Spurious regressions with stationary series

Granger, Clive W. J.; Hyung, Namwon; Jeon, Yongil

doi:10.1080/00036840121734

Cited by 131 publications

(83 citation statements)

References 7 publications

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“…Some precautionary remarks on the danger of spurious relations between climatic indices and ecological variables are in order. It is well known that strong temporal dependence in two independent time-series may induce spurious relations between the two series according to standard inference in an ordinary regression model (see Granger et al (2001) and the references therein). This problem is further exacerbated in the setting of nonlinear models.…”

Section: The Climate-local Weather Interfacementioning

confidence: 99%

Review article. Studying climate effects on ecology through the use of climate indices: the North Atlantic Oscillation, El Niño Southern Oscillation and beyond

Stenseth

Ottersen

Hurrell

et al. 2003

Proc. R. Soc. Lond. B

693

695

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Whereas the El Niñ o Southern Oscillation (ENSO) affects weather and climate variability worldwide, the North Atlantic Oscillation (NAO) represents the dominant climate pattern in the North Atlantic region. Both climate systems have been demonstrated to considerably influence ecological processes. Several other large-scale climate patterns also exist. Although less well known outside the field of climatology, these patterns are also likely to be of ecological interest. We provide an overview of these climate patterns within the context of the ecological effects of climate variability. The application of climate indices by definition reduces complex space and time variability into simple measures, 'packages of weather'. The disadvantages of using global climate indices are all related to the fact that another level of problems are added to the ecology-climate interface, namely the link between global climate indices and local climate. We identify issues related to: (i) spatial variation; (ii) seasonality; (iii) non-stationarity; (iv) nonlinearity; and (v) lack of correlation in the relationship between global and local climate. The main advantages of using global climate indices are: (i) biological effects may be related more strongly to global indices than to any single local climate variable; (ii) it helps to avoid problems of model selection; (iii) it opens the possibility for ecologists to make predictions; and (iv) they are typically readily available on Internet.

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Section: The Climate-local Weather Interfacementioning

confidence: 99%

Review article. Studying climate effects on ecology through the use of climate indices: the North Atlantic Oscillation, El Niño Southern Oscillation and beyond

Stenseth

Ottersen

Hurrell

et al. 2003

Proc. R. Soc. Lond. B

693

695

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“…Granger et al, 2001). Therefore we used Monte Carlo simulations to calculate 1% critical values for t-tests that account for the observed persistence in the series.…”

Section: Empirical Frameworkmentioning

confidence: 99%

On the time-varying relationship between EMU sovereign spreads and their determinants

et al. 2015

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We use a dynamic multipath general-to-specific algorithm to capture structural instability in the link between euro area sovereign bond yield spreads against Germany and their underlying determinants over the period January 1999 -August 2011. We offer new evidence suggesting a significant heterogeneity across countries, both in terms of the risk factors determining spreads over time as well as in terms of the magnitude of their impact on spreads. Our findings suggest that the relationship between euro area sovereign risk and the underlying fundamentals is strongly timevarying, turning from inactive to active since the onset of the global financial crisis and further intensifying during the sovereign debt crisis. As a general rule, the set of financial and macro spreads' determinants in the euro area is rather unstable but generally becomes richer and stronger in significance as the crisis evolves.JEL: C22, C52, E43, E62, G12.

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“…Regression between time series is known to produce spurious results in the following settings: trending or auto correlated time series (Granger and Newbold 1974), I(1) processes without drift (Phillips 1986), I(1) processes with further stationary regressors (Hassler 1996), stationary AR processes (Granger, Hyung and Jeon 2001), random walks with and without drift for fixed effects panel models (Entorf 1997), time-varying means (Hassler 2003), and stationary processes around linear trends (Kim, Lee and Newbold 2004), as well as in fixed effects (or first differences) estimations with weak variation in the time series (Choi 2011). It seems unlikely that none of these situations occurred in the original analysis, and thus there may be more sources for spurious results than just the ratio problem.…”

Section: º¿ ùø E95 × Aeóø èóôùð ø óòmentioning

confidence: 99%

The Social Costs of Gun Ownership: Spurious Regression and Unfounded Public Policy Advocacy

Westphal

2013

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. This version: July 8, 2013 Terms of use: Documents in AbstractIn 2006, a study, published in the Journal of Public Economics, employing a panel regression of 200 U.S. counties across 20 years, found a significant elasticity of homicides with respect to firearms ownership. Based on this finding the authors made the public policy recommendation of taxing gun ownership. However that study fell prey to the ratio fallacy, a trap known since 1896. All the "explanatory power" (goodness-of-fit-wise and significance-wise) of the original analysis was due to regional and intertemporal differences and population being explained by itself. When the ratio fallacy is accounted for, all authors' results can no longer be found. This is illustrated in this paper using a balanced panel from the data for 1980 to 2004. My findings are robust to (i) alternative specifications not subject to the ratio problem, (ii) using only data from 1980 to 1999 as in the original paper, (iii) using an unbalanced panel for 1980 to either 1999 or 2004, (iv) applying weighting as done by the original authors and (v) using data aggregated at the state level.JEL Classifications: C51; H21; I18; K42 Keywords: Gun Ownership; Social Costs; Ratio Fallacy; Spurious Regression a Thanks to participants of a Brown Bag Seminar held at Philipps-University Marburg and to participants of a Seminar on replication studies held at University of Göttingen both in which some good thoughts on the problem were had. Thanks to Bernd Hayo for contributing the 'moving averages' solution for the noisy proxy mentioned in section 7 and to Florian Neumeier for contributing the growth model used in section 6.4.

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Spurious regressions with stationary series

Cited by 131 publications

References 7 publications

Review article. Studying climate effects on ecology through the use of climate indices: the North Atlantic Oscillation, El Niño Southern Oscillation and beyond

Review article. Studying climate effects on ecology through the use of climate indices: the North Atlantic Oscillation, El Niño Southern Oscillation and beyond

On the time-varying relationship between EMU sovereign spreads and their determinants

The Social Costs of Gun Ownership: Spurious Regression and Unfounded Public Policy Advocacy

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