Hyper-spherical and Elliptical Stochastic Cycles
A univariate first order stochastic cycle can be represented as an element of a bivariate first order vector autoregressive process, or VAR(1), where the transition matrix is associated with a Givens rotation. From the geometrical viewpoint, the kernel of the cyclical dynamics is described by a clockwise rotation along a circle in the plane. The reduced form of the cycle is either ARMA(2,1), with complex roots, or AR(1), when the rotation angle equals 2k\pi or (2k + 1)\pi; k = 0; 1;... This paper generalizes this representation in two directions. According to the first, the cyclical dynamics originate from the motion of a point along an ellipse. The reduced form is also ARMA(2,1), but the model can account for certain types of asymmetries. The second deals with the multivariate case: the cyclical dynamics result from the projection along one of the coordinate axis of a point moving in Rn along an hyper-sphere. This is described by a VAR(1) process whose transition matrix is obtained by a sequence of n-dimensional Givens rotations. The reduced form of an element of the system is shown to be ARMA(n, n - 1). The properties of the resulting models are analyzed in the frequency domain, and we show that this generalization can account for a multimodal spectral density. The illustrations show that the proposed generalizations can be fitted successfully to some well known case studies of the econometric and time series literature. For instance, the elliptical model provides a parsimonious but effective representation of the mink-muskrat interaction. The hyperspherical model provides an interesting re-interpretation of the cycle in US Gross Domestic Product quarterly growth and the cycle in the Fortaleza rainfall series.
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- James Morley & Charles Nelson & Eric Zivot, 2003.
"Why are Beveridge-Nelson and Unobserved-component decompositions of GDP so Different?,"
UWEC-2002-18-P, University of Washington, Department of Economics.
- James Morley & Charles Nelson & Eric Zivot, 2002. "Why Are Beveridge-Nelson and Unobserved-Component Decompositions of GDP So Different?," Working Papers UWEC-2002-01, University of Washington, Department of Economics.
- James C. Morley & Charles Nelson & Eric Zivot, 2000. "Why Are Beveridge-Nelson and Unobserved-Component Decompositions of GDP So Different?," Discussion Papers in Economics at the University of Washington 0013, Department of Economics at the University of Washington.
- James C. Morley & Charles Nelson & Eric Zivot, 2000. "Why Are Beveridge-Nelson and Unobserved-Component Decompositions of GDP So Different?," Working Papers 0013, University of Washington, Department of Economics.
- Charles Nelson & Eric Zivot, 2000. "Why are Beveridge-Nelson and Unobserved-Component Decompositions of GDP so Different?," Econometric Society World Congress 2000 Contributed Papers 0692, Econometric Society.
- Wenyang Zhang & Qiwei Yao & Howell Tong & Nils Chr Stenseth, 2003. "Smoothing for spatiotemporal models and its application to modeling Muskrat-Mink interaction," LSE Research Online Documents on Economics 5832, London School of Economics and Political Science, LSE Library.
- ZELLNER, Arnold & PALM, Franz, .
"Time series analysis and simultaneous equation econometric models,"
CORE Discussion Papers RP
-173, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Zellner, Arnold & Palm, Franz, 1974. "Time series analysis and simultaneous equation econometric models," Journal of Econometrics, Elsevier, vol. 2(1), pages 17-54, May.
- Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-27, June.
- Andrew C. Harvey & Thomas M. Trimbur, 2003.
"General Model-Based Filters for Extracting Cycles and Trends in Economic Time Series,"
The Review of Economics and Statistics,
MIT Press, vol. 85(2), pages 244-255, May.
- Harvey, A.C. & Trimbur, T.M., 2001. "General Model-based Filters for Extracting Cycles and Trends in Economic Time Series," Cambridge Working Papers in Economics 0113, Faculty of Economics, University of Cambridge.
- James C. Morley & Charles R. Nelson & Eric Zivot, 2003.
"Why Are the Beveridge-Nelson and Unobserved-Components Decompositions of GDP So Different?,"
The Review of Economics and Statistics,
MIT Press, vol. 85(2), pages 235-243, May.
- Tom Doan, . "RATS programs to replicate Morley-Nelson-Zivot state space decomposition," Statistical Software Components RTZ00115, Boston College Department of Economics.
- Durbin, James & Koopman, Siem Jan, 2001.
"Time Series Analysis by State Space Methods,"
Oxford University Press, number 9780198523543, March.
- Tom Doan, . "SEASONALDLM: RATS procedure to create the matrices for the seasonal component of a DLM," Statistical Software Components RTS00251, Boston College Department of Economics.
- M. Ruth & K. Donaghy & P. Kirshen, 2006. "Introduction," Chapters, in: Regional Climate Change and Variability, chapter 1 Edward Elgar.
- Thomas M. Trimbur, 2006. "Properties of higher order stochastic cycles," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(1), pages 1-17, 01.
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