Journal Articles

1. Demiralp, S; Hoover, KD, Searching for the Causal Structure of a Vector Autoregression, Oxford Bulletin of Economics and Statistics, vol. 65 no. SUPPL. (December, 2003), pp. 745-767, WILEY [doi].
   (last updated on 2024/04/18)

   Abstract:
   We provide an accessible introduction to graph-theoretic methods for causal analysis. Building on the work of Swanson and Granger (Journal of the American Statistical Association, Vol. 92, pp. 357-367, 1997), and generalizing to a larger class of models, we show how to apply graph-theoretic methods to selecting the causal order for a structural vector autoregression (SVAR). We evaluate the PC (causal search) algorithm in a Monte Carlo study. The PC algorithm uses tests of conditional independence to select among the possible causal orders - or at least to reduce the admissible causal orders to a narrow equivalence class. Our findings suggest that graph-theoretic methods may prove to be a useful tool in the analysis of SVARs.