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Determining the Structure of Dynamic Factor Models

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  • Sangmyung Ha

Abstract

We propose two procedures for determining the number of dynamic factors, extending Bai and Ng (2002) and Ahn and Horenstein (2013) to dynamic factor models where lagged factors may directly influence the observed variables. As an intermediate step, we develop a simple and computationally efficient alternating least squares algorithm that directly estimates the dynamic factors, rather than their static representations. By working with these direct estimates, our approach enables joint determination of the number of factors and the filter length. Our approach does not require the exact finite-order VAR specification maintained by Bai and Ng (2007) and Amengual and Watson (2007). We apply our procedures to estimate the number of primitive shocks in a large panel of U.S. macroeconomic time series.

Suggested Citation

  • Sangmyung Ha, 2026. "Determining the Structure of Dynamic Factor Models," Papers 2606.26142, arXiv.org, revised Aug 2026.
    • Handle: RePEc:arx:papers:2606.26142
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    References listed on IDEAS

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    3. Michael W. McCracken & Serena Ng, 2016. "FRED-MD: A Monthly Database for Macroeconomic Research," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 574-589, October.
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