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Project selection in NIH: A natural experiment from ARRA

Author

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  • Park, Hyunwoo
  • Lee, Jeongsik (Jay)
  • Kim, Byung-Cheol

Abstract

Using a natural experiment in research funding by the National Institutes of Health (NIH) following the American Recovery and Reinvestment Act (ARRA) of 2009, we study the NIH's revealed preference in project selection. We do so by comparing the characteristics of the projects additionally selected for funding due to an unexpected increase in resources under the ARRA with those supported through regular NIH budget. We find that the regular-funded projects are on average of higher quality, as measured by the number of publications per project and the impact of these publications, than ARRA-funded projects. Moreover, compared to ARRA projects, regular projects are more likely to produce highest-impact articles and exhibit greater variance in research output. The output from regular projects also seems more closely fitting the purpose of funding. The differences in project quality are largely explained by observable attributes of the projects and research teams, suggesting that the NIH may use these attributes as cues for discerning underlying project quality. In addition, ARRA projects are more likely than regular projects to involve investigators with past grant experience. Many of these inter-group differences are specific to R01 grants, the largest funding category in the NIH. Overall, these results suggest that the NIH's project selection appears generally in line with its purported mission. In particular, our results contrast starkly with the frequent criticism that the NIH is extremely risk-averse and unwarrantedly favors experienced investigators. We discuss the implications of our findings on the NIH's behavior in project selection.

Suggested Citation

  • Park, Hyunwoo & Lee, Jeongsik (Jay) & Kim, Byung-Cheol, 2015. "Project selection in NIH: A natural experiment from ARRA," Research Policy, Elsevier, vol. 44(6), pages 1145-1159.
    • Handle: RePEc:eee:respol:v:44:y:2015:i:6:p:1145-1159
    DOI: 10.1016/j.respol.2015.03.004
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    References listed on IDEAS

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    Cited by:

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    2. Chaojiang Wu & Erjia Yan & Yongjun Zhu & Kai Li, 2021. "Gender imbalance in the productivity of funded projects: A study of the outputs of National Institutes of Health R01 grants," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(11), pages 1386-1399, November.
    3. Hu, Albert G.Z., 2020. "Public funding and the ascent of Chinese science: Evidence from the National Natural Science Foundation of China," Research Policy, Elsevier, vol. 49(5).
    4. Erjia Yan & Chaojiang Wu & Min Song, 2018. "The funding factor: a cross-disciplinary examination of the association between research funding and citation impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 369-384, April.
    5. Yu, Nannan & Dong, Yueyan & de Jong, Martin, 2022. "A helping hand from the government? How public research funding affects academic output in less-prestigious universities in China," Research Policy, Elsevier, vol. 51(10).
    6. O'Kane, Conor & Mangematin, Vincent & Zhang, Jing A. & Cunningham, James A., 2020. "How university-based principal investigators shape a hybrid role identity," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    7. Cheng Peng & Zhepeng (Lionel) Li & Chaojiang Wu, 2023. "Researcher geographic mobility and publication productivity: an investigation into individual and institutional characteristics and the roles of academicians," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 379-406, January.
    8. Jeongsik “Jay” Lee & Hyun Ju Jung & Hyunwoo Park, 2023. "Rare is beautiful? Rareness, technology value, and the moderating role of search domain and knowledge maturity," Production and Operations Management, Production and Operations Management Society, vol. 32(4), pages 1019-1040, April.
    9. Li, Heyang & Wu, Meijun & Wang, Yougui & Zeng, An, 2022. "Bibliographic coupling networks reveal the advantage of diversification in scientific projects," Journal of Informetrics, Elsevier, vol. 16(3).
    10. Unutmaz Durmuşoğlu, Zeynep Didem, 2018. "Assessment of techno-entrepreneurship projects by using Analytical Hierarchy Process (AHP)," Technology in Society, Elsevier, vol. 54(C), pages 41-46.
    11. Chen Zhu & Kazuyuki Motohashi, 2023. "Government R&D spending as a driving force of technology convergence: a case study of the Advanced Sequencing Technology Program," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 3035-3065, May.

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    More about this item

    Keywords

    Public research funding; Project selection; Natural experiment; National Institutes of Health; American Recovery and Reinvestment Act; Revealed preference;
    All these keywords.

    JEL classification:

    • D2 - Microeconomics - - Production and Organizations
    • H0 - Public Economics - - General
    • H5 - Public Economics - - National Government Expenditures and Related Policies
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

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