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The impact of perceptions in averting-decision models: An application of the special regressor method to drinking water choices

Listed author(s):
  • Bontemps, Christophe
  • Nauges, Céline

Individuals are commonly surveyed about their perception or assessment of risk and these variables are often 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 present different models that can be useful to the practitioner when estimating 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 model and underlying assumptions. The special regressor appears to be a valuable alternative to the more common bivariate probit model.

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File URL: http://www.tse-fr.eu/sites/default/files/medias/doc/wp/eee/wp_tse_537.pdf
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Paper provided by Toulouse School of Economics (TSE) in its series TSE Working Papers with number 14-537.

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Date of creation: 05 Nov 2014
Publication status: Published in American Journal of Agricultural Economics, vol. 98, n°1, janvier 2016, p. 297-313.
Handle: RePEc:tse:wpaper:28776
Contact details of provider: Phone: (+33) 5 61 12 86 23
Web page: http://www.tse-fr.eu/

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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. 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.
  4. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
  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. 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.
  7. 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.
  8. 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.
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