Uncertainty about economic policy looks to be subsiding.

Government shutdowns and debt ceiling standoffs, battles over the implementation of the Affordable Care Act, “fiscal cliff” effects and disputes over raising upper-income tax rates — in recent years, major economic policy issues have been shrouded in uncertainty. There’s general agreement that uncertainty can hurt the economy by stalling investment and delaying consumption (although there’s a lot of disagreement about what causes uncertainty and how much effect it has).

According to one measure of uncertainty, though, it’s been dropping ever since the government shutdown in late 2013.

How do we quantitatively measure this squishy concept of uncertainty? Although an imperfect measure, the go-to source is the Economic Policy Uncertainty Index, developed by Nick Bloom and Scott Baker at Stanford and Steven Davis of the University of Chicago. The index — which has been trending downward since the government shutdown last October — is constructed from three sources:

the number of tax provisions set to expire; the variation in forecasts from professional economists; a news-based search for keywords reflecting talk of such uncertainty.

That third category is both particularly innovative and controversial. Each day, the authors of the index scan the 10 largest U.S. newspapers and create a normalized index of the volume of stories about economic policy uncertainty. They search for keywords (such as “uncertainty”) paired in articles about the “economy,” “budget” or “Federal Reserve,” for example. This is innovative in that it makes use of a huge amount of real-time data. But it has limitations: It’s frequently revised, and more importantly, critics claim it’s more a reflection of talk of uncertainty rather than the actual thing.

These caveats aside, it’s a useful tool in analyzing an important economic issue that can have serious effects on economic activity.