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Building a Sample Frame of SMEs Using Patent, Search Engine, and Website Data

Author

Listed:
  • Arora Sanjay K.

    (Ernst & Young, LLP, 1101 New York Ave NW, Washington, D.C., 20005, U.S.A.)

  • Kelley Sarah

    (Child Trends, 7315 Wisconsin Avenue, Suite 1200W, Bethesda, MD, 20814, U.S.A.)

  • Madhavan Sarvothaman

    (American Institutes for Research, Washington, D.C., 20007, U.S.A.)

Abstract
This research outlines the process of building a sample frame of US SMEs. The method starts with a list of patenting organizations and defines the boundaries of the population and subsequent frame using free to low-cost data sources, including search engines and websites. Generating high-quality data is of key importance throughout the process of building the frame and subsequent data collection; at the same time, there is too much data to curate by hand. Consequently, we turn to machine learning and other computational methods to apply a number of data matching, filtering, and cleaning routines. The results show that it is possible to generate a sample frame of innovative SMEs with reasonable accuracy for use in subsequent research: Our method provides data for 79% of the frame. We discuss implications for future work for researchers and NSIs alike and contend that the challenges associated with big data collections require not only new skillsets but also a new mode of collaboration.

Suggested Citation

  • Arora Sanjay K. & Kelley Sarah & Madhavan Sarvothaman, 2021. "Building a Sample Frame of SMEs Using Patent, Search Engine, and Website Data," Journal of Official Statistics, Sciendo, vol. 37(1), pages 1-30, March.
    • Handle: RePEc:vrs:offsta:v:37:y:2021:i:1:p:1-30:n:6
    DOI: 10.2478/jos-2021-0001
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