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Common Feature Analysis of Economic Time Series: An Overview and Recent Developments

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Abstract

In this paper we overview the literature on common features analysis of economic time series. Starting from the seminal contributions by Engle and Kozicki (1993) and Vahid and Engle (1993), we present and discuss the various notions that have been proposed to detect and model common cyclical features in macroeconometrics. In particular, we analyze in details the link between common cyclical features and the reduced-rank regression model. We also illustrate similarities and differences between the common features methodology and other popular types of multivariate time series modelling. Finally, we discuss some recent developments in this area, such as the implications of common features for univariate time series models and the analysis of common autocorrelation in medium-large dimensional systems.

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  • Marco Centoni & Gianluca Cubadda, 2015. "Common Feature Analysis of Economic Time Series: An Overview and Recent Developments," CEIS Research Paper 355, Tor Vergata University, CEIS, revised 05 Oct 2015.
  • Handle: RePEc:rtv:ceisrp:355
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    Cited by:

    1. Cubadda, Gianluca & Hecq, Alain & Telg, Sean, 2017. "Detecting Co-Movements in Noncausal Time Series," MPRA Paper 77254, University Library of Munich, Germany, revised 02 Mar 2017.

    More about this item

    Keywords

    Common features; common cycles; reduced-rank regression; canonical correlation analysis; vector autoregressive models; dynamic factor models; business cycles.;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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