TY  - JOUR
AU  - Chari,V. V.
AU  - Kehoe,Patrick J.
AU  - McGrattan,Ellen R.
TI  - Are Structural VARs with Long-Run Restrictions Useful in Developing Business Cycle Theory?
JF  - National Bureau of Economic Research Working Paper Series
VL  - No. 14430
PY  - 2008
Y2  - October 2008
UR  - http://www.nber.org/papers/w14430
L1  - http://www.nber.org/papers/w14430.pdf
N1  - Author contact info:
Varadarajan V. Chari
Department of Economics
University of Minnesota
1035 Heller Hall
271 - 19th Avenue South
Minneapolis, MN 55455
Tel: 612/626-5171
Fax: (612) 624-0209
E-Mail: varadarajanvchari@gmail.com

Patrick Kehoe
Research Department
Federal Reserve Bank of Minneapolis
90 Hennepin Avenue
Minneapolis, MN  55480-0291
Tel: 612/204-5525
Fax: 612/204-5515
E-Mail: pkehoe@res.mpls.frb.fed.us

Ellen McGrattan
Research Department
Federal Reserve Bank of Minneapolis
90 Hennepin Avenue
Minneapolis, MN 55480
Tel: 612/204-5523
Fax: 612/204-5515
E-Mail: erm@mcgrattan.mpls.frb.fed.us
AB  - The central finding of the recent structural vector autoregression (SVAR) literature with a differenced specification of hours is that technology shocks lead to a fall in hours. Researchers have used this finding to argue that real business cycle models are unpromising. We subject this SVAR specification to a natural economic test by showing that when applied to data generated from a multiple-shock business cycle model, the procedure incorrectly concludes that the model could not have generated the data as long as demand shocks play a nontrivial role. We also test another popular specification, which uses the level of hours, and show that with nontrivial demand shocks, it cannot distinguish between real business cycle models and sticky price models. The crux of the problem for both SVAR specifications is that available data necessitate a VAR with a small number of lags and, when demand shocks play a nontrivial role, such a VAR is a poor approximation to the model's infinite order VAR.
ER  -