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Relation of early career performance and recognition to the probability of winning the Nobel Prize in economics

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  • Ho F. Chan

    (Queensland University of Technology)

  • Franklin G. Mixon

    (Columbus State University)

  • Benno Torgler

    (Queensland University of Technology)

Abstract

To explore the relation between early career performance or recognition and receiving the Nobel Prize in Economic Sciences, we compare winners of the John Bates Clark Medal, the most prestigious early career recognition for economists, with other successful scholars. The initial comparison combines JBCM winners with scholars published in leading economics journals, controlling for educational background (institution conferring the Ph.D.) and publication and citation success. We then narrow the comparison group down to those given relatively early recognition (based on age category) in the form of other major awards. Lastly, we compare the JBCM awardees with synthetic counterfactuals that best resemble their pre-award academic career performance. All three analyses provide strong support for the notion that winning the JBCM is related to receiving the Nobel Prize, the award of which is also correlated with early career performance success as measured by number of publications and citations.

Suggested Citation

  • Ho F. Chan & Franklin G. Mixon & Benno Torgler, 2018. "Relation of early career performance and recognition to the probability of winning the Nobel Prize in economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 1069-1086, March.
    • Handle: RePEc:spr:scient:v:114:y:2018:i:3:d:10.1007_s11192-017-2614-5
    DOI: 10.1007/s11192-017-2614-5
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    Cited by:

    1. Ho Fai Chan & Benno Torgler, 2020. "Gender differences in performance of top cited scientists by field and country," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2421-2447, December.
    2. Torgler Benno, 2019. "To the John Bates Clark Medal Committee," Open Economics, De Gruyter, vol. 2(1), pages 40-42, January.
    3. Iván Aranzales & Ho Fai Chan & Benno Torgler, 2023. "Finally! How time lapse in Nobel Prize reception affects emotionality in the Nobel Prize banquet speeches," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(7), pages 4089-4115, July.
    4. Jianhua Hou & Bili Zheng & Yang Zhang & Chaomei Chen, 2021. "How do Price medalists’ scholarly impact change before and after their awards?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5945-5981, July.
    5. Tol, Richard S.J., 2023. "Nobel begets Nobel in economics," Journal of Informetrics, Elsevier, vol. 17(4).
    6. Ho Fai Chan & Franklin G. Mixon & Benno Torgler, 2019. "Fame in the sciences: a culturomics approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(2), pages 605-615, February.
    7. Weilong Bi & Ho Fai Chan & Benno Torgler, 2019. "Self-esteem, self-symbolizing, and academic recognition: behavioral evidence from curricula vitae," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 495-525, April.
    8. João Ricardo Faria & Franklin G. Mixon, 2020. "The Peter and Dilbert Principles applied to academe," Economics of Governance, Springer, vol. 21(2), pages 115-132, June.
    9. Pandelis Mitsis, 2022. "The Nobel Prize time gap," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-11, December.
    10. Wen Lou & Jiangen He & Lingxin Zhang & Zhijie Zhu & Yongjun Zhu, 2023. "Support behind the scenes: the relationship between acknowledgement, coauthor, and citation in Nobel articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5767-5790, October.
    11. Bin Wang & Feng Wu & Lukui Shi, 2023. "AGSTA-NET: adaptive graph spatiotemporal attention network for citation count prediction," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 511-541, January.
    12. Jingda Ding & Yifan Chen & Chao Liu, 2023. "Exploring the research features of Nobel laureates in Physics based on the semantic similarity measurement," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5247-5275, September.
    13. Zhao, Qihang & Feng, Xiaodong, 2022. "Utilizing citation network structure to predict paper citation counts: A Deep learning approach," Journal of Informetrics, Elsevier, vol. 16(1).
    14. João Ricardo Faria & Franklin G. Mixon & William C. Sawyer, 2023. "Human Capital, Networks and Segmentation in the Market for Academic Economists," Economies, MDPI, vol. 11(6), pages 1-15, June.
    15. Ho Fai Chan & Franklin G. Mixon & Jayanta Sarkar & Benno Torgler, 2022. "Recognition and longevity: an examination of award timing and lifespan in Nobel laureates," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3629-3659, June.

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