Recovering stars in macroeconomics

Daniel Buncic, Adrian Pagan and Tim Robinson

Melbourne Institute Working Paper Series from Melbourne Institute of Applied Economic and Social Research, The University of Melbourne

Abstract: Many key macroeconomic variables such as the NAIRU, potential GDP, and the neutral real rate of interest—which are needed for policy analysis—are latent. Collectively, these latent variables are known as ‘stars’ and are typically estimated using the Kalman filter or smoother from models that can be expressed in State Space form. When these models contain more shocks than observed variables, they are ‘short’, and potentially create issues in recovering the star variable of interest from the observed data. Recovery issues can occur when the model is correctly specified and its parameters are known. In this paper, we summarize the literature on shock recovery and demonstrate its implications for estimating stars in a number of widely used models in policy analysis. The ability of many popular and recent models to recover stars is shown to be limited. We suggest ways this can be addressed.

Keywords: Kalman filter and smoother; State Space models; shock recovery; short systems; natural rate of interest; macroeconomic policy; Beveridge-Nelson decomposition (search for similar items in EconPapers)
JEL-codes: C22 C32 E58 (search for similar items in EconPapers)
Pages: 48pp
Date: 2023-09
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https://melbourneinstitute.unimelb.edu.au/__data/a ... 751740/wp2023n12.pdf (application/pdf)

Related works:
Working Paper: Recovering Stars in Macroeconomics (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:iae:iaewps:wp2023n12

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