Retrieval from Mixed Sampling Frequency: Generic Identifiability in the Unit Root VAR

TL;DR

This paper establishes that in mixed sampling frequency vector error correction models, the parameters of the high frequency system can be generically identified from second moments of the differenced blocked process, advancing understanding of retrieval methods.

Contribution

It proves generic identifiability of high frequency parameters in mixed frequency VAR models using second moments, extending previous retrieval approaches.

Findings

Parameters are identifiable from second moments after differencing at lag N.

Results apply to stock, flow, and deterministic cases.

Advances retrieval of high frequency models from mixed frequency data.

Abstract

The "REtrieval from MIxed Sampling" (REMIS) approach based on blocking developed in Anderson et al. (2016a) is concerned with retrieving an underlying high frequency model from mixed frequency observations. In this paper we investigate parameter-identifiability in the Johansen (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 as well as deterministic terms.