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Systematic non-response in discrete choice experiments: implications for the valuation of climate risk reductions

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  • Robert J. Johnston
  • Abdulallah S. Abdulrahman

Abstract

Discrete choice experiments (DCEs) addressing adaptation to climate-related risks may be subject to response biases associated with variations in risk exposure across sampled populations. Systematic adjustments for such response patterns are hindered by the absence of rigorous, standardised selection-correction models for multinomial DCEs, together with a lack of information on non-respondents. This paper illustrates an empirical approach to accommodate risk-related response patterns in DCEs, where variations in risk exposure may be linked to observable landscape characteristics. The approach adapts reduced form response-propensity models to correct for survey non-response, capitalising on the fact that indicators of risk exposure may be linked to the geocoded locations of respondents and non-respondents. An application to coastal flood adaptation in Connecticut, USA illustrates implications for welfare estimation. Results demonstrate systematic effects of risk-related response patterns on estimated willingness to pay.

Suggested Citation

  • Robert J. Johnston & Abdulallah S. Abdulrahman, 2017. "Systematic non-response in discrete choice experiments: implications for the valuation of climate risk reductions," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 6(3), pages 246-267, July.
    • Handle: RePEc:taf:teepxx:v:6:y:2017:i:3:p:246-267
    DOI: 10.1080/21606544.2017.1284695
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    References listed on IDEAS

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    1. Trudy Ann Cameron & W. Douglas Shaw & Shannon R. Ragland & Sally Keefe & John M. (Mac) Callaway, 1996. "Using Distance and Zip Code Census Information For Nonresponse Correction In the Analysis of Mail Survey Data," UCLA Economics Working Papers 751, UCLA Department of Economics.
    2. A. Colin Cameron & Pravin K. Trivedi, 2010. "Microeconometrics Using Stata, Revised Edition," Stata Press books, StataCorp LP, number musr, March.
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    Cited by:

    1. Tharaka A. Jayalath & Patrick Lloyd-Smith & Marcus Becker, 2023. "Biodiversity Benefits of Birdwatching Using Citizen Science Data and Individualized Recreational Demand Models," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 86(1), pages 83-107, October.
    2. Salmai Qari & Tobias Börger & Tim Lohse & Jürgen Meyerhoff, 2023. "The Value of National Defense: Assessing Public Preferences for Defense Policy Options," CESifo Working Paper Series 10872, CESifo.
    3. Tobias Börger & Nick Hanley & Robert J. Johnston & Keila Meginnis & Tom Ndebele & Ghamz E. Ali Siyal & Frans de Vries, 2024. "Equity preferences and abatement cost sharing in international environmental agreements," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(1), pages 416-441, January.
    4. Klaus Glenk & Robert J. Johnston & Jürgen Meyerhoff & Julian Sagebiel, 2020. "Spatial Dimensions of Stated Preference Valuation in Environmental and Resource Economics: Methods, Trends and Challenges," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 75(2), pages 215-242, February.
    5. Robert J. Johnston & Ewa Zawojska, 2020. "Relative Versus Absolute Commodity Measurements in Benefit Transfer: Consequences for Validity and Reliability," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1245-1270, August.
    6. Hermine Vedogbeton & Robert J. Johnston, 2020. "Commodity Consistent Meta-Analysis of Wetland Values: An Illustration for Coastal Marsh Habitat," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 75(4), pages 835-865, April.
    7. Farolfi, Giulio & Johnston, Robert J., 2022. "Understanding Public Preferences for Shellfish Aquaculture Expansion: The Role of Production Technology and Environmental Impacts," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322131, Agricultural and Applied Economics Association.
    8. Kolstoe, Sonja & Naald, Brian Vander & Cohan, Alison, 2022. "A tale of two samples: Understanding WTP differences in the age of social media," Ecosystem Services, Elsevier, vol. 55(C).
    9. Robert J. Johnston & Tom Ndebele & David A. Newburn, 2023. "Modeling transaction costs in household adoption of landscape conservation practices," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(1), pages 341-367, January.
    10. Holland, Benedict M. & Johnston, Robert J., 2017. "Optimized quantity-within-distance models of spatial welfare heterogeneity," Journal of Environmental Economics and Management, Elsevier, vol. 85(C), pages 110-129.
    11. Trudy Ann Cameron & Sonja H. Kolstoe, 2022. "Using Auxiliary Population Samples for Sample-Selection Correction in Models Based on Crowd-Sourced Volunteered Geographic Information," Land Economics, University of Wisconsin Press, vol. 98(1), pages 1-21.
    12. Robert J. Johnston & Ewa Zawojska, 2018. "Benefit Transfer and Commodity Measurement Scales: Consequences for Validity and Reliability," Working Papers 2018-26, Faculty of Economic Sciences, University of Warsaw.
    13. Johnston, Robert J. & Börger, Tobias & Hanley, Nick & Meginnis, Keila & Ndebele, Tom & Siyal, Ghamz E. Ali & Beaumont, Nicola & de Vries, Frans P., 2024. "Consequences of omitting non-lethal wildlife impacts from stated preference scenarios," Journal of Environmental Economics and Management, Elsevier, vol. 126(C).

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