Can Long-Run Restrictions Identify Technology Shocks?

Christopher Erceg, Luca Guerrieri and Christopher Gust

Journal of the European Economic Association, 2005, vol. 3, issue 6, 1237-1278

Abstract: Galí's innovative approach of imposing long-run restrictions on a vector autoregression (VAR) to identify the effects of a technology shock has become widely utilized. In this paper, we inves-tigate its reliability through Monte Carlo simulations using calibrated business cycle models. Overall, Galí's methodology appears to be fruitful: the impulse responses derived from the artificial data generally have the same sign and qualitative pattern as the true responses, and the approach can be informative in discriminating between alternative models. However, our results reveal some important quantitative shortcomings, including considerable estimation uncertainty about the impact of technology shocks on macroeconomic variables. More gen-erally, the conditions under which the methodology performs well appear considerably more restrictive than implied by the key identifying assumption. This underscores the importance of using economic models to guide in the implementation of the approach, in interpreting the results, and in assessing its limitations. (JEL: C32, E32, O33) Copyright (c) 2005 by the European Economic Association.

Date: 2005
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Working Paper: Can long-run restrictions identify technology shocks? (2004)
Working Paper: Can Long-Run Restrictions Identify Technology Shocks? (2004)
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