Effectiveness of data correction rules in process-produced data: The case of educational attainment

The use of process-produced data plays a large and growing role in empirical labor market research. To address data problems, previous research have developed deductive correction rules that make use of within-person information. We test data reliability and the effectiveness of different correction rules for information about educational degrees as reported in German register data. Therefore we use the unique dataset ALWA-ADIAB, which combines interview data and process-produced data from exactly the same individuals. This approach enables us to assess how effective the existing correction rules are and whether they manage to eliminate structural biases. In sum, we can state that simple editing rules based on logic assumptions are suitable for improving the quality of process-produced data, but they are not able to correct for structural biases.