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

Amy O'Hara, Stephanie Straus, Ron Borzekowski, Paul Arnsberger and Barry Johnson

No 32969, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: H20 I18 I20 I23 I25 I28 I30 I31 J10 J15 J18 J19 J30 J38 J40 Y10 (search for similar items in EconPapers)
Date: 2024-09
Note: TWP
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