Learning design contingent valuation (LDCV): NOAA guidelines, preference learning and coherent arbitrariness

Abstract

We extend the contingent valuation (CV) method to test three differing conceptions of individuals' preferences as either (i) a-priori well-formed or readily divined and revealed through a single dichotomous choice question (as per the NOAA CV guidelines [K. Arrow, R. Solow, P.R. Portney, E.E. Leamer, R. Radner, H. Schuman, Report of the NOAA panel on contingent valuation, Fed. Reg. 58 (1993) 4601-4614]); (ii) learned or 'discovered' through a process of repetition and experience [J.A. (2003) 73-105]. Findings reject both the first and last of these conceptions in favour of a model in which preferences converge towards standard expectations through a process of repetition and learning. In doing so, we show that such a 'learning design CV' method overturns the 'stylised facts' of bias and anchoring within the double bound dichotomous choice elicitation format. r

Choice Certainty and Consistency in Repeated Choice Experiments

“…In the case of 'coherent arbitrariness' (CA) (Ariely et al 2003), preferences are also assumed to converge to a stable level allowing the respondent to make coherent and consistent choices, but here the convergence level is dependent on contextual cues and other arbitrary framing effects arising in the survey. Bateman et al (2008) find support for the DPH and show that learning effects through repeated choices may overturn the wide-spread value anchoring biases found in double bounded CV, hence minimizing the influence of arbitrary effects in SP valuation research.…”

Constructed preference stability: a test–retest

“…Through repetition, individuals will gradually discover their exact preferences and adjust their behavior accordingly. Bateman et al (2008) find support for the DPH in a series of double bound CV questions for different goods. They argue that because of stabilizing learning effects it is the last response in a series of valuation questions rather than the first that yields the most reliable value statement, hence questioning the NOAA endorsed 'one-shot' single bound dichotomous choice (DC) approach in CV.…”

“…Contrary to predicting choice behavior in other behavioral sciences such as marketing and decision theory, empirical evidence explicitly addressing preference construction in economic valuation research is rare (e.g. Slovic 1995, McFadden 1999, Spash 2002, Bateman et al 2008. Although preferences and expressions of preferences are very likely to be influenced by the information provided during the time of the choice task and the ability of respondents to fit and position this information (selectively) into their mental value system, this does not necessarily mean, as Payne et al (1999) point out, that there is no 'true' value to be measured.…”

“…Possible reasons for the SB-DB gap are given in Carson and Grooves (2007) and relate primarily to incentive compatibility differences. Bateman et al (2008) add to this the learning effect, arguing that 'the imprecise estimates in initial valuations appear inconsistent with a-priori well-formed preferences' (ibid, p.131). Due to choice repetition and experience, the DB format is therefore expected to produce more stable preferences and WTP values in the test-retest experiment.…”

Intra-respondent Heterogeneity in a Stated Choice Survey on Wetland Conservation in Belarus: First Steps Towards Creating a Link with Uncertainty in Contingent Valuation

“…Bateman et al (2008) identify (i) a-priori well-formed or readily divined through a single incentive compatible question;…”