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Forecasting economic activity for Estonia : The application of dynamic principal component analyses

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  • Christian Schulz

Abstract

In this paper, the dynamic common factors method of Forni et al. (2000) is applied to a large panel of economic time series on the Estonian economy. In order to improve forecasting of economic activity in Estonia, we derive a leading indicator composed of the common components of twelve series, which were identified as leading. The resulting indicator performs better than two other indicators, which are based on a small-scale state-space model used by Stock and Watson (1991) and a large-scale static principal components model used by Stock and Watson (2002), respectively. It also clearly outperforms the naive benchmark in both in-sample and out-of-sample forecast comparisons

Suggested Citation

  • Christian Schulz, 2008. "Forecasting economic activity for Estonia : The application of dynamic principal component analyses," Bank of Estonia Working Papers 2008-02, Bank of Estonia, revised 30 Oct 2008.
    • Handle: RePEc:eea:boewps:wp2008-2
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Estonia; forecasting; turning points; dynamic factor models; dynamic principal components; forecast performance;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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