Overview of Data-linkage Methods for Policy Design and Evaluation

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


This chapter provides an overview of data linkage for exploiting and combining information about the same entities across data sources. Data linkage can be deterministic (exact), where each matching variable needs to agree exactly to determine a correct match, or probabilistic, where users allow for errors in the matching variables and assign a probability of a correct match. Through classic decision theory, the chapter determines the set of matches (and non-matches) and provides a linked dataset for further analysis. The chapter also describes some recent advances in record linkage and concludes with some initial research on compensating for linkage errors in the analysis of linked data.
Original languageEnglish
Title of host publicationData Driven Policy Impact Evaluation: How Microdata is Transforming Policy Design
EditorsN Crato, P Paruolo
PublisherSpringer Nature
Number of pages38
ISBN (Electronic)9783319784618
Publication statusPublished - 2018


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