Monte Carlo SSA: Detecting irregular oscillations in the Presence of Colored Noise

Allen, Myles; Smith, Leonard A.

doi:10.1175/1520-0442(1996)009<3373:mcsdio>2.0.co;2

Cited by 457 publications

(401 citation statements)

References 40 publications

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“…6 vs. their dominant frequency f , as suggested by Allen and Smith [1996], rather than vs. their rank k, as originally proposed by Vautard and Ghil [1989]; see Appendix B. We note, in this spectrum, a maximum of two nearly equal eigenvalues at the usually reported mean business cycle length of 5-6 years.…”

Section: Cyclical Behaviorsupporting

confidence: 49%

“…Since macroeconomic variables typically exhibit greater variance at lower frequencies, it is quite possible, however, to obtain such a high-variance oscillatory pair even though no truly oscillatory behavior occurs. To ensure that the eigenvalue pair associated with f 0.2(year) −1 is not merely a result of the detrending procedure and thus subject to the Nelson and Kang [1981] criticism of spurious cycles, we submit our set of indicators to Monte Carlo SSA [Allen and Smith, 1996]; the latter approach provides a robust statistical significance test for such oscillations. Allen and Smith [1996] proposed to fit an autoregressive process of order one, AR(1), to a scalar, univariate time series, which replicates the variance and decorrelation time of the data but in the absence of oscillations.…”

Section: Cyclical Behaviormentioning

confidence: 99%

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Impacts of Natural Disasters on a Dynamic Economy

et al. 2012

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Abstract. This paper presents a modeling framework for macroeconomic growth dynamics; it is motivated by recent attempts to formulate and study "integrated models" of the coupling between natural and socio-economic phenomena. The challenge is to describe the interfaces between human activities and the functioning of the earth system. We examine the way that this interface works in the presence of endogenous business cycle dynamics, based on a non-equilibrium dynamic model. Recent findings about the macroeconomic response to natural disasters in such a nonequilibrium setting have shown a more severe response to natural disasters during expansions than during recessions. These findings raise questions about the assessment of climate change damages or natural disaster losses that are based purely on long-term growth models. In order to compare the theoretical findings with observational data, we analyze cyclic behavior in the U.S. economy, based on multivariate singular spectrum analysis. We analyze a total of nine aggregate indicators in a 52-year interval and demonstrate that the behavior of the U.S. economy changes significantly between intervals of growth and recession, with higher volatility during expansions.

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Section: Cyclical Behaviorsupporting

confidence: 49%

Section: Cyclical Behaviormentioning

confidence: 99%

Impacts of Natural Disasters on a Dynamic Economy

et al. 2012

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“…In this context the recent analysis of a multicentury coral record near New Caledonia might be of particular interest where only marginally significant evidence for an interdecadal peak could be found [Quinn et al, 1998]. A similar conclusion was obtained from analysis of a long temperature time series fi'om central England [Allen and Smith, 1996]. It may turn out that other cited significant decadal peaks [Dunbar et al, 1994] will also not meet this more stringent criteria.…”

Section: Discussionmentioning

confidence: 81%

Stochastically induced climate shift of El Niño‐Southern Oscillation

Flügel

Chang

1999

Geophysical Research Letters

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Abstract.Observational studies indicate that the characteristics of E1 Nifio-Southern Oscillation (ENSO) during the 1980s are noticeably different from those during the 1960s and 1970s. Here, we provide modeling evidence that stochastic processes can not only produce a shift in the persistence of sea-surface temperature (SST) but also causes changes in the predictability of ENSO. Based on this result, we suggest that climate shifts of ENSO, such as that occurred around 1976, could be induced by stochastic processes. Therefore, the stochastic mechanism should be taken as a null hypothesis for climate shifts against which competing mechanisms must be compared.

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“…Singular spectrum analysis is an extension of principal components for time series, ⇤ with applications in climatology (Allen and Smith, 1996), geophysics (Kondrashov and Ghil, 2006), and meteorology (Paegle et al, 2000); other applications include forecasting (Hassani et al, 2009). The business cycle indicator yielded through this method resembles band-pass filtered output, it is in line with the contraction periods dated by the NBER, and a real-time exercise indicates it possesses better revision performance than some competing filters.…”

Section: Introductionmentioning

confidence: 99%