IDEAS home Printed from https://ideas.repec.org/a/eee/respol/v39y2010i6p835-841.html
   My bibliography  Save this article

Tackling undue concentration of federal research funding: An empirical assessment on NSF's Experimental Program to Stimulate Competitive Research (EPSCoR)

Author

Listed:
  • Wu, Yonghong

Abstract

This empirical study focuses on NSF's Experimental Program to Stimulate Competitive Research (EPSCoR) and its effect on a state's share of federal academic science and engineering (S&E) support to higher education institutions. Based on a panel of 50 states in period 1979-2006, the statistical results suggest that EPSCoR may have enhanced research capacity and competitiveness of EPSCoR states as reflected in a significant and positive effect of state's tenure in the program. The small effect of EPSCoR indicates that enhanced and more innovative efforts are needed in order to effectively tackle undue concentration of federal S&E support.

Suggested Citation

  • Wu, Yonghong, 2010. "Tackling undue concentration of federal research funding: An empirical assessment on NSF's Experimental Program to Stimulate Competitive Research (EPSCoR)," Research Policy, Elsevier, vol. 39(6), pages 835-841, July.
  • Handle: RePEc:eee:respol:v:39:y:2010:i:6:p:835-841
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0048-7333(10)00077-6
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yonghong Wu, 2009. "NSF's Experimental Program to Stimulate Competitive Research (EPSCoR): Subsidizing academic research or state budgets?," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 28(3), pages 479-495.
    2. Unknown, 2007. "NAREA Awards," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 36(2), pages 1-6.
    3. James S Dietz, 2000. "Building a social capital model of research development: The case of the Experimental Program to Stimulate Competitive Research," Science and Public Policy, Oxford University Press, vol. 27(2), pages 137-145, April.
    4. J. Scott Hauger, 2004. "From Best Science Toward Economic Development: The Evolution of NSF’s Experimental Program to Stimulate Competitive Research (EPSCoR)," Economic Development Quarterly, , vol. 18(2), pages 97-112, May.
    5. Bozeman, Barry & Corley, Elizabeth, 2004. "Scientists' collaboration strategies: implications for scientific and technical human capital," Research Policy, Elsevier, vol. 33(4), pages 599-616, May.
    6. Julia Melkers & Yonghong Wu, 2009. "Evaluating the Improved Research Capacity of EPSCoR States: R&D Funding and Collaborative Networks in the NSF EPSCoR Program," Review of Policy Research, Policy Studies Organization, vol. 26(6), pages 761-782, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Drivas, Kyriakos & Economidou, Claire & Karamanis, Dimitris & Zank, Arleen, 2014. "Academic Patents and Technology Transfer," MPRA Paper 57476, University Library of Munich, Germany.
    2. Lawson, Cornelia & Salter, Ammon, 2023. "Exploring the effect of overlapping institutional applications on panel decision-making," Research Policy, Elsevier, vol. 52(9).
    3. Bozeman, Barry & Youtie, Jan, 2017. "Socio-economic impacts and public value of government-funded research: Lessons from four US National Science Foundation initiatives," Research Policy, Elsevier, vol. 46(8), pages 1387-1398.
    4. Rodríguez-Pose, Andrés & Crescenzi, Riccardo, 2012. "R&D, Socio-Economic Conditions and Regional Innovation in the United States," CEPR Discussion Papers 9265, C.E.P.R. Discussion Papers.
    5. Riccardo Crescenzi & Andrés Rodríguez-Pose, 2013. "R&D, Socio-Economic Conditions, and Regional Innovation in the U.S," Growth and Change, Wiley Blackwell, vol. 44(2), pages 287-320, June.
    6. Vincent Mangematin & Paul O’Reilly & James Cunningham, 2014. "PIs as boundary spanners, science and market shapers," The Journal of Technology Transfer, Springer, vol. 39(1), pages 1-10, February.
    7. Jeffrey M. Keisler & Christy M. Foran & Maija M. Kuklja & Igor Linkov, 2017. "Undue concentration of research and education: multi-criteria decision approach to assess jurisdiction eligibility for NSF funding," Environment Systems and Decisions, Springer, vol. 37(3), pages 367-378, September.
    8. Jianping Li & Yongjia Xie & Dengsheng Wu & Yuanping Chen, 2017. "Underestimating or overestimating the distribution inequality of research funding? The influence of funding sources and subdivision," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 55-74, July.
    9. Huang, Ding-wei, 2018. "Optimal distribution of science funding," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 613-618.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bozeman, Barry & Youtie, Jan, 2017. "Socio-economic impacts and public value of government-funded research: Lessons from four US National Science Foundation initiatives," Research Policy, Elsevier, vol. 46(8), pages 1387-1398.
    2. Jeffrey M. Keisler & Christy M. Foran & Maija M. Kuklja & Igor Linkov, 2017. "Undue concentration of research and education: multi-criteria decision approach to assess jurisdiction eligibility for NSF funding," Environment Systems and Decisions, Springer, vol. 37(3), pages 367-378, September.
    3. Julia Melkers & Agrita Kiopa, 2010. "The Social Capital of Global Ties in Science: The Added Value of International Collaboration," Review of Policy Research, Policy Studies Organization, vol. 27(4), pages 389-414, July.
    4. Andrea Fronzetti Colladon & Ciriaco Andrea D’Angelo & Peter A. Gloor, 2020. "Predicting the future success of scientific publications through social network and semantic analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 357-377, July.
    5. Dietz, James S. & Bozeman, Barry, 2005. "Academic careers, patents, and productivity: industry experience as scientific and technical human capital," Research Policy, Elsevier, vol. 34(3), pages 349-367, April.
    6. Julia Melkers & Yonghong Wu, 2009. "Evaluating the Improved Research Capacity of EPSCoR States: R&D Funding and Collaborative Networks in the NSF EPSCoR Program," Review of Policy Research, Policy Studies Organization, vol. 26(6), pages 761-782, November.
    7. Lu, Wei & Ren, Yan & Huang, Yong & Bu, Yi & Zhang, Yuehan, 2021. "Scientific collaboration and career stages: An ego-centric perspective," Journal of Informetrics, Elsevier, vol. 15(4).
    8. Duk Hee Lee & Il Won Seo & Ho Chull Choe & Hee Dae Kim, 2012. "Collaboration network patterns and research performance: the case of Korean public research institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(3), pages 925-942, June.
    9. Belén Álvarez-Bornstein & Adrián A. Díaz-Faes & María Bordons, 2019. "What characterises funded biomedical research? Evidence from a basic and a clinical domain," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 805-825, May.
    10. Jan Resenga Maluleka & Omwoyo Bosire Onyancha & Isola Ajiferuke, 2016. "Factors influencing research collaboration in LIS schools in South Africa," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 337-355, May.
    11. Saskia C. Hin, 2013. "Interdisciplinary research collaboration as the future of ancient history? Insights from spying on demographers," MPIDR Working Papers WP-2013-002, Max Planck Institute for Demographic Research, Rostock, Germany.
    12. Malte Hückstädt, 2022. "Coopetition between frenemies–interrelations and effects of seven collaboration problems in research clusters," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5191-5224, September.
    13. Andrej Kastrin & Jelena Klisara & Borut Lužar & Janez Povh, 2017. "Analysis of Slovenian research community through bibliographic networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 791-813, February.
    14. Giovanni Abramo & Ciriaco Andrea D'Angelo & Flavia Costa, 2012. "Identifying interdisciplinarity through the disciplinary classification of coauthors of scientific publications," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(11), pages 2206-2222, November.
    15. van Rijnsoever, Frank J. & Hessels, Laurens K., 2011. "Factors associated with disciplinary and interdisciplinary research collaboration," Research Policy, Elsevier, vol. 40(3), pages 463-472, April.
    16. Christopher S. Hayter, 2016. "A trajectory of early-stage spinoff success: the role of knowledge intermediaries within an entrepreneurial university ecosystem," Small Business Economics, Springer, vol. 47(3), pages 633-656, October.
    17. Corsini, Alberto & Pezzoni, Michele & Visentin, Fabiana, 2022. "What makes a productive Ph.D. student?," Research Policy, Elsevier, vol. 51(10).
    18. Mehdi Rhaiem & Nabil Amara, 2020. "Determinants of research efficiency in Canadian business schools: evidence from scholar-level data," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 53-99, October.
    19. Josh Yamamoto & Eitan Frachtenberg, 2022. "Gender Differences in Collaboration Patterns in Computer Science," Publications, MDPI, vol. 10(1), pages 1-21, February.
    20. Malte Hückstädt, 2023. "Ten reasons why research collaborations succeed—a random forest approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1923-1950, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:respol:v:39:y:2010:i:6:p:835-841. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/respol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.