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Latent variables analysis in structural models: A New decomposition of the kalman smoother

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  • Chung, Hess
  • Fuentes-Albero, Cristina
  • Paustian, Matthias
  • Pfajfar, Damjan

Abstract

Standard latent variable analysis in structural state space models decomposes latent variables into contributions of structural shocks (shock decomposition), or into contributions of the observable variables (data decomposition). We propose to link the shock decomposition of the latent variables and the data decomposition of the structural shocks in what we call the double decomposition. This decomposition allows us to better gauge the influence of data on latent variables by taking into account the transmission mechanism of each type of shock. We show the usefulness of the double decomposition by analyzing the role of observable variables in estimating the output gap in two models and by studying the role of news in revisions of the output gap.

Suggested Citation

  • Chung, Hess & Fuentes-Albero, Cristina & Paustian, Matthias & Pfajfar, Damjan, 2021. "Latent variables analysis in structural models: A New decomposition of the kalman smoother," Journal of Economic Dynamics and Control, Elsevier, vol. 125(C).
    • Handle: RePEc:eee:dyncon:v:125:y:2021:i:c:s0165188921000324
    DOI: 10.1016/j.jedc.2021.104097
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    1. Marco Del Negro & Marc P. Giannoni & Frank Schorfheide, 2015. "Inflation in the Great Recession and New Keynesian Models," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 168-196, January.
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    4. Andrle, Michal, 2012. "Understanding DSGE Filters in Forecasting and Policy Analysis," Dynare Working Papers 16, CEPREMAP.
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    More about this item

    Keywords

    Kalman smoother; Latent variables; Shock decomposition; Data decomposition; Double decomposition;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: 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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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