Our study looks at two large categories of cases, torts and inmate civil rights, and separates two aspects of case outcomes: which party obtained judgment and the amount of the judgment when plaintiffs prevail. With respect to the coding for the party obtaining judgment, we find that the AO data are very accurate when they report a judgment for plaintiff or defendant, except in cases in which judgment is reported for plaintiff but damages are reported as zero. As to this anomalous category (which is far more significant in the inmate sample than in the torts sample), defendants are frequently the actual victors in the inmate cases. In addition, when the data report a judgment for "both" parties (a characterization that is ambiguous even as a matter of theory), the actual victor is nearly always the plaintiff. Because such cases are quite infrequent, this conclusion is premised on relatively few observations and merits further testing.
With respect to award amounts, we find that the unmodified AO data are more error prone, but that the data remain usable for many research purposes. While they systematically overestimate the mean award, the data apparently yield a more accurate estimate as to median awards. Researchers and policymakers interested in more precise estimates of mean and median awards have two reasonably efficient options available. First, as described below, they can exclude two easily-identified classes of awards with evidently suspect values entered in the AO data. Second, using PACER or courthouse records, they can ascertain the true award only in the suspect cases without having to research the mass of cases. Either technique provides reasonable estimates of the median award. The second technique may provide a reasonable estimate of the mean award, at least for some case categories.
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