Working paper

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

Christophe Bontemps, and Céline Nauges

Abstract

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.

Keywords

Discrete choice; special regressor; endogeneity; water consumption;

JEL codes

  • C14: Semiparametric and Nonparametric Methods: General
  • C25: Discrete Regression and Qualitative Choice Models • Discrete Regressors • Proportions
  • Q51: Valuation of Environmental Effects
  • Q53: Air Pollution • Water Pollution • Noise • Hazardous Waste • Solid Waste • Recycling

Replaced by

Christophe Bontemps, and Céline Nauges, The impact of perceptions in averting-decision models: an application of the special regressor method to drinking water choices, American Journal of Agricultural Economics, vol. 98, n. 1, January 2016, pp. 297–313.

See also

Published in

TSE Working Paper, n. 14-537, November 5, 2014