The Policy Evaluation and Research Linkage Initiative (PERLI) is a four-year project funded by the National Science Foundation that will establish powerful new datasets of linked administrative microdata from California state and local government sources.
FAQ
Q: When will the PERLI data become available?
A: We began receiving applications for research projects using the PERLI datasets in 2020. Subscribe to our updates list to stay informed.
Q: For what years are the data available?
A: It depends on the dataset. The Life Course dataset spans July 2013 to July 2021. There are seven component datasets in the Safety Net dataset, all of which include at least 10 years of data, although the years available vary by dataset. The Household Economics dataset has data starting in 2004 and continuing quarterly through the present.
Q: Can I link the data with other datasets not on CPL’s Data Hub?
A: We encourage you to reach out to us on this topic (perli@capolicylab.org). This may prove difficult and/or expensive, but we are eager to help you if possible.
Q: Are there costs or fees associated with access?
A: Not for regular access, which we anticipate will cover most PERLI projects. CPL may request reimbursement for specialized requests that require additional staff time, such as a project that requires linking in an additional dataset.
Q: How will you protect the privacy of the individuals whose data you will be distributing?
A: All PERLI datasets are fully anonymized so that no personally identifiable information is available for analysis. However, even with anonymized data there is some risk of re-identification. To prevent against it, CPL protects the data on a highly secure Data Hub, trains users on appropriate data use, monitors the activity of users on the Hub, and carefully reviews all results taken off the Hub.
Q: Is data documentation available now to help me determine whether my research is a good fit?
A: Yes, each dataset is accompanied by relevant and detailed data documentation, developed by CPL in partnership with each data provider. These include descriptions of variables, codebooks, and any known issues of reliability or missingness.