Discrete choice experiments (DCEs) are widely used across economic disciplines to value multi-attribute commodities. DCEs ask survey-respondents to choose between mutually exclusive hypothetical alternatives that are described by a set of common attributes. The analysis of DCE data assumes that respondents consider and trade all attributes before making these choices. However, several studies show that many respondents ignore attributes. Respondents might choose not to consider all attributes to simplify choices or as a preference, because some attributes are not important to them. However, empirical approaches that account for attribute non-consideration only assume simplifying choice behaviour. This thesis shows that this assumption may lead to misleading welfare conclusions and therefore suboptimal policy advice. The analysis explores 'why' attribute are ignored using statistical analysis or by asking respondents. Both approaches are commonly used to identify attribute non-consideration in DCEs. However, the results of this thesis suggest that respondents struggle to recall ignored attributes and their reasons for non-consideration unless attributes are ignored due to non-valuation. This questions the validity of approaches in the literature that rely on respondents' ability to reflect on their decision rule. Further analysis explores how the complexity of choices affects the probability that respondents do not consider all attributes. The results show that attribute consideration first increases and then decreases with complexity. This raises questions about the optimal design complexity of DCEs. The overall findings of the thesis challenge the applicability of current approaches that account for attribute non-consideration in DCEs to policy analysis and emphasis the need for further research in this area.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:685267 |
| Date | January 2016 |
| Creators | Heidenreich, Sebastian |
| Publisher | University of Aberdeen |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=229468 |
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