Based on the simple what first comes to mind rule, the theory of visual attention (TVA; Bundesen, 1990) provides a comprehensive account of visual attention that has been successful in explaining performance in visual categorization for a variety of attention tasks. If the stimuli to be categorized are mutually confusable, a response rule based on the amount of evidence collected over a longer time seems more appropriate. In this paper, we extend the idea of a simple race to continuous sampling of evidence in favor of a certain response category. The resulting Poisson random walk model is a TVA-based response time model in which categories are reported based on the amount of evidence obtained. We demonstrate that the model provides an excellent account for response time distributions obtained in speeded visual categorization tasks. The model is mathematically tractable and its parameters are well founded and easily interpretable. We also provide an extension of the Poisson random walk to any number of response alternatives. We tested the model in experiments with speeded and non-speeded binary responses and a speeded response task with multiple report categories. The Poisson random walk model agreed very well with the data. A thorough investigation of processing rates revealed that the perceptual categorizations described by the Poisson random walk were the same as those obtained from TVA. The Poisson random walk model could therefore provide a unifying account of attention and response times.
We construct and run an experiment to test the most basic choice effect predicted by Salience Theory. Subjects allocate wealth between a risky and a safe investment. While we vary an apparent payoff ratio to influence salience, treatments have economically equivalent consequences. Most other theories of behavior then predict zero effect. Our experimental findings are strongly consistent with the behavioral implication of a continuous version of Salience Theory. We provide a novel structural estimate on the strength of salience. In our setting, increasing the relative payoff contrast by one percent is equivalent to an increased odds ratio by about 0.4 percent.
Experiments have become a well-established methodological tool in economics. e development of experi- mental economics and the diversi cation of experimental methods have equipped economists with new and powerful means of scienti c investigation. eir worth is readily demonstrated in the exciting and promising results they have produced, and will continue to produce. Against the background of this success story, our selective discussion critically highlights four important aspects of experimentation in economics. We concen- trate on the role and importance of material incentives, potentially confounding experimenter demand e ects and strategies to minimise these, the no deception rule as well as the issue of external validity.
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