Everyone who follows the U.S. economy closely knows that the unemployment rate was 9.4% in July, down 0.1% from June.
Everyone, that is, except Google.
If you ask Google (by searching for ”unemployment rate United States“), it will tell you the unemployment rate in July was 9.7%.
What’s going on? Well, it turns out that Google is directing users to the wrong data series. As I discussed last month, almost everyone who talks about unemployment is using (whether they know it or not) data that have been adjusted to remove known seasonal patterns in hiring and layoffs (e.g., many school teachers become unemployed in June and reemployed in August or September). Adjusting for such seasonal patterns is standard protocol because it makes it easier for data users to extract signals from the noisy movements in data over time.
For unknown reasons, Google has chosen not to direct users to these data. Instead, Google reports data that haven’t been seasonally adjusted and thus do not match what most of the world is using.
This is troubling, since I have high hopes for Google’s vision of bringing the power of search to data sets. The ability of users to find and access data lags far behind their ability to find and access text. I am hopeful that Google will solve part of this problem.
But data search is not about mindlessly pointing users to data series. You need to make sure that users get directed to the right data series. So far, Google is failing on that front, at least with unemployment data.
P.S. As I discussed in a follow-up post last month, Wofram Alpha has an even more ambitious vision for making data — and computation — available through search. I like many of the things Alpha is trying to do, but they are lagging behind Google in several ways. For example, as I write this, they haven’t updated the unemployment data yet to reflect the new July data. (Click here for Alpha results.)