Abstract
Big Data changed the paradigm of how the private sector serves its clients. The adroit use of Program Administrative Data (PAD) collected as part of the normal delivery of government services, when linked to records in other datasets, can change the cost and empirical paradigm of how the government learns what works and what does not, and can serve as the foundation for evidence-based policymaking. The linking of individual records is best achieved when records are associated with a Unique Identifier. The use of these linked datasets require a robust data-sharing and data-use infrastructure of laws and technologies that include regulations and procedures on (1) Privacy that outline which data are collected, (2) Confidentiality that outline the allowable users and uses these data, and (3) Security, that outline the excluded users and uses of these data. PAD is used for Performance Measurements to asses who was served, when they were served, how intensively they were served, and at what costs. These measurements, however, do not inform on the change in recipient behavior, or how the recipient behavior impacted a community or a region. Tracing and evaluating a program’s impacts on recipients or communities requires linking PAD to micro data found across government and possibly private entities. There are several challenges with this learning process. The most common among them is learning from insignificant, null or negative findings. Similar challenges arise when evaluating new programs that may not have been in existence long enough to gestate impacts, or for evaluating the impacts of small programs that may not have generated sufficient service-provision observations.
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