Linking data for better evidence-based policy: A landscape review in central banks

Abstract

The growing availability of information sources has offered central banks new opportunities to enhance their statistical, analytical, and policy functions. By linking—or integrating—various data sets, they have been able to produce more granular, timely, and diverse statistics in a cost-efficient way. These advancements have also enabled a better use of information available in society, such as administrative records, to improve statistical agility in responding to user needs. Yet integrating alternative data—often generated as a by-product of other processes—also raises challenges, including concerns over accuracy, representativeness, and reliability. This paper aims to review systematically the opportunities and limitations of data integration in central banks, taking stock of their experience thus far. Results underscore the need for strengthening the global statistical infrastructure through adequate data governance, management, and public resources.