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Can Calibration Reconcile Stated and Observed Preferences?

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  • Norwood, F. Bailey

Abstract

Hypothetical bias is a pervasive problem in stated-preference experiments. Recent research has developed two empirically successful calibrations to remove hypothetical bias, though the calibrations have not been tested using the same data or in a conjoint analysis. This study compares the two calibrations in a conjoint analysis involving donations to a public good. Results find the calibrations are biased predictors of true donations but that calibrated and uncalibrated models together provide upper and lower bounds to true donations.

Suggested Citation

  • Norwood, F. Bailey, 2005. "Can Calibration Reconcile Stated and Observed Preferences?," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 37(01), April.
  • Handle: RePEc:ags:joaaec:43735
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    References listed on IDEAS

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    1. Christian A. Vossler & Robert G. Ethier & Gregory L. Poe & Michael P. Welsh, 2003. "Payment Certainty in Discrete Choice Contingent Valuation Responses: Results from a Field Validity Test," Southern Economic Journal, Southern Economic Association, vol. 69(4), pages 886-902, April.
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    3. Messer, Kent D. & Kaiser, Harry M. & Schulze, William D., 2004. "Status Quo Bias and Voluntary Contributions: Can Lab Experiments Parallel Real World Outcomes for Generic Advertising?," Research Bulletins 122094, Cornell University, Department of Applied Economics and Management.
    4. Karen Blumenschein & Magnus Johannesson & Glenn C. Blomquist & Bengt Liljas & Richard M. O’Conor, 1998. "Experimental Results on Expressed Certainty and Hypothetical Bias in Contingent Valuation," Southern Economic Journal, Southern Economic Association, vol. 65(1), pages 169-177, July.
    5. Richard A. Hofler & John A. List, 2004. "Valuation on the Frontier: Calibrating Actual and Hypothetical Statements of Value," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(1), pages 213-221.
    6. Blumenschein, Karen & Johannesson, Magnus & Yokoyama, Krista K. & Freeman, Patricia R., 2001. "Hypothetical versus real willingness to pay in the health care sector: results from a field experiment," Journal of Health Economics, Elsevier, vol. 20(3), pages 441-457, May.
    7. John List & Craig Gallet, 2001. "What Experimental Protocol Influence Disparities Between Actual and Hypothetical Stated Values?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 20(3), pages 241-254, November.
    8. Winn, Chris & Norwood, F. Bailey & Chung, Chanjin & Ward, Clement E., 2004. "Surveying the Feasibility of a Voluntary Beef Checkoff," 2004 Annual meeting, August 1-4, Denver, CO 20385, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Patricia Champ & Richard Bishop, 2001. "Donation Payment Mechanisms and Contingent Valuation: An Empirical Study of Hypothetical Bias," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 19(4), pages 383-402, August.
    10. Gregory Poe & Jeremy Clark & Daniel Rondeau & William Schulze, 2002. "Provision Point Mechanisms and Field Validity Tests of Contingent Valuation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 23(1), pages 105-131, September.
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    Cited by:

    1. Rose, John M. & Beck, Matthew J. & Hensher, David A., 2015. "The joint estimation of respondent-reported certainty and acceptability with choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 71(C), pages 141-152.
    2. Fifer, Simon & Rose, John & Greaves, Stephen, 2014. "Hypothetical bias in Stated Choice Experiments: Is it a problem? And if so, how do we deal with it?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 61(C), pages 164-177.
    3. Moore, Rebecca & Colson, Gregory & Champ, Patricia, 2013. "The effect of decision rule and response format on hypothetical bias in contingent valuation," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150807, Agricultural and Applied Economics Association.
    4. Fifer, Simon & Rose, John M., 2016. "Can you ever be certain? Reducing hypothetical bias in stated choice experiments via respondent reported choice certaintyAuthor-Name: Beck, Matthew J," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 149-167.
    5. Richard C. Ready & Patricia A. Champ & Jennifer L. Lawton, 2010. "Using Respondent Uncertainty to Mitigate Hypothetical Bias in a Stated Choice Experiment," Land Economics, University of Wisconsin Press, vol. 86(2), pages 363-381.
    6. Beck, Matthew J. & Rose, John M. & Hensher, David A., 2013. "Consistently inconsistent: The role of certainty, acceptability and scale in choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 56(C), pages 81-93.
    7. Stephane Hess & Marek Giergiczny, 2015. "Intra-respondent Heterogeneity in a Stated Choice Survey on Wetland Conservation in Belarus: First Steps Towards Creating a Link with Uncertainty in Contingent Valuation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 60(3), pages 327-347, March.

    More about this item

    Keywords

    calibration; experimental economics; forecasting; hypothetical bias; public goods; stated preference; voluntary contributions; Research Methods/ Statistical Methods; Q51; H41;

    JEL classification:

    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods

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