Challenges in Assigning Panel Data With Cryptographic Self-generated Codes – Between Anonymity, Data Protection and Loss of Empirical Information

Christina Beckord


The assignment of questionnaires between the 13 survey waves in the panel study “Crime in the Modern City” (CrimoC) was done by matching self-generated codes. This method was challenging because the individual codes tend to be ambiguous, prone to errors and the resulting panel data can be biased. The individual data were merged over time using an error-tolerant matching process with manual handwriting comparison. Despite these problems, there is no alternative to the chosen method with regard to anonymity and data-protection. Until now, the self-generated codes of each new survey wave were matched against the codes of the last and second-last wave. Over the years, this led to an increasing discrepancy between the data originally collected and the data linked to the panel. For this reason, first in a pretest and later for the complete sample, the cases that had not yet been linked to the panel were subsequently matched with earlier waves. This panel consolidation proved to be very successful. A total of 3,589 original missing units were subsequently filled with case data. This paper describes the steps taken to optimize the quality of the panel data set and illustrates exemplarily on specified criteria which properties of the panel data set could be improved. Since the importance of panel studies is steadily increasing in social science research this paper is relevant for researchers who need to make matching decisions within panel studies. Assurance of anonymity can counteract panel attrition. Self-generated codes represent one possibility in this regard, and are discussed in terms of feasibility and effectiveness.


panel data, missing unit, personal codes, assignment rates

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