Retrieval from mixed sampling frequency: generic identifiability in the unit root VAR

Philipp Gersing (), Leopold Sögner () and Manfred Deistler ()
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Philipp Gersing: Vienna University of Technology, Institute for Statistics and Mathematics, Vienna University of Economics and Business
Leopold Sögner: Institute for Advanced Studies
Manfred Deistler: Vienna University of Technology, Institute for Statistics and Mathematics, Vienna University of Economics and Business

Metrika: International Journal for Theoretical and Applied Statistics, 2025, vol. 88, issue 6, No 30, 1507 pages

Abstract: Abstract The “retrieval from mixed frequency sampling” approach based on blocking—described e.g., in Anderson et al. (Econom Theory 32:793–826, 2016a)—is concerned with retrieving an underlying high frequency model from mixed frequency observations. In this paper, we investigate parameter-identifiability in the Johansen (Likelihood-based inference in cointegrated vector autoregressive models. Oxford University Press, Oxford, 1995) vector error correction model for mixed frequency data. We prove that from the second moments of the blocked process after taking differences at lag N (N is the slow sampling rate), the parameters of the high frequency system are generically identified. We treat the stock and the flow case.

Keywords: Mixed frequency; REMIS; VAR; Cointegration; Vector error correction model; Identifiability; 62M10; 62P20 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s00184-025-00994-4

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