When Claimant Characteristics and Prior Performance Predict Bureaucratic Error

The public administration literature has paid scant attention to bureaucratic errors as performance measures. This has largely been due to a lack of data. Unlike most programs, the unemployment insurance (UI) program has systematically collected performance data and has independently audited those data to determine error responsibility (employer, employee, and agency error). In the first comprehensive analysis of these data, we examine the probability that a bureaucrat makes an error involving nonpayment of UI benefits and theorize about the reasons for these errors. Our findings indicate that the previous UI office error rate is a good predictor of current error rates, demonstrating that poorly performing offices remain poor performers. In addition, local offices with high error rates account for a disproportionate percentage of the errors, indicating a need to examine agency management. Second, errors are more commonly made on cases involving White UI claimants and claimants with a college education. Finally, we find that claimants who have higher self-valuation, are less likely to experience agency errors. Taken together, these results point to systematic agency errors. Public managers and the unemployed would be better served if training efforts and performance targets were developed with these systematic error effects in mind.