IDEAS home Printed from https://ideas.repec.org/a/vrs/offsta/v39y2023i1p103-121n6.html
   My bibliography  Save this article

A Statistical Comparison of Call Volume Uniformity Due to Mailing Strategy

Author

Listed:
  • Raim Andrew M.
  • Nichols Elizabeth
  • Mathew Thomas

    (1 U.S. Census Bureau, Washington, D.C., 20233, U.S.A.)

Abstract

For operations such as a decennial census, the U.S. Census Bureau sends mail to potential respondents inviting a self-response. It is suspected that the mailing strategy affects the distribution of call volumes to the U.S. Census Bureau's telephone helplines. For staffing purposes, more uniform call volumes throughout the week are desirable. In this work, we formulate tests and confidence intervals to compare uniformity of call volumes resulting from competing mailing strategies. Regarding the data as multinomial observations, we compare pairs of call volume observations to determine whether one mailing strategy has multinomial cell probabilities closer to the uniform probability vector compared to another strategy. A motivating illustration is provided by call volume data recorded in three studies which were carried out in advance of the 2020 Decennial Census.

Suggested Citation

  • Raim Andrew M. & Nichols Elizabeth & Mathew Thomas, 2023. "A Statistical Comparison of Call Volume Uniformity Due to Mailing Strategy," Journal of Official Statistics, Sciendo, vol. 39(1), pages 103-121, March.
    • Handle: RePEc:vrs:offsta:v:39:y:2023:i:1:p:103-121:n:6
    DOI: 10.2478/jos-2023-0005
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/jos-2023-0005
    Download Restriction: no
    File URL: https://libkey.io/10.2478/jos-2023-0005?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    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. Fabrice Gilles & Sabina Issehnane & Florent Sari, 2022. "Using short-term jobs as a way to find a regular job. What kind of role for local context?," TEPP Working Paper 2022-07, TEPP.
    2. repec:hal:spmain:info:hdl:2441/dambferfb7dfprc9m052g20qh is not listed on IDEAS
    3. Paulo M. D. C. Parente & Richard J. Smith, 2021. "Quasi‐maximum likelihood and the kernel block bootstrap for nonlinear dynamic models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(4), pages 377-405, July.
    4. Cornelia Lawson, 2013. "Academic Inventions Outside the University: Investigating Patent Ownership in the UK," Industry and Innovation, Taylor & Francis Journals, vol. 20(5), pages 385-398, July.
    5. Vipin Arora & Shuping Shi, 2016. "Nonlinearities and tests of asset price bubbles," Empirical Economics, Springer, vol. 50(4), pages 1421-1433, June.
    6. Luiz Paulo Fávero & Joseph F. Hair & Rafael de Freitas Souza & Matheus Albergaria & Talles V. Brugni, 2021. "Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships," Mathematics, MDPI, vol. 9(10), pages 1-28, May.
    7. Da Fonseca José & Grasselli Martino & Ielpo Florian, 2014. "Estimating the Wishart Affine Stochastic Correlation Model using the empirical characteristic function," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 1-37, May.
    8. Hansen, Lars Peter & Heaton, John & Luttmer, Erzo G J, 1995. "Econometric Evaluation of Asset Pricing Models," The Review of Financial Studies, Society for Financial Studies, vol. 8(2), pages 237-274.
    9. Das, Marcel & van Soest, Arthur, 1999. "A panel data model for subjective information on household income growth," Journal of Economic Behavior & Organization, Elsevier, vol. 40(4), pages 409-426, December.
    10. Gillespie, Colin S., 2015. "Fitting Heavy Tailed Distributions: The poweRlaw Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(i02).
    11. Luis Garicano & Thomas N. Hubbard, 2016. "The Returns to Knowledge Hierarchies," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 32(4), pages 653-684.
    12. Yen, Steven T. & Chern, Wen S. & Lee, Hwang-Jaw, 1991. "Effects Of Income Sources On Household Food Expenditures," 1991 Annual Meeting, August 4-7, Manhattan, Kansas 271167, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    13. Adrian Bruhin & Ernst Fehr & Daniel Schunk, 2019. "The many Faces of Human Sociality: Uncovering the Distribution and Stability of Social Preferences," Journal of the European Economic Association, European Economic Association, vol. 17(4), pages 1025-1069.
    14. Bel, K. & Paap, R., 2013. "Modeling the impact of forecast-based regime switches on macroeconomic time series," Econometric Institute Research Papers EI 2013-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    15. Seok, Sang Ik & Cho, Hoon & Ryu, Doojin, 2020. "The information content of funds from operations and net income in real estate investment trusts," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    16. Downward, Paul & Rasciute, Simona, 2015. "Assessing the impact of the National Cycle Network and physical activity lifestyle on cycling behaviour in England," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 425-437.
    17. Filiz-Ozbay, Emel & Guryan, Jonathan & Hyndman, Kyle & Kearney, Melissa & Ozbay, Erkut Y., 2015. "Do lottery payments induce savings behavior? Evidence from the lab," Journal of Public Economics, Elsevier, vol. 126(C), pages 1-24.
    18. Arthur Caplan & John Gilbert, 2010. "Can fighting grade inflation help the bottom line?," Applied Economics Letters, Taylor & Francis Journals, vol. 17(17), pages 1663-1667.
    19. Mozhaeva, Irina, 2022. "Inequalities in utilization of institutional care among older people in Estonia," Health Policy, Elsevier, vol. 126(7), pages 704-714.
    20. Magnus, Jan R., 2007. "The Asymptotic Variance Of The Pseudo Maximum Likelihood Estimator," Econometric Theory, Cambridge University Press, vol. 23(5), pages 1022-1032, October.
    21. repec:lan:wpaper:2935 is not listed on IDEAS
    22. Ronelle Burger & Canh Thien Dang & Trudy Owens, 2017. "Better performing NGOs do report more accurately: Evidence from investigating Ugandan NGO financial accounts," Discussion Papers 2017-10, University of Nottingham, CREDIT.

    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:vrs:offsta:v:39:y:2023:i:1:p:103-121:n:6. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    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.