Abstract: I analyze the business cycle implications of noisy economic indicators in the context of a dynamic general equilibrium model. Two main results emerge. First, measurement error in preliminary data releases can have a quantitatively important effect on economic fluctuations. For instance, under efficient signal-extraction, the introduction of accurate economic indicators would make aggregate output 10 to 30 percent more volatile than suggested by the post-war experience of the U.S. economy. Second, the sign---but not the magnitude---of the measurement error effect depends crucially on the signal processing capabilities of agents. In particular, if agents take the noisy data at face value, significant improvements in the quality of key economic indicators would lead to considerably less cyclical volatility.

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