As we head into the holiday weekend, consumers are likely to notice a weaker dollar, which could impact their day-to-day purchases and travel abroad. The price of chocolate is rising due to a shortage of cocoa beans, and the cost of airfares is also climbing. Meanwhile, truckers are concerned about a labor shortage and the impact of Trump’s tariffs on their incomes.
Despite presidential saber-rattling and huge tariff threats, asset prices continue to rise. But this is not because investors have decided that the threat will be resolved in the end or because the administration has changed its policy on tariffs. Instead, it’s because investors have misjudged the sensitivity of asset prices to changes in expectations about economic data.
One reason for this misjudgment is that survey-based estimates of market expectations have lead times ranging from a few days to a week or more, which means that by the time the data are released, a lot of information has accumulated. This accumulated information is called “measured news” in the literature.
A team of economists led by Refet Gurkaynak and Justin Wolfers has developed an approach to estimate the impact of this accumulated noise on asset price responses. This approach combines the standard OLS estimate of asset response with a filter that removes the measured news and its measurement error. It turns out that the resulting estimates of asset price responses are more precise than their standard counterparts and yield estimates of asset responses that agree in sign with those estimated using the traditional OLS approach.
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