretoria, Department of Economics.
  10. Rangan Gupta & Stephen M. Miller, 2009. "The Time-Series Properties of House Prices: A Case Study of the Southern California Market," Working Papers, University of Nevada, Las Vegas , Department of Economics 0912, University of Nevada, Las Vegas , Department of Economics, revised Dec 2009.

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