Department of Economics and Business Economics

Consistent estimation of time-varying loadings in high-dimensional factor models

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • Jakob Guldbæk Mikkelsen, Danmarks Nationalbank
  • ,
  • Eric Hillebrand
  • Giovanni Urga, Cass Business School, Bergamo University

In this paper, we develop a two-step maximum likelihood estimator of time-varying loadings in high-dimensional factor models. We specify the loadings to evolve as stationary vector autoregressions (VAR) and show that consistent estimates of the loadings parameters can be obtained. In the first step, principal components are extracted from the data to form factor estimates. In the second step, the parameters of the loadings VARs are estimated as a set of linear regression models with time-varying coefficients. We document the finite-sample properties of the maximum likelihood estimator through an extensive simulation study and illustrate the empirical relevance of the time-varying loadings structure using a large quarterly dataset for the US economy.

Original languageEnglish
JournalJournal of Econometrics
Pages (from-to)535-562
Publication statusPublished - 2019

    Research areas

  • Consistent estimation, Factor models, Maximum likelihood estimation, Principal components, Time-varying loadings, Two-step estimation

See relations at Aarhus University Citationformats

ID: 138926060