Short-term macroeconomic data can pose challenges for analysis of policy changes, according to an article in Bloomberg. “Every time a new macro data point comes out,” it says, “commentators rush to interpret it…Using these data points to do on-the-spot policy analysis is fraught with dangers.”

The article outlines the following reasons:

1. Government data is imperfect, since it depends on surveys that “may contain biases, noise, and incorrect assumptions.”
2. Such data is subject to revisions, sometimes as long as years after the data is first released. While over the long term, such revisions may not make a difference, the article points out, it “can entirely invalidate the stories that commentators tell based on monthly or quarterly data points.”
3. Short-term data points are “often inadequate for analyzing the effects of an economic policy”.” For example, it could take several quarters for businesses to increase wages in response to the recent tax cut. Further, it says, changes in real wages or GDP are affected by changes in gasoline prices “that have little to do with policy.”

The article concludes that it makes the most sense to look at as many different data sources as possible when analyzing the effects of policy changes, and to avoid “putting much weight on any single number. And it’s best to draw only the most tentative of conclusions from the tea leaves.”