IDEAS home Printed from https://ideas.repec.org/a/bla/ajarec/v54y2010i4p407-420.html
   My bibliography  Save this article

Choice experiment adaptive design benefits: a case study

Author

Listed:
  • Geoffrey N. Kerr
  • Basil M. H. Sharp

Abstract

Efficient experimental designs offer the potential to reduce required sample sizes, or to reduce confidence intervals for parameters of interest, in choice experiments. Choice experiment designs have typically addressed efficiency of utility function parameter estimates. The recently developed concept of C-efficiency recognises the salience of willingness to pay estimates rather than utility function parameters in studies that seek to put money values on attributes. C-efficiency design benefits have been illustrated in a theoretical context, but have not been tested in applied settings. This study reports a choice experiment field application that used initial responses to update statistical designs to maximise C-efficiency. Consistent with theoretical predictions, the revised design delivered significant reductions in the variance of willingness to pay estimates, illustrating that C-efficient designs can indeed decrease costs of choice experiments by reducing required sample sizes. Copyright 2010 The Authors. AJARE 2010 Australian Agricultural and Resource Economics Society Inc. and Blackwell Publishing Asia Pty Ltd.

Suggested Citation

  • Geoffrey N. Kerr & Basil M. H. Sharp, 2010. "Choice experiment adaptive design benefits: a case study ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(4), pages 407-420, October.
  • Handle: RePEc:bla:ajarec:v:54:y:2010:i:4:p:407-420
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1467-8489.2010.00507.x
    File Function: link to full text
    Download Restriction: Access to full text is restricted to subscribers.

    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. Espey, Molly, 1998. "Gasoline demand revisited: an international meta-analysis of elasticities," Energy Economics, Elsevier, vol. 20(3), pages 273-295, June.
    2. Jasper M. Dalhuisen & Raymond J. G. M. Florax & JHenri L. F. de Groot & Peter Nijkamp, 2003. "Price and Income Elasticities of Residential Water Demand: A Meta-Analysis," Land Economics, University of Wisconsin Press, vol. 79(2), pages 292-308.
    3. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    4. James Banks & Richard Blundell & Arthur Lewbel, 1997. "Quadratic Engel Curves And Consumer Demand," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 527-539, November.
    5. Alston, Julian M. & Chalfant, James A., 1991. "Can We Take The Con Out Of Meat Demand Studies?," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 16(01), July.
    6. Richardson, Robert A., 1976. "Structural Estimates Of Domestic Demand For Agricultural Products In Australia: A Review," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 44(03), September.
    7. Blundell, Richard & Pashardes, Panos & Weber, Guglielmo, 1993. "What Do We Learn About Consumer Demand Patterns from Micro Data?," American Economic Review, American Economic Association, vol. 83(3), pages 570-597, June.
    8. Craig A. Gallet, 2007. "The demand for alcohol: a meta-analysis of elasticities," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 51(2), pages 121-135, June.
    9. Craig A. Gallet, 2010. "Meat Meets Meta: A Quantitative Review of the Price Elasticity of Meat," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(1), pages 258-272.
    10. Craig A. Gallet & John A. List, 2003. "Cigarette demand: a meta-analysis of elasticities," Health Economics, John Wiley & Sons, Ltd., vol. 12(10), pages 821-835.
    11. Bollino, Carlo Andrea, 1987. "Gaids: a generalised version of the almost ideal demand system," Economics Letters, Elsevier, vol. 23(2), pages 199-202.
    12. G. M. Kuznets, 1953. "Measurement of Market Demand with Particular Reference to Consumer Demand for Food," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 35(5), pages 878-895.
    13. Moschini, Giancarlo & Moro, Daniele, 1996. "Structural Change and Demand Analysis: A Cursory Review," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, pages 239-261.
    14. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
    15. Denton, Frank T. & Mountain, Dean C., 2001. "Income distribution and aggregation/disaggregation biases in the measurement of consumer demand elasticities," Economics Letters, Elsevier, vol. 73(1), pages 21-28, October.
    16. Chouinard Hayley H & Davis David E & LaFrance Jeffrey T & Perloff Jeffrey M, 2007. "Fat Taxes: Big Money for Small Change," Forum for Health Economics & Policy, De Gruyter, vol. 10(2), pages 1-30, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kerr, Geoffrey N. & Abell, Walter L., 2014. "What’s your game? Heterogeneity amongst New Zealand hunters," 2014 Conference, August 28-29, 2014, Nelson, New Zealand 187501, New Zealand Agricultural and Resource Economics Society.
    2. Rungie, Cam & Scarpa, Riccardo & Thiene, Mara, 2014. "The influence of individuals in forming collective household preferences for water quality," Journal of Environmental Economics and Management, Elsevier, vol. 68(1), pages 161-174.
    3. Richard Yao & Riccardo Scarpa & John Rose & James Turner, 2015. "Experimental Design Criteria and Their Behavioural Efficiency: An Evaluation in the Field," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(3), pages 433-455, November.
    4. Yao, Richard T. & Scarpa, Riccardo & Turner, James A. & Barnard, Tim D. & Rose, John M. & Palma, João H.N. & Harrison, Duncan R., 2014. "Valuing biodiversity enhancement in New Zealand's planted forests: Socioeconomic and spatial determinants of willingness-to-pay," Ecological Economics, Elsevier, vol. 98(C), pages 90-101.

    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:bla:ajarec:v:54:y:2010:i:4:p:407-420. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum). General contact details of provider: http://edirc.repec.org/data/aaresea.html .

    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.

    We have no references for this item. You can help adding them by using 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.