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Forecasting Macroeconomic Variables Using Large Datasets: Dynamic Factor Model versus Large-Scale BVARs

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Author Info
Rangan Gupta () (Department of Economics, University of Pretoria)
Alain Kabundi () (Department of Economics and Econometrics, University of Johannesburg)

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Abstract

This paper uses two-types of large-scale models, namely the Dynamic Factor Model (DFM) and Bayesian Vector Autoregressive (BVAR) Models based on alternative hyperparameters specifying the prior, which accommodates 267 macroeconomic time series, to forecast key macroeconomic variables of a small open economy. Using South Africa as a case study and per capita growth rate, inflation rate, and the short-term nominal interest rate as our variables of interest, we estimate the two-types of models over the period 1980Q1 to 2006Q4, and forecast one- to four-quarters-ahead over the 24-quarters out-of-sample horizon of 2001Q1 to 2006Q4. The forecast performances of the two large-scale models are compared with each other, and also with an unrestricted three-variable Vector Autoregressive (VAR) and BVAR models, with identical hyperparameter values as the large-scale BVARs. The results, based on the average Root Mean Squared Errors (RMSEs), indicate that the large-scale models are better-suited for forecasting the three macroeconomic variables of our choice, and amongst the two types of large-scale models, the DFM holds the edge.

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Publisher Info
Paper provided by University of Pretoria, Department of Economics in its series Working Papers with number 200816.

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Length: 14 pages
Date of creation: Jun 2008
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Handle: RePEc:pre:wpaper:200816

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Related research
Keywords: Dynamic Factor Model BVAR Forecast Accuracy

Other versions of this item:

Find related papers by JEL classification:
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications

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  1. Richard M. Todd, 1984. "Improving economic forecasting with Bayesian vector autoregression," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall. [Downloadable!]
  2. 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. [Downloadable!] (restricted)
    Other versions:
  3. Chamberlain, Gary, 1983. "Funds, Factors, and Diversification in Arbitrage Pricing Models," Econometrica, Econometric Society, vol. 51(5), pages 1305-23, September. [Downloadable!] (restricted)
  4. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January. [Downloadable!] (restricted)
  5. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April. [Downloadable!] (restricted)
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  6. 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.
  7. Christine De Mol & Domenico Giannone & Lucrezia Reichlin, 2006. "Forecasting using a large number of predictors - Is Bayesian regression a valid alternative to principal components?," Working Paper Series 700, European Central Bank. [Downloadable!]
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  8. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October. [Downloadable!] (restricted)
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  9. Rangan Gupta & Moses m. Sichei, 2006. "A Bvar Model For The South African Economy," South African Journal of Economics, Economic Society of South Africa, vol. 74(3), pages 391-409, 09. [Downloadable!] (restricted)
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  10. LeSage, James P, 1990. "A Comparison of the Forecasting Ability of ECM and VAR Models," The Review of Economics and Statistics, MIT Press, vol. 72(4), pages 664-71, November. [Downloadable!] (restricted)
  11. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November. [Downloadable!] (restricted)
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  12. 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. [Downloadable!]
  13. Cristadoro, Riccardo & Forni, Mario & Reichlin, Lucrezia & Veronese, Giovanni, 2005. "A Core Inflation Indicator for the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 539-60, June.
  14. Robert B. Litterman, 1984. "Above-average national growth in 1985 and 1986," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall. [Downloadable!]
  15. 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. [Downloadable!] (restricted)
  16. Rangan Gupta, 2007. "Bayesian Methods of Forecasting Inventory Investment in South Africa," Working Papers 200704, University of Pretoria, Department of Economics.
  17. 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. [Downloadable!] (restricted)
  18. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
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  19. Rangan Gupta, 2006. "FORECASTING THE SOUTH AFRICAN ECONOMY WITH VARs AND VECMs," South African Journal of Economics, Economic Society of South Africa, vol. 74(4), pages 611-628, December. [Downloadable!] (restricted)
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  20. 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. [Downloadable!] (restricted)
  21. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January. [Downloadable!] (restricted)
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