The thesis contains four chapters on the structure and predictability of individual differences Chapter 1. Re-analyses data from Holt and Laury's (2002) risk aversion experiments. Shows that big-stakes hypothetical payoffs are better than small-stakes real-money payoffs for predicting choices in big-stakes real-money gambles (in spite of the presence of hypothetical bias). Argues that hypothetical bias is a problem for calibration of mean preferences but not for prediction of the rank order of subjects' preferences. Chapter 2. Describes an experiment: Participants were given personality tests and played a series of dictator and response games over a two week period. It was found that social preferences are one-dimensional, stable across a two-week interval and significantly related to the Big Five personality traits. Suggestions are given about ways to modify existing theories of social preference to accommodate these findings. Chapter 3. Applies a novel statistical technique (spectral clustering) to a personality data set for the first time. Finds the HEXACO six-factor structure in an English-language five-factor questionnaire for the first time. Argues that the emphasis placed on weak relationships is critical to settling the dimensionality debate within personality theory, and that spectral clustering provides a more useful perspective on personality data than does traditional factor analysis. Chapter 4. Outlines the relevance of extraversion for economics, and sets up a model to argue that personality differences in extraversion may have evolved through something akin to a war of attrition. This model implies a positive relationship between extraversion and risk aversion, and a U-shaped relationship between extraversion and loss aversion.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:563802 |
| Date | January 2012 |
| Creators | Brocklebank, Sean |
| Contributors | Hopkins, Ed. : Kornienko, Tatiana |
| Publisher | University of Edinburgh |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1842/6281 |
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