A Bootstrap Method for Identifying and Evaluating a Structural Vector Autoregression
AbstractGraph-theoretic methods of causal search based on the ideas of Pearl (2000), Spirtes "et al". (2000), and others have been applied by a number of researchers to economic data, particularly by Swanson and Granger (1997) to the problem of finding a data-based contemporaneous causal order for the structural vector autoregression, rather than, as is typically done, assuming a weakly justified Choleski order. Demiralp and Hoover (2003) provided Monte Carlo evidence that such methods were effective, provided that signal strengths were sufficiently high. Unfortunately, in applications to actual data, such Monte Carlo simulations are of limited value, as the causal structure of the true data-generating process is necessarily unknown. In this paper, we present a bootstrap procedure that can be applied to actual data (i.e. without knowledge of the true causal structure). We show with an applied example and a simulation study that the procedure is an effective tool for assessing our confidence in causal orders identified by graph-theoretic search algorithms. Copyright (c) Blackwell Publishing Ltd and the Department of Economics, University of Oxford, 2008.
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): 70 (2008)
Issue (Month): 4 (08)
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:
- 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.
- C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Kevin Hoover, 2005. "Economic Theory and Causal Inference," Working Papers 64, University of California, Davis, Department of Economics.
- Chauvet, Marcelle & Tierney, Heather L. R., 2007. "Real Time Changes in Monetary Policy," MPRA Paper 16199, University Library of Munich, Germany, revised Apr 2009.
- Pu Chen & Chih-Ying Hsiao, 2010. "Causal Inference for Structural Equations: With an Application to Wage-Price Spiral," Computational Economics, Society for Computational Economics, vol. 36(1), pages 17-36, June.
- 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).
- Henry L. Bryant & David A. Bessler & Michael S. Haigh, 2009. "Disproving Causal Relationships Using Observational Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(3), pages 357-374, 06.
- Wang, Zijun, 2012. "The causal structure of bond yields," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 93-102.
- Andrew Rettenmaier & Zijun Wang, 2013. "What determines health: a causal analysis using county level data," The European Journal of Health Economics, Springer, vol. 14(5), pages 821-834, October.
- 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.
- Selva Demiralp & Kevin Hoover & Stephen Perez, 2014. "Still puzzling: evaluating the price puzzle in an empirically identified structural vector autoregression," Empirical Economics, Springer, vol. 46(2), pages 701-731, March.
- Jinjarak, Yothin, 2013. "Supply Chains and Credit-Market Shocks: Some Implications for Emerging Markets," ADBI Working Papers 443, Asian Development Bank Institute.
- Piyachart Phiromswad, 2014. "Measuring monetary policy with empirically grounded identifying restrictions," Empirical Economics, Springer, vol. 46(2), pages 681-699, March.
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.