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Modelling comovements of economic time series: a selective survey

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Author Info

  • Marco Centoni

    (LUMSA Università, Roma)

  • Gianluca Cubadda

    (Dipartimento SEFEMEQ, Università di Roma "Tor Vergara")

Abstract

Modelling comovements amongst multiple economic variables takes up a relevant part of the literature in time series econometrics. Comovement can be defined as “move together”, that is as movement that several series have in common. The pattern of the series could be of different nature, such as trend, cycles, seasonality, being the results of different driving forces. As a results, series that comove share some common features. Common trends, common cycles, common seasonality are terms that are often found in the literature, different in scope but all aimed at modeling common behavior of the series. However, modeling comovements is not only a statistical matter, since in many cases common features are predicted by economic theory, resulting from the optimizing behavior of economic agents.

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Bibliographic Info

Article provided by Department of Statistics, University of Bologna in its journal STATISTICA.

Volume (Year): 71 (2011)
Issue (Month): 2 ()
Pages: 267-294

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Handle: RePEc:bot:rivsta:v:71:y:2011:i:2:p:267-294

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References

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Cited by:
  1. Justyna Wróblewska, 2012. "Bayesian Analysis of Weak Form Polynomial Reduced Rank Structures in VEC Models," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 4(4), pages 253-267, December.

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