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The Estimation of Continuous Time Models with Mixed Frequency Data

Marcus Chambers

Economics Discussion Papers from University of Essex, Department of Economics

Abstract: This paper derives exact representations for discrete time mixed frequency data generated by an underlying multivariate continuous time model. Allowance is made for different combinations of stock and flow variables as well as deterministic trends, and the variables themselves may be stationary or nonstationary (and possibly co-integrated). The resulting discrete time representations allow for the information contained in high frequency data to be utilised alongside the low frequency data in the estimation of the parameters of the continuous time model. Monte Carlo simulations explore the finite sample performance of the maximum likelihood estimator of the continuous time system parameters based on mixed frequency data, and a comparison with extant methods of using data only at the lowest frequency is provided. An empirical application demonstrates the methods developed in the paper and it concludes with a discussion of further ways in which the present analysis can be extended and refined.

Keywords: Continuous time; mixed frequency data; exact discrete time models; stock and flow variables. (search for similar items in EconPapers)
Date: 2016
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mst
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Journal Article: The estimation of continuous time models with mixed frequency data (2016) Downloads
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