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Choosing variables in macroeconomic modelling

Author

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  • Marek Jarociński
  • Bartosz Maćkowiak

Abstract

An important challenge when formulating an econometric time series model in a data-rich environment is the question of how to choose the variables to put in the model. Recent research has developed a simple methodology to choose variables in vector autoregressions. Applying this methodology to euro area data shows that a modeller interested in tracking the price level, real GDP and the short-term nominal interest rate should pay close attention to survey-based indicators of economic sentiment and activity, changes in inventories and interest rate spreads. JEL Classification: C32, C52, E32

Suggested Citation

  • Marek Jarociński & Bartosz Maćkowiak, 2014. "Choosing variables in macroeconomic modelling," Research Bulletin, European Central Bank, vol. 20, pages 5-8.
  • Handle: RePEc:ecb:ecbrbu:2014:0020:2
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    References listed on IDEAS

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    More about this item

    Keywords

    vector autoregression; Granger-causal-priority; Granger-noncausality; Bayesian model choice;
    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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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