https://doi.org/10.5061/dryad.18931zd4h

The Stata dataset used for the analysis (_main_data.dta) and the Stata code (_replication_stata.do) have been submitted to facilitate the reproduction of the findings reported in the article of Kwon (2024) and its supplementary materials. The data for reproducing the first figure in the manuscript is available in _department_data.xlsx. The data for comparing patents listed in the FDA’s Orange Book with their matched comparison group is available in _patents_match_fda.xlsx.

Readers are advised to select the patent-paper pairs (PPPs) with a PPP score of 4 if concerned about potential false positives in the PPPs (The precision rate of PPPs with a PPP score of 4 is evaluated at 100%, see Marx & Scharfmann, 2024). The findings and implications discussed in the article remain consistent across all levels of PPP score.

The patent numbers (U.S. patent numbers) and paper IDs (OpenAlex IDs) have been anonymized due to concerns about the potential misuse of this information for non-academic purposes.

Individuals seeking to de-anonymize the patent or paper IDs may request the codebook of the anonymized paper/patent IDs to the true IDs. To do so, please complete the request form using the link provided below. Access to the download link for the codebook will be granted to individuals who demonstrate a reasonable academic basis for the request and commit to using the information exclusively for academic purposes*.

*For the purposes of this policy, academic purposes include: replicating the findings of this research, extending the analysis, integrating the data with other research datasets, and validating the data points.

[Request form]

Please cite the following article when using this data.

Kwon, S. (2024). Underappreciated government research support in patents. Science, 385(6712), 936-938.

Description of the data and file structure

Variables in _main_data.dta (origin of the variable is indicated in [ ]).

• paperid_anonymized: Anonymized OpenAlex ID of paper.
• patent_anonymized: Anonymized US patent number.
• ppp_score: Patent-Paper Pair (PPP) confidence score assigned by Marx & Scharfmann (2024): 1 = low, 4 = high. For PPP scores of 4, the precision rate is calculated to be 100%.[M&S]
• daysdiffcont: Difference in days between the patent filing date and the paper publication date. [M&S]
• nus_fed_gov_auth: Number of authors affiliated with US federal government agencies (organizations). [OA]
• paper_teamsize: Number of authors as recorded in OpenAlex. [OA]
• pyr: Publication year of the paper, as recorded in OpenAlex. [OA]
• paper_bwd: Number of cited references in the paper (OpenAlex). [OA]
• patent_filing_yr2: Patent filing year (years prior to 1987 aggregated into 1986). [USPTO]
• patent_teamsize: Number of inventors listed on the patent. [USPTO]
• tech_class: Aggregated patent technology class based on the WIPO technology classification scheme. [USPTO&Author]
• tech_classnum: Encoded numeric value for tech_class. [USPTO]
• patent_bwd: Number of cited references in patent. [USPTO]
• us_federal_funder: Equals 1 if the paper acknowledges support from a U.S. federal government agency in the funding acknowledgment field, as recorded in the Web of Science. [WOS]
• firm_funder: Equals 1 if the paper acknowledges support from a private firm in the funding acknowledgment field, as recorded in the Web of Science. [WOS]
• ngov_interest_patent: Equals 1 if the patent includes a government interest statement. [USPTO]
• assignee_type*: *Type of assignee for the patent (academia, firm, others, us_gov). [USPTO]
• patent_on_fda: Equals 1 if the patent is listed in the FDA Orange Book. [FDA]
• represent_ppp_family: Equals 1 if the patent-paper pair represents a PPP family.
• confirmatory_license: Equals 1 if the patent is in a confirmatory license agreement. [USPTO]
• firm_author: Equals 1 if the paper is authored by at least one researcher affiliated with a corporation. [OA]
• patent_qi4: Patent Quality Index 4. [OECD]
• patent_qi6: Patent Quality Index 6. [OECD]
• private_support: Equals 1 if the paper acknowledges private firm support in the funding acknowledgment field as recorded in the Web of Science or includes a corporate researcher as an author. [OA][WOS]
• usgov: Equals 1 if the assignee is the US federal government. [USPTO]
• academic: Equals 1 if the assignee is an academic institution (university or research institute). [USPTO]
• firm: Equals 1 if the assignee is a private firm. [USPTO]
• others: Equals 1 for other types of assignees. [USPTO]
• ack_us_gov: Equals 1 if the patent acknowledges U.S. government research support, either through a government interest statement or by including federal researchers as inventors.
• ack_us_gov_confirmatory: Equals 1 if ack_us_gov is 1 or confirmatory_license=1. [USPTO]
• no_private_support: Equals 1 if no private support is indicated.
• no_fda: Equals 1 if the patent is not listed in the FDA Orange Book. [FDA]
• nous_support_ack: Equals 1 if the patent does not acknowledge US federal government support.

Key information source

Variables in this dataset were derived from the following sources:

• [OA]OpenAlex (https://openalex.org/)
• [WOS]Web of Science Core Collection (https://www.webofscience.com/wos/woscc/)
• [USPTO]PatentsView.org serviced by USPTO
• [FDA]US Food & Drug Administration Orange book (https://www.fda.gov/drugs/drug-approvals-and-databases/orange-book-data-files)
• [OECD]OECD Patent Quality Indicators Database (https://www.oecd.org/en/data/datasets/intellectual-property-statistics.html)
• [M&S]Patent-Paper Pairs (PPP) dataset compiled by Marx and Scharfmann* (2024)

• Marx and Scharfmann’s PPPs dataset can be downloaded from https://relianceonscience.org/

  *M. Marx, E. Scharfmann, Does Patenting Promote the Progress of Science? Working Paper (2024); https://assets.zyrosite.com/YZ97xEPgM7SegrpN/ppp20240531-m5KvaGBojMIza35N.pdf. 

Code/Software

Stata code: _replication_stata.do (Stata do file)