|摘要: ||In this article, we extend an early agent-based spatial model of the prediction market|
by taking into account the heterogeneities of agents in their tolerance capacity (tolerance
to neighbors with different political identities) and in their exploration capacity (exploration
of the political identities of other agents). We then study the effects of these heterogeneities
on the behavior of the prediction market, including prediction accuracy, determinants
of earnings, and income distribution. First, in terms of prediction accuracy, we
find that, compared to the homogeneous case, bringing heterogeneity into the model can
generally improve the prediction accuracy, although its statistical significance is limited.
In particular, the well-known empirical regularity known as the favorite-longshot bias
remains almost unchanged with this extension. Second, through the heterogeneous-agent
design, we find that both capacities (personality traits) of agents have a significant positive
effect on earnings, and the effect of the exploration capacity is even more dramatic.
Third, through their effects on earnings, both capacities also contribute to income inequality,
but only to a mild degree with a Gini coefficient of 0.20.