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Forecasting with Factor-augmented Error Correction

Author

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  • Anindya Banerjee
  • Massimiliano Marcellino
  • Igor Masten

Abstract

As a generalization of the factor-augmented VAR (FAVAR) and of the Error Correction Model (ECM), Banerjee and Marcellino (2009) introduced the Factor- augmented Error Correction Model (FECM). The FECM combines error-correction, cointegration and dynamic factor models, and has several conceptual advantages over standard ECM and FAVAR models. In particular, it uses a larger dataset compared to the ECM and incorporates the long-run information lacking from the FAVAR because of the latter's speci cation in dfferences. In this paper we examine the forecasting performance of the FECM by means of an analytical example, Monte Carlo simula- tions and several empirical applications. We show that relative to the FAVAR, FECM generally offers a higher forecasting precision and in general marks a very useful step forward for forecasting with large datasets.

Suggested Citation

  • Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2010. "Forecasting with Factor-augmented Error Correction," Discussion Papers 09-06r, Department of Economics, University of Birmingham.
  • Handle: RePEc:bir:birmec:09-06r
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    Cited by:

    1. Rangan Gupta & Alain Kabundi & Stephen Miller & Josine Uwilingiye, 2014. "Using large data sets to forecast sectoral employment," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 229-264, June.
    2. Qin, Duo & He, Xinhua, 2012. "Modelling the impact of aggregate financial shocks external to the Chinese economy," BOFIT Discussion Papers 25/2012, Bank of Finland, Institute for Economies in Transition.

    More about this item

    Keywords

    Forecasting with Factor-augmented Error Correction;

    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
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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