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Forecasting with FAVAR: macroeconomic versus financial factors

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  • Alessia Paccagnini

    (University College Dublin, School of Economics)

Abstract

We assess the predictive power of macroeconomic and financial latent factors on the key variables for the US economy before and after the recent Great Recession. We implement a forecasting horserace among Factor Augmented VAR (FAVAR), Classical, and Bayesian VAR models. FAVAR models outperform others. Focusing only on macroeconomic or on nancial latent factors,we nd how the nancial variables have not a driver role in forecasting the US economy including the Great Recession.

Suggested Citation

  • Alessia Paccagnini, 2017. "Forecasting with FAVAR: macroeconomic versus financial factors," NBP Working Papers 256, Narodowy Bank Polski.
    • Handle: RePEc:nbp:nbpmis:256
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    References listed on IDEAS

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    2. Behera, Harendra & Gunadi, Iman & Rath, Badri Narayan, 2023. "COVID-19 uncertainty, financial markets and monetary policy effects in case of two emerging Asian countries," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 173-189.

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    More about this item

    Keywords

    Factor Models; Factor Augmented VAR; VAR models; Bayesian VAR models; Forecasting;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

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