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Choice experiment adaptive design benefits: a case study

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  • 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
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    File URL: http://hdl.handle.net/10.1111/j.1467-8489.2010.00507.x
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    Citations

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    Cited by:

    1. 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.
    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. Rajesh K. Rai & Mani Nepal & Laxmi D. Bhatta & Saudamini Das & Madan S. Khadayat & E. Somanathan & Kedar Baral, 2019. "Ensuring Water Availability to Water Users through Incentive Payment for Ecosystem Services Scheme: A Case Study in a Small Hilly Town of Nepal," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 5(04), pages 1-26, October.
    4. Lilavanichakul, Apichaya & Boecker, Andreas, 2013. "Consumer Acceptance of a New Traceability Technology: A Discrete Choice Application to Ontario Ginseng," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 16(4), pages 1-26, November.
    5. Xin Yang & Anlu Zhang & Fan Zhang, 2019. "Farmers’ Heterogeneous Willingness to Pay for Farmland Non-Market Goods and Services on the Basis of a Mixed Logit Model—A Case Study of Wuhan, China," IJERPH, MDPI, vol. 16(20), pages 1-14, October.
    6. Kerr, Geoffrey N. & Abell, Walter L., 2014. "Hunting for optimality: preferences for Sika deer hunting experiences," 2014 Conference (58th), February 4-7, 2014, Port Macquarie, Australia 165845, Australian Agricultural and Resource Economics Society.
    7. 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.
    8. 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.

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