Identifying Vars Based on High Frequency Futures Data

44 Pages Posted: 27 Apr 2002

See all articles by Jon Faust

Jon Faust

Board of Governors of the Federal Reserve System

Eric T. Swanson

University of California, Irvine - Department of Economics

Jonathan H. Wright

Johns Hopkins University - Department of Economics

Date Written: February 2002

Abstract

Using the prices of federal funds futures contracts, we measure the impact of the surprise component of Federal Reserve policy decisions on the expected future trajectory of interest rates. We show how this information can be used to identify the effects of a monetary policy shock in a standard monetary policy VAR. This constitutes an alternative approach to identification that is quite different, and, we would argue, more plausible, than the conventional short-run restrictions. We find that the usual recursive identification of the model is rejected, but we nevertheless agree with the literature's conclusion that only a small fraction of the variance of output can be attributed to monetary policy shocks.

Keywords: partial identification, monetary policy, vector autoregressions

JEL Classification: C32, E50

Suggested Citation

Faust, Jon and Swanson, Eric T. and Wright, Jonathan H., Identifying Vars Based on High Frequency Futures Data (February 2002). Available at SSRN: https://ssrn.com/abstract=307002 or http://dx.doi.org/10.2139/ssrn.307002

Jon Faust

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States
202-452-2328 (Phone)
202-736-5638 (Fax)

Eric T. Swanson

University of California, Irvine - Department of Economics ( email )

University of California, Irvine
3151 Social Science Plaza
Irvine, CA 92697-5100
United States
(949) 824-8305 (Phone)

HOME PAGE: http://www.ericswanson.org

Jonathan H. Wright (Contact Author)

Johns Hopkins University - Department of Economics ( email )

3400 Charles Street
Baltimore, MD 21218-2685
United States

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

Paper statistics

Downloads
143
Abstract Views
1,364
rank
241,102
PlumX Metrics