Random-Coefficient periodic autoregression

Philip Hans Franses and Richard Paap

No EI 2005-34, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute

Abstract: We propose a new periodic autoregressive model for seasonally observed time series, where the number of seasons can potentially be very large. The main novelty is that we collect the periodic parameters in a second-level stochastic model. This leads to a random-coefficient periodic autoregression with a substantial reduction in the number of parameters to be estimated. We discuss representation, estimation, and inference. An illustration for monthly growth rates of US industrial production shows the merits of the new model specification.

Keywords: periodic autoregression; random coefficient model (search for similar items in EconPapers)
JEL-codes: C22 C51 (search for similar items in EconPapers)
Date: 2005-01-01
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Citations: View citations in EconPapers (2)

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Journal Article: Random‐coefficient periodic autoregressions (2011)
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