IDEAS home Printed from https://ideas.repec.org/a/eee/eejocm/v43y2022ics175553452200015x.html
   My bibliography  Save this article

Optimal sequential strategy to improve the precision of the estimators in a discrete choice experiment: A simulation study

Author

Listed:
  • Pérez-Troncoso, Daniel

Abstract

In order to solve the problems related to prior parameter misspecification in DCEs, Bliemer and Rose (2010) proposed a sequential approach where the design is updated after each respondent. This paper tries to find a more efficient alternative sequential method since the original proposal could be very time-consuming and expensive under some circumstances.

Suggested Citation

  • Pérez-Troncoso, Daniel, 2022. "Optimal sequential strategy to improve the precision of the estimators in a discrete choice experiment: A simulation study," Journal of choice modelling, Elsevier, vol. 43(C).
  • Handle: RePEc:eee:eejocm:v:43:y:2022:i:c:s175553452200015x
    DOI: 10.1016/j.jocm.2022.100357
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S175553452200015X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jocm.2022.100357?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. John M. Rose & Michiel C.J. Bliemer, 2014. "Stated choice experimental design theory: the who, the what and the why," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 7, pages 152-177, Edward Elgar Publishing.
    2. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    3. Ferrini, Silvia & Scarpa, Riccardo, 2007. "Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study," Journal of Environmental Economics and Management, Elsevier, vol. 53(3), pages 342-363, May.
    4. Hynes, Stephen & Chen, Wenting & Vondolia, Kofi & Armstrong, Claire & O'Connor, Eamonn, 2021. "Valuing the ecosystem service benefits from kelp forest restoration: A choice experiment from Norway," Ecological Economics, Elsevier, vol. 179(C).
    5. Daniel McFadden, 1994. "Contingent Valuation and Social Choice," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(4), pages 689-708.
    6. Daniel Pérez-Troncoso & David M. Epstein & José A. Castañeda-García, 2021. "Consumers' Preferences and Willingness to Pay for Personalised Nutrition," Applied Health Economics and Health Policy, Springer, vol. 19(5), pages 757-767, September.
    7. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    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. Choi, Andy S., 2013. "Nonmarket values of major resources in the Korean DMZ areas: A test of distance decay," Ecological Economics, Elsevier, vol. 88(C), pages 97-107.
    2. Richard G. Newell & Juha Siikamäki, 2014. "Nudging Energy Efficiency Behavior: The Role of Information Labels," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 1(4), pages 555-598.
    3. Jianhua Wang & Jiaye Ge & Yuting Ma, 2018. "Urban Chinese Consumers’ Willingness to Pay for Pork with Certified Labels: A Discrete Choice Experiment," Sustainability, MDPI, vol. 10(3), pages 1-14, February.
    4. Mohammed H. Alemu & Søren Bøye Olsen & Suzanne E. Vedel & John Kinyuru & Kennedy O. Pambo, 2016. "Integrating sensory evaluations in incentivized discrete choice experiments to assess consumer demand for cricket flour buns in Kenya," IFRO Working Paper 2016/02, University of Copenhagen, Department of Food and Resource Economics.
    5. Scarpa, Riccardo & Rose, John M., 2008. "Design efficiency for non-market valuation with choice modelling: how to measure it, what to report and why," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 52(3), pages 1-30.
    6. Chenyi He & Lijia Shi & Zhifeng Gao & Lisa House, 2020. "The impact of customer ratings on consumer choice of fresh produce: A stated preference experiment approach," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 68(3), pages 359-373, September.
    7. Jürgen Meyerhoff & Ulf Liebe, 2009. "Status Quo Effect in Choice Experiments: Empirical Evidence on Attitudes and Choice Task Complexity," Land Economics, University of Wisconsin Press, vol. 85(3), pages 515-528.
    8. Parron, Lucilia Maria & Villanueva, Anastasio Jose & Glenk, Klaus, 2022. "Estimating the value of ecosystem services in agricultural landscapes amid intensification pressures: The Brazilian case," Ecosystem Services, Elsevier, vol. 57(C).
    9. John Gibson & Riccardo Scarpa & Halahingano Rohorua, 2013. "Respiratory Health of Pacific Island Immigrants and Preferences for Indoor Air Quality Determinants in New Zealand," Working Papers in Economics 13/09, University of Waikato.
    10. Heng, Yan & Lu, Chao-Lin & Yu, Luqing & Gao, Zhifeng, 2020. "The heterogeneous preferences for solar energy policies among US households," Energy Policy, Elsevier, vol. 137(C).
    11. Enni Ruokamo & Mikołaj Czajkowski & Nick Hanley & Artti Juutinen & Rauli Svento, 2016. "Linking perceived choice complexity with scale heterogeneity in discrete choice experiments: home heating in Finland," Working Papers 2016-30, Faculty of Economic Sciences, University of Warsaw.
    12. Giergiczny, Marek & Czajkowski, Mikołaj & Żylicz, Tomasz & Angelstam, Per, 2015. "Choice experiment assessment of public preferences for forest structural attributes," Ecological Economics, Elsevier, vol. 119(C), pages 8-23.
    13. Christoph Rheinberger, 2011. "A Mixed Logit Approach to Study Preferences for Safety on Alpine Roads," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 49(1), pages 121-146, May.
    14. Conti, G.; & Giustinelli, P.;, 2022. "For Better or Worse? Subjective Expectations and Cost-Benefit Trade-Offs in Health Behavior: An Application to Lockdown Compliance in the United Kingdom," Health, Econometrics and Data Group (HEDG) Working Papers 22/14, HEDG, c/o Department of Economics, University of York.
    15. Irie, Noriko & Kawahara, Naoko, 2022. "Consumer preferences for local renewable electricity production in Japan: A choice experiment," Renewable Energy, Elsevier, vol. 182(C), pages 1171-1181.
    16. Cicia, Gianni & Cembalo, Luigi & Del Giudice, Teresa & Scarpa, Riccardo, 2011. "The Impact of Country-of-Origin Information on Consumer Perception of Environment-Friendly Characteristics," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 2(1), pages 1-7, September.
    17. Meenakshi, J.V. & Banerji, A. & Manyong, Victor & Tomlins, Keith & Mittal, Nitya & Hamukwala, Priscilla, 2012. "Using a discrete choice experiment to elicit the demand for a nutritious food: Willingness-to-pay for orange maize in rural Zambia," Journal of Health Economics, Elsevier, vol. 31(1), pages 62-71.
    18. Bakhtiari, Fatemeh & Jacobsen, Jette Bredahl & Thorsen, Bo Jellesmark & Lundhede, Thomas Hedemark & Strange, Niels & Boman, Mattias, 2018. "Disentangling Distance and Country Effects on the Value of Conservation across National Borders," Ecological Economics, Elsevier, vol. 147(C), pages 11-20.
    19. Sheremet, Oleg & Ruokamo, Enni & Juutinen, Artti & Svento, Rauli & Hanley, Nick, 2018. "Incentivising Participation and Spatial Coordination in Payment for Ecosystem Service Schemes: Forest Disease Control Programs in Finland," Ecological Economics, Elsevier, vol. 152(C), pages 260-272.
    20. Franceschinis, Cristiano & Thiene, Mara & Scarpa, Riccardo & Rose, John & Moretto, Michele & Cavalli, Raffaele, 2017. "Adoption of renewable heating systems: An empirical test of the diffusion of innovation theory," Energy, Elsevier, vol. 125(C), pages 313-326.

    More about this item

    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:eee:eejocm:v:43:y:2022:i:c:s175553452200015x. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/journal-of-choice-modelling .

    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.