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Forecasting the South African Economy: A DSGE-VAR Approach

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  • Guangling (Dave) Liu

    ()
    (Department of Economics, University of Pretoria)

  • Rangan Gupta

    ()
    (Department of Economics, University of Pretoria)

  • Eric Schaling

    ()
    (Department of Economics, University of Pretoria)

Abstract

This paper develops an estimable hybrid model that combines the theoretical rigor of a micro-founded DSGE model with the flexibility of an atheoretical VAR model. The model is estimated via maximum likelihood technique based on quarterly data on real Gross National Product (GNP), consumption, investment and hours worked, for the South African economy, over the period of 1970:1 to 2000:4. Based on a recursive estimation using the Kalman filter algorithm, the out-of-sample forecasts from the hybrid model are then compared with the forecasts generated from the Classical and Bayesian variants of the VAR for the period 2001:1-2005:4. The results indicate that, in general, the estimated hybrid DSGE model outperforms the Classical VAR, but not the Bayesian VARs in terms of out-of-sample forecasting performances.

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Bibliographic Info

Paper provided by University of Pretoria, Department of Economics in its series Working Papers with number 200724.

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Length: 21 pages
Date of creation: Jul 2007
Date of revision:
Handle: RePEc:pre:wpaper:200724

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Keywords: DSGE Model; VAR and BVAR Model; Forecast Accuracy; DSGE Forecasts; VAR Forecasts; BVAR Forecasts.;

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References

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  1. Peter N. Ireland, 2000. "Money's Role in the Monetary Business Cycle," Boston College Working Papers in Economics, Boston College Department of Economics 458, Boston College Department of Economics.
  2. Ingram, Beth F. & Whiteman, Charles H., 1994. "Supplanting the 'Minnesota' prior: Forecasting macroeconomic time series using real business cycle model priors," Journal of Monetary Economics, Elsevier, Elsevier, vol. 34(3), pages 497-510, December.
  3. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, Elsevier, vol. 1(1), pages 19-46, January.
  4. Richard Rogerson, 2010. "Indivisible Labor, Lotteries and Equilibrium," Levine's Working Paper Archive 250, David K. Levine.
  5. Ingram, B.F. & Kocherlakota, N.R. & Savin, N.E., 1992. "Explaining Business Cycles : A Multiple Shock Approach," Working Papers, University of Iowa, Department of Economics 92-09, University of Iowa, Department of Economics.
  6. Marco Del Negro & Frank Schorfheide, 2003. "Take your model bowling: forecasting with general equilibrium models," Economic Review, Federal Reserve Bank of Atlanta, Federal Reserve Bank of Atlanta, issue Q4, pages 35-50.
  7. Zellner, Arnold, 1986. "A tale of forecasting 1001 series : The Bayesian knight strikes again," International Journal of Forecasting, Elsevier, Elsevier, vol. 2(4), pages 491-494.
  8. DeJong, David N. & Ingram, Beth F. & Whiteman, Charles H., 2000. "A Bayesian approach to dynamic macroeconomics," Journal of Econometrics, Elsevier, Elsevier, vol. 98(2), pages 203-223, October.
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Cited by:
  1. 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.

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