Nicholas Pairolero

Senior Research Economist

Nicholas A. Pairolero is a Senior Research Economist at the United States Patent and Trademark Office. Nick's interests are in evidence-based policy and decision making, with research in the economics of innovation. His research has received professional and academic awards, including the Department of Commerce Gold Medal for scientific/engineering achievement, and Best Paper for the Technology and Innovation Management Division of the Academy of Management. He holds a Ph.D. and M.A. in Economics from Indiana University Bloomington, and a B.B.A. in Economics and Mathematics from the University of Wisconsin Eau Claire.


Selected publications

USPTO pilot program reduced gender disparities in patenting (with C. deGrazia, P. Pappas, M. Teodorescu and A. Toole), USPTO IP Economic Note, Issue 102, 2022. Available at

Closing the gender gap in patenting: Evidence from a randomized control trial at the USPTO (with C. deGrazia, P. Pappas, M. Teodorescu and A. Toole), Academy of Management Proceedings, 2022. Available at

Patents and the independent inventor lifecycle (with C. deGrazia, P. Pappas, M. Teodorescu and A. Toole), Academy of Management Proceedings, 2022. Available  at

Using Intellectual Property Data to Measure Cross-border Knowledge Flows (with J. Dubbert, A. Giczy and A. Toole), Trade in Knowledge: Intellectual Property, Trade and Development in a Transformed Global Economy, 2022. Available at

Identifying Artificial Intelligence (AI) Invention: A Novel AI Patent Dataset (with A. Giczy and A. Toole), The Journal of Technology Transfer, 47(2), 2021. Available at

Examination incentives, learning, and patent office outcomes: The use of examiner’s amendments at the USPTO (with C. deGrazia and M. Teodorescu). Research Policy, 50(10), 2021. Available at

Inventing AI: Tracing the Diffusion of Artificial Intelligence with US Patents (with A. Toole, A. Giczy, J. Forman, C. Pulliam, M. Such, K. Chaki, D. Orange, A. Thomas Homescu, J. Frumkin, YY. Chen, V. Gonzales, C. Hannon, S. Melnick, E. Nilsson, and B. Rifkin), USPTO IP Data Highlights, No. 5, 2020. Available at

The Promise of Machine Learning for Patent Landscaping (with A. Toole, J. Forman, and A. Giczy), Santa Clara High Tech. LJ, 36, p.433., 2020. Available at

Adjusting to Alice: USPTO Patent Examination Outcomes after Alice Corp. v. CLS Bank International (with A. Toole), USPTO IP Data Highlights, No. 3, 2020. Available at

Embracing Invention Similarity for the Measurement of Vertically Overlapping Claims (with C. deGrazia and J. Frumkin), Economics of Innovation and New Technology, 2019. Available at