A Secure Query System to Improve Access to Individual Income Tax Data

In recent years, important and headline-grabbing findings have emerged from research using individual income tax data for statistical purposes. Demand for these microdata, accessible under the tax administration authority of the Internal Revenue Code and through the IRS Statistics of Income (SOI) Division’s Joint Statistical Research Program, continues to grow. This paper describes a new approach to address demand from government agencies and nonprofit institutions for such statistics.
The project explores the feasibility of a privacy preserving secure query system (SQS) linking end-users of the data, a data intermediary, and SOI. In the early stages of development, end-users may be state or local government agencies or nonprofit institutions (e.g., non-degree programs at community colleges); the intermediary is Georgetown University; and all processing will be done within and by SOI staff. The objective is for an SQS client, such as a state department of social services, to prepare and submit a dataset with personal identifiers for SOI to match to individual income tax records, in order to produce tables of predefined output statistics. This efficient and automated process should allow greater production of evidence at much lower cost and burden for clients and SOI.