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Statistical Framework: Estimating the Cumulative Shares of Nobel Prizes from 1901 to 2022

Author

Listed:
  • Xu Zhang

    (Department of Mathematics, University of Maryland, College Park, MD 20742, USA)

  • Bruce Golden

    (Robert H. Smith School of Business, University of Maryland, College Park, MD 20742, USA)

  • Edward Wasil

    (Kogod School of Business, American University, Washington, DC 20016, USA)

Abstract

Studying trends in the geographical distribution of the Nobel Prize is an interesting topic that has been examined in the academic literature. To track the trends, we develop a stochastic estimate for the cumulative shares of Nobel Prizes awarded to recipients in four geographical groups: North America, Europe, Asia, Other. Specifically, we propose two models to estimate how cumulative shares change over time in the four groups. We estimate parameters, develop a prediction interval for each model, and validate our models. Finally, we apply our approach to estimate the distribution of the cumulative shares of Nobel Prizes for the four groups from 1901 to 2022.

Suggested Citation

  • Xu Zhang & Bruce Golden & Edward Wasil, 2024. "Statistical Framework: Estimating the Cumulative Shares of Nobel Prizes from 1901 to 2022," Stats, MDPI, vol. 7(1), pages 1-15, January.
    • Handle: RePEc:gam:jstats:v:7:y:2024:i:1:p:7-109:d:1322804
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    References listed on IDEAS

    as
    1. Marasco, A. & Picucci, A. & Romano, A., 2016. "Market share dynamics using Lotka–Volterra models," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 49-62.
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