News-Driven Uncertainty Fluctuations News-Driven Uncertainty Fluctuations

By Dongho Song and Jenny Tang

By incorporating news shocks into a two-state Markov-switching growth model, this paper seeks to understand the channels through which news influences agents’ subjective beliefs. More specifically, it looks at how information about the future state increases or reduces levels of uncertainty and how, in turn, fluctuations in news-driven uncertainty affect asset prices. This model is estimated using a novel filtering technique that allows the use of data on both actual output growth and recession probability forecasts from the Survey of Professional Forecasters. The procedure delivers estimates of historical probabilities of the economy being in a recession and agents receiving bad news about the future.

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