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Purpose – This experimental economics study using brain imaging techniques investigates the risk-ambiguity distinction in relation to the source preference hypothesis (Fox & Tversky, 1995) in which identically distributed risks arising from different sources of uncertainty may engender distinct preferences for the same decision maker, contrary to classical economic thinking. The use of brain imaging enables sharper testing of the implications of different models of decision-making including Chew and Sagi's (2008) axiomatization of source preference.

Methodology/approach – Using fMRI, brain activations were observed when subjects make 48 sequential binary choices among even-chance lotteries based on whether the trailing digits of a number of stock prices at market closing would be odd or even. Subsequently, subjects rate familiarity of the stock symbols.

Findings – When contrasting brain activation from more familiar sources with those from less familiar ones, regions appearing to be more active include the putamen, medial frontal cortex, and superior temporal gyrus. ROI analysis showed that the activation patterns in the familiar–unfamiliar and unfamiliar–familiar contrasts are similar to those in the risk–ambiguity and ambiguity–risk contrasts reported by Hsu et al. (2005). This supports the conjecture that the risk-ambiguity distinction can be subsumed by the source preference hypothesis.

Research limitations/implications – Our odd–even design has the advantage of inducing the same “unambiguous” probability of half for each subject in each binary comparison. Our finding supports the implications of the Chew–Sagi model and rejects models based on global probabilistic sophistication, including rank-dependent models derived from non-additive probabilities, e.g., Choquet expected utility and cumulative prospect theory, as well as those based on multiple priors, e.g., α-maxmin. The finding in Hsu et al. (2005) that orbitofrontal cortex lesion patients display neither ambiguity aversion nor risk aversion offers further support to the Chew–Sagi model. Our finding also supports the Levy et al. (2007) contention of a single valuation system encompassing risk and ambiguity aversion.

Originality/value of chapter – This is the first neuroimaging study of the source preference hypothesis using a design which can discriminate among decision models ranging from risk-based ones to those relying on multiple priors.

Neuroeconomics is the study of how the brain makes economic decisions. By its nature neuroeconomics studies the mechanisms of decision-making, assumed to be computational, in order to better understand the strategies people use and the choices that people make. The focus of this book is how neuroeconomics connects to health economics in a way that improves our understanding of health care and treatment decisions. This is natural for several reasons. First, the brain and the body are intimately connected to each other and the health of one depends on the other. Second, the health system is inherently about decisions. Decisions to stay healthy, decisions to diagnose illness, decisions to treat, decisions to invest in new treatments, decisions to insure, and decisions to pay. Finally, these decisions can be difficult, as the media's consistent attention to this area attests. In light of this, for this volume we chose to include chapters that review basic research on emotion or social preference that have direct relevance to decisions in health economics. We have also included chapters that refer more specifically to some aspect of people's health care or treatment decisions. In the following we indicate the chapters within each topic area. Although many chapters could arguably fit in multiple categories, we have listed each chapter only once and without particular order.

The author presents new estimates of the probability weighting functions found in rank-dependent theories of choice under risk. These estimates are unusual in two senses. First, they are free of functional form assumptions about both utility and weighting functions, and they are entirely based on binary discrete choices and not on matching or valuation tasks, though they depend on assumptions concerning the nature of probabilistic choice under risk. Second, estimated weighting functions contradict widely held priors of an inverse-s shape with fixed point well in the interior of the (0,1) interval: Instead the author usually finds populations dominated by “optimists” who uniformly overweight best outcomes in risky options. The choice pairs used here mostly do not provoke similarity-based simplifications. In a third experiment, the author shows that the presence of choice pairs that provoke similarity-based computational shortcuts does indeed flatten estimated probability weighting functions.

Singapore is perceived to be the least corrupt country in Asia according to Transparency International's Corruption Perceptions Index (CPI) from 1995 to 2010. In 2010, Singapore was ranked joint first with Denmark and New Zealand among 178 countries on the CPI with a score of 9.3. However, this does not mean that corruption does not exist in Singapore, which has its share of corruption scandals too. Indeed, the scandal involving Teh Cheang Wan attracted a great deal of attention because he was the Minister for National Development in Singapore from 1979 to 1986.