Searching for the Causal Structure of a Vector Autoregression

UC Davis Working Paper No. 03-03

41 Pages Posted: 21 Apr 2003

See all articles by Kevin D. Hoover

Kevin D. Hoover

Duke University - Departments of Economics and Philosophy

Selva Demiralp

Koc University - Department of Economics

Date Written: March 6, 2003

Abstract

Vector autoregressions (VARs) are economically interpretable only when identified by being transformed into a structural form (the SVAR) in which the contemporaneous variables stand in a well-defined causal order. These identifying transformations are not unique. It is widely believed that practitioners must choose among them using a priori theory or other criteria not rooted in the data under analysis. We show how to apply graph-theoretic methods of searching for causal structure based on relations of conditional independence to select among the possible causal orders - or at least to reduce the admissible causal orders to a narrow equivalence class. The graph-theoretic approaches were developed by computer scientists and philosophers (Pearl, Glymour, Spirtes among others) and applied to cross-sectional data. We provide an accessible introduction to this work. Then building on the work of Swanson and Granger (1997), we show how to apply it to searching for the causal order of an SVAR. We present simulation results to show how the efficacy of the search method algorithm varies with signal strength for realistic sample lengths. Our findings suggest that graph-theoretic methods may prove to be a useful tool in the analysis of SVARs.

JEL Classification: C15, C32, C49, C51

Suggested Citation

Hoover, Kevin D. and Demiralp, Selva, Searching for the Causal Structure of a Vector Autoregression (March 6, 2003). UC Davis Working Paper No. 03-03, Available at SSRN: https://ssrn.com/abstract=388840 or http://dx.doi.org/10.2139/ssrn.388840

Kevin D. Hoover (Contact Author)

Duke University - Departments of Economics and Philosophy ( email )

213 Social Sciences Building
Box 90097
Durham, NC 27708-0204
United States

Selva Demiralp

Koc University - Department of Economics ( email )

Rumeli Feneri Yolu
Sariyer 80910 Istanbul
Turkey
+212 338 1842 (Phone)

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
215
Abstract Views
2,592
rank
170,055
PlumX Metrics