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In this paper I propose a novel method of identifying technological news shocks through instrumental variables based on forecast revisions from the Survey of Professional Forecasters. I construct proxy measures for the slope of the long-run trend of GDP, investment and industrial production, which are strong instruments for recovering the underlying technological news shock. The procedure has the advantage of relying on information about agents' expectations, instead of the statistical procedures currently used for the news shock identification. By employing a proxy SVAR, I show that a news shock produces substantial effects on impact on GDP and investment. The effects on consumption in the short-run, however, are milder than usually presented by the news shock literature.
