Payment and provision consequentiality in voluntary contribution mechanism: separate or joint effects?
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Payment and provision consequentiality in voluntary contribution mechanism: separate or joint effects? Jie He1 · Jérôme Dupras2 · Franck Ndefo1 · Thomas Poder3 Received: 15 September 2019 / Accepted: 6 January 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract We conducted a field stated preferences survey to understand the influence of payment and provision consequentiality script on valuation associated with voluntary contribution. Based on four treatment groups with single or combined consequentiality scripts and a contingent-ranking willingness to pay question, this paper provided some evidence that at least for some attributes, a respondent facing positive provision probability reported a significantly higher preference for the opt-in projects if and only if the payment consequentiality was co-presented. For the payment consequentiality, its impact on valuation was independent of the presence of provision consequentiality. We also discussed the limits of our study and provided suggestions for future research in this line. Keywords Hypothetical bias · Payment consequentiality · Provision consequentiality · Contingent ranking · Voluntary donation · Ecosystem services valuation JEL Classification Q51 · Q57
* Jie He [email protected] Jérôme Dupras [email protected] Franck Ndefo [email protected] Thomas Poder [email protected] 1
Département d’Économique, École de Gestion, Université de Sherbrooke, 2500 boulevard de l’Université, Sherbrooke, QC J1K2R1, Canada
2
Département des sciences naturelles, l’Institut des sciences de la forêt tempérée (ISFORT), Université du Québec à Outaouais, Ripon, Canada
3
École de santé publique ‑ Département de gestion, d’évaluation et de politique de santé, Université de Montréal, Montreal, Canada
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1 Introduction Despite their popularity in eliciting willingness to pay (WTP) for environmental public goods and services, stated preference methods are known to be influenced by biases due to their hypothetical nature. The meta-analyses by List and Gallet (2001) and Little and Berrens (2004), with a larger database reported average overestimation by a calibration factor of approximately 3 in hypothetical settings. The meta-analysis by Murphy et al. (2005) suggested a smaller median ratio of about 1.35 for hypothetical to actual value. More recently, Little et al. (Little et al. 2012) reported that 60.9% of the 93 studies that they included in their meta-analysis reported statistically significant disparity between hypothetical and actual valuation responses. Penn and Hu (2018) reported a median ratio of 1.39 based on the 132 articles included in their enhanced meta-analysis. Carson and Groves (2007) advocated the stated preference methods by identifying consequential scenarios. According to them, consequential surveys should satisfy two conditions. First, the respondent must view his responses as potentially influencing the agency’s actions. Second, the respondent must care about the outcomes of
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