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Short-term Forecasting Methods Based on the LEI Approach: The Case of the Czech Republic

Author

Listed:
  • Vojtech Benda
  • Lubos Ruzicka

Abstract

This paper is aimed at developing short-term forecasting methods based on the LEI (leading economic indicators) approach. We use a set of econometric models (PCA, SURE) that provide estimates of GDP growth for the Czech economy for a co-incident quarter and a few quarters ahead. These models exploit monthly or quarterly indicators such as business surveys, financial or labour market indicators, monetary aggregates, interest rates and spreads, etc. that become available before the release of data on GDP growth itself. Our tests show that the LEIs provide relatively accurate forecasts of GDP fluctuations in the short run.

Suggested Citation

  • Vojtech Benda & Lubos Ruzicka, 2007. "Short-term Forecasting Methods Based on the LEI Approach: The Case of the Czech Republic," Research and Policy Notes 2007/01, Czech National Bank.
    • Handle: RePEc:cnb:rpnrpn:2007/01
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    File URL: https://www.cnb.cz/export/sites/cnb/en/economic-research/.galleries/research_publications/irpn/download/rpn_1_2007.pdf
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    References listed on IDEAS

    as
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    3. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
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    7. Victor Zarnowitz, 1973. "A Review of Cyclical Indicators for the United States: Preliminary Results," NBER Working Papers 0006, National Bureau of Economic Research, Inc.
    8. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    9. Peter Grasmann & Filip Keereman, 2001. "An indicator-based short-term forecast for quarterly GDP in the euro area," European Economy - Economic Papers 2008 - 2015 154, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    10. Neftici, Salih N., 1982. "Optimal prediction of cyclical downturns," Journal of Economic Dynamics and Control, Elsevier, vol. 4(1), pages 225-241, November.
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    12. Christian Schumacher, 2007. "Forecasting German GDP using alternative factor models based on large datasets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 271-302.
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    Citations

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    Cited by:

    1. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
    2. Katerina Arnostova & David Havrlant & Luboš Rùžièka & Peter Tóth, 2011. "Short-Term Forecasting of Czech Quarterly GDP Using Monthly Indicators," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(6), pages 566-583, December.

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    More about this item

    Keywords

    Leading indicators; principal component analysis; seemingly unrelated regression estimate.;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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