IDEAS home Printed from https://ideas.repec.org/p/ven/wpaper/202528.html

A Negative Binomial model for the donations count in Fundraising Management

Author

Listed:
  • Luca Barzanti

    (University of Bologna)

  • Martina Nardon

    (Ca’ Foscari University of Venice)

Abstract

Forecasting expected gifts is a key task in Fundraising Management. In this study, we propose modeling a gift as an individual risk that can be analyzed from multiple perspectives: the occurrence, frequency, and timing of donations, as well as their monetary amounts. We focus specifically on modeling the number of donations as a Poisson random variable whose intensity parameter depends on individual donor characteristics. By introducing a Gamma-distributed heterogeneity factor, a Negative Binomial model arises as a natural extension of the starting framework. This approach enables the estimation of both the expected number of donations and the probability of a gift through Negative Binomial regression. We illustrate the methodology with an empirical application.

Suggested Citation

  • Luca Barzanti & Martina Nardon, 2025. "A Negative Binomial model for the donations count in Fundraising Management," Working Papers 2025: 28, Department of Economics, University of Venice "Ca' Foscari".
  • Handle: RePEc:ven:wpaper:2025:28
    as

    Download full text from publisher

    File URL: https://www.unive.it/web/fileadmin/user_upload/dipartimenti/DEC/doc/Pubblicazioni_scientifiche/working_papers/2025/WP_DSE_barzanti_nardon_28_25.pdf
    File Function: First version, anno
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. William Smith & Cyril Chang, 2002. "Shipping the good apples out: a note on contributions of time and money," Economics Bulletin, AccessEcon, vol. 10(1), pages 1-14.
    2. Duncan, Brian, 1999. "Modeling charitable contributions of time and money," Journal of Public Economics, Elsevier, vol. 72(2), pages 213-242, May.
    3. Duffy, John & Ochs, Jack & Vesterlund, Lise, 2007. "Giving little by little: Dynamic voluntary contribution games," Journal of Public Economics, Elsevier, vol. 91(9), pages 1708-1730, September.
    4. Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Causal Machine-Learning Approach," Papers 2103.10251, arXiv.org, revised Sep 2021.
    5. G. A. Verhaert & D. Van Den Poel, 2012. "The Role of Seed Money and Threshold Size in Optimizing Fundraising Campaigns: Past Behavior Matters!," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/815, Ghent University, Faculty of Economics and Business Administration.
    6. Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Machine-Learning Approach," Economics working papers 2021-08, Department of Economics, Johannes Kepler University Linz, Austria.
    7. repec:ebl:ecbull:v:10:y:2002:i:1:p:1-14 is not listed on IDEAS
    8. Leily Farrokhvar & Azadeh Ansari & Behrooz Kamali, 2018. "Predictive models for charitable giving using machine learning techniques," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-14, October.
    Full references (including those not matched with items on IDEAS)

    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. Diana Barro & Luca Barzanti & Marco Corazza & Martina Nardon, 2023. "Machine Learning and Fundraising: Applications of Artificial Neural Networks," Working Papers 2023: 33, Department of Economics, University of Venice "Ca' Foscari".
    2. Corina Haita-Falah, 2021. "Bygones in a public project," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 57(2), pages 229-256, August.
    3. Cappellari, Lorenzo & Ghinetti, Paolo & Turati, Gilberto, 2011. "On time and money donations," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(6), pages 853-867.
    4. Takanori Ida & Takunori Ishihara & Koichiro Ito & Daido Kido & Toru Kitagawa & Shosei Sakaguchi & Shusaku Sasaki, 2021. "Paternalism, Autonomy, or Both? Experimental Evidence from Energy Saving Programs," Papers 2112.09850, arXiv.org.
    5. Achim Ahrens & Alessandra Stampi‐Bombelli & Selina Kurer & Dominik Hangartner, 2024. "Optimal multi‐action treatment allocation: A two‐phase field experiment to boost immigrant naturalization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1379-1395, November.
    6. Minguez, Ana & Javier Sese, F., 2022. "Why do you want a relationship, anyway? Consent to receive marketing communications and donors’ willingness to engage with nonprofits," Journal of Business Research, Elsevier, vol. 148(C), pages 356-367.
    7. Eva Macková & Vojtech Stanek, 2005. "Teoretické prístupy k ekonomike dobrovoľníctva ako fenoménu sociálnej práce [Theoretical approaches to the economics of volunteering as a social labour phenomenon]," Politická ekonomie, Prague University of Economics and Business, vol. 2005(5), pages 634-645.
    8. He Tingting, 2021. "Comparing Money and Time Donation: What Do Experiments Tell Us?," Marketing of Scientific and Research Organizations, Sciendo, vol. 41(3), pages 65-94, September.
    9. Al-Ubaydli, Omar & Yeomans, Mike, 2017. "Do people donate more when they perceive a single beneficiary whom they know? A field experimental test of the identifiability effect," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 66(C), pages 96-103.
    10. Aoki, Yu, 2014. "Donating Time to Charity: Not Working for Nothing," IZA Discussion Papers 7990, IZA Network @ LISER.
    11. Warren B. Hrung, 2004. "After‐Life Consumption and Charitable Giving," American Journal of Economics and Sociology, Wiley Blackwell, vol. 63(3), pages 731-745, July.
    12. van de Ven, J., 2000. "The Economics of the Gift," Other publications TiSEM c4c17d0c-941f-4bb6-b9e6-e, Tilburg University, School of Economics and Management.
    13. De Gruyter, Elaine & Petrie, Dennis & Black, Nicole, 2023. "Household donations of time and money in response to a health shock," Social Science & Medicine, Elsevier, vol. 333(C).
    14. Gaechter, S. & Mengel, F. & Tsakas, E. & Vostroknutov, A., 2013. "Growth and inequality in public good games," Research Memorandum 070, Maastricht University, Graduate School of Business and Economics (GSBE).
    15. Chau Do & Irina Paley, 2012. "Altruism from the house: the impact of home equity on charitable giving," Review of Economics of the Household, Springer, vol. 10(3), pages 375-393, September.
    16. Lilley, Andrew & Slonim, Robert, 2014. "The price of warm glow," Journal of Public Economics, Elsevier, vol. 114(C), pages 58-74.
    17. Wei Yang, 2016. "Are contributions of time and money substitutes or complements?," Applied Economics, Taylor & Francis Journals, vol. 48(37), pages 3526-3537, August.
    18. Ludwig, Sandra & Strassmair, Christina, 2009. "An Experimental study on the information structure in teams," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 277, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
    19. Altınok, Ahmet & Yılmaz, Murat, 2018. "Dynamic voluntary contribution to a public project under time inconsistency," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 114-140.
    20. Nisvan Erkal & Boon Han Koh & Nguyen Lam, 2023. "Using Milestones as a Source of Feedback in Teamwork: Insights from a Dynamic Voluntary Contribution Mechanism," Discussion Papers 2310, University of Exeter, Department of Economics.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • D64 - Microeconomics - - Welfare Economics - - - Altruism; Philanthropy; Intergenerational Transfers
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:ven:wpaper:2025:28. 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: Sassano Sonia (email available below). General contact details of provider: https://edirc.repec.org/data/dsvenit.html .

    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.