Trend, Seasonality and Economic Time Series:the Nonstationary Errors-in-variables Models

Naoto Kunitomo and Seisho Sato
Additional contact information
Naoto Kunitomo: Faculty of Economics, The University of Tokyo
Seisho Sato: Faculty of Economics, The University of Tokyo

No CIRJE-F-977, CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo

Abstract: The use of seasonally adjusted (official) data may have statistical problem because it is a common practice to use X-12-ARIMA in the official seasonal adjustment , which adopts the univariate ARIMA time series modeling with some renements. Instead of using the seasonally adjusted data, for estimating the structural parameters and relationships among non-stationary economic time series with seasonality and noise, we propose a new method called the Separating Information Maximum Likelihood (SIML) estimation. We show that the SIML estimation can identify the nonstationary trend, the seasonality and the noise components, which have been observed in many macro-economic time series, and recover the structural parameters and relationships among the non-stationary trends with seasonality. The SIML estimation is consistent and it has the asymptotic normality when the sample size is large. Based on simulations, we nd that the SIML estimator has reasonable nite sample properties and thus it would be useful for practice. --

Pages: 50pages
Date: 2015-06
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.cirje.e.u-tokyo.ac.jp/research/dp/2015/2015cf977.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:tky:fseres:2015cf977

Access Statistics for this paper

More papers in CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo Contact information at EDIRC.
Bibliographic data for series maintained by CIRJE administrative office ().