Addressing Attribute Value Substitution in Discrete Choice Experiments to Avoid Unintended Consequences
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Addressing Attribute Value Substitution in Discrete Choice Experiments to Avoid Unintended Consequences Gregory Howard1 · Brian E. Roe2 · Matthew G. Interis3 · Jay Martin2 Accepted: 15 October 2020 © Springer Nature B.V. 2020
Abstract Choice experiments are a popular method of generating stated preference data for a variety of fields from marketing to health, transportation and environmental economics. They allow researchers to systematically vary choice attributes in a manner that can both increase estimation efficiency and allay endogeneity concerns. An increasing number of studies have included elicited subjective beliefs in their stated preference models. We discuss why this strategy may be warranted in some cases, specifically when the researcher suspects subjects will engage in attribute value substitution or scenario adjustment. While there are multiple ways one could integrate subjective beliefs, in all cases a proper understanding of the econometric ramifications of their inclusion is necessary. We show that excluding subjective beliefs yields biased parameter estimates yet policy-relevant welfare measures, whereas including subjective beliefs yields unbiased parameter estimates but can generate less policy-relevant welfare estimates. We demonstrate how policy-relevant welfare measures should be calculated from models that include subjective beliefs and illustrate our theory with an application to payment for ecosystem services to farmers. Keywords Subjective beliefs · Discrete choice · Attribute value substitution · Scenario adjustment Discrete choice experiments (DCEs), coupled with discrete choice econometric models, are regularly used by researchers in fields ranging from environmental and transportation * Gregory Howard [email protected] Brian E. Roe [email protected] Matthew G. Interis [email protected] Jay Martin [email protected] 1
East Carolina University, Greenville, NC, USA
2
Ohio State University, Columbus, OH, USA
3
Mississippi State University, Mississippi State, MS, USA
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economics to marketing. DCEs allow the researcher to treat respondent preferences for different alternatives in a choice as a function of exogenously and systematically varied attributes. The ability to assign attribute levels serves the joint purpose of increasing the efficiency of preference parameter estimation (Adamowicz et al. 1998) and allaying endogeneity concerns (Phaneuf and Requate 2017, ch. 19; Freeman et al. 2014). This is one of the main advantages of stated preference DCEs over revealed preference methods, as the latter may suffer from collinearity and endogeneity issues among market-driven attribute levels (Phaneuf and Requate 2017, ch. 19; Freeman 1992; Earnhart 2001). One of the basic tenets of survey data collection and analysis is that the survey respondent should interpret survey questions the way the survey designer intended. It is obvious that problems arise when a respondent answers a question different from the one the researcher intended to as
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