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Dynamic Factor Models in Forecasting Latvia's Gross Domestic Product

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  • Viktors Ajevskis
  • Gundars Davidsons

Abstract

The study aims at evaluating how useful the application of models using large panels of data in forecasting Latvia's GDP is. Two factor models have been used: the Stock-Watson factor model and the generalised dynamic factor model. The forecast findings by the two models have been compared with the results obtained by the benchmark autoregressive model. The results suggest that compared with simpler autoregressive models both the Stock-Watson factor model and the generalised dynamic factor model ensure forecast improvement, which, however, has not been statistically significant if statistical tests are used.

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Bibliographic Info

Paper provided by Latvijas Banka in its series Working Papers with number 2008/02.

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Date of creation: 29 Apr 2008
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Handle: RePEc:ltv:wpaper:200802

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Keywords: forecasting; factor models; large cross section;

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References

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  4. Massimiliano Marcellino & James H. Stock & Mark W. Watson, . "Macroeconomic Forecasting in the Euro Area: Country Specific versus Area-Wide Information," Working Papers 201, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  5. D’Agostino, Antonello & Giannone, Domenico, 2006. "Comparing alternative predictors based on large-panel factor models," Working Paper Series 0680, European Central Bank.
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  18. Christophe Van Nieuwenhuyze, 2006. "A generalised dynamic factor model for the Belgian economy - Useful business cycle indicators and GDP growth forecasts," Working Paper Research 80, National Bank of Belgium.
  19. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
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Citations

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Cited by:
  1. Boriss Siliverstovs & Konstantin A. Kholodilin, 2010. "Assessing the Real-Time Informational Content of Macroeconomic Data Releases for Now-/Forecasting GDP: Evidence for Switzerland," Discussion Papers of DIW Berlin 970, DIW Berlin, German Institute for Economic Research.
  2. Konstantins Benkovskis, 2008. "Short-Term Forecasts of Latvia's Real Gross Domestic Product Growth Using Monthly Indicators," Working Papers 2008/05, Latvijas Banka.
  3. Konstantins Benkovskis, 2010. "LATCOIN: Determining Medium to Long-Run Tendencies of Economic Growth in Latvia in Real Time," Working Papers 2010/01, Latvijas Banka.
  4. Buss, Ginters, 2010. "A note on GDP now-/forecasting with dynamic versus static factor models along a business cycle," MPRA Paper 22147, University Library of Munich, Germany.
  5. Bušs, Ginters, 2009. "Comparing forecasts of Latvia's GDP using simple seasonal ARIMA models and direct versus indirect approach," MPRA Paper 16684, University Library of Munich, Germany.

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