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Vector Autoregressions, Policy Analysis, and Directed Acyclic Graphs: An Application to the U.S. Economy

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  • Titus O. Awokuse
  • David A. Bessler

Abstract

The paper considers the use of directed acyclic graphs (DAGs), and their construction from observational data with PC-algorithm TETRAD II, in providing over-identifying restrictions on the innovations from a vector autoregression. Results from Sims' 1986 model of the US economy are replicated and compared using these data-driven techniques. The directed graph results show Sims' six-variable VAR is not rich enough to provide an unambiguous ordering at usual levels of statistical significance. A significance level in the neighborhood of 30% is required to find a clear structural ordering. Although the DAG results are in agreement with Sims' theory-based model for unemployment, differences are noted for the other five variables: income, money supply, price level, interest rates, and investment. Overall the DAG results are broadly consistent with a monetarist view with adaptive expectations and no hyperinflation.

Suggested Citation

  • Titus O. Awokuse & David A. Bessler, 2003. "Vector Autoregressions, Policy Analysis, and Directed Acyclic Graphs: An Application to the U.S. Economy," Journal of Applied Economics, Taylor & Francis Journals, vol. 6(1), pages 1-24, May.
    • Handle: RePEc:taf:recsxx:v:6:y:2003:i:1:p:1-24
    DOI: 10.1080/15140326.2003.12040583
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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • E1 - Macroeconomics and Monetary Economics - - General Aggregative Models

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