Inferred Valuation as a Tool to Alleviate Social Desirability Bias: Testing the Systematic Influence of Individual-Specific Factors

• Author / Creator

  Zambrano Orellana, Roxana Patricia

• Social desirability bias (SDB) is a problem often found in the elicitation of preferences for goods of moral concern, where individuals tend to behave in a way that makes them 'look good' complying with social norms. Inferred valuation has been proposed to overcome this problem in stated preference surveys by asking individuals to predict others’ behavior instead of their own. However, the validity of the method is still a matter of discussion. In this research, we examine potential systematic differences between preferences captured with direct and inferred valuation questions, as well as potential systematic effects of several individual-specific characteristics on those differences. For this purpose, we use survey data from four previous stated preference studies which focused on the elicitation of preferences for passive-use values of public goods. We estimated logit and multinomial logit models of choice behavior as a function of alternative and individual specific variables including age, gender, income, education, and involvement in environmental conservation. In addition, conditional logit models of preferences were estimated to analyze differences between valuation approaches by the inclusion of interactions of alternative specific variables with a valuation method dummy and with the socio-demographic factors. Statistically significant differences between the probabilities of voting yes with direct and inferred questions suggested the presence of SDB in all four valuation studies. Older respondents appeared more prone to exhibit SDB in their answers given that the effects of age are significant and consistent across the four studies, with similar conclusions for female respondents in two studies. In line with previous literature, our results provide additional evidence for the assessment of inferred valuation’s validity as a promising tool to alleviate social desirability bias in the non-market valuation of public goods.

• Subjects / Keywords

  • Stated preference methods
  • Non-market valuation
  • Social desirability bias
  • Inferred valuation

• Graduation date

  Spring 2019

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/r3-2h66-t540

• License

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