Inference on Transformed Stationary Time Series

Yuzo Hosoya and Takahiro Terasaka
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Yuzo Hosoya: Meisei University
Takahiro Terasaka: Otaru University of Commerce

No 11, Discussion Papers from Meisei University, School of Economics

Abstract: The paper is about an approach for parametric inference on instantaneously transformed stationary processes. The paper discusses the asymptotics of the Whittle estimator of the parameters involved and also provides the explicit expression of asymptotic covariance matrix which does not necessarily require the innovation Gaussianity assumption. As a specific instantaneous transformation, the paper introduces a new version of the Box-Cox transformation and investigates in detail the vector ARMA processes implemented by that transformation, proposing a computation-intensive procedure for parametric estimation and testing. As a computationally feasible test not relying upon the explicit analytic form of the asymptotic covariance matrix or on the information inequality, the paper proposes a Monte-Carlo Wald test, providing illustrative simulation and real-data examples.

Keywords: ARMA model; asymptotic theory; Box-Cox transformation; instantaneous transformation; Whittle likelihood (search for similar items in EconPapers)
JEL-codes: C12 C13 C15 C32 C51 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2008-02
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:mei:wpaper:11

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