On the impact of decision rule assumptions in experimental designs on preference recovery: An application to climate change adaptation measures
Sander van Cranenburgh,
Jürgen Meyerhoff,
Katrin Rehdanz and
Andrea Wunsch
Journal of choice modelling, 2024, vol. 50, issue C
Abstract:
Efficient experimental designs aim to maximise the information obtained from stated choice data to estimate discrete choice models' parameters statistically efficiently. Almost without exception efficient experimental designs assume that decision-makers use a Random Utility Maximisation (RUM) decision rule. When using such designs, researchers (implicitly) assume that the decision rule used to generate the design has no impact on respondents' choice behaviour. This study investigates whether the decision rule assumption underlying an experimental design affects respondents' choice behaviour. We use four stated choice experiments on coastal adaptation to climate change: Two are based on experimental designs optimised for utility maximisation and two are based on experimental designs optimised for a mixture of RUM and Random Regret Minimisation (RRM). Generally, we find that respondents place value on adaptation measures (e.g., dykes and beach nourishments). We evaluate the models' fits and investigate whether some choice tasks particularly invoke RUM or RRM decision rules. For the latter, we develop a new sampling-based approach that avoids the confounding between preference and decision rule heterogeneity. We find no evidence that RUM-optimised designs invoke RUM-consistent choice behaviour. However, we find a relationship between some of the attributes and decision rules, and compelling evidence that some choice tasks invoke RUM consistent behaviour while others invoke RRM consistent behaviour. This implies that respondents’ choice behaviour and choice modelling outcomes are not exogenous to the choice tasks, which can be particularly critical when information on preferences is used to inform actual decision-making on a sensitive issue of common interest as climate change.
Keywords: Coastal adaptation; Climate change; Experimental design theory; Decision rules; Random regret minimisation (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1755534523000660
Full text for ScienceDirect subscribers only
Related works:
Working Paper: On the impact of decision rule assumptions in experimental designs on preference recovery: An application to climate change adaptation measures (2024) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:eejocm:v:50:y:2024:i:c:s1755534523000660
DOI: 10.1016/j.jocm.2023.100465
Access Statistics for this article
Journal of choice modelling is currently edited by S. Hess and J.M. Rose
More articles in Journal of choice modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().