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Discovering Stars: Problems in Recovering Latent Variables from Models

Author

Listed:
  • Daniel Buncic
  • Adrian Pagan

Abstract

There exist many latent variables in macroeconometrics that are commonly referred to as "stars". Examples of such "stars" are the NAIRU, potential GDP, and the neutral real rate of interest. Because these "stars" are defined as latent variables, they are estimated using the Kalman filter and/or smoother from models that can be expressed in State Space Form. When there are more shocks than observables in the State Space Form representation of such models, issues arise related to the recoverability of these "stars" from the data. Recoverability is problematic in this setting even if the assumed model for the data is correct and all model parameters are known. In this paper, we examine recoverability in a range of popular models and show that many of these "stars" cannot be recovered.

Suggested Citation

  • Daniel Buncic & Adrian Pagan, 2022. "Discovering Stars: Problems in Recovering Latent Variables from Models," CAMA Working Papers 2022-52, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Handle: RePEc:een:camaaa:2022-52
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    File URL: https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2022-09/52_2022_buncic_pagan.pdf
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    Cited by:

    1. Buncic, Daniel, 2024. "Econometric issues in the estimation of the natural rate of interest," Economic Modelling, Elsevier, vol. 132(C).
    2. Ye Lu & Adrian Pagan, 2023. "To Boost or Not to Boost? That is the Question," CAMA Working Papers 2023-12, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    More about this item

    Keywords

    Recoverability; excess shocks; latent variables; neutral rates; Kalman Filter;
    All these keywords.

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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