Disproving Causal Relationships Using Observational Data
AbstractEconomic theory is replete with causal hypotheses that are scarcely tested because economists are generally constrained to work with observational data. This article describes the use of causal inference methods for testing a hypothesis that one random variable causes another. Contingent on a sufficiently strong correspondence between the hypothesized cause and effect, an appropriately related third variable can be employed for such a test. The procedure is intuitive, and is easy to implement. The basic logic of the procedure naturally suggests strong and weak grounds for rejecting the hypothesized causal relationship. Monte Carlo results suggest that weakly-grounded rejections are unreliable for small samples, but reasonably reliable for large samples. Strongly-grounded rejections are highly reliable, even for small samples.
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 Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics and Statistics.
Volume (Year): 71 (2009)
Issue (Month): 3 (06)
Contact details of provider:
Postal: Manor Rd. Building, Oxford, OX1 3UQ
Web page: http://www.blackwellpublishing.com/journal.asp?ref=0305-9049
More information through EDIRC
Other versions of this item:
- Bryant, Henry L. & Bessler, David A. & Haigh, Michael S., 2006. "Disproving Causal Relationships Using Observational Data," 2006 Annual meeting, July 23-26, Long Beach, CA 21166, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hoover,Kevin D., 2001.
"Causality in Macroeconomics,"
Cambridge University Press, number 9780521452175, December.
- Peltzman, Sam, 1975. "The Effects of Automobile Safety Regulation," Journal of Political Economy, University of Chicago Press, vol. 83(4), pages 677-725, August.
- Selva Demiralp & Kevin D. Hoover & Stephen J. Perez, 2008.
"A Bootstrap Method for Identifying and Evaluating a Structural Vector Autoregression,"
Oxford Bulletin of Economics and Statistics,
Department of Economics, University of Oxford, vol. 70(4), pages 509-533, 08.
- Kevin Hoover & Selva Demiralp & Stephen J. Perez, 2006. "A Bootstrap Method for Identifying and Evaluating a Structural Vector Autoregression," Working Papers 614, University of California, Davis, Department of Economics.
- Selva Demiralp & Kevin D. Hoover, 2003.
"Searching for the Causal Structure of a Vector Autoregression,"
Oxford Bulletin of Economics and Statistics,
Department of Economics, University of Oxford, vol. 65(s1), pages 745-767, December.
- Kevin Hoover & Selva Demiralp, 2003. "Searching for the Causal Structure of a Vector Autoregression," Working Papers 33, University of California, Davis, Department of Economics.
- Hoover, Kevin D., 2005. "Automatic Inference Of The Contemporaneous Causal Order Of A System Of Equations," Econometric Theory, Cambridge University Press, vol. 21(01), pages 69-77, February.
- Swanson, N.R. & Granger, C.W.J., 1994. "Impulse Response Functions Based on Causal Approach to Residual Orthogonalization in Vector Autoregressions," Papers 9-94-1, Pennsylvania State - Department of Economics.
- Hogun Chong & Mary Zey & David A. Bessler, 2010. "On corporate structure, strategy, and performance: a study with directed acyclic graphs and PC algorithm," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 31(1), pages 47-62.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.