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

84 Downloads (Pure)

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

Access to Document

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

Cite this

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

@inbook{04d25e5c8a2f437fa43e98aab4d24f9d,

title = "The distortionary effects of temporal aggregation on Granger causality",

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 leastsquares 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 establishthe direction of causality between contemporaneously correlated variables.",

author = "Gulasekaran Rajaguru and Tilak Abeysinghe",

year = "2012",

language = "English",

isbn = "9781612335735",

pages = "38--56",

editor = "Kumar Kuldeep and Anoop Chaturvedi",

booktitle = "Some recent developments in statistical theory and applications",

publisher = "Brown Walker Press",

note = "2001 Econometric Society Australasian Meetings ; Conference date: 06-07-2001 Through 09-07-2001",

}

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

TY - CHAP

T1 - The distortionary effects of temporal aggregation on Granger causality

AU - Rajaguru, Gulasekaran

AU - Abeysinghe, Tilak

PY - 2012

Y1 - 2012

N2 - 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 leastsquares 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 establishthe direction of causality between contemporaneously correlated variables.

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 leastsquares 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 establishthe direction of causality between contemporaneously correlated variables.

UR - http://www.brownwalker.com/book/161233573X

M3 - Chapter

SN - 9781612335735

SP - 38

EP - 56

BT - Some recent developments in statistical theory and applications

A2 - Kuldeep, Kumar

A2 - Chaturvedi, Anoop

PB - Brown Walker Press

CY - Boca Raton, Florida

T2 - 2001 Econometric Society Australasian Meetings

Y2 - 6 July 2001 through 9 July 2001

ER -

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

Abstract

Conference

Access to Document

Other files and links

Fingerprint

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

The distortionary effects of temporal aggregation on Granger causality

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Related Research Outputs

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