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Forecasting Macroeconomic Variables in a Small Open Economy: A Comparison between Small- and Large-Scale Models

  • Rangan Gupta

    ()

    (Department of Economics, University of Pretoria)

  • Alain Kabundi

    ()

    (Department of Economics and Econometrics, University of Johannesburg)

This paper compares the forecasting ability of five alternative types of models in predicting four key macroeconomic variables, namely, per capita growth rate, the CPI inflation, the money market rate, and the growth rate of the nominal effective exchange rate for the South African economy. Unlike the theoretical Small Open Economy New Keynesian Dynamic Stochastic General Equilibrium, the unrestricted VAR, and the small-scale Bayesian Vector Autoregressive models, which are estimated based on four variables, Dynamic Factor Models and the large-scale BVAR models use information from a data-rich environment containing 266 macroeconomic time series observed over the period of 1983:01 to 2002:04. The results, based on Root Mean Square Errors, for one- to eight-quarters-ahead out-of-sample forecasts over the horizon of 2003:01 to 2006:04, show that, except for the growth rate of the of nominal effective exchange rate, large-scale BVARs outperform the other four types of models consistently and, generally, significantly.

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Paper provided by University of Pretoria, Department of Economics in its series Working Papers with number 200830.

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Length: 17 pages
Date of creation: Sep 2008
Date of revision:
Handle: RePEc:pre:wpaper:200830
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Web page: http://www.up.ac.za/economics

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  1. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
  2. Thomas Lubik & Frank Schorfheide, 2003. "Do Central Banks Respond to Exchange Rate Movements? A Structural Investigation," Economics Working Paper Archive 505, The Johns Hopkins University,Department of Economics.
  3. Rangan Gupta & Moses M. Sichei, 2006. "A BVAR Model for the South African Economy," Working Papers 200612, University of Pretoria, Department of Economics.
  4. Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
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  9. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2005. "The generalised dynamic factor model: one sided estimation and forecasting," ULB Institutional Repository 2013/10129, ULB -- Universite Libre de Bruxelles.
  10. Rangan Gupta, 2006. "Forecasting the South African Economy with VARs and VECMs," Working Papers 200618, University of Pretoria, Department of Economics.
  11. Jordi Galí & Tommaso Monacelli, 2004. "Monetary policy and exchange rate volatility in a small open economy," Economics Working Papers 835, Department of Economics and Business, Universitat Pompeu Fabra.
  12. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-44, January.
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  14. Albert H. De Wet & Renee´ Van Eyden & Rangan Gupta, 2007. "Linking Global Economic Dynamics to a South African-Specific Credit Risk Correlation Model," Working Papers 200719, University of Pretoria, Department of Economics.
  15. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  16. 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.
  17. Terrence Kinal & Jonathan Ratner, 1986. "A VAR Forecasting Model of a Regional Economy: Its Construction and Comparative Accuracy," International Regional Science Review, SAGE Publishing, vol. 10(2), pages 113-126, August.
  18. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2006. "Forecasting using a large number of predictors: Is Bayesian regression a valid alternative to principal components?," Working Paper Series 0700, European Central Bank.
  19. Rangan Gupta & Sonali Das, 2008. "Spatial Bayesian Methods of Forecasting House Prices in Six Metropolitan Areas of South Africa," Working Papers 200813, University of Pretoria, Department of Economics.
  20. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
  21. Gupta, Rangan & Kabundi, Alain, 2011. "Forecasting Macroeconomic Variables Using Large Datasets: Dynamic Factor Model versus Large-Scale BVARs," Indian Economic Review, Department of Economics, Delhi School of Economics, vol. 46(1), pages 23-40.
  22. 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, 03.
  23. Zellner, Arnold, 1986. "A tale of forecasting 1001 series : The Bayesian knight strikes again," International Journal of Forecasting, Elsevier, vol. 2(4), pages 491-494.
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  25. Forni, Mario & Lippi, Marco, 2000. "The Generalized Dynamic Factor Model: Representation Theory," CEPR Discussion Papers 2509, C.E.P.R. Discussion Papers.
  26. Guangling (Dave) Liu & Rangan Gupta & Eric Schaling, 2008. "A New-Keynesian DSGE Model for Forecasting the South African Economy," Working Papers 200805, University of Pretoria, Department of Economics.
  27. Rangan Gupta & Alain Kabundi, 2008. "A Dynamic Factor Model for Forecasting Macroeconomic Variables in South Africa," Working Papers 200815, University of Pretoria, Department of Economics.
  28. Alberto Ortiz & Federico Sturzenegger, 2007. "Estimating Sarb'S Policy Reaction Rule," South African Journal of Economics, Economic Society of South Africa, vol. 75(4), pages 659-680, December.
  29. Bai, Jushan & Ng, Serena, 2007. "Determining the Number of Primitive Shocks in Factor Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 52-60, January.
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