The distortionary effects of temporal aggregation on Granger causality

Gulasekaran Rajaguru; Tilak Abeysinghe

The distortionary effects of temporal aggregation on Granger causality

Gulasekaran Rajaguru
, Tilak Abeysinghe

Bond Business School

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Research › peer-review

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Abstract

Economists often have to use temporally aggregated data in causality tests. A number of theoretical studies have pointed out that temporal aggregation has distorting effects on causal inference. This paper provides a quantitative assessment of the magnitude of the distortions created by temporal aggregation by plugging in theoretical cross covariances into the limiting values of least
squares estimates. Some Monte Carlo results and an application are provided to assess the impact in small samples. It is observed that in general the most distorting causal inferences are likely at low levels of temporal aggregation. At high levels of aggregation, causal information concentrates in contemporaneous correlations. At present, a data-based approach is not available to establish
the direction of causality between contemporaneously correlated variables.

Original language	English
Title of host publication	Some recent developments in statistical theory and applications
Subtitle of host publication	Selected Proceedings of the International Conference on Recent Developments in Statistics, Econometrics and Forecasting, University of Allahabad, India, December 27-28, 2010
Editors	Kumar Kuldeep, Anoop Chaturvedi
Place of Publication	Boca Raton, Florida
Publisher	Brown Walker Press
Pages	38-56
Number of pages	19
ISBN (Print)	9781612335735
Publication status	Published - 2012
Event	2001 Econometric Society Australasian Meetings - Auckland, New Zealand Duration: 6 Jul 2001 → 9 Jul 2001

Conference

Conference	2001 Econometric Society Australasian Meetings
Country/Territory	New Zealand
City	Auckland
Period	6/07/01 → 9/07/01

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The distortionary effects of temporal aggregation on granger causalityAccepted author manuscript, 356 KB

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Rajaguru, G., & Abeysinghe, T. (2012). The distortionary effects of temporal aggregation on Granger causality. In K. Kuldeep, & A. Chaturvedi (Eds.), Some recent developments in statistical theory and applications: Selected Proceedings of the International Conference on Recent Developments in Statistics, Econometrics and Forecasting, University of Allahabad, India, December 27-28, 2010 (pp. 38-56). Brown Walker Press.

Rajaguru, Gulasekaran ; Abeysinghe, Tilak. / The distortionary effects of temporal aggregation on Granger causality. Some recent developments in statistical theory and applications: Selected Proceedings of the International Conference on Recent Developments in Statistics, Econometrics and Forecasting, University of Allahabad, India, December 27-28, 2010. editor / Kumar Kuldeep ; Anoop Chaturvedi. Boca Raton, Florida : Brown Walker Press, 2012. pp. 38-56

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Rajaguru, G & Abeysinghe, T 2012, The distortionary effects of temporal aggregation on Granger causality. in K Kuldeep & A Chaturvedi (eds), Some recent developments in statistical theory and applications: Selected Proceedings of the International Conference on Recent Developments in Statistics, Econometrics and Forecasting, University of Allahabad, India, December 27-28, 2010. Brown Walker Press, Boca Raton, Florida, pp. 38-56, 2001 Econometric Society Australasian Meetings, Auckland, New Zealand, 6/07/01.

The distortionary effects of temporal aggregation on Granger causality. / Rajaguru, Gulasekaran; Abeysinghe, Tilak.
Some recent developments in statistical theory and applications: Selected Proceedings of the International Conference on Recent Developments in Statistics, Econometrics and Forecasting, University of Allahabad, India, December 27-28, 2010. ed. / Kumar Kuldeep; Anoop Chaturvedi. Boca Raton, Florida: Brown Walker Press, 2012. p. 38-56.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Research › peer-review

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AU - Abeysinghe, Tilak

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AB - Economists often have to use temporally aggregated data in causality tests. A number of theoretical studies have pointed out that temporal aggregation has distorting effects on causal inference. This paper provides a quantitative assessment of the magnitude of the distortions created by temporal aggregation by plugging in theoretical cross covariances into the limiting values of least squares estimates. Some Monte Carlo results and an application are provided to assess the impact in small samples. It is observed that in general the most distorting causal inferences are likely at low levels of temporal aggregation. At high levels of aggregation, causal information concentrates in contemporaneous correlations. At present, a data-based approach is not available to establish the direction of causality between contemporaneously correlated variables.

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Rajaguru G, Abeysinghe T. The distortionary effects of temporal aggregation on Granger causality. In Kuldeep K, Chaturvedi A, editors, Some recent developments in statistical theory and applications: Selected Proceedings of the International Conference on Recent Developments in Statistics, Econometrics and Forecasting, University of Allahabad, India, December 27-28, 2010. Boca Raton, Florida: Brown Walker Press. 2012. p. 38-56

The distortionary effects of temporal aggregation on Granger causality

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Some recent developments in statistical theory and applications: Selected proceedings of the Interenational conference on recent developments in statistics, econometrics and forecasting, University of Allahabad, India, December 27-28, 2010

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The distortionary effects of temporal aggregation on Granger causality

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Some recent developments in statistical theory and applications: Selected proceedings of the Interenational conference on recent developments in statistics, econometrics and forecasting, University of Allahabad, India, December 27-28, 2010

Cite this