An alternative solution to the Autoregressivity Paradox in time series analysis
AbstractThis note concerns with the marginal models associated with a given vector autoregressive model. In particular, it is shown that a reduction in the orders of the univariate ARMA marginal models can be determined by the presence of variables integrated with different orders. The concepts and methods of the paper are illustrated via an empirical investigation of the low-frequency properties of hours worked in the US.
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Bibliographic InfoArticle provided by Elsevier in its journal Economic Modelling.
Volume (Year): 28 (2011)
Issue (Month): 3 (May)
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Web page: http://www.elsevier.com/locate/inca/30411
VAR models ARIMA models Final equations;
Other versions of this item:
- Gianluca Cubadda & Umberto Triacca, 2011. "An Alternative Solution to the Autoregressivity Paradox in Time Series Analysis," CEIS Research Paper 184, Tor Vergata University, CEIS, revised 24 Jan 2011.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
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