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Do turbines in the vicinity of respondents' residences influence choices among programmes for future wind power generation?

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  • Meyerhoff, Jürgen

Abstract

This paper contributes to the literature on accounting for spatial characteristics in the analysis of stated choices. It is studied whether the present spatial allocation of turbines in a region affects choices on alternative programmes describing the future shape of wind power generation. Due to the present allocation turbines affect inhabitants of the study region differently. Using a Geographical Information System variables describing respondents' exposure to turbines are calculated, e.g. distance to the nearest turbine. Including them into multinomial and latent class logit models shows that exposure to turbines affects the propensity to choose the non-buy alternative and willingness to pay (WTP) values. Respondents who live further away from turbines are more likely to be the opponents of wind power generation and thus have a higher willingness to pay for moving turbines further away from residential areas. Tests for global and local spatial autocorrelation reveal that global spatial autocorrelation of the individual-specific WTP values is low. However, local clusters of similar WTP exist. Particularly in the biggest city of the study region clusters of respondents with low WTP values are present. Spatial analysis thus provides otherwise invisible pattern.

Suggested Citation

  • Meyerhoff, Jürgen, 2013. "Do turbines in the vicinity of respondents' residences influence choices among programmes for future wind power generation?," Journal of choice modelling, Elsevier, vol. 7(C), pages 58-71.
  • Handle: RePEc:eee:eejocm:v:7:y:2013:i:c:p:58-71
    DOI: 10.1016/j.jocm.2013.04.010
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    1. Concu, Giovanni B., 2007. "Investigating distance effects on environmental values: a choice modelling approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 51(2), pages 1-20.
    2. Maurizio Pisati, 2012. "Exploratory spatial data analysis using Stata," German Stata Users' Group Meetings 2012 07, Stata Users Group.
    3. John Rolfe & Jill Windle, 2012. "Distance Decay Functions for Iconic Assets: Assessing National Values to Protect the Health of the Great Barrier Reef in Australia," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 53(3), pages 347-365, November.
    4. Ladenburg, Jacob & Dahlgaard, Jens-Olav, 2012. "Attitudes, threshold levels and cumulative effects of the daily wind-turbine encounters," Applied Energy, Elsevier, vol. 98(C), pages 40-46.
    5. Roy Brouwer & Julia Martin-Ortega & RJulio Berbel, 2010. "Spatial Preference Heterogeneity: A Choice Experiment," Land Economics, University of Wisconsin Press, vol. 86(3).
    6. Kurt E. Schnier & Ronald G. Felthoven, 2011. "Accounting for Spatial Heterogeneity and Autocorrelation in Spatial Discrete Choice Models: Implications for Behavioral Predictions," Land Economics, University of Wisconsin Press, vol. 87(3), pages 382-402.
    7. H. Allen Klaiber & Daniel J. Phaneuf, 2009. "Do Sorting and Heterogeneity Matter for Open Space Policy Analysis? An Empirical Comparison of Hedonic and Sorting Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(5), pages 1312-1318.
    8. Allen Klaiber, H. & Phaneuf, Daniel J., 2010. "Valuing open space in a residential sorting model of the Twin Cities," Journal of Environmental Economics and Management, Elsevier, vol. 60(2), pages 57-77, September.
    9. Johnston, Robert J. & Ramachandran, Mahesh & Schultz, Eric T. & Segerson, Kathleen & Besedin, Elena Y., 2011. "Characterizing Spatial Pattern in Ecosystem Service Values when Distance Decay Doesn’t Apply: Choice Experiments and Local Indicators of Spatial Association," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103374, Agricultural and Applied Economics Association.
    10. McNair, Ben J. & Bennett, Jeff & Hensher, David A. & Rose, John M., 2011. "Households' willingness to pay for overhead-to-underground conversion of electricity distribution networks," Energy Policy, Elsevier, vol. 39(5), pages 2560-2567, May.
    11. Naresh Kumar, 2007. "Spatial Sampling Design for a Demographic and Health Survey," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 26(5), pages 581-599, December.
    12. Sergio Colombo & Nick Hanley & Jordan Louviere, 2009. "Modeling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture," Agricultural Economics, International Association of Agricultural Economists, vol. 40(3), pages 307-322, May.
    13. Schaafsma, Marije & Brouwer, Roy & Rose, John, 2012. "Directional heterogeneity in WTP models for environmental valuation," Ecological Economics, Elsevier, vol. 79(C), pages 21-31.
    14. Meyerhoff, Jürgen & Ohl, Cornelia & Hartje, Volkmar, 2010. "Landscape externalities from onshore wind power," Energy Policy, Elsevier, vol. 38(1), pages 82-92, January.
    15. Wolsink, Maarten, 2007. "Planning of renewables schemes: Deliberative and fair decision-making on landscape issues instead of reproachful accusations of non-cooperation," Energy Policy, Elsevier, vol. 35(5), pages 2692-2704, May.
    16. Bhat, Chandra R. & Guo, Jessica, 2004. "A mixed spatially correlated logit model: formulation and application to residential choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 147-168, February.
    17. Tait, Peter & Baskaran, Ramesh & Cullen, Ross & Bicknell, Kathryn, 2012. "Nonmarket valuation of water quality: Addressing spatially heterogeneous preferences using GIS and a random parameter logit model," Ecological Economics, Elsevier, vol. 75(C), pages 15-21.
    18. Garrod, Guy & Ruto, Eric & Willis, Ken & Powe, Neil, 2012. "Heterogeneity of preferences for the benefits of Environmental Stewardship: A latent-class approach," Ecological Economics, Elsevier, vol. 76(C), pages 104-111.
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