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The Impact of Perceptions in Averting-decision Models: An Application of the Special Regressor Method to Drinking Water Choices

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  • Christophe Bontemps
  • Céline Nauges

Abstract

Households' monetary valuation of water quality is a prerequisite for efficient water resource management and the valuation of water quality protection policies. Individuals are commonly questioned about their perception of risk in valuation surveys based on stated-preference methods and revealed-preference methods such as averting-behavior models. These subjective and often discrete measures are commonly used to explain individuals' actions to protect themselves against these risks. Perceptions appear as endogenous variables in traditional theoretical averting-decision models but, quite surprisingly, endogeneity of perceived risk is not always controlled for in empirical studies. In this article, we argue that perceptions have to be treated as endogenous to averting decisions in order to produce accurate and reliable measures of households' valuation of water quality improvements. We present various binary averting decision models featuring an endogenous discrete variable (such as risk perception). In particular, we compare the traditional bivariate probit model with the special regressor model, which is less well-known and relies on a different set of assumptions. In the empirical illustration using household data from Australia, Canada, and France, we study how the perceived health impacts of tap water affect a household's decision to drink water from the tap. Individuals' perceptions are found to be endogenous and significant for all models, but the estimated marginal effect is sensitive to the chosen model. Our empirical application also includes some tests of the special regressor estimator's sensitivity to underlying assumptions.

Suggested Citation

  • Christophe Bontemps & Céline Nauges, 2016. "The Impact of Perceptions in Averting-decision Models: An Application of the Special Regressor Method to Drinking Water Choices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(1), pages 297-313.
  • Handle: RePEc:oup:ajagec:v:98:y:2016:i:1:p:297-313.
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    File URL: http://hdl.handle.net/10.1093/ajae/aav046
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    References listed on IDEAS

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    1. John C. Whitehead, 2006. "Improving Willingness to Pay Estimates for Quality Improvements through Joint Estimation with Quality Perceptions," Southern Economic Journal, Southern Economic Association, vol. 73(1), pages 100-111, July.
    2. Maurin, Eric, 2002. "The impact of parental income on early schooling transitions: A re-examination using data over three generations," Journal of Public Economics, Elsevier, vol. 85(3), pages 301-332, September.
    3. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, January.
    4. BONTEMPS Christophe & NAUGES Céline, 2006. "Carafe ou bouteille ? Le rôle de la qualité de l'environnement dans la décision du consommateur," LERNA Working Papers 06.07.200, LERNA, University of Toulouse.
    5. Yingying Dong & Arthur Lewbel, 2015. "A Simple Estimator for Binary Choice Models with Endogenous Regressors," Econometric Reviews, Taylor & Francis Journals, vol. 34(1-2), pages 82-105, February.
    6. Lewbel, Arthur & Schennach, Susanne M., 2007. "A simple ordered data estimator for inverse density weighted expectations," Journal of Econometrics, Elsevier, vol. 136(1), pages 189-211, January.
    7. Konishi, Yoshifumi & Adachi, Kenji, 2011. "A framework for estimating willingness-to-pay to avoid endogenous environmental risks," Resource and Energy Economics, Elsevier, vol. 33(1), pages 130-154, January.
    8. Bryan J. Hubbell & Jeffrey L. Jordan, 2000. "Joint Production and Averting Expenditure Measures of Willingness to Pay: Do Water Expenditures Really Measure Avoidance Costs?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(2), pages 427-437.
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    Cited by:

    1. Lanz, Bruno & Provins, Allan, 2017. "Using averting expenditures to estimate the demand for public goods: Combining objective and perceived quality," Resource and Energy Economics, Elsevier, vol. 47(C), pages 20-35.
    2. Whelan, Adele & McGuinness, Seamus, 2017. "Does a Satisfied Student Make a Satisfied Worker?," IZA Discussion Papers 10698, Institute for the Study of Labor (IZA).
    3. repec:eee:ecolec:v:141:y:2017:i:c:p:87-94 is not listed on IDEAS
    4. Bruno Lanz & Allan Provins, 2014. "The demand for tap water quality: Survey evidence on water hardness and aesthetic quality," CIES Research Paper series 23-2014, Centre for International Environmental Studies, The Graduate Institute.
    5. Nauges, Céline & Wheeler, Sarah Ann, 2017. "The Complex Relationship Between Households' Climate Change Concerns and Their Water and Energy Mitigation Behaviour," Ecological Economics, Elsevier, vol. 141(C), pages 87-94.
    6. Wang, Pengfei, 2017. "Syndication and Foreignness: Venture Capital Investments in Emerging and Developed Markets," Journal of International Management, Elsevier, vol. 23(1), pages 1-15.
    7. Gautam, Tej K. & Paudel, Krishna P. & Guidry, Kurt M., 2017. "Willingness To Pay For Irrigation Water In Louisiana," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252821, Southern Agricultural Economics Association.
    8. Ahamad, Mazbahul & Gustafson, Christopher & VanWormer, Elizabeth, 2016. "Ex-post Livestock Diseases, and Pastoralists' Averting Decisions in Tanzania," 2016 Annual Meeting, July 31-August 2, 2016, Boston, Massachusetts 235764, Agricultural and Applied Economics Association.
    9. Bontemps, Christophe & Nauges, Céline, 2017. "Endogenous Variables in Binary Choice Models: Some Insights for Practitioners," TSE Working Papers 17-855, Toulouse School of Economics (TSE).

    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling

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