Time aggregation and causality tests: results from a monte carlo experiment
AbstractThis paper examines the importance of time aggregation in causality testing. We find that temporal aggregates are between two and ten times more unlikely to detect a true causal relationship than are systematic sampled aggregates over short aggregation spans.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Economics Letters.
Volume (Year): 2 (1995)
Issue (Month): 10 ()
Contact details of provider:
Web page: http://www.tandfonline.com/RAEL20
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Rajaguru, Gulasekaran, 2004.
"Impact of systematic sampling on causality in the presence of unit roots,"
Elsevier, vol. 84(1), pages 127-132, July.
- Rajaguru GULASEKARAN, 2002. "Impact of Systematic Sampling on Causality in the presence of Unit Roots," Departmental Working Papers wp0210, National University of Singapore, Department of Economics.
- Bolkesjø, Torjus F. & Buongiorno, Joseph, 2006. "Short- and long-run exchange rate effects on forest product trade: Evidence from panel data," Journal of Forest Economics, Elsevier, vol. 11(4), pages 205-221, January.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If references are entirely missing, you can add them using this form.