Temporal aggregation, causality distortions and a sign rule

Tilak Abeysinghe () and Gulasekaran Rajaguru

No 73, Econometric Society 2004 Australasian Meetings from Econometric Society

Abstract: Temporally aggregated data is a bane for Granger causality tests. The same set of variables may lead to contradictory causality inferences at different levels of temporal aggregation. Obtaining temporally disaggregated data series is impractical in many situations. Since cointegration is invariant to temporal aggregation and implies Granger causality this paper proposes a sign rule to establish the direction of causality. Temporal aggregation leads to a distortion of the sign of the adjustment coefficients of an error correction model. The sign rule works better with highly temporally aggregated data. The practitioners, therefore, may revert to using annual data for Granger causality testing instead of looking for quarterly, monthly or weekly data. The method is illustrated through three applications.

Keywords: Granger causality test; cointegration; ecm; sign rule (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Date: 2004-08-11

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Working Paper: Temporal Aggregation, Causality Distortions, and a Sign Rule (2003)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Access Statistics for this paper

More papers in Econometric Society 2004 Australasian Meetings from Econometric Society
Contact information at EDIRC.
Series data maintained by Christopher F. Baum ().