Are structural VARs with long-run restrictions useful in developing business cycle theory?

Varadarajan Chari, Patrick Kehoe and Ellen McGrattan

No 364, Staff Report from Federal Reserve Bank of Minneapolis

Abstract: 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 and show that when applied to data 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 require a VAR with a small number of lags and such a VAR is a poor approximation to the model?s VAR. ; Formerly titled: A critique of structural VARs using business cycle theory ; Originally Working paper no. 631

Date: 2007
New Economics Papers: this item is included in nep-dge and nep-mac
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Citations: View citations in EconPapers (40)

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Journal Article: Are structural VARs with long-run restrictions useful in developing business cycle theory? (2008)
Working Paper: Are Structural VARs with Long-Run Restrictions Useful in Developing Business Cycle Theory? (2008)
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