A Flexible Finite-Horizon Alternative to Long-Run Restrictions with an Application to Technology Shocks

Neville Francis, Michael Owyang, Jennifer E. Roush and Riccardo DiCecio
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Neville Francis: University of North Carolina
Jennifer E. Roush: Board of Governors, Federal Reserve System

The Review of Economics and Statistics, 2014, vol. 96, issue 4, 638-647

Abstract: Recent studies using long-run restrictions question the validity of the technology-driven real business cycle hypothesis. We propose an alternative identification that maximizes the contribution of technology shocks to the forecast-error variance of labor productivity at a long but finite horizon. In small-sample Monte Carlo experiments, our identification outperforms standard long-run restrictions by significantly reducing the bias in the short-run impulse responses and raising their estimation precision. Unlike its long-run restriction counterpart, when our Max Share identification technique is applied to U.S. data, it delivers the robust result that hours worked responds negatively to positive technology shocks. © 2014 The President and Fellows of Harvard College and the Massachusetts Institute of Technology

Keywords: long-run restriction; technology shock; finite horizon (search for similar items in EconPapers)
JEL-codes: O21 O33 O40 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (125)

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Working Paper: A flexible finite-horizon alternative to long-run restrictions with an application to technology shock (2010)
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