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Time-Series Analysis Econometrics pp 361-385 | Cite as Badi H. Baltagi (1) 1. Department of Economics, Texas A&M University, College Station, USA Chapter 286 Downloads
Abstract Recently, there has been an enormous amount of research in time-series econometrics, and many economics departments have required a time-series econometrics course in their graduate sequence. Obviously, one chapter on this topic will not do it justice. Therefore, this chapter will focus on some of the basic concepts needed for such a course. Section 14.2 defines what is meant by a stationary time-series, while sections 14.3 and 14.4 briefly review the Box-Jenkins and Vector Autoregression (VAR) methods for time-series analysis. Section 14.5 considers a random walk model and various tests for the existence of a unit root. Section 14.6 studies spurious regressions and trend stationary versus difference stationary models. Section 14.7 gives a simple explanation of the concept of cointegration and illustrates it with an economic example. Finally, section 14.8 looks at Autoregressive Conditionally Heteroskedastic (ARCH) time-series.
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About this chapter Cite this chapter as: Baltagi B.H. (2002) Time-Series Analysis. In: Econometrics. Springer, Berlin, Heidelberg DOI (Digital Object Identifier) https://doi.org/10.1007/978-3-662-04693-7_14 Publisher Name Springer, Berlin, Heidelberg Print ISBN 978-3-540-43501-3 Online ISBN 978-3-662-04693-7 eBook Packages Springer Book Archive About this book Reprints and Permissions
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