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Combining mixed logit models and random effects models to identify the determinants of willingness to pay for rural landscape improvements

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  • Campbell, Danny

Abstract

This paper reports the findings from a discrete choice experiment study designed to estimate the economic benefits associated with rural landscape improvements in Ireland. Using a mixed logit model, the panel nature of the dataset is exploited to retrieve willingness to pay values for every individual in the sample. This departs from customary approaches in which the willingness to pay estimates are normally expressed as measures of central tendency of an a priori distribution. In a different vein from analysis conducted in previous discrete choice experiment studies, this paper uses random effects models for panel data to identify the determinants of the individual-specific willingness to pay estimates. In comparison with the standard methods used to incorporate individual-specific variables into the analysis of discrete choice experiments, the analytical approach outlined in this paper is shown to add considerably more validity and explanatory power to welfare estimates

Suggested Citation

  • Campbell, Danny, 2007. "Combining mixed logit models and random effects models to identify the determinants of willingness to pay for rural landscape improvements," 81st Annual Conference, April 2-4, 2007, Reading University 7975, Agricultural Economics Society.
  • Handle: RePEc:ags:aes007:7975
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    File URL: http://purl.umn.edu/7975
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    References listed on IDEAS

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    Cited by:

    1. Wang, Xin & Maynard, Leigh J. & Butler, J.S., 2010. "Using Linked Household-level Datasets to Explain Consumer Response to BSE in Canada," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 60859, Agricultural and Applied Economics Association.

    More about this item

    Keywords

    Agri-environment; discrete choice experiments; mixed logit; panel data; random effects; willingness to pay; Demand and Price Analysis; Environmental Economics and Policy; C33; C35; Q24; Q51;

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • Q24 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Land
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

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