Recovery Act Data Shows Recipients Are Learning

Earlier today, the Recovery Board released the list of Recovery Act recipients who did not file during the second reporting period. According to the Board, recipients of 1,036 awards failed to file during this quarter, which was from Oct. 1 through Dec. 31. That number represents a whopping 76 percent decline from the first reporting cycle, which saw 4,359 missing award reports, and is less than one percent of all the award reports. Equally good news is that of the 1,036 missing reports, only 389 were from "repeat offenders," or recipients who failed to file in both quarters.

The trend from the non-filer list echoes other data the Recovery Board also posts, such as the late filers and report corrections. According to the Board, the second reporting cycle saw half as many late reports, which are award reports filed after the filing deadline. This past cycle, 7.3 percent of recipients filed late, down from 14.9 percent of reporters in the first round of reporting, and of these late reports, a vast majority of them were not repeat offenders. Similarly, only 12.75 percent of award reports were changed after the fact (recipients can change their reports for several months after the filing deadline), as opposed to over 21 percent in the first round.

These data sets show what we've been assuming would happen: Recovery Act recipients are learning. As time passes, and recipients learn how the reporting system works and how they're supposed to file, the number of reporting errors are slowly decreasing. More recipients are reporting on time, fewer are forgetting to report (or are understanding that they have to report), and there are fewer mistakes to correct after the fact. And this progress is despite the fact that there are more award reports in the second round than the first.

This trend will probably continue over the coming cycles, although it will be interesting to see if it hits a floor at some point, i.e. if there is some baseline level of user error we just can't escape.

The next important statistic to look at will be the change in data quality between quarters. While we know recipients are learning how to file, what we don't know is if they are entering better quality information this time around. Are there fewer award amount errors? Fewer job counting errors? Late reports are bad, but flawed data is even worse.

Image by Flickr user ekilby used under a Creative Commons license.

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