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Do money and financial variables help forecasting output in emerging European Economies?

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  • Petre Caraiani

Abstract

Whether including monetary aggregates and different financial variables into small scale BVAR models improves the accuracy of output forecasts is tested for three emerging European economies. Various specifications for the priors of the BVAR models are used. The results are found to vary with respect to prior specification, variables, as well as prediction horizon. The evidence is stronger when the forecasting accuracy is compared based on log predictive likelihood but weaker when the RMSEs are used. These results may constitute evidence against dismissing the monetary aggregates or financial variables as completely irrelevant. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Petre Caraiani, 2014. "Do money and financial variables help forecasting output in emerging European Economies?," Empirical Economics, Springer, vol. 46(2), pages 743-763, March.
    • Handle: RePEc:spr:empeco:v:46:y:2014:i:2:p:743-763
    DOI: 10.1007/s00181-013-0686-5
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    Cited by:

    1. Dimitris P. Louzis, 2014. "Macroeconomic and credit forecasts in a small economy during crisis: A large Bayesian VAR approach," Working Papers 184, Bank of Greece.
    2. Dimitrios P. Louzis, 2017. "Macroeconomic and credit forecasts during the Greek crisis using Bayesian VARs," Empirical Economics, Springer, vol. 53(2), pages 569-598, September.

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    More about this item

    Keywords

    Forecasting; Bayesian VARs; New Keynesian; Simulation; C11; C15; C32;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • 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

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