Abstract In this paper, we examine the behavior of subjects in a mock financial investment experiment to investigate the effects of “skin in the game” and ego utility on hedonic information acquisition decisions. We observe how often subjects “check” their portfolios after given general market returns, and whether conditions impact the existence and magnitude of the ostrich effect – the tendency to avoid information expected to be negative. When considering these experiment conditions as well as subject sex, risk aversion, curiosity, financial literacy and investing experience, we do not find an ostrich effect. We do find that females check their portfolios more often on average than males. Finally, we find that risk-averse people will check their portfolios more often, regardless of market returns or sex.

Statistical data, such as in the form of microdata, is used by different organisations as a basis for creating knowledge to assist in their planning and decision-making activities. However, before microdata can be made available for analysis, it needs to be anonymised in order to protect the privacy of the individuals whose data is released. The protection of privacy requires us to hide or obscure the released data. On the other hand, making data useful for its users implies that we should provide data that is accurate, complete and precise. Ideally, we should maximise both the level of privacy and the level of information utility of a released microdata set. However, as we increase the level of privacy, the level of information utility decreases. Without guidelines to guide the selection of the optimum levels of privacy and information utility, it is difficult to determine the optimum balance between the two goals. The objective and constraints of this optimisation problem can be captured naturally with concepts from Economic Price Theory. In this thesis, we present an approach based on Economic Price Theory for guiding the process of microdata anonymisation such that optimum levels of privacy and information utility are achieved. / Thesis (PhD)--University of Pretoria, 2010. / Computer Science / unrestricted