IDEAS home Printed from https://ideas.repec.org/a/vrs/offsta/v32y2016i3p549-578n1.html
   My bibliography  Save this article

Weighting Strategies for Combining Data from Dual-Frame Telephone Surveys: Emerging Evidence from Australia

Author

Listed:
  • Baffour Bernard

    (The University of Queensland - Institute for Social Science Research, Building 39A Campbell Road St Lucia, Brisbane, Queensland, 4067, Australia.)

  • Haynes Michele

    (The University of Queensland - Institute for Social Science Research, Building 39A Campbell Road St Lucia, Brisbane, Queensland, 4067, Australia.)

  • Western Mark

    (The University of Queensland - Institute for Social Science Research, Building 39A Campbell Road St Lucia, Brisbane, Queensland, 4067, Australia.)

  • Pennay Darren

    (Australian National University - Australian Centre for Applied Social Research Methods, Canberra, Australian Capital Territory, Australia.)

  • Misson Sebastian

    (The Social Research Centre - Research Methodology, Melbourne, Victoria, Australia.)

  • Martinez Arturo

    (The University of Queensland - Institute for Social Science Research, Building 39A Campbell Road St Lucia, Brisbane, Queensland, 4067, Australia.)

Abstract

Until quite recently, telephone surveys have typically relied on landline telephone numbers. However, with the increasing popularity and affordability of mobile phones, there has been a surge in households that do not have landline connections. Additionally, there has been a decline in the response rates and population coverage of landline telephone surveys, creating a challenge to collecting representative social data. Dual-frame telephone surveys that use both landline and mobile phone sampling frames can overcome the incompleteness of landline-only telephone sampling. However, surveying mobile phone users introduces new complexities in sampling, nonresponse measurement and statistical weighting. This article examines these issues and illustrates the consequences of failing to include mobile-phone-only users in telephone surveys using data from Australia. Results show that there are significant differences in estimates of populations’ characteristics when using information solely from the landline or mobile telephone sample. These biases in the population estimates are significantly reduced when data from the mobile and landline samples are combined and appropriate dual-frame survey estimators are used. The optimal choice of a dual-frame estimation strategy depends on the availability of good-quality information that can account for the differential patterns of nonresponse by frame.

Suggested Citation

  • Baffour Bernard & Haynes Michele & Western Mark & Pennay Darren & Misson Sebastian & Martinez Arturo, 2016. "Weighting Strategies for Combining Data from Dual-Frame Telephone Surveys: Emerging Evidence from Australia," Journal of Official Statistics, Sciendo, vol. 32(3), pages 549-578, September.
    • Handle: RePEc:vrs:offsta:v:32:y:2016:i:3:p:549-578:n:1
    DOI: 10.1515/jos-2016-0029
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/jos-2016-0029
    Download Restriction: no
    File URL: https://libkey.io/10.1515/jos-2016-0029?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. Britta Busse & Marek Fuchs, 2012. "The components of landline telephone survey coverage bias. The relative importance of no-phone and mobile-only populations," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(4), pages 1209-1225, June.
    2. Grace M. Barnes & John W. Welte & Marie-Cecile O. Tidwell & Joseph H. Hoffman, 2015. "Gambling and substance use: co-occurrence among adults in a recent general population study in the United States," International Gambling Studies, Taylor & Francis Journals, vol. 15(1), pages 55-71, April.
    3. Sonia Akter & Jeff Bennett, 2011. "Household perceptions of climate change and preferences for mitigation action: the case of the Carbon Pollution Reduction Scheme in Australia," Climatic Change, Springer, vol. 109(3), pages 417-436, December.
    4. Prepared for AAPOR Council by the Cell Phone Task Force operating under the auspices of the AAPOR Standards Committee of which John Hall is a member, 2010. "New Considerations for Survey Researchers When Planning and Conducting RDD Telephone Surveys in the US with Respondents Reached Via Cell Phone Numbers," Mathematica Policy Research Reports 23c89114b85e4baf9cea146d3, Mathematica Policy Research.
    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. Dienes, Christian, 2015. "Actions and intentions to pay for climate change mitigation: Environmental concern and the role of economic factors," Ecological Economics, Elsevier, vol. 109(C), pages 122-129.
    2. Ahmet Tolunay & Çağlar Başsüllü, 2015. "Willingness to Pay for Carbon Sequestration and Co-Benefits of Forests in Turkey," Sustainability, MDPI, vol. 7(3), pages 1-27, March.
    3. Jens Abildtrup & Jette Bredahl Jacobsen & Suzanne Elizabeth Vedel & Udo Mantau & Robert Mavsar & Davide Pettenella & Irina Prokofieva & Florian Schubert & Anne Stenger & Elsa Varela & Enrico Vidale & , 2024. "Preferences for climate change policies: the role of co-benefits," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 13(1), pages 110-128, January.
    4. Giuseppe Coco & Daniele Simone & Laura Serlenga & Sabrina Molinaro, 2023. "Risk awareness and complexity in students’ gambling," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 40(3), pages 971-994, October.
    5. Benjamin, Emmanuel O. & Hall, Daniel & Sauer, Johannes & Buchenrieder, Gertrud, 2022. "Are carbon pricing policies on a path to failure in resource-dependent economies? A willingness-to-pay case study of Canada," Energy Policy, Elsevier, vol. 162(C).
    6. Antonio Arcos & María del Mar Rueda & Manuel Trujillo & David Molina, 2015. "Review of Estimation Methods for Landline and Cell Phone Surveys," Sociological Methods & Research, , vol. 44(3), pages 458-485, August.
    7. Shewmake, Sharon & Okrent, Abigail M. & Thabrew, Lanka & Vandenbergh, Michael, 2012. "Carbon Labeling for Consumer Food Goods," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124369, Agricultural and Applied Economics Association.
    8. Mohorko Anja & Leeuw Edith de & Hox Joop, 2013. "Internet Coverage and Coverage Bias in Europe: Developments Across Countries and Over Time," Journal of Official Statistics, Sciendo, vol. 29(4), pages 609-622, December.
    9. Artjoms Ivlevs, 2019. "Adverse Welfare Shocks and Pro‐Environmental Behavior: Evidence from the Global Economic Crisis," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 65(2), pages 293-311, June.
    10. Dafne Muntanyola Saura & Pedro Romero Balsas, 2014. "Interviewing and surveying over the phone: a reflexive account of a research on parenting," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(5), pages 2615-2630, September.
    11. Hou, L. & Min, S. & Huang, Q. & Huang, J., 2018. "Farmers perceptions of, ex ante and ex post adaptations to drought: Empirical evidence from maize farmers in China," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277208, International Association of Agricultural Economists.
    12. Xiaoyi Wen & Shangjiu Wang & Shaoyong Li & Liang Cheng & Keqiang Li & Qing Zheng & Baoreng Zhang, 2024. "Impact Factors of Industrial Pollution and Carbon Reduction under the “Dual Carbon” Target: A Case Study of Urban Aggregation in the Pearl River Delta and Yangtze River Delta," Sustainability, MDPI, vol. 16(5), pages 1-16, February.
    13. Diederich, Johannes & Goeschl, Timo, 2011. "Willingness to Pay for Individual Greenhouse Gas Emissions Reductions: Evidence from a Large Field Experiment," Working Papers 0517, University of Heidelberg, Department of Economics.
    14. Alló, Maria & Loureiro, Maria L., 2014. "The role of social norms on preferences towards climate change policies: A meta-analysis," Energy Policy, Elsevier, vol. 73(C), pages 563-574.
    15. Acquah, H. de-Graft & Onumah, Edward E., 2011. "Farmers Perception and Adaptation to Climate Change: An Estimation of Willingness to Pay," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 3(4), pages 1-9, December.
    16. Tanya O'Garra & Susana Mourato, 2016. "Are we willing to give what it takes? Willingness to pay for climate change adaptation in developing countries," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 5(3), pages 249-264, September.
    17. Johannes Diederich & Timo Goeschl, 2014. "Willingness to Pay for Voluntary Climate Action and Its Determinants: Field-Experimental Evidence," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 57(3), pages 405-429, March.
    18. Galina Williams, 2015. "Households Willingness to Pay for the Emissions Reduction Policy, Queensland, Australia," SAGE Open, , vol. 5(3), pages 21582440156, September.
    19. Meng, Weizhen & Li, Shilin & Yang, Jinqiang, 2024. "Mitigating disaster risks caused by carbon emissions," Economics Letters, Elsevier, vol. 241(C).
    20. Wadud, Zia & Chintakayala, Phani Kumar, 2019. "Personal Carbon Trading: Trade-off and Complementarity Between In-home and Transport Related Emissions Reduction," Ecological Economics, Elsevier, vol. 156(C), pages 397-408.

    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:32:y:2016:i:3:p:549-578:n:1. 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.