Federal agencies, such as the Bureau of Labor Statistics and Bureau of Economic Analysis, provide timely, relevant, and accurate economic account data in an objective and cost-effective manner, which can promote a better understanding of the US economy. But most of these economic data are not available to the public because of privacy concerns, as the data have small counts of people and businesses within certain industries. As a result, public policymakers may lack basic information about economies, which they could use to promote evidence-based economic development planning and investments.
Applying newer data privacy and confidentiality methods, such as synthetic data generation, to expand access could offer one possible solution. Although newer methods have existed for several years, few practitioners are knowledgeable of the data privacy mathematics and skilled in coding these methods. Research, education, and training around promising new privacy protection techniques are vital for expanding access to data that can inform government statistics and improve that data’s reliability and accuracy.