Vector autoregressions and cointegration
AbstractThis paper surveys three topics: vector autoregressive (VAR) models with integrated regressors, cointegration, and structural VAR modeling. The paper begins by developing methods to study potential "unit root" problems in multivariate models, and then presents a simple set of rules designed to help applied researchers conduct inference in VARs. A large number of examples are studied, including tests for Granger causality, tests for VAR lag length, spurious regressions and OLS estimators of cointegrating vectors. The survey of cointegration begins with four alternative representations of cointegrated systems: the vector error correction model (VECM), and the moving average, common trends and triangular representations. A variety of tests for cointegration and efficient estimators for cointegrating vectors are developed and compared. Finally, structural VAR modeling is surveyed, with an emphasis on interpretation, econometric identification and construction of efficient estimators. Each section of this survey is largely self-contained. Inference in VARs with integrated regressors is covered in Section 2, cointegration is surveyed in Section 3, and structural VAR modeling is the subject of Section 4.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoPaper provided by Federal Reserve Bank of Chicago in its series Working Paper Series, Macroeconomic Issues with number 93-14.
Date of creation: 1993
Date of revision:
Contact details of provider:
Postal: P.O. Box 834, 230 South LaSalle Street, Chicago, Illinois 60690-0834
Web page: http://www.chicagofed.org/
More information through EDIRC
Other versions of this item:
- C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Ben Fung & Rohit Gupta, 1995. "Searching for the Liquidity Effect in Canada," Macroeconomics 9502004, EconWPA.
- Dupasquier, Chantal & Guay, Alain & St-Amant, Pierre, 1999. "A Survey of Alternative Methodologies for Estimating Potential Output and the Output Gap," Journal of Macroeconomics, Elsevier, vol. 21(3), pages 577-595, July.
- Pierre St-Amant, 1996.
"Decomposing U.S. Nominal Interest Rates into Expected Inflation and Ex Ante Real Interest Rates Using Structural VAR Methodology,"
- St-Amant, P., 1996. "Decomposing U.S. Nominal Interest Rates into Expected Inflation and Ex Ante Real Interest rates Using Structural VAR Methodology," Working Papers 96-2, Bank of Canada.
- Barsky, Robert B. & Sims, Eric R., 2011. "News shocks and business cycles," Journal of Monetary Economics, Elsevier, vol. 58(3), pages 273-289.
- Chantal Dupasquier & Alain Guay & Pierre St-Amant, 1997. "A Comparison of Alternative Methodologies for Estimating Potential Output and the Output Gap," Working Papers 97-5, Bank of Canada.
- Ben Fung & Rohit Gupta, . "Searching for the Liquidity Effect in Canada," Working Papers 94-12, Bank of Canada.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Bernie Flores).
If references are entirely missing, you can add them using this form.