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Benefit Transfer Combining Revealed and Stated Preference Data

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Benefit Transfer of Environmental and Resource Values

Part of the book series: The Economics of Non-Market Goods and Resources ((ENGO,volume 14))

Abstract

Benefit transfers often combine data from revealed preference (RP) and stated preference (SP) analyses. RP/SP estimation allows a researcher to generate more broadly-applicable benefit functions, leading to potential improvements in transfer reliability and validity. The appropriateness of various types of RP/SP data combinations within benefit transfer has also been subject to disagreement, for example with regard to the potential pooling of theoretically inconsistent welfare measures within meta-analysis. This chapter provides a summary and case study illustration of RP/SP modeling within benefit transfer. The chapter begins with an introduction to the use of these techniques for benefit transfer and typology of applicable methods. This is followed by an illustration that uses RP/SP micro-data to quantify recreational benefit changes under Delaware Department of Natural Resources and Environmental Control beach nourishment and retreat scenarios. Unlike most benefit transfers in the academic literature implemented in artificial and idealized circumstances, the present case study represents an actual, policy-driven benefit transfer used within agency cost benefit analysis (CBA). The chapter concludes with a discussion of the role of RP/SP data within benefit transfer.

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Notes

  1. 1.

    A few examples include Adamowicz et al. (1997), Cameron et al. (1996), Huang et al. (1997), Haener et al. (2001), Kling (1997), Boxall et al. (2003), Englin and Cameron (1996) and Parsons et al. (1999).

  2. 2.

    Borrowing the terminology of Whitehead et al. (2011a, b, p. 3), this chapter emphasizes joint estimation RP/SP analysis, in which “relationships between the independent … and … dependent variables are estimated in a single model.” We do not address data comparison or other analyses in which RP and SP data are not jointly estimated, including the large literatures on convergent validity and hypothetical bias in SP estimation (Carson et al. 1996; Murphy et al. 2005).

  3. 3.

    As described by Whitehead et al. (2008a), “[b]each … nourishment is the placement of sand on beaches to increase … width for the purposes of protecting property and maintaining recreation opportunities (Jones and Mangun 2001).”

  4. 4.

    As discussed by Parsons et al. (2013), the Delaware Bay beaches under consideration for the present analysis are smaller and less populated than the better-known ocean beaches located further south. Current average beach widths above mean high tide range from approximately 27 to 70 ft, with some areas as narrow as 13 ft (Johnson, Mirmiran and Thompson, Inc. 2012). Parsons et al. (2013) estimated a total of approximately 49,000 adult visitors per year to the seven beaches combined in 2010.

  5. 5.

    A short overnight trip was defined as three or fewer nights.

  6. 6.

    The overwhelming majority of the respondents made no visits to other beaches in the set.

  7. 7.

    We assume that for all practical purposes widths in 2010 and 2011 are identical.

  8. 8.

    This is likely a reasonable assumption for these communities, given the lack of hotel accommodations.

  9. 9.

    These estimates only reflect changes in recreational consumer surplus (benefits). The costs of each scenario (e.g., to nourish a beach, remove homes, etc.) are not included.

  10. 10.

    For example, underlying assumptions and errors in primary studies will carry through to subsequent benefit transfers.

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Acknowledgments

This research is partially supported by the Delaware Department of Natural Resources and Environmental Control in partnership with Johnson, Mirmiran and Thompson, Inc. We acknowledge helpful comments of Ari Michelsen. Opinions are those of the authors and do not imply endorsement of the funding agency. Any remaining errors are the sole responsibility of the authors.

Author information

Authors and Affiliations

  1. Department of Economics and George Perkins Marsh Institute, Clark University, Worcester, MA, USA

    Robert J. Johnston

  2. Cape Cod Commission, Barnstable, MA, USA

    Mahesh Ramachandran

  3. School of Marine Science and Policy, Department of Economics and Department of Applied Economics and Statistics, University of Delaware, Newark, DE, USA

    George R. Parsons

Authors
  1. Robert J. Johnston
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  2. Mahesh Ramachandran
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  3. George R. Parsons
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Corresponding author

Correspondence to Robert J. Johnston .

Editor information

Editors and Affiliations

  1. Department of Economics and George Perkins Marsh Institute, Clark University, Worcester, Massachusetts, USA

    Robert J. Johnston

  2. School of Business and Law, CQUniversity, Rockhampton, Queensland, Australia

    John Rolfe

  3. Dept. of Forest Ecosystems & Society, Oregon State University, Corvallis, Oregon, USA

    Randall S. Rosenberger

  4. Department of Environmental Economics, Vrije Universiteit, Amsterdam, The Netherlands

    Roy Brouwer

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Johnston, R.J., Ramachandran, M., Parsons, G.R. (2015). Benefit Transfer Combining Revealed and Stated Preference Data. In: Johnston, R., Rolfe, J., Rosenberger, R., Brouwer, R. (eds) Benefit Transfer of Environmental and Resource Values. The Economics of Non-Market Goods and Resources, vol 14. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9930-0_9

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