Your path in the tree: Start > Econometrics > Time Series Models > VAR Models > Sign Restrictions
This entry is not rated
Log in to rate or make a suggestion

Sign Restrictions

Narrower topics in the RePEc Biblio tree

This RePEc Biblio topic is edited by Renee A. Fry-McKibbin. It was first published on 2013-02-10 21:44:11 and last updated on 2013-02-10 21:44:11.

Introduction by the editor

Structural vector autoregressions have become one of the major ways of extracting information about the macro economy. To determine this information, a vector autoregression (VAR) is first fitted to summarize the data and then a structural VAR (SVAR) is proposed whose structural equation errors are taken to be the economic shocks. The parameters of these structural equations are then estimated by utilizing the information in the VAR. The VAR is a reduced form that summarizes the data; the SVAR provides an interpretation of the data. As for any set of structural equations, recovery of the structural equation parameters (shocks) requires the use of identification restrictions that reduce the number of “free” parameters in the structural equations to the number that can be recovered from the information in the reduced form. Recently, a new method for estimating SVARs has arisen that employs sign restrictions upon the impulse responses as a way of identifying shocks (Jon Faust 1998; Harald Uhlig 2005; Fabio Canova and Gianni De Nicoló 2002). Applications of this method have been growing, as seen in the papers listed below. Most of the papers below are reviewed in Fry and Pagan 2010 which examininges this literature in more detail.

Most relevant JEL codes

Most relevant research

  1. Renée Fry & Adrian Pagan, 2011. "Sign Restrictions in Structural Vector Autoregressions: A Critical Review," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 938-960, December.
  2. Faust, Jon, 1998. "The robustness of identified VAR conclusions about money," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 49(1), pages 207-244, December.
  3. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
  4. Canova, Fabio & Nicolo, Gianni De, 2002. "Monetary disturbances matter for business fluctuations in the G-7," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1131-1159, September.
  5. Gert Peersman, 2005. "What caused the early millennium slowdown? Evidence based on vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 185-207.
  6. Paustian Matthias, 2007. "Assessing Sign Restrictions," The B.E. Journal of Macroeconomics, De Gruyter, vol. 7(1), pages 1-33, August.
  7. Lutz Kilian & Daniel P. Murphy, 2012. "Why Agnostic Sign Restrictions Are Not Enough: Understanding The Dynamics Of Oil Market Var Models," Journal of the European Economic Association, European Economic Association, vol. 10(5), pages 1166-1188, October.
  8. Canova, Fabio & Paustian, Matthias, 2011. "Business cycle measurement with some theory," Journal of Monetary Economics, Elsevier, vol. 58(4), pages 345-361.
  9. Dungey, Mardi & Fry, Renée, 2009. "The identification of fiscal and monetary policy in a structural VAR," Economic Modelling, Elsevier, vol. 26(6), pages 1147-1160, November.
  10. Eickmeier, Sandra & Hofmann, Boris & Worms, Andreas, 2006. "Macroeconomic fluctuations and bank lending: evidence for Germany and the euro area," Discussion Paper Series 1: Economic Studies 2006,34, Deutsche Bundesbank, Research Centre.