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The Multivariate Linear Prediction Problem: Model-Based and Direct Filtering Solutions

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  • McElroy, Tucker S.
  • Wildi, Marc

Abstract

Numerous contexts in macroeconomics, finance, and quality control require real-time estimation of trends, turning points, and anomalies. The real-time signal extraction problem is formulated as a multivariate linear prediction problem, the optimal solution is presented in terms of a known model, and multivariate direct filter analysis is proposed to address the more typical situation where the process’ model is unknown. It is shown how general constraints – such as level and time shift constraints – can be imposed on a concurrent filter in order to guarantee that real-time estimates have requisite properties. The methodology is applied to petroleum and construction data.

Suggested Citation

  • McElroy, Tucker S. & Wildi, Marc, 2020. "The Multivariate Linear Prediction Problem: Model-Based and Direct Filtering Solutions," Econometrics and Statistics, Elsevier, vol. 14(C), pages 112-130.
    • Handle: RePEc:eee:ecosta:v:14:y:2020:i:c:p:112-130
    DOI: 10.1016/j.ecosta.2019.12.004
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