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Applications of Computer Aided Time Series Modeling (Paperback, Softcover reprint of the original 1st ed. 1997)
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Applications of Computer Aided Time Series Modeling (Paperback, Softcover reprint of the original 1st ed. 1997)
Series: Lecture Notes in Statistics, 119
Expected to ship within 10 - 15 working days
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This book consists of three parts: Part One is composed of two
introductory chapters. The first chapter provides an instrumental
varible interpretation of the state space time series algorithm
originally proposed by Aoki (1983), and gives an introductory
account for incorporating exogenous signals in state space models.
The second chapter, by Havenner, gives practical guidance in apply
ing this algorithm by one of the most experienced practitioners of
the method. Havenner begins by summarizing six reasons state space
methods are advanta geous, and then walks the reader through
construction and evaluation of a state space model for four monthly
macroeconomic series: industrial production in dex, consumer price
index, six month commercial paper rate, and money stock (Ml). To
single out one of the several important insights in modeling that
he shares with the reader, he discusses in Section 2ii the effects
of sampling er rors and model misspecification on successful
modeling efforts. He argues that model misspecification is an
important amplifier of the effects of sampling error that may cause
symplectic matrices to have complex unit roots, a theoretical
impossibility. Correct model specifications increase efficiency of
estimators and often eliminate this finite sample problem. This is
an important insight into the positive realness of covariance
matrices; positivity has been emphasized by system engineers to the
exclusion of other methods of reducing sampling error and
alleviating what is simply a finite sample problem. The second and
third parts collect papers that describe specific applications."
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