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Testing and Correcting for Sample Selection Bias in Discrete Choice Contingent Valuation Studies

Author

Listed:
  • Eklöf, Jan

    () (Department of Economic Statistics)

  • Karlsson, Sune

    () (Department of Economic Statistics)

Abstract

The discrete choice or ”referendum” contingent valuation technique has become a popular tool for assessing the value of non-market goods. Surveys used in these studies frequently suffer from large non-response which can lead to significant bias in parameter estimates and in the estimate of mean Willingness to Pay. We investigate the properties of tests for sample selection bias and the losses made by applying estimators assuming no sample selection. The effects of sample selection bias can be sizable but bivariate probit estimation give unbiased estimates. A computationally straightforward test for sample selection bias is found to perform well.

Suggested Citation

  • Eklöf, Jan & Karlsson, Sune, 1997. "Testing and Correcting for Sample Selection Bias in Discrete Choice Contingent Valuation Studies," SSE/EFI Working Paper Series in Economics and Finance 171, Stockholm School of Economics, revised 23 Jun 1999.
  • Handle: RePEc:hhs:hastef:0171
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    Citations

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    Cited by:

    1. Seung-Hoon Yoo & Hee-Jong Yang, 2001. "Application of Sample Selection Model to Double-Bounded Dichotomous Choice Contingent Valuation Studies," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 20(2), pages 147-163, October.
    2. Lyssenko, Nikita & Martinez-Espineira, Roberto, 2009. "`Been there done that': Disentangling option value effects from user heterogeneity when valuing natural resources with a use component," MPRA Paper 21976, University Library of Munich, Germany, revised 08 Apr 2010.
    3. Xie, Jing & Gao, Zhifeng, 2013. "The Comparison of three Non-hypothetical Valuation Methods: Choice Experiments, Contingent Valuation, and Experimental Auction," 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida 143103, Southern Agricultural Economics Association.
    4. Jennifer Grannis & Dawn D. Thilmany, 2002. "Marketing natural pork: An empirical analysis of consumers in the mountain region," Agribusiness, John Wiley & Sons, Ltd., vol. 18(4), pages 475-489.

    More about this item

    Keywords

    Bivariate probit; non-response; willingness to pay; omitted variables test;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • Q20 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - General

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